UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

The effect of acute high-intensity interval exercise on toll-like receptor expression and monocyte subsets… Durrer, Cody 2016

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2016_september_Durrer_Cody.pdf [ 1.5MB ]
Metadata
JSON: 24-1.0304569.json
JSON-LD: 24-1.0304569-ld.json
RDF/XML (Pretty): 24-1.0304569-rdf.xml
RDF/JSON: 24-1.0304569-rdf.json
Turtle: 24-1.0304569-turtle.txt
N-Triples: 24-1.0304569-rdf-ntriples.txt
Original Record: 24-1.0304569-source.json
Full Text
24-1.0304569-fulltext.txt
Citation
24-1.0304569.ris

Full Text

  THE EFFECT OF ACUTE HIGH-INTENSITY INTERVAL EXERCISE ON TOLL-LIKE RECEPTOR EXPRESSION AND MONOCYTE SUBSETS IN TYPE 2 DIABETES by Cody Durrer B.H.K, University of British Columbia, 2014 A THESIS SUBMITTED IN PARTIAL FULLFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Interdisciplinary Studies) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) May 2016 © Cody Durrer, 2016             The undersigned certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled:    The Effect of Acute High-Intensity Interval Exercise on Toll-Like Receptor Expression and Monocyte Subsets in Type 2 Diabetes  Submitted by                Cody Durrer                               in partial fulfillment of the requirements of   The degree of             Master of Science                                                    .  Dr. Jonathan Little, School of Health and Exercise Sciences, UBC Okanagan Supervisor, Professor (please print name and faculty/school above the line)  Dr. Nathan Jenkins, College of Education, University of Georgia Supervisory Committee Member, Professor (please print name and faculty/school in the line above)  Dr. Glen Foster, School of Health and Exercise Sciences, UBC Okanagan Supervisory Committee Member, Professor (please print name and faculty/school in the line above)  Dr. Normand Boule, Faculty of Physical Education & Recreation, University of Alberta  University Examiner, Professor (please print name and faculty/school in the line above)   External Examiner, Professor (please print name and university in the line above)   May 31, 2016 (Date submitted to Grad Studies)            iii  Abstract Type 2 diabetes (T2D) is characterized by a state of chronic low-grade inflammation that is implicated in driving the pathophysiology of the disease. Exercise has been shown to have anti-inflammatory effects but the impact of high-intensity interval training, an exercise strategy gaining popularity for the prevention and treatment of T2D, is not known. The research in this thesis examined the impact of a single session of high-intensity interval training (HIIT) on cellular, molecular, and circulating markers of inflammation in individuals with T2D and healthy age-matched controls. Participants completed an acute bout of high-intensity interval training (7 X 1-min @ ~85% maximal aerobic power output, separated by 1-min recovery) on a cycle ergometer with blood samples obtained before (Pre), immediately after (Post), and at one hour of recovery (1-h Post). Inflammatory markers on white blood cells were measured by flow cytometry, plasma cytokines assessed by multiplex assay, and innate immune activation measured in whole blood cultures stimulated with bacterial lipopolysaccharide (LPS). Results showed that a single session of HIIT had an overall anti-inflammatory effect, as evidenced by: i) significantly lower levels of toll-like receptor 2 (TLR2) surface protein expression on both classical and CD16+ monocytes assessed at both Post and 1-h Post compared with Pre (p<0.05 for all); ii) significantly lower levels of plasma tumour necrosis factor (TNF)-alpha at 1-h Post (p<0.05 vs. Pre); and iii) significantly lower LPS-stimulated TNF-alpha release in whole blood cultures at 1-h Post (p<0.05 vs. Pre).  There were no differences between T2D and age-matched control participants in these responses to exercise (all main effects of time, p<0.05). In conclusion, the results of this study provide evidence that a single session of low-volume HIIT has direct immunomodulatory effects and supports the potential anti-inflammatory benefits of this type of exercise for people with, and without, T2D.     iv  Preface The design of this research study was developed by myself and my supervisor, Dr. Jonathan Little. Date collection was completed by myself, Ms. Monique Francois, and Dr. Jonathan Little. Participants with type 2 diabetes (T2D) were recruited from a larger 12-week exercise training intervention (ClinicalTrials.gov Identifier: NCT02251301) and completed the experimental testing to collect data for this thesis during the third week of training. The experimental exercise trials were completed following 48 hours of rest from four sessions of high-intensity interval training (HIIT) cycling familiarization. Age-matched normoglycemic healthy control participants were recruited from the local community via poster advertisements and word of mouth. Ethics for this study was approved by the UBC Clinical Research Ethics Board, H14-01636 and H14-01783 It is planned that the manuscript included as Chapter 2 of this thesis will be submitted to a peer-reviewed journal for publication. However, at the time of thesis submission, this manuscript has not been submitted anywhere for consideration for publication. A portion of the data included in this thesis was presented as a poster at the International Diabetes Federation World Diabetes Congress held in Vancouver, British Columbia on November 30 to December 4, 2015. The reference for the published abstract is:  Durrer C, Francois M, Little JP. (2015). Acute interval exercise decreases toll-like receptor 2 in healthy older adults but not in adults with type 2 diabetes. Proceedings of the World Diabetes Congress, Vancouver, BC, December 2015, 0320-P.      v  Table of Contents Abstract ......................................................................................................................................... iii Preface ........................................................................................................................................... iv Table of Contents .......................................................................................................................... v List of Tables .............................................................................................................................. viii List of Figures ............................................................................................................................... ix List of Abbreviations .................................................................................................................... x Acknowledgements ..................................................................................................................... xii 1.0 Overview .................................................................................................................................. 1 1.1 Inflammation in T2D .......................................................................................................... 2 1.1.1 Inflammation and insulin resistance ........................................................................... 2 1.1.2 Inflammation and beta-cell dysfunction ..................................................................... 3 1.1.3 Inflammation as a common thread in T2D-related complications .......................... 4 1.2 Innate Immune System: Key players in T2D-related inflammation .............................. 4 1.2.1 Toll-like Receptors and T2D ........................................................................................ 6 1.2.2 Pro-inflammatory monocyte phenotype in T2D ........................................................ 7 1.3 Anti-inflammatory effects of exercise ................................................................................ 8 1.3.1 Circulating anti-inflammatory factors produced during acute exercise ................. 9 1.3.2 TLRs and exercise ...................................................................................................... 10 1.3.3 CD16+ Monocytes and Exercise ................................................................................ 12 1.4 Research overview, aims and hypotheses ........................................................................ 16 1.4.1 Summary ..................................................................................................................... 16 1.4.2 Overall objective and approach ................................................................................ 17 1.4.1 Specific Aims and Hypotheses ................................................................................... 18 2.0 Manuscript from thesis data ................................................................................................ 20 2.1 Introduction ....................................................................................................................... 20 2.1 Methodology ...................................................................................................................... 24 2.1.1 Study Design and Participants .................................................................................. 24 2.1.2 Acute Exercise Trial ................................................................................................... 25   vi  2.1.3 Blood Samples ............................................................................................................. 26 2.1.4 Whole Blood Cultures ................................................................................................ 27 2.1.5 Flow Cytometry .......................................................................................................... 27 2.1.5 Statistical Analyses ..................................................................................................... 29 2.3 Results ................................................................................................................................ 29 2.3.1 Participant Characteristics ........................................................................................ 29 2.3.2 Leukocyte Numbers .................................................................................................... 33 2.3.3 Toll-like Receptor 2 .................................................................................................... 35 2.3.4 Toll-like Receptor 4 .................................................................................................... 37 2.3.5 Whole Blood Cultures ................................................................................................ 39 2.3.5.1 Absolute cytokine concentration ........................................................................ 39 2.3.5.2 Leukocyte corrected cytokine release ................................................................ 41 2.3.6 Plasma Cytokines ........................................................................................................ 43 2.4 Discussion ........................................................................................................................... 45 2.4.1 Effects of Exercise on TLRs ....................................................................................... 45 2.4.2 Cytokine Response ...................................................................................................... 47 2.4.3 Limitations .................................................................................................................. 49 2.4.4 Summary ..................................................................................................................... 50 3.0 Overall Discussion ............................................................................................................. 52 3.1 Impact of acute HIIT on TLRs ........................................................................................ 52 3.1.2 Reduction in TLR2 on monocytes ............................................................................. 52 3.1.2.1 Decreased Gene Expression ................................................................................ 52 3.1.2.2 Receptor Shedding. .............................................................................................. 53 3.1.2.3 Receptor Internalization ..................................................................................... 54 3.1.4 Monocyte TLR4 .......................................................................................................... 54 3.1.5 Neutrophil TLR2 and TLR4 ...................................................................................... 55 3.2 Impact of HIIT on CD16+ Monocytes ............................................................................. 56 3.3 Impact of HIIT on whole blood culture cytokine secretion ........................................... 57   vii  3.3.1 LPS-induced TNF-α response.................................................................................... 57 3.3.2 Anti-inflammatory cytokine responses ..................................................................... 58 3.4 Plasma cytokines ............................................................................................................... 59 3.5 Limitations ......................................................................................................................... 60 4.0 Future research, significance, and conclusions .............................................................. 63 4.1 Future research ................................................................................................................. 63 4.2 Significance ........................................................................................................................ 63 4.3 Conclusion .......................................................................................................................... 64 Appendices ................................................................................................................................... 93 Appendix A. Supplemental Data............................................................................................ 93     viii  List of Tables Table 1. Summary of human studies investigation toll-like receptor 2 and 4 expression in  response to a bout of acute exercise…………………………...………...………………13 Table 2. Participant characteristics………………………………………………………………29 Table 3. Leukocyte response to an acute bout of high-intensity interval training (HIIT)……….30    ix  List of Figures Figure 1. Circulating hormones and cytokines induced by a bout of acute exercise……………11 Figure 2. Simplified gating strategy for analysis of surface toll-like receptor (TLR) 2 and  4 on monocytes and neutrophils………………………………………………………...27 Figure 3. Toll-like receptor 2 expression on CD14+/CD16- classic monocytes, CD16+  monocytes, and neutrophils in response to an acute bout of high-intensity interval training (HIIT)…………………………………………………………………………...34 Figure 4. Toll-like receptor 4 expression on CD14+/CD16- classic monocytes, CD16+  monocytes, and neutrophils in response to an acute bout of high-intensity interval  training (HIIT)…………………………………………………………………………...36 Figure 5. Whole blood culture cytokine concentration from 4-H supernatants stimulated with 10ng/ml lipopolysaccharide (LPS) in response to an acute bout of high- intensity interval training (HIIT)………………………………………………………...38 Figure 6. Whole blood culture cytokine concentration, corrected for total leukocyte numbers,  from 4-H supernatants stimulated with 10ng/ml lipopolysaccharide (LPS) in response  to an acute bout of high-intensity interval training (HIIT)……………………………...40 Figure 7. Circulating plasma cytokine concentration in response to an acute bout of high- intensity interval training (HIIT)………………………………………………………..42    x  List of Abbreviations T2D  Type 2 Diabetes Mellitus HIIT   High-intensity interval training T1D  Type 1 Diabetes IL  Interleukin CRP  C-reactive protein IRS-1  Insulin receptor substrate protein 1 GLUT4 Glucose transporter type 4 JNK  c-Jun NH2-terminal kinase IκB  Inhibitor of kappa B IKK  Inhibitor of kappa B kinase TNF-α  Tumor necrosis factor-α TLR  Toll-like receptor ROS  Reactive oxygen species AGEs  Advanced glycation end-products NK  Natural killer MyD88 Myeloid differentiation factor 88 TRIF  Toll-interleukin-1 receptor domain-containing adapter-inducing interferon-β NF-κB  Nuclear factor kappa-light-chain-enhancer of activated B cells LPS  Lipopolysaccharide Pam  Pam3CSK4 CD  Cluster of differentiation mRNA  Messenger RNA VLA-4  Very late antigen-4 VCAM-1 Vascular cell adhesion molecule-1 VO2PEAK Peak oxygen uptake VO2  Oxygen uptake VCO2  Carbon dioxide output   xi  HR  Heart rate RER  Respiratory exchange ratio ECG  Echocardiogram MFI  Median fluorescence intensity PI  Propidium iodide FMO  Florescence minus one HSP  Heat shock protein GM-CSF Granulocyte macrophage colony-stimulating factor sTLR2  Soluble TLR2 MMP  Matrix metalloproteinase ADAM A disintegrin and metalloproteinase     xii  Acknowledgements First and foremost, I would like to thank my supervisor, Jonathan Little, for being an incredible friend and mentor for me. You showed me that you can work hard and play hard, as long as you have enough coffee. You lead by example, and make it hard to complain about long hours in the lab as you are often there working with us long after the sun goes down. You have had a huge impact on my life and I can’t imagine a better supervisor. My committee, Dr. Jenkins and Dr. Foster. I appreciate the guidance and knowledge. EMIL, I am grateful for all of you. Emily, thanks for keeping me organized and on track, it’s been much more hectic since you left. Monique, I could’ve never done this without the tremendous amount of work you do. Julianne, always so happy and helpful to be around. Svetlana, my go-to person in the wet lab. I could always count on you if I needed help. Etienne, always good for some comic relief, thanks for keeping me relatively sane. Courtney, you bring so much energy into the lab. Helena, you’ve been an awesome partner in the lab. You made running these experiments much more enjoyable. Mary, you use our coffee machine so much you belong in this group too. Thank you for all the support and encouragement you’ve given me since I started working with Jon. You have really been a positive figure for me.  To the guys back at 1293 Centennial: Pat, Reid and Kyle. Although you probably delayed the completion of this thesis, you made the last two years a lot of fun. Can’t imagine a better group of guys to live with. And finally, Mom and Dad. From the countless dinners to the numerous other times you’ve been there for me. Thank you for always being so supportive.      1  1.0 Overview Diabetes is one of the most prevalent metabolic disorders in the world. In 2011, an estimated 366 million people worldwide were living with the disease with a projected increase of ~50% by 2030 (Whiting, Guariguata, Weil, & Shaw, 2011). The criteria for diabetes diagnosis includes one of the following: fasting blood glucose ≥7.0 mmol/l, blood glucose of ≥11.1 mmol/l 2-hour post consumption of a 75 gram glucose load, or haemoglobin A1C ≥6.5% (Canadian Diabetes Association). Diabetes comes in two main forms: type 1 diabetes (T1D), characterized by an auto-immune mediated destruction of the pancreatic beta-cells, and type 2 diabetes (T2D), characterized by insulin resistance and pancreatic beta-cell dysfunction. Approximately 95% of diabetes cases are T2D (National Diabetes Statistics Report, 2014), which is the focus of this thesis. In Canada alone there are >2.5 million people living with T2D (Whiting et al., 2011). An aging population, rising obesity rates, physical inactivity, and unhealthy diets are expected to increase this number to 3.6 million by 2030 (Whiting et al., 2011). This widespread presence of diabetes does not come without burden to the Canadian economy. In a recent report commissioned by the Canadian Diabetes Association, the economic impact of diabetes is projected to increase from $6.3 billion annually in the year 2000 to $16.9 billion annually by 2020 (Doucet & Beatty, 2010). It is also worthy to note that this projection was based on the assumptions that the annual incidence of diabetes will be lower than it has been in the past and that the cost of healthcare services will remain unchanged until 2020. Consequently, the economic impact of diabetes in Canada may be much larger than anticipated.    2  1.1 Inflammation in T2D The hallmark pathophysiology of T2D is insulin resistance in peripheral tissues (e.g., skeletal muscle, liver, adipose) and progressive beta-cell dysfunction. In recent years, it has become increasingly recognized that T2D is also characterized by a state of chronic low-grade inflammation. As such, it has been labelled as an inflammatory disease (Shoelson & Donath, 2011). It was first suggested that T2D may be associated with abnormalities in the innate immune system when elevated levels of circulating interleukin (IL)-6, C-reactive protein (CRP), and other acute-phase reactants were detected in patients with T2D compared to healthy controls (Pickup, Mattock, Chusney, & Burt, 1997). Since then, a number of prospective and cross-sectional studies have investigated various markers of inflammation in T2D, and confirmed the early findings of Pickup and colleagues (Herder et al., 2005; Spranger et al., 2003). Furthermore, it has been shown that elevated levels of IL-6, CRP, and IL-1β are predictive of future development of T2D (Buring, Pradhan, Manson, Rifai, & Ridker, 2001; Spranger et al., 2003). The elevated level of CRP observed is particularly significant as it has been shown to be an independent risk factor for cardiovascular disease (Parrinello et al., 2015), suggesting that inflammation may be linked with the leading cause of death in people with T2D.  1.1.1 Inflammation and insulin resistance Inflammation plays a key role in both the progression of T2D and the development of diabetes complications, including cardiovascular disease, nephropathy, neuropathy, and retinopathy (Duarte, Silva, Rosales, Lopes de Faria, & Lopes de Faria, 2013; Duksal, Tiftikcioglu, Bilgin, Kose, & Zorlu, 2016; 2015; Haffner, 2006; Navarro & Mora, 2006). Normal insulin signalling in key metabolic tissues (e.g., skeletal muscle, liver, adipose) involves the binding of insulin   3  to the insulin receptor, which results in tyrosine phosphorylation of insulin receptor substrate protein 1 (IRS-1) and eventually translocation of glucose transporter type 4 (GLUT4) to the plasma membrane (Emanuelli, Kahn, & Taniguchi, 2006). Activation of pro-inflammatory serine kinase c-Jun NH2-terminal kinase (JNK) also causes phosphorylation of IRS-1, however this occurs exclusively on serine residues that directly interfere with tyrosine phosphorylation resulting in impaired insulin signalling and action (Aguirre, Uchida, Yenush, Davis, & White, 2000). The pro-inflammatory kinase inhibitor of kappa B (IκB) kinase (IKK) is also implicated in the development of insulin resistance as inhibition of IKK by administration of high-dose salicylates has been shown to improve both fasting and postprandial hyperglycemia in patients with T2D (Hundal et al., 2002). JNK and IKK signalling pathways are activated by inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and IL-6, providing molecular links between chronically elevated circulating cytokines and insulin signalling impairment, thereby perpetuating insulin resistance (Calle & Fernandez, 2012).  1.1.2 Inflammation and beta-cell dysfunction Chronic inflammation is also implicated in promoting beta-cell dysfunction and destruction in the pancreas of individuals with T2D. Evidence of islet inflammation in T2D is presented via increased islet and beta-cell expression of the pro-inflammatory cytokine IL-1β (Maedler et al., 2002) as well as increased numbers of macrophages (Ehses et al., 2007). A high glucose environment, typical of T2D, has been shown to induce expression of the pro-inflammatory cytokine IL-1β in monocytes (Dasu, Devaraj, & Jialal, 2007). IL-1β is implicated in both the destruction and dysfunction of pancreatic β-cells (Bendtzen et al., 1986; Kaneto et al., 1995). The combination of elevated glucose and free fatty acids seen in T2D can also induce inflammatory pathways via stimulation of toll-like receptors (TLRs) (Dasu & Jialal, 2011).   4  Rodent models have demonstrated that absence of TLR2 and TLR4 protect mice from the insulin resistance and β-cell dysfunction induced by a high-fat diet (Ehses et al., 2010; Tsukumo et al., 2007). Furthermore, TLR2 and TLR4 activated macrophages have been shown contribute to islet pancreatic islet inflammation and impair β-cell function via suppression of insulin gene expression (Nackiewicz et al., 2014).  1.1.3 Inflammation as a common thread in T2D-related complications Insulin resistance, hyperglycemia and T2D are linked to various macrovascular and microvascular complications. Compared to age-matched controls, patients with T2D or insulin resistance are at a much higher risk for the occurrence of cardiovascular ischemia, myocardial infarction, and strokes (Singleton, Smith, Russell, & Feldman, 2003). Among the microvascular complications attributed to T2D are peripheral neuropathy, nephropathy, and retinopathy. Both macro- and microvascular complications are thought to be caused by a combination of reduced vascular reactivity leading to endothelial injury and tissue ischemia, as well as the direct cellular injury induced by reactive oxygen species (ROS) and advanced glycation end-products (AGEs) (Singleton et al., 2003). Inflammation represents a common thread among these vascular complications as heightened inflammation (perhaps directly caused by hyperglycemia; (Dasu & Jialal, 2011; Dasu, Devaraj, Zhao, Hwang, & Jialal, 2008) is mechanistically linked to endothelial dysfunction, ROS, and AGEs (Esposito et al., 2002).  1.2 Innate Immune System: Key players in T2D-related inflammation As discussed above, Pickup and colleagues (Pickup et al., 1997) were first to link over activation of innate immune system with T2D pathophysiology. Unlike the adaptive immune system, the innate immune system consists of various mechanisms of defense that are able to respond to infection immediately and in a non-specific manner. These mechanisms consist of   5  both anatomical barriers as well as cellular responses. Cellular responses to infection are initiated by recognition of conserved molecular components of pathogens. These pathogen-associated molecular patterns are recognized by intracellular or cell surface receptors called pattern recognition receptors, which are expressed on various types of leukocytes. Toll-like receptors (TLRs) are one of many different families of pattern recognition receptors and have been implicated in metabolic dysfunction and T2D pathogenesis (Dasu, Ramirez, & Isseroff, 2012). In circulating blood, leukocytes can be divided into three main subsets: monocytes, granulocytes, and lymphocytes. Monocytes and granulocytes both stem from common myeloid progenitor cells, and are generally the first cells to respond to invading pathogens. Monocytes make up approximately 5-10% of circulating leukocytes and are comprised of three different subsets (see section 1.1.2 for further details) (Owen, Punt, Stranford, Jones, & Kuby, 2013). These cells are considered primary producers of the IL-6, TNF-α, and IL-10 in stimulated whole blood (Smits, GRUnberg, Derijk, Sterk, & Hiemstra, 1998). Monocytes that migrate into tissues can differentiate into macrophages, which appear to be the major sources of inflammatory factors that are implicated in the development of insulin resistance (Olefsky & Glass, 2010). The majority of granulocytes in circulation are neutrophils (>95%), which also constitute the largest subset of circulating leukocytes (~50-70%) (Owen et al., 2013). Neutrophils express a wide range of PRRs and are capable of producing both pro- and anti-inflammatory cytokines upon stimulation (Cassatella, Jaillon, Costantini, & Mantovani, 2011). Lymphocytes originate from lymphoid precursors and include a diverse group of cells including T cells, B cells and natural killer (NK) cells. T and B cells are principally responsible for adaptive immune responses whereas NK cells are involved in innate immune responses to viral infections (Owen et al., 2013). Over-activation of cells in the innate immune system is   6  hypothesized to perpetuate a state of chronic low-grade inflammation in T2D (Dasu et al., 2007; Dasu et al., 2008; Dasu, Devaraj, Park, & Jialal, 2010a; Dasu et al., 2012; Pickup et al., 1997). 1.2.1 Toll-like Receptors and T2D Given the role of inflammation in both the development of insulin resistance and the progression of T2D-related complications, understanding the potential cellular mediators of innate immune system activation in T2D is important. TLRs are evolutionary preserved pattern-recognition receptors that are primarily expressed on immune cells (Takeda & Akira, 2004). Responsible for regulating the innate immune response, TLRs are capable of binding to conserved pathogen associated molecular patterns and initiating a signalling cascade leading to the activation of downstream adaptor molecules. The two most well-known adaptor molecules are myeloid differentiation factor 88 (MyD88) and Toll-interleukin-1 receptor domain-containing adapter-inducing interferon-β (TRIF) (Woolard & Kevil, 2015). Almost all TLRs signal through MyD88 whereas only toll-like receptor 3 and 4 (TLR3 & TLR4) signal through TRIF (Yamamoto et al., 2002). Signaling through MyD88 and TRIF ultimately results in activation of the classic inflammatory transcription factor nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and subsequent increase in expression of cytokines such as TNF-α, IL-12, IL-6, and IL-1β (Kumar, Kawai, & Akira, 2009; Takeda & Akira, 2004). Dasu et al. (2008) were the first to demonstrate direct involvement of TLRs in T2D-related inflammation. Their work demonstrated that exposure of cultured monocytes to high glucose increased TLR2 and TLR4 surface protein expression and enhanced the basal release of pro-inflammatory cytokines (Dasu et al., 2008). These findings appear to translate to diabetes in vivo as studies have reported that individuals with T2D have elevated CD14+ monocyte TLR2   7  and TLR4 expression and elevated release of IL-1β, IL-6, IL-8, and TNFα both basally and upon stimulation with lipopolysaccharide (LPS) and Pam3CSK4 (Pam), when compared to healthy controls (Dasu et al., 2010a). As such, an increase in monocyte TLR2 and TLR4, potentially driven by the direct metabolic consequence of the disease (i.e., high glucose), are hypothesized to perpetuate chronic low-grade inflammation in T2D (Dasu et al., 2012).  1.2.2 Pro-inflammatory monocyte phenotype in T2D In addition to elevated TLRs, there is also evidence that monocyte subsets may be skewed towards a more pro-inflammatory profile in T2D. Monocytes can be categorized as classic, intermediate, and non-classical with the use of immunofluorescence analysis to determine cell surface expression of CD14 and CD16. Classic, intermediate, and non-classical monocyte subsets are distinguished by cell surface expression of CD14++/CD16-, CD14++/CD16+, and CD14+/CD16++, respectively (Ziegler-Heitbrock et al., 2010). For the purposes of this thesis, all CD14+/CD16- monocytes will be referred to as classical monocytes while intermediate and non-classical monocytes expressing CD16 will be grouped together and referred to as CD16+ monocytes in accordance with the recent consensus on the nomenclature of monocytes in blood (Ziegler-Heitbrock et al., 2010). It has been demonstrated that CD16+ monocytes produce higher levels of both TNF-α mRNA and protein compared to classical monocytes when stimulated with the same concentration of LPS (Belge et al., 2002; Frankenberger, Sternsdorf, Pechumer, Pforte, & Ziegler-Heitbrock, 1996). Furthermore, CD16+ monocytes show a blunted production of the anti-inflammatory cytokine IL-10 (Belge et al., 2002). In addition to cytokine production, CD16+ monocytes are reported to have elevated surface expression of TLR2 and TLR4 compared to classical monocytes, although these findings have not been confirmed in a T2D population (Golovkin et al., 2013; Skinner, MacIsaac, Hamilton, &   8  Visvanathan, 2005). For these reasons, CD16+ monocytes are widely considered to be “pro-inflammatory” monocytes.  CD16+ monocytes have been reported to be elevated in various inflammatory disease states (Hanai, 2008; Ryba-Stanisławowska, Myśliwska, Juhas, & Myśliwiec, 2015; Schlitt et al., 2004). As such, it would be expected that the same elevated pro-inflammatory monocyte profile would be seen in T2D, however, research in this area is limited and contradictory. Terasawa et al. (2015) reported a significantly higher percentage of CD16+ monocytes in patients with T2D compared to people with impaired or normal glucose tolerance. In contrast, Fadini et al. (2013) only show a reduction in classical monocytes in T2D patients with nephropathy with no differences in CD16+ monocytes. Horvath et al. have also shown elevated CD16 surface protein expression on CD14+/CD16+ monocytes in patients with T2D compared with normoglycemic controls (Horvath et al., 2013). The disparity in conclusions outlines a need for further investigation into monocyte subsets in T2D. 1.3 Anti-inflammatory effects of exercise It has long been established that exercise has anti-inflammatory effects, and therefore, can aid in the prevention of chronic inflammatory diseases (Petersen & Pedersen, 2005; Mastana et al., 2011; Pedersen, 2006). Exercise is already recommended as one of the primary treatments to ameliorate symptoms associated with T2D. Although some of the anti-inflammatory effects of exercise are likely associated with changes in body composition over the course of a longer-term training program, there are many mechanisms by which exercise exerts a direct anti-inflammatory effect independent of weight loss (Balducci et al., 2010). One of such mechanisms works through the exercise-induced production of circulating anti-inflammatory factors, which include the myokine IL-6, cortisol, and epinephrine.   9  1.3.1 Circulating anti-inflammatory factors produced during acute exercise It is now well-established that plasma IL-6 is increased in response to aerobic-based exercise without muscle damage (Drenth et al., 1995a; Ostrowski, Rohde, Zacho, Asp, & Pedersen, 1998a). Evidence suggests that contracting skeletal muscle is the source of IL-6, making IL-6 the most well-characterized myokine (Steensberg et al., 2000a).  IL-6 has been shown to suppress LPS-induced production of TNFα and IL-1β by peripheral blood mononuclear cells (PBMCs) in vitro (Schindler et al., 1990). Furthermore, IL-6 is known to induce the production and release of several anti-inflammatory cytokines including interleukin-1 receptor antagonist (IL-1RA) and IL-10 as well as soluble TNF-α receptors, which act as competitive inhibitors for TNFα (Steensberg, Fischer, Keller, Møller, & Pedersen, 2003; Tilg, Dinarello, & Mier, 1997). Together this has led to the hypothesis that exercise-induced release of IL-6 from contracting skeletal muscle promotes in an anti-inflammatory response characterized by an immediate rise in IL-6 (in the absence of TNF-α) followed by a delayed (1-2 hr) increase in anti-inflammatory IL-10 and IL1-RA (Petersen & Pedersen, 2005).  The impact of acute exercise on circulating IL-6 is positively related to both exercise intensity and duration (Fischer, 2006). High-intensity exercise, by recruiting more muscle mass and depleting more muscle glycogen, may lead to a more robust increase in circulating IL-6 (Fischer, 2006). Similar mechanisms are likely involved with the greater IL-6 induction seen with longer duration exercise (i.e., >2 hours; (Fischer, 2006)), although a greater overall stress response is also a possibility. In addition to IL-6, higher-intensity or prolonged exercise is also known to induce greater secretion of adrenal hormones cortisol and adrenaline (Nieman et al., 2008). Cortisol is a potent anti-inflammatory hormone and it, as well as catecholamines, have been shown to reduce LPS-stimulated production of TNF-α and IL-1β (Bergmann et al., 1999;   10  Cupps & Fauci, 1982). Thus, there are several circulating factors that are increased by prolonged and/or high-intensity exercise that may promote direct anti-inflammatory responses (Figure 1). The impact of acute exercise on circulating anti-inflammatory factors in people with T2D has not been adequately studied, but evidence does suggest that exercise of sufficient intensity and/or duration can elicit an IL-6 response in a model of low-grade inflammation (Starkie, Ostrowski, Jauffred, Febbraio, & Pedersen, 2003). Interestingly, walking, which is the commonly prescribed exercise mode for people with T2D, does not appear to stimulate an increase in plasma IL-6 (or the subsequent IL10 and IL1RA response; (Morettini, Storm, Sacchetti, Cappozzo, & Mazzà, 2015)). This suggests that lower intensity exercise, although clearly beneficial for T2D patients (Hill, 2005), may not be optimal for reducing inflammation.   1.3.2 TLRs and exercise The anti-inflammatory effects of exercise also extend beyond the production of putative circulating anti-inflammatory factors. Cross-sectional studies support the idea that monocyte TLR expression, both at the cell surface and mRNA level, is lower in people who are more physically active (Mastana et al., 2011). This is associated with a reduction in cytokine production upon stimulation with LPS (Stewart et al., 2005). Following up on these findings, studies have demonstrated reduced TLR1, TLR2 and TLR4 expression on monocytes following an acute bout of extended strenuous exercise (Lancaster et al., 2005; Oliveira & Gleeson, 2010a; Simpson et al., 2009a). Furthermore, Lancaster et al. (2005) demonstrated that prolonged exercise resulted in a reduced upregulation of co-stimulatory      11    Figure 1. Circulating hormones and cytokines induced by a bout of acute exercise. Exercise has been shown to induce an increase in various hormones and cytokines that could have potentially anti-inflammatory effects. Adapted from: (Petersen & Pedersen, 2005; Van Soeren, Sathasivam, Spriet, & Graham, 1993; Powell, Dileo, Roberge, Coca, & Kim, 2015; 2014)  molecules and production of cytokines in monocytes following stimulation with TLR ligands. The results of studies examining immune cell TLR expression following acute exercise are summarized in Table 1. Taken together, it is clear that acute exercise can suppress the function of TLRs although the majority of the research done on this topic has focused on prolonged, strenuous exercise, suggesting that there may be a threshold intensity and/or volume of   12  exercise to elicit these direct cellular anti-inflammatory impacts of exercise. There have been no studies, to my knowledge, in people with T2D.  The physiological mechanism responsible for the post-exercise reduction in TLR expression has yet to be determined, but it has been suggested that anti-inflammatory cytokines, stress hormones, and/or heat shock proteins could possibly be responsible (Gleeson, McFarlin, & Flynn, 2006a). Although the reduction in TLR expression in response to exercise may be relatively short-lived (Simpson et al., 2009a), a sustained reduction in basal TLR expression as a result of exercise training has been demonstrated (Robinson et al., 2015; Stewart et al., 2005) suggesting both acute and chronic anti-inflammatory potential. Given that the inflammatory responses to high glucose in vitro and T2D in vivo are associated with increased immune cell TLR2 and TLR4 expression, it stands to reason that the potential for exercise to reduce TLR expression could be a beneficial anti-inflammatory effect in people with T2D. 1.3.3 CD16+ Monocytes and Exercise A reduced amount of pro-inflammatory monocytes, i.e. CD16+ monocytes, in response to regular exercise training is also thought to be an anti-inflammatory mechanism of exercise (Mastana et al., 2011). Although these cells make up only ~5-10% of the monocyte population, they contribute significantly to the inflammatory potential of the monocyte pool due to their pro-inflammatory nature. Evidence suggests they respond to acute exercise by mobilization from the marginal pool, as is typical of other leukocytes. However, following acute, maximal-intensity, exercise, circulating levels of CD16+ monocytes have been shown to increase to a greater degree than their classically activated CD14+/CD16- counterparts (Steppich et al., 2000). This increase in circulating CD16+ monocytes appears to be regulated by epinephrine   13  and does not persist, however, as the number of CD16+ monocytes returns to baseline levels after 20 minutes of rest (Steppich et al., 2000).     14  Table 1.        Summary of human studies investigating toll-like receptor 2 and 4 expression in response to a bout of acute exercise Reference Participants Exercise Blood sample timing Cell Type Method of TLR detection Main findings Conclusions McFarlin, B., Flynn, M., Campbell, W., Stewart, L., Timmerman, K. (2004) Trained (aged 67±5, n=10) and untrained (aged 69±5, n=10) postmenopausal women  1 rep maximum test of the bench press, lat pulldown, and knee extension Before, immediately post, 2-H post, 6-H post, and 24-H post exercise CD14+ monocytes Flow cytometry -No change in TLR4 expression Acute resistance exercise does not affect TLR4 expression in postmenopausal women  Lancaster, G. Qamar K., Drysdale, P., Wallace, F., Jeukendrup, A., Drayson, M., & Gleeson, M. (2005) Moderate-to-well endurance-trained males aged 25±1 years (n=11) 1.5 hours of cycling @ ~65% VO2max with a room temperature of 34°C Before, immediately post, and 2-H post exercise CD14+ monocytes Flow cytometry -~48% reduction immediately post and ~56% reduction 2-H post exercise of TLR2 expression -~52% reduction immediately post and ~50% reduction 2-H post exercise of TLR4  Acute prolonged exercise in the heat reduces TLR2 and 4 expression on monocytes Gleeson, M., McFarlin, B. & Flynn, M. (2006) Endurance trained males aged 20±2 years (n=11) 2.5 hour cycle @ 60% VO2max Before, immediately post, and 1-H post exercise CD14+ monocytes Flow cytometry -~36% reduction immediately post and ~59% reduction 1-H post exercise of TLR2 -~50% reduction 1-H post exercise of TLR4 Acute prolonged exercise reduces TLR2 and 4 expression on monocytes Simpson R., McFarlin, B., McSporran, C., Guillaume, S., Briain, H., Guy, K. (2009) Moderately trained males aged 26.4±6.7 years (n=15) 45 minute run @ 75% VO2max Before, immediately post, and 1-H post exercise CD14++/CD16-, CD14+/CD16++, CD14++/CD16+ monocytes Flow cytometry -12% reduction of TLR2 on CD14+/CD16+ cells immediately post exercise -12% reduction of TLR4 1-H post exercise on CD14+ cells -34% increase in TLR4 on CD14+/CD16+ cells Acute moderate to vigorous exercise reduces TLR2 and 4 on classical monocytes but increases TLR4 in CD16+ monocytes    15  Reference Participants Exercise Blood sample timing Cell Type Method of TLR detection Main findings Conclusions Oliviera, M. & Gleeson, M. 2010 Healthy endurance trained males aged 25±5 years (n=9)  1.5 hour cycle @ 75% VO2peak Before, immediately post, 1-H post, 2-H post, and 24-H post exercise CD14+ monocytes Flow cytometry -No change of TLR2 expression -32% reduction and 45% reduction of TLR4 immediately post exercise and 1-H post exercise, respectively Acute prolonged exercise reduces TLR4 on monocytes Booth, S., Florida-James, G., McFarlin, B., Spielmann, G., O’Connor, D., & Simpson, R. (2010) Club-level athletes aged 32.1±4.2 (n=8) 60km cycling time trial Before, immediately post, and 1-H post CD14++/CD16-, CD14+/CD16++, CD14++/CD16+ monocytes Flow cytometry -41% increase of TLR2 expression immediately post exercise and a 53% increase 1-H post exercise -84% increase of TLR4 expression 1-H post exercise Acute strenuous exercise increases TLR2 and TLR4 expression Fernandez-Gonzalo, R., Paz, J., Rodriguez-Miguelez, P., Cuevas, M., & González-Gallego, J. (2012) Active men aged 22.4±2.01 (n=20) 12 sets of 10 repetitions of eccentric squats @ 60% maximal voluntary isometric contraction Before, immediately post, 2-H post exercise Peripheral blood mononuclear cells Reverse transcription and quantitative real-time polymerase chain reaction, western blot -~27% increase of TLR4 mRNA immediately post and ~35% increase 2-H post exercise -~40% increase of TLR4 protein immediately post and ~80% increase 2-H post exercise Acute moderate intensity resistance training increases TLR4 mRNA and protein Fernandez-Gonzalo, R., Paz, J., Rodriguez-Miguelez, P., & González-Gallego, J. (2014) Active women aged 22.5±1.34 (n=20) 12 sets of 10 repetitions of eccentric squats @ 60% maximal voluntary isometric contraction Before, immediately post, 2-H post exercise Peripheral blood mononuclear cells Reverse transcription and quantitative real-time polymerase chain reaction, western blot -~80% increase of TLR4 mRNA immediately post and ~110% increase 2-H post exercise -~25% increase of TLR4 protein immediately post and ~30% increase 2-H post exercise Acute moderate intensity resistance training increases TLR4 mRNA and protein           16   Interestingly, it seems that the cumulative effect of exercise training leads to a reduction in the circulating levels of CD16+ monocytes, and is thought to contribute to the anti-inflammatory effects of exercise (Timmerman, Flynn, Coen, Markofski, & Pence, 2008). It has been demonstrated that an increase in glucocorticoids in circulation leads to a decrease in CD16+ monocytes (Fingerle-Rowson, Angstwurm, Andreesen, & Ziegler-Heitbrock, 1998). CD16+ monocytes express higher levels of adhesion molecules CD11d and Very Late Antigen-4 (VLA-4) which act as ligands for vascular cell adhesion molecule-1 (VCAM-1) (Steppich et al., 2000). Based on these observations CD16+ monocytes are believed to infiltrate the blood vessel wall more readily and contribute to the progression of atherosclerosis (Yang, Zhang, Yu, Yang, & Wang, 2014a). As such, the potential for exercise to reduce the amount of circulating CD16+ monocytes may be linked to improved cardiovascular health outcomes. As high-intensity training, including high-intensity interval training, has been shown to induce a transient increase in circulating cortisol levels (Tanner, Nielsen, & Allgrove, 2014), it is reasonable to suggest that an acute bout of interval training would lead to a reduction in circulating CD16+ monocytes which, as a result, would have an anti-inflammatory effect. This hypothesis has, to my knowledge, not been tested. 1.4 Research overview, aims and hypotheses 1.4.1 Summary T2D is characterized by a heightened level of pro-inflammatory cytokines and acute phase reactants. This chronic inflammation appears to play a direct role in the pathogenesis of insulin resistance and beta-cell dysfunction and is linked to diabetes complications. The pro-inflammatory nature of T2D can be seen at the cellular level, as blood monocytes in particular   17  have been shown to express elevated levels of pro-inflammatory TLRs and release greater amounts of pro-inflammatory cytokines. These cellular changes may be related to greater numbers of CD16+ monocytes, which are considered to be of a pro-inflammatory phenotype. Exercise has been shown to have anti-inflammatory effects, ranging from the release of anti-inflammatory cytokines and the down-regulation of TLRs to the reduction in circulating CD16+ cells. However, whether exercise can elicit these direct anti-inflammatory effects in immune cells of people with T2D has not been previously studied. 1.4.2 Overall objective and approach The overall objective of my thesis is to examine the direct effect of acute exercise on leukocyte inflammatory phenotype in patients with T2D. To accomplish this, a number of cellular and molecular markers of inflammation will be examined by flow cytometry, cell culture, and plasma of blood samples obtained from people with T2D and healthy age-matched controls before and after a single bout of exercise. I will be using a model of high-intensity interval training (HIIT) because previous research has shown this to be a potent stimulus for inducing cardiometabolic benefits and HIIT is becoming a popular exercise modality for the prevention and treatment of T2D (Kilpatrick, Jung, & Little, 2014; Little et al., 2011; Little & Francois, 2014). The impact of HIIT on inflammation is currently unclear but the potential for vigorous exercise to induce a heightened IL-6, epinephrine, and cortisol response (Figure 1; Petersen & Pedersen, 2005) suggest it could have unique anti-inflammatory potential. The following aims will be addressed:    18  1.4.1 Specific Aims and Hypotheses Aim #1:  To determine the impact of a single session of HIIT on TLR2 and TLR4 expression on monocytes and neutrophils in individuals with T2D.  Hypothesis 1: I hypothesize that TLR expression will be lower following a bout of acute HIIT.  Aim #2: To examine the effect of a single session of HIIT on the percentage of CD16+ monocytes versus classical CD14+/CD16- monocytes in individuals with T2D.  Hypothesis 2: I hypothesize that the proportion of CD16+ monocytes will decrease following an acute bout of HIIT. Aim #3: To examine immune cell function by assessing lipopolysaccharide (LPS)-induced cytokine secretion in whole blood cultures from samples obtained both before and after a bout of acute HIIT in individuals with T2D.  Hypothesis 3: I hypothesize that LPS-induced pro-inflammatory cytokine secretion will be reduced, and anti-inflammatory cytokine secretion increased, following a single session of HIIT.  Aim #4: To explore potential circulating factors that regulate the leukocyte responses to acute HIIT in individuals with T2D.  Hypothesis 4: I will test the hypothesis that changes in circulating cytokines will accompany the changes in immune cell phenotype following a single session of HIIT. Aim #5: To explore whether T2D patients differ from physically active age-matched control participants.   19  Hypothesis 5: I hypothesize that there will be no difference in response to a single session of HIIT between T2D patients and physically active age-matched control participants.     20  2.0 Manuscript from thesis data 2.1 Introduction  Chronic low-grade inflammation, characterized by increases in basal leukocyte numbers, circulating pro-inflammatory cytokines and/or acute phase reactants is implicated in the pathogenesis of obesity, insulin resistance, and type 2 diabetes (T2D) (Shoelson & Donath, 2011). While the underlying cause of inflammation has not yet been fully elucidated, studies have shown elevation in surface protein expression of toll-like receptors [TLRs; Dasu et al., 2010a] and augmented release of pro-inflammatory cytokines by immune cells isolated from patients with T2D compared to age-matched normoglycemic controls (Dasu et al., 2008; Kumar, Kawai, & Akira, 2011), implicating altered immune cell phenotype and function with the inflammatory pathology in T2D. TLRs are conserved pattern-recognition receptors that recognize a variety of exogenous and endogenous pathogens to coordinate innate immune responses (Mastana et al., 2011). Increased TLR2 and TLR4 expression and the resulting pro-inflammatory environment are associated with a cluster of cardiometabolic risk factors, including insulin resistance, T2D and atherosclerosis (Dasu & Jialal, 2011; Dasu et al., 2010a; Huang et al., 2012).  In addition to elevated TLRs, there is also evidence that monocyte subsets may be skewed towards a more pro-inflammatory profile in T2D. Monocytes can be categorized as classic, intermediate, and non-classical with the use of immunofluorescence analysis to determine cell surface expression of CD14 and CD16 (32). CD14++/CD16- “classical” monocytes are regarded as anti-inflammatory whereas it has been demonstrated that CD16+, i.e. intermediate and non-classical, monocytes produce higher levels of both tumor necrosis factor (TNF)-α mRNA and protein compared to classical monocytes when stimulated with the same   21  concentration of bacterial lipopolysaccharide (LPS; reviewed in: Ziegler-Heitbrock et al., 2010). CD16+ monocytes also show a blunted production of the anti-inflammatory cytokine interleukin IL-10 (Booth et al., 2010). Additionally, CD16+ monocytes are reported to have elevated surface expression of TLR2 and TLR4 compared to classical monocytes (Golovkin et al., 2013), further supporting the notion that CD16+ monocytes have a “pro-inflammatory” phenotype.  Exercise improves metabolic health and is a frontline therapy for the treatment and prevention of T2D (Colberg et al., 2010). One potent systemic benefit of regular exercise is thought to be its anti-inflammatory effects (Mastana et al., 2011). Some of the anti-inflammatory effects of regular exercise are likely attributable to a reduction in adipose tissue (Balducci et al., 2010) but there is also growing evidence that acute exercise, in the absence of weight loss, can directly impact immune cell phenotype and alter systemic inflammatory mediators [for review see (Mastana et al., 2011; Pedersen, 2006)]. The ability of exercise to reduce monocyte TLRs is one hypothesized mechanism through which acute exercise may create a systemic anti-inflammatory mileau (Flynn & McFarlin, 2006). Most studies have shown reduced monocyte TLR2 and TLR4 expression after acute endurance exercise (Gleeson et al., 2006a) but there are reports of increased monocyte TLRs immediately and 1 hr following a 60 km cycling ergometer time trial (Booth et al., 2010). The influence of exercise on TLR expression on other distinct immune cells, including granulocytes/neutrophils, has not been adequately studied but our initial studies show that short-term exercise training can reduce TLR expression on neutrophils in addition to monocytes in individuals with obesity (Robinson et al., 2015), suggesting a systemic impact of exercise for lowering leukocyte TLRs. Research also suggests that regular exercise training can lead to a reduction in the ratio of CD16+ “pro-inflammatory”   22  monocytes to classical monocytes (Timmerman et al., 2008), indicating that exercise might promote skewing towards a more anti-inflammatory monocyte profile but this has not been tested in T2D.  The release of IL-6 from contracting skeletal muscle is also thought to mediate some of the anti-inflammatory effects of a bout of aerobic exercise (Pedersen, 2006). The overall anti- versus pro-inflammatory impact of IL-6 is still debated (Rincon, 2012) but exercise-induced IL-6 production is believed to create an anti-inflammatory environment during the immediate post-exercise recovery period by directly acting on immune cells (Pedersen, 2006) and/or by promoting the subsequent release of anti-inflammatory cytokines, such as IL-10 and IL-1RA (Steensberg et al., 2003). Infusing IL-6 to the same levels as seen during exercise has been shown to blunt the induction of pro-inflammatory TNF-α following a bacterial endotoxin challenge in humans (Starkie et al., 2003), suggesting direct inhibitory effects of exercise-induced IL-6 on innate immune activation.  High intensity interval training (HIIT) has gained recent attention as a time-efficient exercise strategy for improving cardiometabolic health, providing a unique physiological stimulus compared to traditional exercise (Gibala, Little, MacDonald, & Hawley, 2012). Several studies have shown potent glucose lowering and cardiovascular health benefits of HIIT (Karstoft et al., 2013; Little et al., 2011; Little, Jung, Wright, Wright, & Manders, 2014) and a recent meta-analyses concluded that HIIT was superior to traditional continuous exercise for improving insulin sensitivity and glucose control (Jelleyman et al., 2015). These findings highlight the potential utility of HIIT as a therapeutic exercise strategy but the impact of HIIT on inflammation in T2D has not, to our knowledge, been studied. On the one hand, HIIT may be a time-efficient means to deliver vigorous exercise and by engaging more muscle fibres (Edgett   23  et al., 2013) lead to a potent IL-6 response. However, there are speculations that vigorous exercise may be pro-inflammatory in people with cardiometabolic disease (Kasapis & Thompson, 2005), even though empirical evidence showing that HIIT promotes inflammation is lacking. Further understanding of the inflammatory impact of HIIT in T2D is needed before this exercise strategy can be promoted for health benefits.  The primary purpose of this study was to examine the impact of a single bout of HIIT on indicators of cellular inflammation and circulating cytokines in people with T2D and in age-matched normoglycemic controls. We examined: 1) leukocyte numbers and expression of TLR2 and TLR4 on CD14+ monocytes, CD16+ monocytes, and CD16+ granulocytes (i.e., neutrophils) 2) circulating pro- and anti-inflammatory cytokines; and 3) ex vivo endotoxin-stimulated cytokine secretion in whole blood cultures as an index of innate immune cell activation to test the hypothesis that acute HIIT would promote anti-inflammatory effects in T2D.         24  2.1 Methodology 2.1.1 Study Design and Participants  Ten T2D patients and nine age-matched normoglycemic controls were recruited for this two-group time-series study. T2D participants were diagnosed by a physician according to CDA criteria, based on haemoglobin A1C ≥6.4, fasting plasma glucose ≥7.0 mmol/l, and/or 2-h oral glucose tolerance test glucose ≥11.1 mmol/l. All T2D participants were enrolled in the Kelowna Diabetes Program (Innes et al., 2008) and had an A1C value <8.0% [mean(SD) = 6.5(0.7)]. Descriptive characteristics are presented in Table 2. Informed consent was obtained from all subjects prior to the study, which was approved by the UBC Clinical Research Ethics Board (H14-01636). Participants underwent baseline fitness testing using a ramp protocol (15 W/min) on an electronically-braked cycle ergometer (Lode Excalibur, Groningen, The Netherlands) to determine peak power output (defined as the highest Watts achieved) and peak oxygen uptake (VO2PEAK). Expired gas was collected via a mouthpiece (7600 Series V2 Mask, Hans Rudolph, Shawnee, KS) and oxygen uptake (VO2) and carbon dioxide output (VCO2) were determined by a metabolic cart (Parvomedics TrueOne 2400, Salt Lake City, Utah, USA), which was calibrated with a 3.0 L syringe and gases of known concentration prior to each test. Participants were instructed to pedal at a constant rate above 50 rpm for the duration of the test, which was stopped when participants could not maintain this cadence and/or volitional exhaustion. VO2PEAK was defined as the highest 30-second average VO2. Heart rate was monitored continuously (Polar Heart Rate Sensor H1, Polar, Kempele, Finland) and maximal heart rate (HR) was defined as the highest value attained during the test. Criteria for verifying maximal exertion were as follows: a peak HR of at least 90% of age-predicted maximal HR   25  (based on 220 – age) and a peak respiratory exchange ratio (RER) of at least 1.15 (Maud & Foster, 1995). T2D patients were screened for any cardiovascular abnormalities and cleared for vigorous exercise by a cardiologist via a 12-lead electrocardiogram (ECG) stress test prior to baseline fitness testing. Participants with T2D were participating in a 12-week exercise trial (ClinicalTrials.gov Identifier: NCT02251301) and this study was carried out during the third week of training. This allowed four cycling HIIT familiarization sessions to be completed prior to the acute exercise trial, which was done gradually to introduce HIIT to T2D participants and ensure completion of the prescribed HIIT protocol. Age-matched normoglycemic controls self-reported completing 150-300 minutes of light-to-moderate physical activity per week (e.g., walking, golfing) but were not participating in any structured exercise training. Sample size was calculated to detect an expected 30-50% reduction in TLR2 (Gleeson et al. 2006) and/or TLR4 (Gleeson, McFarlin, & Flynn, 2006b; Oliveira & Gleeson, 2010a) described previously on CD14+ monocytes using means and standard deviations for median fluorescence intensity (MFI) of CD14+ TLR2 and TLR4 obtained from previous work in our lab (n=25 T2D patients). Using the sample size calculator G Power (version 3.1), 10 participants were needed at 80% power with α set at 0.05 assuming a moderate correlation (r=0.5) among repeated measures.  2.1.2 Acute Exercise Trial  All participants refrained from exercise for 48 hours prior to the acute exercise trial. T2D participants maintained their normal medication schedule throughout the study, including the day of the acute exercise trial. Subjects warmed up on the cycle ergometer at 30 W for four minutes before completing a HIIT session that was based on previously published protocols   26  (Jung, Bourne, Beauchamp, Robinson, & Little, 2015; Little et al., 2011; Robinson et al., 2015) and consisted of 7 X 1-min intervals at 85% peak power output with 1-min rest periods at 15% peak power output in between. A 3-min cool down was completed after the final interval. HR data were collected continuously by 12-lead ECG and ratings of perceived exertion (RPE; CR-10; Borg, 1982) were assessed during the final 10 seconds of each interval. Exercise began at either 11:00am or 4:00pm three hours postprandial and water was provided ad libitum throughout. 2.1.3 Blood Samples  Prior to the acute exercise trial, an indwelling 21-gauge venous catheter (BD Nexiva, Sandy, UT) was inserted into an antecubital vein and kept patent with sterile saline. Venous blood samples were taken before (pre), immediately after (post) and 1 h after the exercise session. These time points were chosen to be consistent with previous studies showing exercise-induced reductions in TLRs (see Table 1) and increases in IL-6, IL-10, and IL-1RA (Steensberg et al., 2003; see Figure 1). Blood was collected into vacutainers containing EDTA and kept at room temperature (for whole blood culture experiments) or on ice (for all other parameters) for further analysis. A portion of the blood collected was centrifuged at 1550g for 15 minutes at 4⁰C with plasma frozen at -80⁰C for later analysis of glucose (via hexokinase method; Robinson et al., 2015), IL6, IL10, TNF-a (custom high-sensitivity T cell magnetic bead panel, Millipore, Massachusetts, USA) and IL1RA (custom cytokine/chemokine magnetic bead panel, Millipore, Massachusetts, USA) via MagPIX multiplex assay, as we have previously described (Robinson et al., 2015). The remainder of the blood was used for whole blood cultures and flow cytometry.    27  2.1.4 Whole Blood Cultures Whole blood cultures were prepared by diluting blood 10 times in serum-free RPMI media (Sigma) supplemented with penicillin (50 U/ml) and streptomycin (50 μg/ml) containing 5 mM glucose and seeding cells in 12x75mm polystyrene culture tubes at 540 μl per well as we have described previously (Robinson et al., 2015; Wan, Durrer, Mah, Simtchouk, & Little, 2014). At each time point, one culture tube was left unstimulated and one was stimulated with 10 ng/ml bacterial lipopolysaccharide (LPS, from Escherichia coli 055:B5; L6529, Sigma). Supernatants were collected after 4 h of incubation at 37 °C in 5% CO2 for analyses of TNF-α, IL10, and IL1RA production using MagPIX multiplex assay according to the manufacturer’s instructions.  2.1.5 Flow Cytometry  FcR blocking reagent (Cat no. 130-059-901, Miltenyi Biotec, Bergisch Gladbach, Germany) was added to 90ul of whole blood and allowed to incubate for 10 minutes at 4°C in the dark. This was followed by addition of conjugated antibodies specific for human CD14 (Vioblue®, Cat no. 130-094-364, Miltenyi Biotec), CD16 (FITC, Cat no. 130-091-244, Miltenyi Biotec), TLR2 (PE, Cat no. 130-099-016, Miltenyi Biotec), and TLR4 (APC, Cat no. 130-096-236, Miltenyi Biotec). Samples were then incubated for 10 minutes at 4°C in the dark again. Finally, 1ml of red blood cell lysis buffer (Cat no. 120-001-339, Miltenyi Biotec) was added to the samples and a final incubation step of 15 minutes at room temperature in the dark was administered. Immediately prior to analysis by the flow cytometer, 2ul of propidium iodide (PI) (Cat no. 130-093-233, Miltenyi Biotec) was added to each sample for dead cell exclusion. Samples were analyzed on a MACSQuant® Analyzer 10 flow cytometer. The flow cytometer was turned on a minimum of 30 minutes prior to analyses to enable the lasers to warm up to   28  their appropriate temperatures, per manufacturer guidelines. Calibration of the flow cytometer was performed following warm-up using Macsquant Calibration Beads (Cat no. 130-093-607, Miltenyi Biotec, Bergisch Gladbach, Germany). 10,000 monocytes, identified by scatter profile, were counted in each sample. Bank instrument settings were used to account for any drift in laser strength over time. Fluorescence minus one (FMO) controls were used to determine gating on positive and negative populations. Compensation was performed prior to analysis to control for any spillover among fluorochromes.  Monocytes, neutrophils, and lymphocytes were identified by their characteristics scatter profiles. Total leukocyte number was calculated by addition of the three sub-populations. CD14+/CD16- classical monocytes, CD16+ monocytes, CD16+ neutrophils were identified in their respective leukocyte gate based on CD14 and CD16 staining patterns. Fluorescence minus one (FMO) controls were used to determine gating on positive and negative populations. The gating strategy for identifying TLR2 and TLR4 on specific cell types is shown in Figure 2. If cell populations had less than 300 total events, TLR expression was not analyzed due to insufficient sample volume.   Figure 2. Simplified gating strategy for analysis of surface toll-like receptor (TLR) 2 and 4 on monocytes and neutrophils. Cells are first gated on expression of CD14 (classical monocytes), CD16 (neutrophils), or both (CD16+ monocytes) (Panel 1). Cell type is then   29  confirmed via forward and side scatter profile (Panel 2 and 3). Fluorescence minus-one (FMO) controls (orange) are used to determine positive TLR staining (blue; Panel 4.)  2.1.5 Statistical Analyses  Statistical analyses were performed using R. Normality was assessed using a Shapiro-Wilk test. Non-normal data was log or square-root transformed in order to reduce skewness. Values that were greater than three standard deviations away from the mean were considered statistical outliers and excluded from analysis. An unpaired t-test was used to determine baseline differences between T2D and controls. A mixed 2-factor ANOVA was used with time as a within subject factor and T2D status as a between subject factor to analyze differences in variables in response to exercise. Significance was set at p<0.05. Significant main effects of time were probed with Fisher LSD post-hoc tests. Significant interactions were probed with Holm-Bonferroni post-hoc tests. 2.3 Results 2.3.1 Participant Characteristics T2D (n=5 males, n=5 females) subjects had a higher body mass, lower VO2PEAK, and lower Wpeak compared to healthy controls (n=4 males, n=5 females) (Table 2). All participants completed the HIIT session with no issues. There were no differences in mean percent maximal HR (T2D: 81.4 ± 8.9%; HC: 83.8 ± 6.4%, p=0.52) or mean RPE (T2D: 5 ± 2; HC: 5 ± 2, p=0.46) measured during exercise between T2D and controls. As expected, T2D participants had elevated plasma glucose compared to controls (main effect of group, p<0.001; Figure 2). A single session of HIIT led to a significant decrease in plasma glucose (main effect of time,   30  p=0.01; Figure 2) with post-hoc tests revealing a significant decrease from pre to 1-H post (p=0.02 vs. Pre) and post to 1-H post exercise (p=0.02 vs. Post).                    31  Table 2. Participant Characteristics Characteristic Type 2 diabetes Healthy controls P-value Weight (kg) 99.6 ± 17.0 71.2 ± 13.6 <0.001 Height (cm) 169.4 ± 11.8 168.8 ± 7.4 0.89 BMI 34.8 ± 5.9 24.8 ± 3.6 <0.001 Age (years) 57.9 ± 5.4 55.8 ± 9.0 0.53 VO2peak (ml/kg/min) 18.9 ± 4.0 31.4 ± 4.5 <0.001 Wattpeak (Watts) 147.6 ± 34.0 189.4 ± 43.1 0.03 Metformin only (n) 7 0 NA Sulfonylurea + GLP1 Agonist 1 0 NA SGLT2 Inhibitor + GLP1 Agonist 1 0 NA DPP4 Inhibitor 1  0 NA Note. Data are means ± standard deviation.  Type 2 diabetes; n=5 males, n=5 females. Healthy controls; n=4 males, n=5 females.   32   Figure 2. Glucose concentration in response to an acute bout of high-intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X 1-min @ 85% peak power output and plasma glucose was measured via the hexokinase method. Repeated measures ANOVA revealed a significant main effect of time (p<0.05). *p<0.05 vs. Pre (Fisher LSD post-hoc). #p<0.05 vs. Post (Fisher LSD post-hoc). †A main effect of group was also detected (p<0.05).     33  2.3.2 Leukocyte Numbers The impact of a single session of HIIT on blood leukocyte numbers is presented in Table 3. There was a main effect of time for total leukocyte concentration (p<0.001) but no main effect of group (p=0.06). The total number of leukocytes in the blood increased immediately after exercise (p<0.001 vs. Pre) and then returned to pre-exercise values at one hour following exercise (p<0.001 vs. Post). There was a main effect of time (p<0.001) for classical monocyte numbers. Classical monocyte numbers were elevated immediately following exercise (Post) compared to before exercise (Pre) (p<0.001 vs. Pre) and decreased one-hour post exercise (1-H Post) compared to pre exercise (p=0.04 vs. Pre) and post exercise (p<0.001 vs. Post). There was also a main effect of time for CD16+ monocytes (p=0.003). CD16+ monocyte numbers were elevated immediately post exercise compared to both pre exercise (p=0.01 vs. Pre) and one-hour post exercise (p=0.005 vs. Post). A main effect of time was detected for neutrophil numbers (p<0.001) with post-hoc tests indicating an increase immediately post exercise compared to both pre exercise (p<0.001) and one-hour post exercise (p<0.001). There were no group effects or group X time interactions for any of the leukocyte subsets analyzed (all p>0.05).    34   Note. Data are means ± standard deviation. Type 2 diabetes; n=5 males, n=5 females. Healthy controls; n=4 males, n=5 females. *Fisher LSD post-hoc vs. Pre (time main effect, p<0.05). #Fisher post-hoc vs. Post (time main effect, p<0.05). Table 3. Leukocyte Response to an Acute Bout of High-Intensity Interval Training (HIIT) Cell Type Type 2 diabetes Healthy controls P-value Pre Post 1-H Post Pre Post 1-H Post Group Time Group X Time Classical Monocytes x 105 /ml 3.2 ± 0.40 4.5 ± 0.56* 3.1 ± 0.31# 3.2 ± 0.72 3.9 ± 1.3* 3.0 ± 0.86# 0.32 <0.001 0.11 CD16+ Monocytes x 105 /ml 0.16 ± 0.13 0.27 ± 0.19* 0.18 ± 0.11# 0.18 ± 0.11 0.21 ± 0.17* 0.11 ± 0.07# 0.68 0.003 0.08 Neutrophils x 105 /ml 29.9 ± 6.4 41.76 ± 8.7* 31.8 ± 6.2# 26.1 ± 7.11 32.9 ± 10.4* 25.2 ± 4.9# 0.07 <0.001 0.14 Lymphocytes x 105 /ml 15.9 ± 4.2 25.7 ± 10.9* 16.8 ± 4.7# 15.6 ± 3.9 26.1 ± 10.4* 15.1 ± 3.4# 0.90 <0.001 0.77 CD16+ Monocytes (%) 4.5 ± 3.5 5.4 ± 3.7 5.3 ± 3.0 4.8 ± 2.4 4.3 ± 2.0 3.5 ± 1.8 0.48 0.62 0.08 Total Leukocytes 49.5 ± 7.9 70.7 ± 12.7* 52.1 ± 8.6# 42.9 ± 13.1 58.9 ± 18.6* 43.5 ± 7.8# 0.06 <0.001 0.95   35  2.3.3 Toll-like Receptor 2 A significant main effect of time was found for TLR2 expression on classical monocytes (p=0.01). TLR2 expression on classical monocytes was decreased by ~16 % Post (p=0.007 vs. Pre) and by ~15% at 1-H Post (p=0.03 vs. Pre) compared to Pre (Figure 3). There was no effect of group for TLR2 expression on classical monocytes (p=0.38) and no interaction effect (p=0.71). TLR2 expression on CD16+ monocytes showed a similar main effect of time (p=0.007) with post-hoc tests revealing a significant decrease of 18% Post (p<0.001 vs. Pre) and by ~11% 1-H Post (p=0.04 vs. Pre) compared to Pre (Figure 2). There was no effect of group (p=0.7) or interaction (p=0.65) for TLR2 expression on CD16+ monocytes (Figure 3). An acute session of HIIT had no effect on CD16+ neutrophil TLR2 expression (p=0.11); however, there was a main effect of group with T2D expressing ~35% higher TLR2 than HC participants (p<0.001) (Figure 2).   36    Figure 3. Toll-like receptor 2 expression on CD14+/CD16- classic monocytes, CD16+ monocytes, and CD16+ neutrophils in response to an acute bout of high-intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X 1-min @ 85% peak power output and TLR2 median fluorescence intensity (MFI) was measured by flow cytometry on CD14+/CD16- monocytes (A), CD16+ monocytes (B), and CD16+ neutrophils (C). Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines. Repeated measures ANOVA revealed a significant main effect of time for CD14+/CD16- monocytes and CD16+ monocytes (all p<0.05). *p<0.05 vs. Pre (Fisher LSD post-hoc). †A main effect of group was also detected for CD16+ neutrophils (p<0.05).A) B) C)   37  2.3.4 Toll-like Receptor 4 There were no effects of time (p=0.81), group (p=0.13), or interaction (p=0.41) for TLR4 expression on classical monocytes (Figure 4). There were no significant effects of time (p=0.22) nor was there an interaction (p=0.4) for TLR4 expression on CD16+ monocytes; however, there was a main effect of group with HC having ~13% lower TLR4 expression compared to T2D participants (p=0.049). There were no effects of time (p=0.32) nor was there an interaction (p=0.8) for TLR4 expression on CD16+ neutrophils. T2D participants appeared to have a higher TLR4 expression compared to HC on CD16+ neutrophils, although this did not reach statistical significance (group main effect, p=0.069).  38   Figure 4. Toll-like receptor 4 expression on CD14+/CD16- classic monocytes, CD16+ monocytes, and CD16+ neutrophils in response to an acute bout of high-intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X 1-min @ 85% peak power output and TLR4 median fluorescence intensity (MFI) was measured by flow cytometry on CD14+/CD16- monocytes (A), CD16+ monocytes (B), and CD16+ neutrophils (C). Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines. †Repeated measures ANOVA revealed a significant main effect of group for CD16+ monocytes (p<0.05). A) B) C)   39  2.3.5 Whole Blood Cultures 2.3.5.1 Absolute cytokine concentration  There was a significant main effect of time (p=0.005) for LPS stimulated IL10 release in whole blood cultures (Figure 5). IL10 release stimulated by LPS was ~38% higher Post (p=0.001 vs. Pre) and ~25% higher 1-H Post (p=0.04 vs. Pre) compared to Pre. LPS stimulated IL1RA release also showed a main effect of time (p=0.004). IL1RA release stimulated by LPS was ~38% higher Post (p=0.005 vs. Pre) and ~6% higher 1-H Post (p=0.02 vs. Pre) compared to Pre. There was a main effect of time for LPS stimulated TNF-α release (p=0.002) with post-hoc tests revealing a ~22% increase Post (p=0.046) and ~16% decrease 1-H Post (p=0.003) compare to Pre. TNF-α release was also significantly lower (by ~32%) 1-H Post compared to immediately Post-exercise (p=0.003). There were no effects of group for LPS stimulated IL10 (p=0.33), IL1RA (p=0.61), or TNF-α (p=0.54) release nor were there any interactions (all p>0.11). No significant group, time or interaction effects were seen for unstimulated IL10, IL1RA or TNF-α release (data not shown, see Appendix I).   40   Figure 5. Whole blood culture cytokine concentration from 4-H supernatants stimulated with 10 ng/ml lipopolysaccharide (LPS) in response to an acute bout of high -intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X1-min @ 85% peak power output and IL10 (A), IL1RA (B), and TNF-α (C) and whole blood cultured in the presence of 10 ng/ml LPS. Supernatants were collected after four hours in culture and cytokines measured by Magpix ELISA. Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines. Repeated measures ANOVA revealed a significant main effect of time for IL10, IL1RA, and TNF-α concentration (all p<0.05). *p<0.05 vs Pre (Fisher LSD post-hoc). #p<0.05 vs Post (Fisher LSD post-hoc).A) B) C)   41  2.3.5.2 Leukocyte corrected cytokine release  When corrected for total leukocyte numbers, there were no effects of time for LPS stimulated IL10 (p=0.08) or IL1RA (p=0.96) release in the whole blood cultures (Figure 6). There was a main effect of time (p=0.04) for LPS-stimulated TNF-α release, with a ~20% decrease seen at 1-H Post compared to Pre (p=0.007 vs. Pre) as well as a main effect of group with T2D releasing ~35% less TNF-α than HC (p=0.035). There were no effects of group for leukocyte-corrected, LPS stimulated IL10 (p=0.91) or IL1RA (p=0.50) release in whole blood cultures. There were no effects of time for leukocyte-corrected, unstimulated IL10 (p=0.11), IL1RA (p=0.091), or TNF-α (p=0.46) release in whole blood cultures (data not shown, see Appendix I). There were also no effects of group for IL10 (p=0.57), IL1RA (p=0.21), or TNF-α (p=0.39) release in unstimulated whole blood cultures (data not shown, see Appendix I).     42   Figure 6. Whole blood culture cytokine concentration, corrected for total leukocyte numbers, from supernatants stimulated with 10 ng/ml lipopolysaccharide (LPS) in response to an acute bout of high -intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X 1-min @ 85% peak power output and IL10 (A), IL1RA (B), and TNF-α (C) and whole blood cultured in the presence of 10 ng/ml LPS. Supernatants were collected after four hours in culture and cytokines measured by Magpix ELISA and were corrected for total leukocyte numbers measured in blood at each timepoint. Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines. Repeated measures ANOVA revealed a significant main effect of time for TNF-α concentration (p<0.05). *p<0.05 vs. Pre (Fisher LSD post-hoc). †A main effect of group was also detected for TNF-α concentration (p<0.05) A) B) C)   43  2.3.6 Plasma Cytokines There were no effects of group for plasma IL10 (p=0.36), IL1RA (p=0.13), IL6 (p=0.88), or TNF-α (p=0.63) concentration (Figure 7). Plasma IL10 and IL1RA concentration did not change significantly over time (main effects of time, p=0.24 and p=0.33, respectively). There was a main effect of time for plasma TNF-α with post-hoc tests showing an ~18% decrease in TNF-α 1-H Post compared to Pre (p=0.05 vs. Pre). There was a significant group X time interaction for IL6 (p=0.027), however no pairwise comparisons reached statistical significance in post-hoc testing.             44      Figure 7. Circulating plasma cytokine concentration in response to an acute bout of high -intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X 1-min @ 85% peak power output and IL-10 (A), IL-1RA (B), IL-6 (C), and TNF-α (D) in plasma samples were measured by Magpix ELISA. Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines. Repeated measures ANOVA revealed a significant main effect of time for TNF-α concentration (p<0.05) and a group x time interaction for IL-6 (p=0.03). *p<0.05 vs. Pre (Fisher LSD post-hoc). ‡Significant Group X Time interaction.  A) B) D) C)   45  2.4 Discussion This study shows that, in both T2D and HC, one bout of HIIT significantly reduces TLR2 expression on classical and CD16+ monocytes measured immediately after and at 1 h recovery from exercise. This was accompanied by small but significant reductions in circulating plasma TNF-α along with increased LPS-induced IL10 and IL1RA production in whole blood cultures. Overall, this suggests an anti-inflammatory effect of HIIT in both T2D and HC.  2.4.1 Effects of Exercise on TLRs One of the proposed cellular mechanisms underlying the anti-inflammatory effect of exercise is a reduction in TLR expression (Mastana et al., 2011). This has been demonstrated after both acute bouts of exercise and longer duration training studies (Oliveira & Gleeson, 2010b; Simpson et al., 2009a; Stewart et al., 2005). The majority of the studies investigating the effect of acute exercise, however, tend to utilize relatively long duration exercise protocols (Table 1). In addition to reductions in cell-surface expression of TLRs, recent evidence also points to an upregulation of genes involved in the negative regulation of TLR signalling following a single bout of exercise (Abbasi et al., 2014). Exercise-induced reductions in TLR may be of particular relevance to inflammation in T2D because mechanistic studies have found that hyperglycemia can increase TLR2 and TLR4 expression in monocytes (Dasu et al., 2008; Dasu, Devaraj, Park, & Jialal, 2010b) and both TLR2 (Caricilli et al., 2008) and TLR4 (Shi et al., 2006) are implicated in the pathogenesis of insulin resistance. We found that, on both types of monocytes, HIIT reduced TLR2, which is in agreement with previous work using longer duration exercise bouts (Gleeson et al., 2006b; Lancaster et al., 2005; Oliveira & Gleeson, 2010b). There were no differences in the response between groups, suggesting that HIIT had equal impact on monocyte TLR2 reduction in T2D participants. In contrast to previous work   46  demonstrating a fairly consistent reduction in TLR4 after prolonged moderate-to-vigorous exercise (see Table 1), we did not see any changes in TLR4. This may suggest that HIIT is not sufficient stimulus to reduce TLR4 and may have a preferential effect on TLR2. Given the previous research, it is reasonable to speculate that TLR4 may be more sensitive to exercise duration than TLR2. As our primary comparison was between T2D and age matched controls we unfortunately did not have a comparison to prolonged continuous exercise. Whether the observed reduction in monocyte TLR2 expression after exercise is mediated by suppression of gene expression, receptor shedding, or internalization is not clear; indeed the precise physiological mechanisms responsible for reductions in TLR expression in response to exercise have not been elucidated (for review see (Flynn & McFarlin, 2006)). It has been suggested that glucocorticoids may play a role (Gleeson et al., 2006a) however in vitro studies have demonstrated that glucocorticoids seem to induce rather than suppress TLR expression (Galon et al., 2002; Gleeson et al., 2006b; Imasato et al., 2002). Furthermore, (Lancaster et al., 2005) found no relationship between circulating cortisol and TLR expression in vivo. Taken together, it is unlikely that exercise-induced changes in circulating glucocorticoids are responsible for reductions seen in TLR expression following an acute bout of exercise. Heat shock proteins are another proposed mediator of TLR expression. While there are data to support that heat shock proteins (HSP) can down-regulate the production of pro-inflammatory cytokines induced through TLR pathways, there is no evidence for a direct effect of HSP70 on TLR expression (Ferat-Osorio et al., 2014). In summary, it appears that acute HIIT can reduce monocyte TLR2 expression but further research is required to determine the precise physiological mechanisms for the reduction in TLR expression seen following acute exercise.   47  The majority of studies in the literature have investigated the role of exercise on TLR expression in monocytes. A novel aspect of this thesis is the characterization of TLR2 and 4 expression on neutrophils (CD16+ granulocytes). Neutrophil TLR2 is implicated in cytokine expression and superoxide production (Kurt-Jones et al., 2002a) while neutrophil TLR4 plays a crucial role in survival (Sabroe et al., 2003a). Although we observed a higher level of TLR2 on neutrophils in T2D compared to HC, there was no effect of exercise on neutrophil expression of either TLR2 or TLR4. These findings suggest that the impact of exercise on TLRs may be specific to monocytes.  Acute HIIT led to an expected increase in monocyte, neutrophils, and lymphocytes measured immediately after exercise (i.e., leukocytosis). Even though T2D participants had higher total leukocytes, there were no apparent group differences in the impact of acute HIIT on leukocyte numbers suggesting that T2D and HC respond similarly to this type of exercise. There were no effects of acute HIIT on the number or % of CD16+ monocytes, which suggests that acute vigorous exercise performed as HIIT does not impact the proportion of “pro-inflammatory” monocytes in circulation.  2.4.2 Cytokine Response It is now well accepted that aerobic exercise can promote the release of IL-6 from contracting skeletal muscle (Febbraio et al., 2003; Steensberg et al., 2000a). This increase is detectable immediately following exercise and appears to be involved in mediating some of the anti-inflammatory effects of exercise via direct anti-inflammatory effects and/or by promoting increases in IL-10 and IL-1RA (Petersen & Pedersen, 2005). Presumably IL-10 and IL-1RA are released from circulating immune cells, although to our knowledge this has not been directly demonstrated. Exercise volume is the primary determinant of skeletal muscle IL-6   48  induction, although intensity also appears to play a role (Fischer, 2006). The acute bout of HIIT did not appear to be a sufficient stimulus to elevate plasma IL-6 in this study, possibly because 7 X 1-min @85% Wpeak was too low in volume. We chose the HIIT protocol in the present study to be feasible for the previously inactive T2D participants. The impact of HIIT on plasma IL-6 in older adults or T2D patients has not been well studied, but a recent paper in healthy young males showed a small, yet significant, increase in plasma IL-6 immediately following both moderate (5 X 5 minutes at 50% VO2max) and high-intensity (5 X 4 minutes at 80% VO2max) exercise (Cullen, Thomas, Webb, & Hughes, 2016).  Given that the low-volume HIIT bout did not increase plasma IL-6, it was perhaps not surprising that we did not see an increase in plasma IL-10 or IL-1RA during the 1 h recovery. Interestingly, there was a small, yet statistically significant, reduction in plasma TNF-α at 1 h recovery from exercise in both T2D and HC. This could be interpreted as an anti-inflammatory effect of acute HIIT, although the mechanisms underlying this effect are not clear. In attempts to better understand the impact of acute HIIT on cytokine secretion from leukocytes, we performed parallel whole blood culture experiments in both unstimulated and LPS-stimulated conditions. There were no differences between groups or across time for unstimulated IL10, IL-1RA, or TNF-α secretion from whole blood cultures, although it is important to note that the levels of these cytokines in the culture medium are very low and below the sensitivity of the assay for several participants. In examining LPS-stimulated absolute cytokine secretion, the results tended to match the changes in leukocyte numbers seen in response to exercise (i.e., an increase cytokine secretion immediately after exercise that tracked leukocytosis) although there were some interesting results seen at 1 h recovery. Absolute LPS-stimulated IL-10 release was higher, and TNF-α release lower, at 1 h recovery from acute HIIT at a time when   49  leukocyte numbers had returned to resting levels. Overall this seems to indicate that blood leukocytes secreted greater amounts of anti-inflammatory cytokines and lower pro-inflammatory TNF during recovery from exercise. When cytokines were corrected for total leukocyte numbers the reduction in LPS-stimulated TNF-α secretion remained significant at 1 h recovery, supporting an anti-inflammatory effect of acute HIIT at this time point.  2.4.3 Limitations Most previous studies examining the anti-inflammatory mechanisms of acute exercise, including monocyte TLRs, plasma IL-6, and LPS-stimulated cytokine release, have used prolonged continuous moderate-to-vigorous exercise protocols (Booth et al., 2010; Gleeson et al., 2006a; Lancaster et al., 2005; Oliveira & Gleeson, 2010a; Simpson et al., 2009a). Due to the popularity of HIIT for improving cardiometabolic health in T2D and the unlikelihood that previously inactive older adults with T2D would perform ≥1 hour of moderate-to-vigorous intensity exercise, we focused on time-efficient HIIT in this study and unfortunately cannot directly compare HIIT to more traditional endurance-oriented exercise.   Similar to previous research (Drenth et al., 1995a; Smits et al., 1998; Starkie, Angus, Rolland, Hargreaves, & Febbraio, 2000), we used LPS to stimulate whole blood cultures to examine blood leukocyte cytokine secretion in response to a standard inflammatory insult. Although TLR2 has been shown to be involved in monocyte responses to LPS (Chuang et al., 2001; Sabroe et al., 2003b), TLR4 is regarded as the main LPS sensing receptor. Given that we saw reductions in TLR2 on monocytes following exercise, and higher TLR2 on neutrophils in T2D, stimulation of cultures with more pure TLR2 ligands such as PamCSK4 or peptidoglycan may have provided more insight into the functional responses of these cells following receptor downregulation.   50  Although we examined leukocyte numbers, phenotype, and function in response to acute HIIT it is not possible to examine or track inflammatory markers in immune cells that have infiltrated tissues (e.g., adipose, skeletal muscle, blood vessels) in human studies. Future work is needed to determine if the changes in monocyte TLR2 and cytokine secretion seen in the circulation are also present in tissue macrophages.  It is important to note that the T2D participants had completed a brief familiarization period prior to the acute exercise trial, as they were participating in a longer-term training study (NCT02251301). This involved four sessions of cycling HIIT (4-6 X 1-min intervals at ~80% maximal HR). This was deemed necessary to ensure the T2D participants could complete 7 X 1-min interval sessions, were accustomed to this type of vigorous exercise, and did not experience any abnormal HR or blood pressures responses to HIIT. Therefore, the results may not generalize to inactive T2D participants or those completely naïve to HIIT. Another potential limitation is that the healthy controls did not complete HIIT familiarization. However, given that they were already physically active and the volume of these HIIT sessions were low (i.e., involving only 4-6 minutes of vigorous exercise) familiarization was deemed unnecessary.  2.4.4 Summary In conclusion this study indicates that, in older adults with and without T2D, one bout of low-volume HIIT can reduce TLR2 expression, but not TLR4 expression, on monocytes with no discernable effect of HIIT exercise on neutrophil TLR2 and TLR4 expression. A single session of HIIT also leads to a reduction in circulating and ligand-induced TNF-α.  The low-volume HIIT protocol was not a sufficient stimulus to substantially increase plasma IL-6 or lead to elevations in IL-10 or IL1-RA that are purported to occur during recovery from more   51  prolonged exercise. Taken together, these results indicate that HIIT is a viable exercise stimulus for inducing cellular and molecular anti-inflammatory effects. As there was no indication of a pro-inflammatory effect of HIIT in either T2D patients or HC, HIIT may be a suitable option for ameliorating the chronically elevated levels of inflammation implicated in T2D pathophysiology. Whether the anti-inflammatory effects induced by individual bouts of HIIT can culminate over time to improve health and impede the pathogenesis of T2D and its complications remains to be determined.     52  3.0 Overall Discussion This study shows that one bout of HIIT significantly reduces TLR2 expression on classical and CD16+ monocytes measured immediately after and at 1 h recovery from exercise, with no apparent differences between T2D and HC. This was accompanied by small but significant reductions in plasma and LPS-induced TNF-α along with increased LPS-induced IL-10 and IL-1RA production in whole blood cultures. Overall, this suggests an anti-inflammatory effect of a single session of HIIT in both T2D and HC. 3.1 Impact of acute HIIT on TLRs A single session of HIIT led to a reduction in TLR2 on classic and CD16+ monocytes, which was in support of hypothesis 1. The acute reduction persisted into one hour recovery, suggesting that a single session of HIIT can promote at least a temporary anti-inflammatory effect measured at the level of individual monocytes. In contrast to my hypothesis, acute HIIT did not impact TLR4 expression on either monocyte subset nor were there effects of HIIT on either TLR2 or TLR4 in neutrophils. 3.1.2 Reduction in TLR2 on monocytes The mechanisms underlying the reduction in TLR2 on monocytes could not be ascertained in the present study, but potential molecular and cellular processes include decreased gene expression, receptor shedding, and/or internalization. 3.1.2.1 Decreased Gene Expression. TLR2 gene expression can be induced by various cytokines such as IL-1, TNF-α, and GM-CSF (Wang, Lafuse, & Zwilling, 2000). Although stress hormones such as glucocorticoids have repeatedly been suggested to play a role in modulating and possibly reducing TLR2 expression (Gleeson et al., 2006a; Lancaster et al.,   53  2005), it seems that in vitro stimulation with glucocorticoids results in the upregulation of TLR2 mRNA (Staege, Schaffner, & Schneemann, 2000). Thus, the evidence points to several potential circulating factors that can increase TLR2 mRNA but there is a paucity of data regarding possible mechanisms that result in suppression of TLR2 mRNA. Stimulation with IL4 has been shown to down-regulate TLR2 mRNA levels (Staege et al., 2000), however it is unlikely this mechanism is responsible for our reported reductions in TLR2 expression for two reasons; IL4 has not been shown to increase following exercise (Moyna et al., 2007; Suzuki et al., 2000), and given the immediate reduction observed in TLR2 (~20 minutes between pre- and post-exercise blood samples) it is unlikely that enough time elapsed for suppressed gene expression to translate into a reduction in surface protein expression of TLR2. 3.1.2.2 Receptor Shedding. Shedding of TLR2 is another proposed mechanism for the reductions seen after exercise (Mastana et al., 2011). There is some evidence that in vivo stimulation with LPS leads to a reduction in TLR2 cell surface expression and a corresponding increase in soluble TLR2 (sTLR2) (Wever et al., 2014), indicative of TLR2 shedding. Langjahr et al. (2014) demonstrated an increase in sTLR2 and a concurrent reduction in cellular TLR2 expression following treatment with the TLR2 ligand Pam3CSK4. Furthermore, they demonstrated that matrix metalloproteinases (MMPs) and A disintegrin and metalloproteinases (ADAMs) are involved in sTLR2 production (Langjahr et al., 2014). This is especially relevant as studies have shown increased levels of MMP mRNA, protein, and plasma levels in response to exercise (Edwards et al., 2009; Rullman et al., 2007). Although determining the cellular mechanism behind the exercise induced reductions in TLR2 was not an aim of this study, a future direction could be to measure monocyte MMPs and ADAMs, along with plasma sTLR2, in order to gather evidence of exercise-induced TLR2 shedding.   54  3.1.2.3 Receptor Internalization. Internalization of TLR2 could be another possible mechanism for the reduction observed in this study. TLR2 has been described as the most promiscuous TLR as it is able to recognize the most diverse set of pathogen associated molecular patterns (Triantafilou et al., 2006). Internalization following stimulation with various TLR2 ligands is well established (Triantafilou et al., 2004; Triantafilou et al., 2006). Given that numerous TLR2 ligands such as heat shock protein (HSP) 70 and HSP60 have been reported to be elevated following exercise (Asea et al., 2002; Banfi, Dolci, Verna, & Corsi, 2004; de Graaf, Kloppenburg, Kitslaar, Bruggeman, & Stassen, 2006), it is possible that reductions in TLR2 following exercise could be, in part, due to ligand-induced internalization of the receptor. It would be beneficial to investigate the effect of an acute bout of HIIT on plasma HSP concentration in order to pursue this concept. Tracking differences in cell surface versus internalized TLR2 using recently-developed imaging flow cytometers may be one technique that could also help determine if TLR2 is internalized after exercise.  3.1.4 Monocyte TLR4 In contrast to several previous studies involving aerobic exercise (See Table 1), acute HIIT did not appear to reduce monocyte TLR4 in either T2D or HC. Based on the studies described in Table 1, it seems that longer duration exercise leads to a more robust TLR4 reduction on monocytes. For example, Simpson et al. (2009) showed a significant 12% reduction following 45 minutes of aerobic exercise whereas Oliviera & Gleeson (2010) showed a 45% reduction following 90 minutes of aerobic exercise and Gleeson et al. (2006) found a 50% reduction following 150 minutes of exercise. Thus it is possible that the short-duration or low-volume of exercise performed as 7 X 1-min HIIT in this study was insufficient to cause TLR4 reductions.   55  3.1.5 Neutrophil TLR2 and TLR4 We observed no impact of exercise on neutrophil TLR2 or TLR4 expression. No previous studies, to my knowledge, have measured neutrophil TLR2 or TLR4 in response to acute exercise, despite the importance of these receptors in neutrophil survival, activation, and inflammatory responses (Sabroe et al., 2003b). The findings from this study and previous studies suggest that the impact of exercise on TLR2 and TLR4 may be specific to monocytes. It is possible that differences in TLR expression, which is generally higher on monocytes versus neutrophils (Flo et al., 2001; Sabroe, Jones, Usher, Whyte, & Dower, 2002), and/or differential regulation of shedding or internalization might be involved in determining differences in exercise responses in the different cell types. Interestingly, we found elevated TLR2 on neutrophils in T2D patients with a tendency for TLR4 to also be higher in T2D. To the best of my knowledge, this is the first study to report these differences, and suggest that neutrophils may display a heightened pro-inflammatory phenotype in T2D. For example, in vitro upregulation of TLR2 on neutrophils has been shown to increase ligand-induced IL8 secretion, a chemotactic factor responsible for the migration of neutrophils into injured tissue (Kurt-Jones et al., 2002b). Increased TLR2 is also linked to greater neutrophil superoxide production (Kurt-Jones et al., 2002), which could be linked to greater oxidative stress commonly seen in T2D. Stimulation of neutrophil TLR2 is also characterized by an elevation in cellular adhesion molecules such as CD11b (Kurt-Jones et al., 2002b; Sabroe et al., 2003b). Taken together, these data suggest that elevated TLR2 in neutrophils results in a potentially greater pro-inflammatory state characterized by exaggerated response to TLR ligands. Whether heightened neutrophil TLR2 plays a role in T2D pathology could be an avenue for future research.    56  3.2 Impact of HIIT on CD16+ Monocytes Hypothesis 2 was not supported in this thesis, as the number CD16+ monocytes or proportion of CD16+ monocytes to classical monocytes was not affected by acute HIIT. Although T2D participants tended to have marginally higher CD16+ monocyte numbers (5% vs. 4%), this did not reach statistical significance. This could be related to the small sample size in the current study. CD16+ monocytes can be further sub-divided into CD14++/CD16+ and CD14+/CD16+ and some previous studies have shown that CD14++/CD16+ may be more pro-inflammatory (Yang, Zhang, Yu, Yang, & Wang, 2014b). Unfortunately, in our sample of both T2D and HC it was difficult to delineate between these two sub-types of CD16+ monocytes so they were analyzed as one population of cells.  Although much more is known on the differences between monocyte subsets in mice (Ziegler-Heitbrock et al., 2010) CD16+ monocytes are believed to act as “patrolling” cells that adhere more readily to the vascular wall. Thus, it is possible that T2D participants had greater CD16+ monocytes that were adhering to the endothelium (due to potential underlying atherosclerosis) which could not be detected by venous blood sampling.  The immediate increase in CD16+ monocyte numbers and subsequent return to basal levels following acute HIIT paralleled the changes in classical monocytes. The reductions in TLR2 were also similar in both monocyte subsets. From these data it can be concluded that a single session of HIIT appears to have similar impact on both classical and CD16+ monocytes.     57  3.3 Impact of HIIT on whole blood culture cytokine secretion 3.3.1 LPS-induced TNF-α response  Hypothesis 3 was partially supported by the findings in the current study. A significant increase in LPS induced TNF-α production was seen Post, which was likely explained by the increase in white blood cell concentration as this difference disappeared upon correction for total leukocyte count. However, there was a reduction in LPS-induced TNF-α secretion 1-H Post, which was still present when correcting for leukocyte number. Therefore, when expressed as both an absolute and a per leukocyte basis, a single session of HIIT resulted in lower LPS-induced TNF-α release assessed at 1 h recovery. Previous studies investigating LPS induced cytokine release in response to exercise tend to show a suppression in pro-inflammatory cytokine production. Specifically, a reduction in LPS stimulated TNF-α production has been demonstrated in various studies following long duration or exhaustive exercise (Baum, Müller-Steinhardt, Liesen, & Kirchner, 1997; Drenth et al., 1995b; Kvernmo, Olsen, & Osterud, 1992; Smits et al., 1998; Starkie et al., 2000; Weinstock et al., 1997). Although TLR4 is recognised as the primary receptor for LPS, there is evidence that TLR2 is also involved (Chuang et al., 2001; Sabroe et al., 2003a). Therefore, it is possible that the reduction in monocyte TLR2 was linked to reduced LPS-induced TNF-α secretion at 1 h recovery. The reduction in LPS-induced TNF-α was paralleled by a reduction in plasma TNF-α seen at 1 h recovery (see more discussion below in section 3.4) suggesting a possible link to an overall anti-inflammatory response. Interestingly, we also observed a main effect of group with whole blood cultures from HC producing greater LPS-stimulated TNF-α than T2D participants. It is possible that lower LPS-induced TNF-α production by T2D participants in this study is due to endotoxin tolerance, as   58  patients with T2D have been shown to have elevated basal and postprandial circulating endotoxin concentrations (Harte et al., 2012). Endotoxin concentrations in plasma (Erridge, Attina, Spickett, & Webb, 2007; Ghanim et al., 2009; Harte et al., 2012) are substantially lower than the concentration used in our whole blood culture stimulations, which elicit a maximal TNF-α response. LPS detection in plasma is notoriously difficult (Erridge et al., 2007), which precluded measurement of plasma LPS in this study. Therefore, we are unable to determine if endotoxin tolerance is potentially responsible for the reduced LPS-stimulated TNF-α production seen. 3.3.2 Anti-inflammatory cytokine responses  Prior to correcting for leukocyte concentration we observed a significant increase in LPS-induced IL-10 and IL-1RA production immediately Post-exercise, with IL-10 production remaining elevated 1-H Post exercise. However, when adjusted for leukocyte concentration there were no significant differences in IL-10 or IL-1RA at any time point. This indicates that the elevations in culture supernatants were largely due to exercise-induced leukocytosis (i.e., more cells were present in the blood cultures to respond to LPS and produce more anti-inflammatory cytokines). Other studies investigating induction of IL-10 in whole blood cultures following a bout of exercise have mixed results. LaVoy et al recently demonstrated an increase in the percentage of CD27-CD8+ T-cells expressing intracellular IL-10 in response to phytohaemagglutinin stimulation following a 40km cycling time trial (LaVoy, Bosch, Lowder, & Simpson, 2013). In contrast, Smits et al reported a reduction in LPS induced IL10 following a short bout of exercise to exhaustion (Smits et al., 1998). Most recently, Svendsen et al reported a potentiated IL-10 production following an antigen challenge after exercise (Svendsen, Killer, & Gleeson, 2014). In summary, our results seem to agree with the majority   59  of the research regarding induction of IL-10 in whole blood cultures following an acute bout of exercise. This suggests that following acute HIIT immune cells respond to the LPS stimulus by secreting more anti-inflammatory IL-10. Although this was not seen in the plasma cytokines this response may indicate altered immune cell function in response to pathogens post HIIT. 3.4 Plasma cytokines Acute HIIT did not cause an immediate increase in plasma IL-6, which was in contrast to Hypothesis 4. It has been shown that exercise and/or muscle contraction leads to an increase in skeletal muscle-derived IL-6, which is implicated in mediating an overall anti-inflammatory response (Pedersen & Fischer, 2007; Pedersen, 2006). One possible mechanism involves subsequent induction of the anti-inflammatory cytokines IL-10 and IL-1RA. Acute HIIT did not have an impact on either of these cytokines measured in plasma, which was not surprising given the lack of IL-6 induction. Generally, studies that demonstrate a pronounced elevation in circulating plasma IL-6 are those measuring IL-6 following long duration, exhaustive exercises (Ostrowski et al., 1998a; Ostrowski, Schjerling, & Pedersen, 2000; Steensberg et al., 2000b; Steensberg et al., 2002). This effect is markedly enhanced when muscle glycogen levels are low (Keller et al., 2001). Given the short duration and low volume of exercise performed in this study it is likely that our HIIT protocol was not a sufficient stimulus to lower muscle glycogen levels to an appreciable amount. Our results indicated a significant group X time interaction for plasma IL-6, a trend for IL-6 to increase at 1 h recovery in T2D and decrease in HC. Post-hoc tests examining pairwise comparisons did not reveal any significant effects. Typically, the myokine IL-6 response is measured immediately after exercise and then returns to basal levels within 2 hours of recovery   60  from exercise (Ostrowski, Rohde, Zacho, Asp, & Pedersen, 1998b; Starkie, Rolland, Angus, Anderson, & Febbraio, 2001). Therefore, it is difficult to attribute the potential increase at 1 hr recovery in T2D to acute release of IL-6 from contracting skeletal muscle. However, given the short duration of exercise in this study (<25 minutes including warm-up and cooldown) it is possible that exercise did induce IL-6 and this was not detected until the 1 hr recovery time point. A more comprehensive timecourse of the response with multiple blood (and muscle biopsy) samples would be needed to directly test this hypothesis. 3.5 Limitations Although comparing the response of HIIT to prolonged endurance-oriented exercise on TLR expression was not a primary aim of this study, the results would have benefited from such a comparison as the majority of previous studies measuring TLRs after acute exercise have used continuous longer-duration exercise (Booth et al., 2010; Gleeson et al., 2006a; Lancaster et al., 2005; Oliveira & Gleeson, 2010a; Simpson et al., 2009b). Furthermore, we could not discount the possibility of diurnal variations in TLR expression in this study. However, this seems unlikely as similar studies have shown no changes in TLR2 and TLR4 expression over the same time periods (Lancaster et al., 2005; Oliveira & Gleeson, 2010a) and within the study design samples were taken over a relatively short ~1.5 hour period.  It is possible that we did not detect a more pronounced difference between T2D and HC in basal inflammatory markers due to the fact that this study was carried out on the third week of training for the T2D patients. However, because T2D participants were previously inactive, it would have been difficult or perhaps not possible for the T2D to complete the HIIT exercise protocol prior to any familiarization or exposure to high-intensity exercise.    61  Similar to previous research (Smits et al., 1998; Starkie et al., 2000), we used LPS to stimulate whole blood cultures to examine blood leukocyte cytokine secretion in response to a standard inflammatory insult. Although TLR2 has been shown to be involved in monocyte responses to LPS (Chuang et al., 2001; Sabroe et al., 2003b), TLR4 is regarded as the main LPS sensing receptor. Given that we saw reductions in TLR2 on monocytes following exercise, and higher TLR2 on neutrophils in T2D, stimulation of cultures with more pure TLR2 ligands such as PamCSK4 or peptidoglycan may have provided more insight into the functional responses of these cells following receptor downregulation. In an attempt to take a more physiological approach to investigating immune function, whole blood cultures were used rather than peripheral blood mononuclear cell (PBMC) or isolated CD14+ monocyte cultures. While whole blood cultures have the advantage of mimicking the interactions between immune cells in vivo, a drawback of this technique is the inability to deduce the cell type responsible for cytokine production. On that note, correcting changes in leukocyte numbers over time by expressing cytokine production per leukocyte may not be sensitive to alterations in individual cell phenotype or subtle changes in cell type distribution (e.g., change in T-regulatory lymphocytes (Lancaster et al., 2005; 2004) that may impact cytokine production. Given this, it is possible that minor changes in cytokine production by specific cell types could go undetected. Although we examined leukocyte numbers, phenotype, and function in response to acute HIIT the nature of the human study prevented examination of inflammatory markers in immune cells that have infiltrated tissues (e.g., adipose, skeletal muscle) that are involved in the propagation of inflammation in T2D. Combining blood leukocyte measures with adipose or   62  muscle biopsies, or the addition of complimentary animal models, could be approaches that would enhance understanding of the integrated immunology response to acute HIIT. A limitation in the study design was that the T2D participants had completed four sessions of cycling HIIT familiarization prior to the acute exercise trial, as they were participating in a longer-term training study (NCT02251301). This was deemed necessary to ensure the T2D participants could complete 7 X 1-min interval sessions and were accustomed to this type of vigorous exercise. The familiarization sessions also lessoned any potential concern of abnormal HR or blood pressures responses to vigorous exercise performed as HIIT in T2D patients. Therefore, the results may not generalize to inactive T2D participants or those completely naïve to HIIT. The physically active age-matched controls did not complete the HIIT familiarization but it is acknowledged that inclusion of these sessions would have strengthened the study design.  Another potential limitation is that the HC group were not BMI-matched with the T2D group. The choice of a “healthy” control group to compare to individuals with T2D is difficult and can be complicated by potential differences in BMI, medications, physical activity levels, and other comorbidities. The HC group in this study was chosen to represent “healthy” older adults but including a non-T2D group matched for age and BMI, if such a group of “healthy” obese older adults could be found, could have helped tease out the direct effects of T2D.     63  4.0 Future research, significance, and conclusions 4.1 Future research As mentioned in the discussion, the cellular or molecular mechanisms responsible for the exercise-induced reduction in TLR2 expression have yet to be determined. Whether a reduction in gene expression, shedding, or internalization are responsible have yet to be determined. While these experiments may have been onerous in the past, the development of imaging flow cytometers allows for a viable high-throughput option to investigate the mechanisms of TLR2 reduction. Furthermore, the precise stimulus responsible for this effect is also undetermined. Analyses of circulating exercise-induced factors (e.g., myokines, “exerkines”, growth factors (Emambokus, Granger, & Messmer-Blust, 2015)) with parallel cell culture experiments (Aoi et al., 2013; Seldin, Peterson, Byerly, Wei, & Wong, 2012) could give insight on this topic. It is well established that a reduction in TLR2 following exercise is considered to be an anti-inflammatory effect. Given that T2D is characterized by a state of heightened inflammation, it makes sense that this would be beneficial in regards to the pathogenesis of the disease. To the best of my knowledge, however, there have been no studies investigating the long term consequences of repeated transient exercise-induced reductions in TLR2 on the pathogenesis of T2D. A study looking at TLR2 expression after a long-term training intervention along with clinical markers of T2D could shed light on any possible relationships. 4.2 Significance Elevated expression of TLR2 and TLR4 are accepted markers of inflammation in T2D that contribute to the pro-inflammatory state of the disease (Dasu et al., 2010a). Therapeutic   64  modulation of TLR expression has been suggested in this population (Dasu et al., 2012) however this is the first study to investigate the effect of exercise in lowering TLR2 and TLR4 expression in T2D. Given the cellular and molecular effects of HIIT on immune cell activation in this population, it may be possible to incorporate HIIT as a lifestyle based approach to lower inflammation and aid in the management of T2D.  This study demonstrates that exercise seems to affect specific leukocyte subsets differently. The effects of exercise on TLR expression might be limited to monocytes, as there were no apparent effects on neutrophils at this level of intensity and duration even in T2D participants who had elevated neutrophil TLR2. Furthermore, the lack of a substantial rise in plasma IL-6, and thereafter IL-10 and IL-1RA, indicates that the well documented anti-inflammatory effect of exercise via IL-6 myokine induction may not be present following low volume HIIT and may require a longer exercise duration.  Overall, the findings provide evidence that HIIT has anti-inflammatory effects and, at the least, does not appear to be a pro-inflammatory stimulus for healthy older adults or those with T2D. This is important information given the recent surge of interest in applying low-volume HIIT for the prevention and treatment of T2D (Mitranun, Deerochanawong, Tanaka, & Suksom, 2014; Robinson et al., 2015; Tjønna et al., 2008) but reluctance by some researchers who have suggested HIIT may be pro-inflammatory (Tuan et al., 2008; Zwetsloot, John, Lawrence, Battista, & Shanely, 2014).  4.3 Conclusion In conclusion this thesis indicates that, in individuals with and without T2D, one bout of low-volume HIIT can reduce TLR2 expression, but not TLR4 expression, on monocytes with no discernable effect of HIIT exercise on neutrophil TLR2 and TLR4 expression. A single session   65  of HIIT also leads to a reduction in circulating and ligand-induced TNF-α.  The low-volume HIIT protocol was not a sufficient stimulus to substantially increase plasma IL-6 or lead to elevations in IL-10 or IL-1RA that are purported to occur during recovery from more prolonged exercise. Based on this initial study, there did not appear to be any differences in the immunomodulatory effects of a single session of HIIT between T2D patients and HC. Taken together, these results indicate that HIIT is a viable exercise stimulus for inducing cellular and molecular anti-inflammatory effects in older adults with and without T2D. As there was no indication of a pro-inflammatory effect of HIIT in either T2D patients or HC, HIIT may be a suitable option for ameliorating the chronically elevated levels of inflammation implicated in T2D pathophysiology. Whether the anti-inflammatory effects induced by individual bouts of HIIT can culminate over time to improve health and impede the pathogenesis of T2D and its complications remains to be determined.       66  References Abbasi, A., Hauth, M., Walter, M., Hudemann, J., Wank, V., Niess, A. M., & Northoff, H. (2014). Exhaustive exercise modifies different gene expression profiles and pathways in LPS-stimulated and un-stimulated whole blood cultures. Brain, Behavior, and Immunity, 39, 130-141. doi:10.1016/j.bbi.2013.10.023 Aguirre, V., Uchida, T., Yenush, L., Davis, R., & White, M. F. (2000). The c-jun NH2-terminal kinase promotes insulin resistance during association with insulin receptor substrate-1 and phosphorylation of Ser307. Journal of Biological Chemistry, 275(12), 9047-9054. doi:10.1074/jbc.275.12.9047 Aoi, W., Naito, Y., Takagi, T., Tanimura, Y., Takanami, Y., Kawai, Y., . . . Yoshikawa, T. (2013). A novel myokine, secreted protein acidic and rich in cysteine (SPARC), suppresses colon tumorigenesis via regular exercise. Gut, 62(6), 882 Asea, A., Rehli, M., Kabingu, E., Boch, J. A., Bare, O., Auron, P. E., . . . Calderwood, S. K. (2002). Novel signal transduction pathway utilized by extracellular HSP70: Role of toll-like receptor (TLR) 2 and TLR4. The Journal of Biological Chemistry, 277(17), 15028.  Balducci, S., Zanuso, S., Nicolucci, A., Fernando, F., Cavallo, S., Cardelli, P., . . . Pugliese, G. (2010). Anti-inflammatory effect of exercise training in subjects with type 2 diabetes and the metabolic syndrome is dependent on exercise modalities and independent of weight loss. Nutrition, Metabolism and Cardiovascular Diseases, 20(8), 608-617. doi:10.1016/j.numecd.2009.04.015   67  Banfi, G., Dolci, A., Verna, R., & Corsi, M. M. (2004). Exercise raises serum heat-shock protein 70 (Hsp70) levels. Clinical Chemistry and Laboratory Medicine, 42(12), 1445-1446. doi:10.1515/CCLM.2004.268 Baum, M., Müller-Steinhardt, M., Liesen, H., & Kirchner, H. (1997). Moderate and exhaustive endurance exercise influences the interferon-γ levels in whole-blood culture supernatants. European Journal of Applied Physiology and Occupational Physiology, 76(2), 165-169. doi:10.1007/s004210050229 Belge, K., Dayyani, F., Horelt, A., Siedlar, M., Frankenberger, M., Frankenberger, B., . . . Ziegler-Heitbrock, L. (2002). The proinflammatory CD14+CD16+DR++ monocytes are a major source of TNF. The Journal of Immunology, 168(7), 3536-3542.  Bendtzen, K., Mandrup-Poulsen, T., Nerup, J., Nielsen, J., Dinarello, C., & Svenson, M. (1986). Cytotoxicity of human pI 7 interleukin-1 for pancreatic islets of langerhans. Science, 232(4757), 1545-1547. doi:10.1126/science.3086977 Bergmann, M., Gornikiewicz, A., Sautner, T., Waldmann, E., Weber, T., Mittlbock, M., . . . Fugger, R. (1999). Attenuation of catecholamine-induced immunosuppression in whole blood from patients with sepsis. SHOCK, 12(6), 421-427. doi:10.1097/00024382-199912000-00002 Booth, S., Florida-James, G. D., McFarlin, B. K., Spielmann, G., O’Connor, D. P., & Simpson, R. J. (2010). The impact of acute strenuous exercise on TLR2, TLR4 and HLA.DR expression on human blood monocytes induced by autologous serum.   68  European Journal of Applied Physiology, 110(6), 1259-1268. doi:10.1007/s00421-010-1616-2 Borg, G. A. (1982). Psychophysical bases of perceived exertion. Medicine and Science in Sports and Exercise, 14(5), 377-381. doi:10.1249/00005768-198205000-00012 Buring, J. E., Pradhan, A. D., Manson, J. E., Rifai, N., & Ridker, P. M. (2001). C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA, 286(3), 327-334. doi:10.1001/jama.286.3.327 Calle, M., & Fernandez, M. (2012). Inflammation and type 2 diabetes. Diabetes & Metabolism, 38(3), 183-191. doi:10.1016/j.diabet.2011.11.006 Caricilli, A. M., Nascimento, P. H., Pauli, J. R., Daniela M L Tsukumo, Velloso, L. A., Carvalheira, J. B., & Mário J A Saad. (2008). Inhibition of toll-like receptor 2 expression improves insulin sensitivity and signaling in muscle and white adipose tissue of mice fed a high-fat diet. Journal of Endocrinology, 199(3), 399-406. doi:10.1677/JOE-08-0354 Cassatella, M. A., Jaillon, S., Costantini, C., & Mantovani, A. (2011). Neutrophils in the activation and regulation of innate and adaptive immunity. Nature Reviews Immunology, 11(8), 519-531. doi:10.1038/nri3024 Chuang, T., Ozinsky, A., Werts, C., Godowski, P. J., Hayashi, F., Aderem, A., . . . Tobias, P. S. (2001). Leptospiral lipopolysaccharide activates cells through a TLR2-dependent mechanism. Nature Immunology, 2(4), 346-352. doi:10.1038/86354   69  Colberg, S. R., Sigal, R. J., Fernhall, B., Regensteiner, J. G., Blissmer, B. J., Rubin, R. R., . . . American Diabetes Association. (2010). Exercise and type 2 diabetes: The american college of sports medicine and the american diabetes association: Joint position statement. Diabetes Care, 33(12), e147-e167. doi:10.2337/dc10-9990 Cullen, T., Thomas, T. W., Webb, R., & Hughes, M. G. (2016). Interleukin-6 and associated cytokine responses to an acute bout of high intensity interval exercise: The effect of exercise intensity and volume. Applied Physiology, Nutrition, and Metabolism: - NRC Research Press. doi:- 10.1139/apnm-2015-0640 Cupps, T. R., & Fauci, A. S. (1982). Corticosteroid-mediated immunoregulation in man. Immunological Reviews, 65(1), 133-155. doi:10.1111/j.1600-065X.1982.tb00431.x Dasu, M. R., Devaraj, S., & Jialal, I. (2007). High glucose induces IL-1β expression in human monocytes: Mechanistic insights. American Journal of Physiology - Endocrinology and Metabolism, 293(1), 337-346. doi:10.1152/ajpendo.00718.2006 Dasu, M. R., & Jialal, I. (2011). Free fatty acids in the presence of high glucose amplify monocyte inflammation via toll-like receptors. American Journal of Physiology - Endocrinology and Metabolism, 300(1), 145-154. doi:10.1152/ajpendo.00490.2010 Dasu, M., Devaraj, S., Park, S., & Jialal, I. (2010a). Increased toll-like receptor (TLR) activation and TLR ligands in recently diagnosed type 2 diabetic subjects. Diabetes Care, 33(4), 861-868. doi:10.2337/dc09-1799   70  Dasu, M., Devaraj, S., Park, S., & Jialal, I. (2010b). Increased toll-like receptor (TLR) activation and TLR ligands in recently diagnosed type 2 diabetic subjects. Diabetes Care, 33(4), 861-868. doi:10.2337/dc09-1799 Dasu, M., Devaraj, S., Zhao, L., Hwang, D., & Jialal, I. (2008). High glucose induces toll-like receptor expression in human monocytes mechanism of activation. Diabetes, 57(11), 3090-3098. doi:10.2337/db08-0564 Dasu, M., Ramirez, S., & Isseroff, R. (2012). Toll-like receptors and diabetes: A therapeutic perspective. Clinical Science, 122(5-6), 203-214. doi:10.1042/CS20110357 de Graaf, R., Kloppenburg, G., Kitslaar, P. J. H. M., Bruggeman, C. A., & Stassen, F. (2006). Human heat shock protein 60 stimulates vascular smooth muscle cell proliferation through toll-like receptors 2 and 4. Microbes and Infection, 8(7), 1859-1865. doi:10.1016/j.micinf.2006.02.024 Doucet, G., & Beatty, M. (2010). The cost of diabetes in canada: The economic tsunami. Canadian Journal of Diabetes, 34(1), 27-29. doi:10.1016/S1499-2671(10)41005-9 Drenth, J. P., S. H. Van Uum, Deuren, M. V., Pesman, G. J., J. Van der Ven-Jongekrijg, & J. W. Van der Meer. (1995a). Endurance run increases circulating IL-6 and IL-1ra but downregulates ex vivo TNF-alpha and IL-1 beta production. Journal of Applied Physiology, 79(5), 1497-1503.  Drenth, J. P., S. H. Van Uum, Deuren, M. V., Pesman, G. J., J. Van der Ven-Jongekrijg, & J. W. Van der Meer. (1995b). Endurance run increases circulating IL-6 and IL-1ra but   71  downregulates ex vivo TNF-alpha and IL-1 beta production. Journal of Applied Physiology, 79(5), 1497-1503.  Edgett, B. A., Foster, W. S., Hankinson, P. B., Simpson, C. A., Little, J. P., Graham, R. B., & Gurd, B. J. (2013). Dissociation of increases in PGC-1α and its regulators from exercise intensity and muscle activation following acute exercise. PloS One, 8(8), e71623.  Edwards, K. M., Sheu, B., Woods, B. G., Hong, S., Penn, A. H., Schmid-Schonbein, G. W., & Mills, P. J. (2009). 35. matrix metalloproteinase (MMP) response to exercise and training in hypertension. Brain Behavior and Immunity, 23, S34-S35. doi:10.1016/j.bbi.2009.06.040 Ehses, J. A., Meier, D. T., Wueest, S., Rytka, J., Boller, S., Wielinga, P. Y., . . . Donath, M. Y. (2010). Toll-like receptor 2-deficient mice are protected from insulin resistance and beta cell dysfunction induced by a high-fat diet. Diabetologia, 53(8), 1795-1806. doi:10.1007/s00125-010-1747-3 Ehses, J. A., Perren, A., Eppler, E., Ribaux, P., Pospisilik, J. A., Maor-Cahn, R., . . . Donath, M. Y. (2007). Increased number of islet-associated macrophages in type 2 diabetes. Diabetes, 56(9), 2356-2370. doi:10.2337/db06-1650 Emambokus, N., Granger, A., & Messmer-Blust, A. (2015). Exercise metabolism. Cell Metabolism, 22(1), 1. doi:10.1016/j.cmet.2015.06.020   72  Emanuelli, B., Kahn, C. R., & Taniguchi, C. M. (2006). Critical nodes in signalling pathways: Insights into insulin action. Nature Reviews Molecular Cell Biology, 7(2), 85-96. doi:10.1038/nrm1837 Erridge, C., Attina, T., Spickett, C. M., & Webb, D. J. (2007). A high-fat meal induces low-grade endotoxemia: Evidence of a novel mechanism of postprandial inflammation. The American Journal of Clinical Nutrition, 86(5), 1286.  Esposito, K., Nappo, F., Marfella, R., Giugliano, G., Giugliano, F., Ciotola, M., . . . Giugliano, D. (2002). Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans - role of oxidative stress. Circulation, 106(16), 2067-2072. doi:10.1161/01.CIR.0000034509.14906.AE Febbraio, M. A., Steensberg, A., Keller, C., Starkie, R. L., Nielsen, H. B., Krustrup, P., . . . Pedersen, B. K. (2003). Glucose ingestion attenuates interleukin-6 release from contracting skeletal muscle in humans. The Journal of Physiology, 549(2), 607-612. doi:10.1113/jphysiol.2003.042374 Ferat-Osorio, E., Sánchez-Anaya, A., Gutiérrez-Mendoza, M., Boscó-Gárate, I., Wong-Baeza, I., Pastelin-Palacios, R., . . . Isibasi, A. (2014). Heat shock protein 70 down-regulates the production of toll-like receptor-induced pro-inflammatory cytokines by a heat shock factor-1/constitutive heat shock element-binding factor-dependent mechanism. Journal of Inflammation (London, England), 11(1), 19-19. doi:10.1186/1476-9255-11-19   73  Fingerle-Rowson, G., Angstwurm, M., Andreesen, R., & Ziegler-Heitbrock, H. W. (1998). Selective depletion of CD14+ CD16+ monocytes by glucocorticoid therapy. Clinical and Experimental Immunology, 112(3), 501-506. doi:10.1046/j.1365-2249.1998.00617.x Fischer, C. P. (2006). Interleukin-6 in acute exercise and training: What is the biological relevance? Exercise Immunology Review, 12, 6.  Flo, T. H., Halaas, Ø, Torp, S., Ryan, L., Lien, E., Dybdahl, B., . . . Espevik, T. (2001). Differential expression of toll-like receptor 2 in human cells. Journal of Leukocyte Biology, 69(3), 474.  Flynn, M. G., & McFarlin, B. K. (2006). Toll-like receptor 4: Link to the anti-inflammatory effects of exercise? Exercise and Sport Sciences Reviews, 34(4), 176-181. doi:10.1249/01.jes.0000240027.22749.14 Frankenberger, M., Sternsdorf, T., Pechumer, H., Pforte, A., & Ziegler-Heitbrock, H. (1996). Differential cytokine expression in human blood monocyte subpopulations: A polymerase chain reaction analysis. Blood, 87(1), 373-377.  Galon, J., Franchimont, D., Hiroi, N., Frey, G., Boettner, A., Ehrhart-Bornstein, M., . . . Bornstein, S. R. (2002). Gene profiling reveals unknown enhancing and suppressive actions of glucocorticoids on immune cells. FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology, 16(1), 61-71. doi:10.1096/fj.01-0245com   74  Ghanim, H., Abuaysheh, S., Sia, C. L., Korzeniewski, K., Chaudhuri, A., Fernandez-Real, J. M., & Dandona, P. (2009). Increase in plasma endotoxin concentrations and the expression of toll-like receptors and suppressor of cytokine signaling-3 in mononuclear cells after a high-fat, high-carbohydrate meal: Implications for insulin resistance. Diabetes Care, 32(12), 2281-2287. doi:10.2337/dc09-0979 Gibala, M. J., Little, J. P., MacDonald, M. J., & Hawley, J. A. (2012). Physiological adaptations to low‐volume, high‐intensity interval training in health and disease. The Journal of Physiology, 590(5), 1077-1084. doi:10.1113/jphysiol.2011.224725 Gleeson, M., McFarlin, B., & Flynn, M. (2006a). Exercise and toll-like receptors. Exercise Immunology Review, 12, 34-53.  Gleeson, M., McFarlin, B., & Flynn, M. (2006b). Exercise and toll-like receptors. Exercise Immunology Review, 12, 34.  Golovkin, A. S., Matveeva, V. G., Kudryavtsev, I. V., Chernova, M. N., Bayrakova, Y. V., Shukevich, D. L., & Grigoriev, E. V. (2013). Perioperative dynamics of TLR2, TLR4, and TREM-1 expression in monocyte subpopulations in the setting of on-pump coronary artery bypass surgery. ISRN Inflammation, 2013, 817901.  Hanai, H. (2008). Adsorptive depletion of elevated proinflammatory CD14+CD16+DR++ monocytes in patients with inflammatory bowel disease. Am J Gastroenterol, 103(5), 1210-1216. doi:10.1111/j.1572-0241.2007.01714.x   75  Harte, A. L., Varma, M. C., Tripathi, G., McGee, K. C., Al-Daghri, N. M., Al-Attas, O. S., . . . McTernan, P. G. (2012). High fat intake leads to acute postprandial exposure to circulating endotoxin in type 2 diabetic subjects. Diabetes Care, 35(2), 375-382. doi:10.2337/dc11-1593 Herder, C., Illig, T., Rathmann, W., Martin, S., Haastert, B., Muller-Scholze, S., . . . KORA Study Group. (2005). Inflammation and type 2 diabetes: Results from KORA augsburg. GESUNDHEITSWESEN, 67, S115-S121. doi:10.1055/s-2005-858252 Hill, J. O. (2005). Walking and type 2 diabetes. Diabetes Care, 28(6), 1524-1525. doi:10.2337/diacare.28.6.1524 Horvath, P., Oliver, S. R., Ganesan, G., Zaldivar, F. P., Radom-Aizik, S., & Galassetti, P. R. (2013). Fasting glucose level modulates cell surface expression of CD11b and CD66b in granulocytes and monocytes of patients with type II diabetes. Journal of Investigative Medicine : The Official Publication of the American Federation for Clinical Research, 61(6), 972-977. doi:10.231/JIM.0b013e3182961517 Huang, S., Rutkowsky, J. M., Snodgrass, R. G., Ono-Moore, K. D., Schneider, D. A., Newman, J. W., . . . Hwang, D. H. (2012). Saturated fatty acids activate TLR-mediated proinflammatory signaling pathways. Journal of Lipid Research, 53(9), 2002-2013. doi:10.1194/jlr.D029546 Hundal, R., Petersen, K., Mayerson, A., Randhawa, P., Inzucchi, S., Shoelson, S., & Shulman, G. (2002). Mechanism by which high-dose aspirin improves glucose   76  metabolism in type 2 diabetes. Journal of Clinical Investigation, 109(10), 1321-1326. doi:10.1172/JCI200214955 Imasato, A., Desbois-Mouthon, C., Han, J., Kai, H., Andrew C. B. Cato, Akira, S., & Li, J. (2002). Inhibition of p38 MAPK by glucocorticoids via induction of MAPK phosphatase-1 enhances nontypeable haemophilus influenzae-induced expression of toll-like receptor 2. Journal of Biological Chemistry, 277(49), 47444-47450. doi:10.1074/jbc.M208140200 Jelleyman, C., Yates, T., O'Donovan, G., Gray, L. J., King, J. A., Khunti, K., & Davies, M. J. (2015). The effects of high-intensity interval training on glucose regulation and insulin resistance: A meta-analysis: The effects of HIIT on metabolic health. Obesity Reviews, 16(11), 942-961. doi:10.1111/obr.12317 Jung, M. E., Bourne, J. E., Beauchamp, M. R., Robinson, E., & Little, J. P. (2015). High-intensity interval training as an efficacious alternative to moderate-intensity continuous training for adults with prediabetes. Journal of Diabetes Research, 2015, 1-9. doi:10.1155/2015/191595 Kaneto, H., Fujii, J., Seo, H. G., Suzuki, K., Matsuoka, T., Nakamura, M., . . . Taniguchi, N. (1995). Apoptotic cell death triggered by nitric oxide in pancreatic beta-cells. Diabetes, 44(7), 733-738. doi:10.2337/diabetes.44.7.733 Karstoft, K., Winding, K., Knudsen, S. H., Nielsen, J. S., Thomsen, C., Pedersen, B. K., & Solomon, T. P. J. (2013). The effects of free-living interval-walking training on   77  glycemic control, body composition, and physical fitness in type 2 diabetic patients: A randomized, controlled trial. Diabetes Care, 36(2), 228-236. doi:10.2337/dc12-0658 Kasapis, C., & Thompson, P. D. (2005). The effects of physical activity on serum C-reactive protein and inflammatory markers: A systematic review. Journal of the American College of Cardiology, 45(10), 1563. doi:10.1016/j.jacc.2004.12.077 Keller, C., Steensberg, A., Pilegaard, H., Osada, T., Saltin, B., Pedersen, B. K., & Neufer, P. D. (2001). Transcriptional activation of the IL-6 gene in human contracting skeletal muscle: Influence of muscle glycogen content. FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology, 15(14), 2748. doi:10.1096/fj.01-0507fje Kilpatrick, M. W., Jung, P. D.,Mary E., & Little, J. P. (2014). HIGH-INTENSITY INTERVAL TRAINING: A review of physiological and psychological responses. ACSM’s Health & Fitness Journal, 18(5), 11-16. doi:10.1249/FIT.0000000000000067 Kumar, H., Kawai, T., & Akira, S. (2009). Toll-like receptors and innate immunity. Biochemical and Biophysical Research Communications, 388(4), 621-625. doi:10.1016/j.bbrc.2009.08.062 Kumar, H., Kawai, T., & Akira, S. (2011). Pathogen recognition by the innate immune system. International Reviews of Immunology, 30(1), 16-34. doi:10.3109/08830185.2010.529976   78  Kurt-Jones, E. A., Mandell, L., Whitney, C., Padgett, A., Gosselin, K., Newburger, P. E., & Finberg, R. W. (2002a). Role of toll-like receptor 2 (TLR2) in neutrophil activation: GM-CSF enhances TLR2 expression and TLR2-mediated interleukin 8 responses in neutrophils. Blood, 100(5), 1860.  Kurt-Jones, E. A., Mandell, L., Whitney, C., Padgett, A., Gosselin, K., Newburger, P. E., & Finberg, R. W. (2002b). Role of toll-like receptor 2 (TLR2) in neutrophil activation: GM-CSF enhances TLR2 expression and TLR2-mediated interleukin 8 responses in neutrophils. Blood, 100(5), 1860.  Kvernmo, H., Olsen, J. O., & Osterud, B. (1992). Changes in blood cell response following strenuous physical exercise. European Journal of Applied Physiology and Occupational Physiology, 64(4), 318-322. doi:10.1007/BF00636218 Lancaster, G. I., Khan, Q., Drysdale, P. T., Wallace, F., Jeukendrup, A. E., Drayson, M. T., & Gleeson, M. (2005; 2004). Effect of prolonged exercise and carbohydrate ingestion on type 1 and type 2 T lymphocyte distribution and intracellular cytokine production in humans. Journal of Applied Physiology, 98(2), 565-571. doi:10.1152/japplphysiol.00754.2004 Lancaster, G., Khan, Q., Drysdale, P., Wallace, F., Jeukendrup, A., Drayson, M., & Gleeson, M. (2005). The physiological regulation of toll-like receptor expression and function in humans. Journal of Physiology-London, 563(3), 945-955. doi:10.1116/jphysiol.2004.081224   79  Lancaster, G. I., Khan, Q., Drysdale, P., Wallace, F., Jeukendrup, A. E., Drayson, M. T., & Gleeson, M. (2005). The physiological regulation of toll-like receptor expression and function in humans. The Journal of Physiology, 563(3), 945-955. doi:10.1113/jphysiol.2004.081224 Langjahr, P., Díaz-Jiménez, D., Marjorie De la Fuente, Rubio, E., Golenbock, D., Bronfman, F. C., . . . Hermoso, M. A. (2014). Metalloproteinase-dependent TLR2 ectodomain shedding is involved in soluble toll-like receptor 2 (sTLR2) production: e104624. PLoS One, 9(12) doi:10.1371/journal.pone.0104624 LaVoy, E. C., Bosch, J. A., Lowder, T. W., & Simpson, R. J. (2013). Acute aerobic exercise in humans increases cytokine expression in CD27(-) but not CD27(+) CD8(+) T-cells. Brain, Behavior, and Immunity, 27(1), 54-62. doi:10.1016/j.bbi.2012.09.006 Little, J. P., & Francois, M. E. (2014). High-intensity interval training for improving postprandial hyperglycemia. Research Quarterly for Exercise and Sport, 85(4), 451-456. doi:10.1080/02701367.2014.963474 Little, J. P., Gillen, J. B., Percival, M. E., Safdar, A., Tarnopolsky, M. A., Punthakee, Z., . . . Gibala, M. J. (2011). Low-volume high-intensity interval training reduces hyperglycemia and increases muscle mitochondrial capacity in patients with type 2 diabetes. Journal of Applied Physiology, 111(6), 1554-1560. doi:10.1152/japplphysiol.00921.2011 Little, J. P., Jung, M. E., Wright, A. E., Wright, W., & Manders, R. J. F. (2014). Effects of high-intensity interval exercise versus continuous moderate-intensity exercise on   80  postprandial glycemic control assessed by continuous glucose monitoring in obese adults. Applied Physiology, Nutrition, and Metabolism, 39(7), 835-841. doi:10.1139/apnm-2013-0512 M. H. Van Soeren, Sathasivam, P., Spriet, L. L., & Graham, T. E. (1993). Caffeine metabolism and epinephrine responses during exercise in users and nonusers. Journal of Applied Physiology, 75(2), 805-812.  Maedler, K., Sergeev, P., Ris, F., Oberholzer, J., Joller-Jemelka, H. I., Spinas, G. A., . . . Donath, M. Y. (2002). Glucose-induced β cell production of IL-1β contributes to glucotoxicity in human pancreatic islets. Journal of Clinical Investigation, 110(6), 851-860. doi:10.1172/JCI0215318 Mastana, S. S., Gleeson, M., Lindley, M. R., Stensel, D. J., Bishop, N. C., & Nimmo, M. A. (2011). The anti-inflammatory effects of exercise: Mechanisms and implications for the prevention and treatment of disease. Nature Reviews Immunology, 11(9), 607-615. doi:10.1038/nri3041 Mitranun, W., Deerochanawong, C., Tanaka, H., & Suksom, D. (2014). Continuous vs interval training on glycemic control and macro- and microvascular reactivity in type 2 diabetic patients: Continuous vs interval training. Scandinavian Journal of Medicine & Science in Sports, 24(2), e69-e76. doi:10.1111/sms.12112 Morettini, M., Storm, F., Sacchetti, M., Cappozzo, A., & Mazzà, C. (2015). Effects of walking on low-grade inflammation and their implications for type 2 diabetes. Preventive Medicine Reports, 2, 538-547. doi:10.1016/j.pmedr.2015.06.012   81  Moyna, N. M., Acker, G. R., Fulton, J. R., Weber, K., Goss, F. L., Robertson, R. J., . . . Rabin, B. S. (2007). Lymphocyte function and cytokine production during incremental exercise in active and sedentary males and females. International Journal of Sports Medicine, 17(8), 585-591.  Nackiewicz, D., Dan, M., He, W., Kim, R., Salmi, A., Rütti, S., . . . Ehses, J. A. (2014). TLR2/6 and TLR4-activated macrophages contribute to islet inflammation and impair beta cell insulin gene expression via IL-1 and IL-6. Diabetologia, 57(8), 1645-1654. doi:10.1007/s00125-014-3249-1 Nieman, D. C., Miller, A. R., Henson, D. A., Warren, B. J., Gusewitch, G., Johnson, R. L., . . . Nehlsen-Cannarella, S. L. (2008). Effect of high- versus moderate-intensity exercise on lymphocyte subpopulations and proliferative response. International Journal of Sports Medicine, 15(4), 199-206.  Olefsky, J. M., & Glass, C. K. (2010). Macrophages, inflammation, and insulin resistance. Annual Review of Physiology, 72(1), 219-246. doi:10.1146/annurev-physiol-021909-135846 Oliveira, M., & Gleeson, M. (2010a). The influence of prolonged cycling on monocyte toll-like receptor 2 and 4 expression in healthy men. European Journal of Applied Physiology, 109(2), 251-257. doi:10.1007/s00421-009-1350-9 Oliveira, M., & Gleeson, M. (2010b). The influence of prolonged cycling on monocyte toll-like receptor 2 and 4 expression in healthy men. European Journal of Applied Physiology, 109(2), 251-257. doi:10.1007/s00421-009-1350-9   82  Ostrowski, K., Rohde, T., Zacho, M., Asp, S., & Pedersen, B. K. (1998a). Evidence that interleukin-6 is produced in human skeletal muscle during prolonged running. The Journal of Physiology, 508(3), 949-953. doi:10.1111/j.1469-7793.1998.949bp.x Ostrowski, K., Rohde, T., Zacho, M., Asp, S., & Pedersen, B. K. (1998b). Evidence that interleukin-6 is produced in human skeletal muscle during prolonged running. The Journal of Physiology, 508(3), 949-953. doi:10.1111/j.1469-7793.1998.949bp.x Ostrowski, K., Schjerling, P., & Pedersen, B. K. (2000). Physical activity and plasma interleukin-6 in humans – effect of intensity of exercise. European Journal of Applied Physiology, 83(6), 512-515. doi:10.1007/s004210000312 Owen, J. A., Punt, J., Stranford, S. A., Jones, P. P., & Kuby, J. (2013). Kuby immunology (7th ed.). New York: W.H. Freeman.  Parrinello, C. M., Lutsey, P. L., Ballantyne, C. M., Folsom, A. R., Pankow, J. S., & Selvin, E. (2015). Six-year change in high-sensitivity C-reactive protein and risk of diabetes, cardiovascular disease, and mortality. American Heart Journal, 170(2), 380-U247. doi:10.1016/j.ahj.2015.04.017 Pedersen, B. K., & Fischer, C. P. (2007). Beneficial health effects of exercise – the role of IL-6 as a myokine. Trends in Pharmacological Sciences, 28(4), 152-156. doi:10.1016/j.tips.2007.02.002 Pedersen, B. K. (2006). The anti-inflammatory effect of exercise: Its role in diabetes and cardiovascular disease control. Essays in Biochemistry, 42, 105.    83  Petersen, & Pedersen, B. K. (2005). The anti-inflammatory effect of exercise. Journal of Applied Physiology, 98(4), 1154-1162. doi:10.1152/japplphysiol.00164.2004 Pickup, J. C., Mattock, M. B., Chusney, G. D., & Burt, D. (1997). NIDDM as a disease of the innate immune system: Association of acute-phase reactants and interleukin-6 with metabolic syndrome X. Diabetologia, 40(11), 1286-1292. doi:10.1007/s001250050822 Powell, J., Dileo, T., Roberge, R., Coca, A., & Kim, J. (2015; 2014). Salivary and serum cortisol levels during recovery from intense exercise and prolonged, moderate exercise. Biology of Sport, 32(2), 91-95. doi:10.5604/20831862.1134314 Rincon, M. (2012). Interleukin-6: From an inflammatory marker to a target for inflammatory diseases. Trends in Immunology, 33(11), 571. doi:10.1016/j.it.2012.07.003 Robinson, E., Durrer, C., Simtchouk, S., Jung, M., Bourne, J., Voth, E., & Little, J. (2015). Short-term high-intensity interval and moderate-intensity continuous training reduce leukocyte TLR4 in inactive adults at elevated risk of type 2 diabetes. Journal of Applied Physiology, 119(5), 508-516. doi:10.1152/japplphysiol.00334.2015 Rullman, E., Rundqvist, H., Wågsäter, D., Fischer, H., Eriksson, P., Sundberg, C. J., . . . Gustafsson, T. (2007). A single bout of exercise activates matrix metalloproteinase in human skeletal muscle. Journal of Applied Physiology, 102(6), 2346-2351. doi:10.1152/japplphysiol.00822.2006 Ryba-Stanisławowska, M., Myśliwska, J., Juhas, U., & Myśliwiec, M. (2015). Elevated levels of peripheral blood CD14(bright) CD16(+) and CD14(dim) CD16(+) monocytes   84  may contribute to the development of retinopathy in patients with juvenile onset type 1 diabetes. APMIS : Acta Pathologica, Microbiologica, Et Immunologica Scandinavica, 123(9), 793-799. doi:10.1111/apm.12419 Sabroe, I., Jones, E. C., Usher, L. R., Whyte, M. K. B., & Dower, S. K. (2002). Toll-like receptor (TLR)2 and TLR4 in human peripheral blood granulocytes: A critical role for monocytes in leukocyte lipopolysaccharide responses. The Journal of Immunology, 168(9), 4701.  Sabroe, I., Prince, L. R., Jones, E. C., Horsburgh, M. J., Foster, S. J., Vogel, S. N., . . . Whyte, M. K. B. (2003a). Selective roles for toll-like receptor (TLR)2 and TLR4 in the regulation of neutrophil activation and life span. The Journal of Immunology, 170(10), 5268.  Sabroe, I., Prince, L. R., Jones, E. C., Horsburgh, M. J., Foster, S. J., Vogel, S. N., . . . Whyte, M. K. B. (2003b). Selective roles for toll-like receptor (TLR)2 and TLR4 in the regulation of neutrophil activation and life span. The Journal of Immunology, 170(10), 5268.  Schindler, R., Mancilla, J., Endres, S., Ghorbani, R., Clark, S., & Dinarello, C. (1990). Correlations and interactions in the production of interleukin-6 (IL- 6), IL-1, and tumor necrosis factor (TNF) in human blood mononuclear cells: IL-6 suppresses IL-1 and TNF. Blood, 75(1), 40-47.  Schlitt, A., Heine, G. H., Blankenberg, S., Espinola-Klein, C., Dopheide, J. F., Bickel, C., . . . Rupprecht, H. J. (2004). CD14+CD16+ monocytes in coronary artery disease and their   85  relationship to serum TNF-α levels. Thrombosis and Haemostasis, 92(2), 419-424. doi:10.1160/TH04-02-0095 Seldin, M. M., Peterson, J. M., Byerly, M. S., Wei, Z., & Wong, G. W. (2012). Myonectin (CTRP15), a novel myokine that links skeletal muscle to systemic lipid homeostasis. The Journal of Biological Chemistry, 287(15), 11968-11980. doi:10.1074/jbc.M111.336834 Shi, H., Kokoeva, M. V., Inouye, K., Tzameli, I., Yin, H., & Flier, J. S. (2006). TLR4 links innate immunity and fatty acid-induced insulin resistance. The Journal of Clinical Investigation, 116(11), 3015-3025. doi:10.1172/JCI28898 Shoelson, S. E., & Donath, M. Y. (2011). Type 2 diabetes as an inflammatory disease. Nature Reviews Immunology, 11(2), 98-107. doi:10.1038/nri2925 Simpson, R. J., McFarlin, B. K., McSporran, C., Spielmann, G., Hartaigh, B. ó, & Guy, K. (2009a). Toll-like receptor expression on classic and pro-inflammatory blood monocytes after acute exercise in humans. Brain Behavior and Immunity, 23(2), 232-239. doi:10.1016/j.bbi.2008.09.013 Simpson, R. J., McFarlin, B. K., McSporran, C., Spielmann, G., Hartaigh, B. ó, & Guy, K. (2009b). Toll-like receptor expression on classic and pro-inflammatory blood monocytes after acute exercise in humans. Brain Behavior and Immunity, 23(2), 232-239. doi:10.1016/j.bbi.2008.09.013   86  Singleton, J. R., Smith, A. G., Russell, J. W., & Feldman, E. L. (2003). Microvascular complications of impaired glucose tolerance. Diabetes, 52(12), 2867-2873. doi:10.2337/diabetes.52.12.2867 Skinner, N. A., MacIsaac, C. M., Hamilton, J. A., & Visvanathan, K. (2005). Regulation of toll-like receptor (TLR)2 and TLR4 on CD14dimCD16 monocytes in response to sepsis-related antigens. Clinical & Experimental Immunology, 141(2), 270-278. doi:10.1111/j.1365-2249.2005.02839.x Smits, GRUnberg, Derijk, Sterk, & Hiemstra. (1998). Cytokine release and its modulation by dexamethasone in whole blood following exercise. Clinical & Experimental Immunology, 111(2), 463-468. doi:10.1046/j.1365-2249.1998.00482.x Spranger, J., Kroke, A., Möhlig, M., Hoffmann, K., Bergmann, M. M., Ristow, M., . . . Pfeiffer, A. F. H. (2003). Inflammatory cytokines and the risk to develop type 2 diabetes. Diabetes, 52(3), 812. doi:10.2337/diabetes.52.3.812 Staege, H., Schaffner, A., & Schneemann, M. (2000). Human toll-like receptors 2 and 4 are targets for deactivation of mononuclear phagocytes by interleukin-4. Immunology Letters, 71(1), 1-3. doi:10.1016/S0165-2478(99)00168-6 Starkie, R. L., Angus, D. J., Rolland, J., Hargreaves, M., & Febbraio, M. A. (2000). Effect of prolonged, submaximal exercise and carbohydrate ingestion on monocyte intracellular cytokine production in humans. The Journal of Physiology, 528(3), 647-655. doi:10.1111/j.1469-7793.2000.t01-1-00647.x   87  Starkie, R. L., Rolland, J., Angus, D. J., Anderson, M. J., & Febbraio, M. A. (2001). Circulating monocytes are not the source of elevations in plasma IL-6 and TNF-α levels after prolonged running. American Journal of Physiology - Cell Physiology, 280(4), 769-774.  Starkie, R., Ostrowski, S. R., Jauffred, S., Febbraio, M., & Pedersen, B. K. (2003). Exercise and IL-6 infusion inhibit endotoxin-induced TNF-alpha production in humans. FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology, 17(8), 884. doi:10.1096/fj.02-0670fje Steensberg, A., Fischer, C. P., Keller, C., Møller, K., & Pedersen, B. K. (2003). IL-6 enhances plasma IL-1ra, IL-10, and cortisol in humans. American Journal of Physiology - Endocrinology and Metabolism, 285(2), 433-437. doi:10.1152/ajpendo.00074.2003 Steensberg, A., Hall, G. v., Osada, T., Sacchetti, M., Saltin, B., & Pedersen, B. K. (2000a). Production of interleukin-6 in contracting human skeletal muscles can account for the exercise-induced increase in plasma interleukin-6. The Journal of Physiology, 529(1), 237-242. doi:10.1111/j.1469-7793.2000.00237.x Steensberg, A., Hall, G. v., Osada, T., Sacchetti, M., Saltin, B., & Pedersen, B. K. (2000b). Production of interleukin-6 in contracting human skeletal muscles can account for the exercise-induced increase in plasma interleukin-6. The Journal of Physiology, 529(1), 237-242. doi:10.1111/j.1469-7793.2000.00237.x Steensberg, A., Keller, C., Starkie, R. L., Osada, T., Febbraio, M. A., & Pedersen, B. K. (2002). IL-6 and TNF-α expression in, and release from, contracting human skeletal   88  muscle. American Journal of Physiology - Endocrinology and Metabolism, 283(6), 1272-1278. doi:10.1152/ajpendo.00255.2002 Steppich, B., Dayyani, F., Gruber, R., Lorenz, R., Mack, M., & H. W. Löms Ziegler-Heitbrock. (2000). Selective mobilization of CD14+CD16+ monocytes by exercise. American Journal of Physiology - Cell Physiology, 279(3), 578-586.  Stewart, L. K., Flynn, M. G., Campbell, W. W., Craig, B. A., Robinson, J. P., McFarlin, B. K., . . . Talbert, E. (2005). Influence of exercise training and age on CD14+ cell-surface expression of toll-like receptor 2 and 4. Brain Behavior and Immunity, 19(5), 389-397. doi:10.1016/j.bbi.2005.04.003 Suzuki, K., Yamada, M., Kurakake, S., Okamura, N., Yamaya, K., Liu, Q., . . . Sugawara, K. (2000). Circulating cytokines and hormones with immunosuppressive but neutrophil-priming potentials rise after endurance exercise in humans. European Journal of Applied Physiology, 81(4), 281-287. doi:10.1007/s004210050044 Svendsen, I. S., Killer, S. C., & Gleeson, M. (2014). Influence of hydration status on changes in plasma cortisol, leukocytes, and antigen-stimulated cytokine production by whole blood culture following prolonged exercise. ISRN Nutrition, 2014, 561401.  Takeda, K., & Akira, S. (2004). Toll-like receptor signalling. Nature Reviews Immunology, 4(7), 499-511. doi:10.1038/nri1391 Tanner, A. V., Nielsen, B. V., & Allgrove, J. (2014). Salivary and plasma cortisol and testosterone responses to interval and tempo runs and a bodyweight-only circuit session   89  in endurance-trained men. Journal of Sports Sciences, 32(7), 680-689. doi:10.1080/02640414.2013.850594 Tilg, H., Dinarello, C. A., & Mier, J. W. (1997). IL-6 and APPs: Anti-inflammatory and immunosuppressive mediators. Immunology Today, 18(9), 428-432. doi:10.1016/S0167-5699(97)01103-1 Timmerman, K. L., Flynn, M. G., Coen, P. M., Markofski, M. M., & Pence, B. D. (2008). Exercise training-induced lowering of inflammatory (CD14+CD16+) monocytes: A role in the anti-inflammatory influence of exercise? Journal of Leukocyte Biology, 84(5), 1271-1278. doi:10.1189/jlb.0408244 Tjønna, A. E., Lee, S. J., Rognmo, Ø, Stølen, T. O., Bye, A., Haram, P. M., . . . Wisløff, U. (2008). Aerobic interval training versus continuous moderate exercise as a treatment for the metabolic syndrome: A pilot study. Circulation, 118(4), 346-354. doi:10.1161/CIRCULATIONAHA.108.772822 Triantafilou, M., Frederick G. J. Gamper, Haston, R. M., Mouratis, M. A., Morath, S., Hartung, T., & Triantafilou, K. (2006). Membrane sorting of toll-like receptor (TLR)-2/6 and TLR2/1 heterodimers at the cell surface determines heterotypic associations with CD36 and intracellular targeting. Journal of Biological Chemistry, 281(41), 31002-31011. doi:10.1074/jbc.M602794200 Triantafilou, M., Manukyan, M., Mackie, A., Morath, S., Hartung, T., Heine, H., & Triantafilou, K. (2004). Lipoteichoic acid and toll-like receptor 2 internalization and   90  targeting to the golgi are lipid raft-dependent. Journal of Biological Chemistry, 279(39), 40882-40889. doi:10.1074/jbc.M400466200 Tsukumo, D. M. L., Carvalho-Filho, M. A., Carvalheira, J. B. C., Prada, P. O., Hirabara, S. M., Schenka, A. A., . . . Saad, M. J. A. (2007). Loss-of-function mutation in toll-like receptor 4 prevents diet-induced obesity and insulin resistance. Diabetes, 56(8), 1986-1998. doi:10.2337/db06-1595 Tuan, T., Hsu, T., Fong, M., Hsu, C., Tsai, K. K. C., Lee, C., & Kong, C. (2008; 2007). Deleterious effects of short-term, high-intensity exercise on immune function: Evidence from leucocyte mitochondrial alterations and apoptosis. British Journal of Sports Medicine, 42(1), 11-15. doi:10.1136/bjsm.2006.029314 Wan, Z., Durrer, C., Mah, D., Simtchouk, S., & Little, J. (2014). One-week high-fat diet leads to reduced toll-like receptor 2 expression and function in young healthy men. Nutrition Research, 34(12), 1045-1051. doi:10.1016/j.nutres.2014.08.012 Wang, T., Lafuse, W. P., & Zwilling, B. S. (2000). Regulation of toll-like receptor 2 expression by macrophages following mycobacterium avium infection. The Journal of Immunology, 165(11), 6308.  Weinstock, C., König, D., Harnischmacher, R., Keul, J., Berg, A., & Northoff, H. (1997). Effect of exhaustive exercise stress on the cytokine response. Medicine and Science in Sports and Exercise, 29(3), 345-354. doi:10.1097/00005768-199703000-00009   91  Wever, P. C., Jansen, T. L. T. A., Pickkers, P., Netea, M. G., Mothapo, K. M., Oever, J. t., . . . Tweehuysen, L. (2014). The discriminative capacity of soluble toll-like receptor (sTLR)2 and sTLR4 in inflammatory diseases. BMC Immunology, 15(1), 55-55. doi:10.1186/s12865-014-0055-y Whiting, D., Guariguata, L., Weil, C., & Shaw, J. (2011). IDF diabetes atlas: Global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Research and Clinical Practice, 94(3), 311-321. doi:10.1016/j.diabres.2011.10.029 Woolard, M. D., & Kevil, C. G. (2015). Paying the toll for glucose regulation: A central role for TLR3. Diabetes, 64(10), 3345.  Yamamoto, M., Sato, S., Mori, K., Hoshino, K., Takeuchi, O., Takeda, K., & Akira, S. (2002). Cutting edge: A novel toll/IL-1 receptor domain containing adapter that preferentially activates the IFN-beta promoter in the toll-like receptor signaling. Journal of Immunology, 169(12), 6668-6672.  Yang, J., Zhang, L., Yu, C., Yang, X., & Wang, H. (2014a). Monocyte and macrophage differentiation: Circulation inflammatory monocyte as biomarker for inflammatory diseases. Biomarker Research, 2(1), 1. doi:10.1186/2050-7771-2-1 Yang, J., Zhang, L., Yu, C., Yang, X., & Wang, H. (2014b). Monocyte and macrophage differentiation: Circulation inflammatory monocyte as biomarker for inflammatory diseases. Biomarker Research, 2(1), 1. doi:10.1186/2050-7771-2-1   92  Ziegler-Heitbrock, L., Ancuta, P., Crowe, S., Dalod, M., Grau, V., Hart, D., . . . Lutz, M. (2010). Nomenclature of monocytes and dendritic cells in blood. Blood, 116(16), E74-E80. doi:10.1182/blood-2010-02-258558 Zwetsloot, K. A., John, C. S., Lawrence, M. M., Battista, R. A., & Shanely, R. A. (2014). High-intensity interval training induces a modest systemic inflammatory response in active, young men. Journal of Inflammation Research, 7, 9-17. doi:10.2147/JIR.S54721    93  Appendices Appendix A. Supplemental Data    Individual values for plasma glucose Subject Glucose (mM/L) Pre Post 1-H Post HC01 4.59 4.92 4.21 HC02 5.46 7.01 5.61 HC03 5.11 4.84 5.1 HC04 5.48 5.32 4.69 HC06 4.76 5.33 4.81 HC07 5.08 5.31 4.51 HC08 4.86 5.51 5.23 HC15 5.62 5.31 5.87 HC17 5.43 5.62 5.33 T2D01 5.25 5.72 5.35 T2D02 6.24 6.14 5.48 T2D04 6.7 6.98 5.58 T2D05 4.96 4.65 4.37 T2D06 8.75 6.67 4.62 T2D07 8.04 7.79 8.21 T2D09 5.74 5.9 5.67 T2D08 11.82 8.94 10.64 T2D10 7.25 6.73 6.12 T2D11 7.14 6.11 6.33    94            Individual values for monocyte numbers        Subject Classical monocytes x 105/ml CD16+ monocytes x 105/ml CD16+ percentage (%) Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 3.83 5.81 4.14 0.3 0.39 0.09 7.2 6.3 2.2 HC02 3.57 5.47 3.15 0.13 0.17 0.05 3.5 3 1.7 HC03 4.45 4.81 4.36 0.14 0.22 0.12 3.1 4.4 2.8 HC04 2.56 3.02 1.9 0.11 0.07 0.07 4.2 2.3 3.4 HC06 2.47 3.04 2.48 0.02 0.02 0.02 0.7 0.7 0.6 HC07 4.5 7.35 4.16 0.38 0.56 0.26 7.7 7 5.9 HC08 2.85 3.75 2.63 0.2 0.18 0.16 6.4 4.7 5.8 HC15 3 2.72 2.49 0.11 0.13 0.11 3.6 4.6 4.2 HC17 2.56 2.77 2.58 0.19 0.16 0.12 7 5.6 4.5 T2D01 3 5.14 2.72 0.07 0.15 0.06 2.4 2.8 2.1 T2D02 2.73 3.45 2.96 0.01 0.03 0.01 0.3 0.8 0.5 T2D04 3.38 4.94 3.03 0.04 0.04 0.23 1.3 0.8 7 T2D05 3.36 3.88 2.84 0.08 0.05 0.06 2.3 1.2 2 T2D06 2.49 4.69 2.72 0.01 0.32 0.15 0.5 6.4 5.4 T2D07 3.59 4.85 3.6 0.37 0.53 0.36 9.3 9.8 9.2 T2D09 3.3 4.31 3.44 0.28 0.4 0.3 9 10.5 7.1 T2D08 2.95 4.02 3.01 0.29 0.47 0.23 7.9 8.5 7.9 T2D10 3.48 4.83 3.39 0.22 0.29 0.15 6 5.8 4.1 T2D11 3.75 4.96 2.95 0.25 0.39 0.25 6.3 7.3 7.7 Note. Strikethrough =  statistical outlier.  95      Individual values for neutrophil numbers  Subject Neutrophils x 105/ml Pre Post 1-H Post HC01 34.78 49.77 32.2 HC02 32.64 46.3 26.92 HC03 18.59 22.2 19.21 HC04 29.17 30.92 23.81 HC06 15.58 20.69 20.82 HC07 26.51 39.41 29.49 HC08 23.1 31.57 20.49 HC15 34.25 32.39 31.12 HC17 20.2 23.06 23.19 T2D01 40.78 70.93 39.87 T2D02 26.35 32.99 29.66 T2D04 32.89 48.44 40.42 T2D05 35.66 48.49 37.2 T2D06 27.19 40.84 28.31 T2D07 25.34 37.41 30.43 T2D09 24.25 30.72 27.28 T2D08 22.66 34.65 25.99 T2D10 42.39 56.85 41.39 T2D11 32.63 45.62 25.47 Note. Strikethrough =  statistical outlier.  96     Individual values for lymphocyte numbers  Subject Lymphocytes x 105/ml Pre Post 1-H Post HC01 13.74 25.79 15.58 HC02 14.97 34.16 13.83 HC03 17.81 22.14 16.57 HC04 17.91 40.18 13.7 HC06 10.93 14.51 10.19 HC07 21.22 41.82 20.81 HC08 13.83 20.99 14.09 HC15 20.02 21.46 19.4 HC17 9.92 13.67 11.55 T2D01 13.89 38.45 14.89 T2D02 12.94 22.33 15.74 T2D04 22.14 38.56 22.87 T2D05 17.01 2.63 18.64 T2D06 8.3 20.71 7.2 T2D07 13.77 21.54 14.12 T2D09 20.37 25.77 22.17 T2D08 20.83 37.89 21.58 T2D10 14.76 24.11 14.85 T2D11 15.08 24.62 15.58     97     Individual values for leukocyte numbers  Subject Leukocytes x 105/ml Pre Post 1-H Post HC01 52.65 81.76 52.02 HC02 51.32 44.43 43.95 HC03 40.98 49.37 40.26 HC04 49.75 74.18 39.48 HC06 29 38.27 33.5 HC07 52.6 89.13 54.72 HC08 19.19 56.5 37.37 HC15 57.38 56.7 53.13 HC17 32.87 39.67 37.44 T2D01 57.74 114.68 57.54 T2D02 42.04 58.79 48.37 T2D04 58.45 91.98 66.55 T2D05 56.11 55.05 58.74 T2D06 38 66.56 38.38 T2D07 43.07 64.33 48.51 T2D09 48.2 61.21 53.19 T2D08 46.73 77.03 50.82 T2D10 60.85 86.08 59.78 T2D11 51.71 75.59 44.25 Note. Strikethrough =  statistical outlier.  98           Individual values for toll-like receptor 2 expression on monocytes and neutrophils    Subject Classical monocytes  CD16+ monocytes Neutrophils Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 9.91 7.31 6.41 11.18 6.96 5.75 3.29 3.2 3 HC02 9.82 6.31 5.92 10.89 8.22 5.9 3.09 3.01 2.91 HC03 8.72 7.9 10.02 12.17 11.62 12.05 3.53 3.55 3.66 HC04 7.07 5.49 6.97 9.09 6.81 8.64 3.15 3.1 3.28 HC06 NA NA NA NA NA NA NA NA NA HC07 13.61 10.66 7.79 14.24 10.84 9.98 3.34 3.32 3.19 HC08 11.97 8.07 18.27 17.31 11.81 21.86 3.29 3.15 3.46 HC15 6.07 7.88 7.64 8.55 11 11.86 2.79 2.82 2.69 HC17 14.76 10.14 11.82 15.64 10.46 13.95 7.28 5.53 5.91 T2D01 7.14 7.41 10.03 11.51 9.66 9.81 4.98 5.01 5.39 T2D02 11.17 7.65 6.69 NA NA NA 5.62 4.67 4.52 T2D04 14.97 9.15 11.11 NA NA NA 5.55 4.92 5.3 T2D05 9.34 10.07 9.35 8.71 8.87 8.16 5.65 6.14 5.64 T2D06 8.91 7.93 7.37 13.41 9.83 8.98 5.1 5.43 4.99 T2D07 10.28 8.8 7.8 11.72 10.42 9.34 6.13 5.66 5.31 T2D09 7.08 7.95 7.25 11.75 11.78 11.02 5.28 5.69 5.07 T2D08 11.23 9.22 12.09 13.76 11.32 14.33 6.19 5.54 6.25 T2D10 10.36 10.64 8.84 13.3 11.04 11.15 5.98 5.77 5.3 T2D11 9.89 8.29 8.21 13.89 11.84 12.09 6.19 5.64 5.87 Note. Strikethrough = statistical outlier. NA = data not collected.  99           Individual values for toll-like receptor 4 expression on monocytes and neutrophils    Subject Classical monocytes  CD16+ monocytes Neutrophils Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 7.87 7.93 9.2 8.69 8.97 9.53 8.08 7.73 8.31 HC02 7.82 7.66 7.8 8.9 7.93 8.88 7.08 7.1 7.07 HC03 7.15 7.12 8.63 7.65 8.01 7.95 6.71 6.84 6.94 HC04 7.66 8.3 8.04 8.53 7.92 7.94 7.1 7.06 6.8 HC06 6.65 6.69 6.64 NA NA NA 6.55 6.58 6.44 HC07 7.4 7.32 6.68 7.72 7.62 6.8 6.78 6.67 6.42 HC08 6.46 6.73 7.26 6.97 6.7 7.05 6.36 6.65 6.59 HC15 7.33 7.84 7.72 8.54 9.58 9.5 6.78 7.37 7.28 HC17 7.8 7.9 8.08 8.66 9.63 9.07 7.17 7.27 7.36 T2D01 6.86 7.28 7.07 7.83 7.94 8.44 6.69 6.93 6.83 T2D02 10.65 7.23 7.36 NA NA NA 6.95 6.9 6.78 T2D04 7.6 7.63 7.91 NA NA NA 6.82 6.76 6.69 T2D05 7.92 7.87 7.94 8.95 9.59 9.37 7.59 7.51 7.51 T2D06 7.38 8.89 9.25 8.03 10.65 9.8 7.17 8.95 8.97 T2D07 8.99 8.96 8.97 9.38 9.35 9.52 8.14 8.06 8.19 T2D09 14.92 15.61 13.84 12.24 12.75 12.39 7.52 7.55 7.59 T2D08 8.54 9 8.88 9.72 9.5 9.96 8.04 8.29 8.37 T2D10 128.47 106.43 106.48 22.25 22.61 20.81 8.83 8.57 7.62 T2D11 6.92 7.44 7.28 8.28 8.73 8.11 6.6 6.98 6.79 Note. Strikethrough = statistical outlier. NA = data not collected.  100           Individual values for lipopolysaccharide stimulated whole blood culture cytokine production   Subject IL-10 (pg/ml) IL-1RA (pg/ml) TNF-ɑ (pg/ml) Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 0.46 0.46 2.99 63.01 78.52 128.99 865.17 1067.39 613.47 HC02 0.75 2.72 1.89 50.67 73.39 56.88 562.62 809.82 561.13 HC03 1.33 1.89 1.89 56.88 45.28 64.75 578.86 464.05 527.3 HC04 1.2 4.41 4.65 87.88 90.28 95.86 270.85 248.2 97.94 HC06 1.53 1.87 1.7 24.71 26.5 19.76 375.9 563.1 513.69 HC07 3.23 4.17 4.65 118.03 160.95 136.07 494.55 726.38 356.47 HC08 1.06 1.84 3.7 48.52 72.66 42.98 334.33 335.98 267.62 HC15 3.31 5.21 3.31 105.92 160.65 64.1 475.78 444.24 172.31 HC17 4.44 3.5 2.76 89.43 106.79 102.02 292.04 231.18 241.74 T2D01 2.05 2.49 2.05 115.01 98.55 72.42 323.2 212.99 346.67 T2D02 NA NA NA 42.56 108.62 47.08 184.98 380.62 164.1 T2D04 1.89 1.61 1.61 83.19 92.86 87.83 389.82 397.42 258.4 T2D05 2.09 2.31 1.86 70.18 110.93 106.98 343.15 388.05 474.98 T2D06 3.81 5.41 3.81 68.22 144.25 74.25 185.33 399.28 250.2 T2D07 6.18 5.99 4.44 102.02 152.06 130.98 384.43 855.23 364.21 T2D09 5.27 6.36 6.36 69.96 91.55 101.38 391.08 534.64 191.34 T2D08 0.91 2.3 2.3 38.65 172.79 46.91 310.53 523.36 191.47 T2D10 0.98 2.09 1.86 63.69 28 33.51 565.05 510.14 689.03 T2D11 3.87 6.58 3.5 94.21 111.12 61.03 413.19 358.41 184.95 Note. Strikethrough = statistical outlier. NA = below detection limit of the assay.  101           Individual values for unstimulated whole blood culture cytokine production     Subject IL-10 (pg/ml) IL-1RA (pg/ml) TNF-ɑ (pg/ml) Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 0.44 0.44 0.29 NA NA NA NA NA NA HC02 NA NA NA 6.42 10.76 6.42 NA NA NA HC03 NA NA NA NA NA NA NA NA NA HC04 4.08 0.75 0.15 24.8 12.85 6.42 NA NA NA HC06 2.54 7.79 1.86 13.28 1070.24 12.39 NA NA NA HC07 1.19 1.87 1.36 NA NA NA NA NA NA HC08 0.98 0.98 1.42 36.45 35.61 37.71 NA NA NA HC15 2.22 2.4 1.96 18.41 17.96 14.79 2.75 0.41 0.63 HC17 2.22 2.76 2.76 25.61 48.71 30.08 1.43 3.53 0.7 T2D01 0.6 1.06 0.75 2.01 4.77 2.01 0.13 1 0.25 T2D02 1.19 1.02 0.86 4.69 5.62 3.75 NA NA NA T2D04 NA NA NA NA NA NA NA NA NA T2D05 NA NA NA 19.43 18.43 16.93 NA NA NA T2D06 1.2 0.76 0.98 2.27 0.24 2.27 0.4 0.76 0.36 T2D07 1.33 1.04 1.04 24.8 17.94 19.92 NA NA NA T2D09 2.22 1.7 3.31 19.31 16.6 27.84 0.79 0.92 1.22 T2D08 4.48 3.86 4.17 33.54 31.45 32.5 NA NA NA T2D10 1.2 1.2 0.76 13.28 13.72 10.6 2.24 0.94 0.19 T2D11 1.53 2.58 2.22 14.33 27.84 15.24 0.11 0.43 0.11 Note. Strikethrough = statistical outlier. NA = below the detection limit of the assay.  102          Individual values for lipopolysaccharide stimulated whole blood culture cytokine production corrected for total leukocytes Subject IL-10 (pg/ml) IL-1RA (pg/ml) TNF-ɑ (pg/ml) Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 0.15 0.09 0.96 19.95 16.01 41.33 273.88 217.59 196.55 HC02 0.24 1.02 0.72 16.46 27.53 21.57 182.73 303.8 212.79 HC03 0.54 0.64 0.78 23.13 15.28 26.81 235.41 156.65 218.31 HC04 0.4 0.99 1.96 29.44 20.28 40.47 90.74 55.76 41.34 HC06 0.88 0.81 0.85 14.2 11.54 9.83 216 245.22 255.54 HC07 1.02 0.78 1.42 37.4 30.1 41.44 156.69 135.82 108.56 HC08 0.92 0.54 1.65 42.14 21.43 19.17 290.38 99.11 119.35 HC15 0.96 1.53 1.04 30.76 47.22 20.11 138.19 130.58 54.05 HC17 2.25 1.47 1.23 45.35 44.87 45.42 148.1 97.13 107.63 T2D01 0.59 0.36 0.59 33.2 14.32 20.98 93.29 30.96 100.42 T2D02 NA NA NA 16.87 30.79 16.22 73.34 107.9 56.54 T2D04 0.54 0.29 0.4 23.72 16.83 21.99 111.15 72.01 64.71 T2D05 0.62 0.7 0.53 20.85 33.59 30.36 101.93 117.49 134.78 T2D06 1.67 1.35 1.65 29.92 36.12 32.24 81.28 99.99 108.65 T2D07 2.39 1.55 1.53 39.48 39.39 45 148.77 221.56 125.12 T2D09 1.82 1.73 1.99 24.19 24.93 31.77 135.22 145.58 59.96 T2D08 0.32 0.5 0.75 13.78 37.39 15.39 110.74 113.24 62.8 T2D10 0.27 0.4 0.52 17.44 5.42 9.34 154.77 98.77 192.11 T2D11 1.25 1.45 1.32 30.36 24.5 22.99 133.16 79.03 69.66 Note. Strikethrough = statistical outlier. NA = below the detection limit of the assay.  103          Individual values for unstimulated whole blood culture cytokine production corrected for total leukocytes  Subject IL-10 (pg/ml) IL-1RA (pg/ml) TNF-ɑ (pg/ml) Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 0.38 0.13 0.13 NA NA NA NA NA NA HC02 NA NA NA 2.03 2.19 2.06 NA NA NA HC03 NA NA NA NA NA NA NA NA NA HC04 1.66 0.25 0.06 10.09 4.34 2.66 NA NA NA HC06 0.85 1.75 0.79 4.45 240.45 5.23 NA NA NA HC07 0.68 0.81 0.68 NA NA NA NA NA NA HC08 0.31 0.18 0.43 11.55 6.66 11.48 NA NA NA HC15 0.64 0.71 0.61 5.35 5.28 4.64 0.8 0.12 0.2 HC17 1.13 1.16 1.23 12.99 20.46 13.39 0.73 1.48 0.31 T2D01 0.21 0.23 0.25 0.72 1.03 0.66 0.05 0.22 0.08 T2D02 0.34 0.15 0.25 1.35 0.82 1.09 NA NA NA T2D04 NA NA NA NA NA NA NA NA NA T2D05 NA NA NA 5.54 3.34 4.24 NA NA NA T2D06 0.36 0.23 0.28 0.67 0.07 0.64 0.12 0.23 0.1 T2D07 0.58 0.26 0.45 10.88 4.49 8.65 NA NA NA T2D09 0.86 0.44 1.14 7.47 4.3 9.56 0.31 0.24 0.42 T2D08 1.55 1.05 1.31 11.6 8.56 10.18 NA NA NA T2D10 0.33 0.23 0.21 3.64 2.66 2.96 0.61 0.18 0.05 T2D11 0.49 0.57 0.84 4.62 6.14 5.74 0.04 0.09 0.04 Note. Strikethrough = statistical outlier. NA = below the detection limit of the assay.      104   Individual values for plasma cytokines Subject IL-10 (pg/ml) IL-1RA (pg/ml) IL-6 (pg/ml) TNF-ɑ (pg/ml) Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post Pre Post 1-H Post HC01 1.53 2.46 2.53 NA NA NA 1.16 1.23 1.65 2.73 2.39 4.1 HC02 1.48 1.43 2.26 11.27 18.42 14.7 2.24 1.47 4.44 1.21 1.41 1.69 HC03 1.76 3.23 0.7 96.14 80.28 84.69 1.95 2.1 1.2 3.07 4.2 1.6 HC04 1.23 1.46 1 10.45 22.39 13.88 1.31 0.98 0.72 2.92 2.57 1.95 HC06 1.99 1.08 0.4 2.27 1.85 3.88 0.83 0.79 0.55 4.12 2.86 1.99 HC07 0.78 0.04 0.04 24.93 25.88 22.71 1.07 0.88 0.74 2.57 1.87 1.52 HC08 NA NA NA 25.51 26.42 18.42 0.8 0.49 0.45 3.05 1.31 1.1 HC15 9.23 8.74 10.45 35.58 44.98 33.45 3.38 3.09 3.77 4.14 3.8 4.44 HC17 NA NA NA 10.95 13.77 10.64 0.21 0.23 0.24 2.29 2.11 1.93 T2D01 2.38 3.23 2.15 35.13 39.06 43.23 2.71 3.09 2.73 2.76 3.35 2.42 T2D02 1.08 0.63 0.25 28.69 14.55 21.11 1.65 1.67 1.59 2.38 2.34 1.91 T2D04 2.69 2.3 2.3 75.43 85.79 96.54 1.8 1.76 1.99 2.84 3.07 2.76 T2D05 0.04 0.04 0.4 19.66 23.67 19.5 0.46 0.74 1.5 3.04 3 2.92 T2D06 4.11 2.44 2.02 26.11 35.28 27.03 1.33 1.34 1.1 4.18 2.45 2.6 T2D07 1 0.78 0.78 16.55 14.55 19.01 0.47 0.46 0.52 1.93 1.45 1.64 T2D09 NA NA NA 15.63 26.11 21.2 0.6 0.51 0.58 2.29 1.23 1.62 T2D08 3.02 4.15 3.49 125.36 99.67 124.17 0.76 1 1.06 1.69 2.17 1.85 T2D10 5.57 6.35 5.93 209.31 244.85 215.7 1.66 1.26 1.7 3.28 2.91 3.29 T2D11 NA NA NA 45.88 56.03 57.33 0.28 0.21 0.34 1.23 0.9 0.99   105      Unstimulated whole blood culture cytokine concentration from 4-H supernatants in response to an acute bout of high -intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X1-min @~90% maximal heart rate and IL10 (A), IL1RA (B), and TNF-α (C) in whole blood culture supernatants were measured by Magpix ELISA. Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines.  A) C) B)   106  A) B)       Whole blood culture cytokine concentration, corrected for total leukocyte numbers, from 4-H unstimulated supernatants in response to an acute bout of high -intensity interval training (HIIT). Blood samples were obtained before (Pre), immediately after (Post), and one hour following (1-H Post) a single session of HIIT involving 7 X1-min @~90% maximal heart rate and IL10 (A), IL1RA (B), and TNF-α (C) in whole blood culture supernatants were measured by Magpix ELISA. Groups means are denoted by dotted (Healthy Controls) or solid (Type 2 Diabetes) horizontal lines. C) 

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.24.1-0304569/manifest

Comment

Related Items