Faculty of Science

IMPACT OF DIETARY SALT ON BLOOD VESSEL HEALTH AND THE ROLE OF
EXERCISE AND IMMUNE SYSTEM ACTIVATION
2024 | DENZEL ENRIQUE ERNEST MARICAN

B.Sc. HONOURS THESIS – BIOLOGY

IMPACT OF DIETARY SALT ON BLOOD VESSEL HEALTH AND THE ROLE OF
EXERCISE AND IMMUNE SYSTEM ACTIVATION
by

DENZEL ENRIQUE ERNEST MARICAN

A THESIS SUBMITTED IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF

BACHELOR OF SCIENCE (HONS.)
in the
DEPARTMENT OF BIOLOGICAL SCIENCES

This thesis has been accepted as conforming to the required standards by:
Mark Rakobowchuk (Ph.D.), Thesis Supervisor, Dept. Biological Sciences
Natasha Ramroop-Singh (Ph.D.), Secondary Supervisor, Dept. Biological Sciences
Gregory Anderson (Ph.D.), External Examiner, Dept. Biological Sciences

Dated this 20th day of June 2024, in Kamloops, British Columbia, Canada

© Denzel Enrique Ernest Marican 2024

ABSTRACT
A diet that is high in salt is known to increase the risk of stroke and cardiovascular disease,
which are leading causes of mortality worldwide (WHO 2024). Additionally, endothelial
dysfunction is a common predictor of cardiovascular disease and an indicator of vascular
impairment. While acute exercise is known to cause transient endothelial dysfunction, the
combined effects of high salt intake and exercise remain unclear. The activation of the immune
system from exercise or alterations in immune functions after high salt intake may contribute to
endothelial dysfunction. In this study, participants underwent standardized acute exercise bouts
during periods of salt and placebo supplementation. Ultrasound measurements of the brachial and
popliteal arteries were taken to assess flow mediated dilation responses, effectively measuring
endothelial function before and after exercise, and before and after high salt intake. Blood samples
were also collected to analyze any changes in immune cell populations. Results indicate that
exercise induced local endothelial dysfunction in the popliteal artery, suggesting that locally
produced reactive oxygen species and glycocalyx damage due to increased shear stress were more
significant factors than immune system activation and sodium related dysfunction in reducing
flow-mediated dilation responses. Additionally, no significant changes were observed in leukocyte
populations before and after exercise or salt supplementation, likely due to insufficient exercise
stimulus, high variation in a small sample size, or the greater importance of alterations in immune
cell functions, such as increases in pro-inflammatory phenotypes, rather than absolute counts.
Thesis Supervisor: Associate Professor Mark Rakobowchuk

ii

ACKNOWLEDGEMENTS
First, I would like to extend my heartfelt gratitude to Dr. Mark Rakobowchuk for his
invaluable guidance, support, and mentorship throughout my work on this project. Over the past
few years, I have learned more than I ever imagined possible under his teaching and direction.
This work would not have been possible without his knowledge, expertise, and understanding. I
will carry his values of professionalism and care with me in my future endeavours. I would also
like to express my sincere thanks to Thane Martin, with whom I spent countless hours in the lab.
Thane's cooperation and guidance were instrumental in the completion of this project, and I could
not have asked for a better teammate. I would also like to thank Alivia Mercer for providing
constant support and feedback throughout the project and writing process. I am greatly
appreciative of the time and care you provided to help me succeed. My sincere appreciation goes
to the TRU UREAP for funding my research journey. I am also deeply grateful to Kathy Baethke
and Matthew Francis for their instrumental role in teaching me about all the equipment and helping
me gain confidence in the lab. Additionally, I would like to thank Dr. Natasha Ramroop-Singh for
serving as my secondary supervisor and Dr. Greg Anderson for being my external examiner.

iii

TABLE OF CONTENTS
ABSTRACT .................................................................................................................................... ii
ACKNOWLEDGEMENTS ........................................................................................................... iii
LIST OF FIGURES ..................................................................................................................... vii
LIST OF TABLES ......................................................................................................................... x
INTRODUCTION .......................................................................................................................... 1
Endothelial surface layer .......................................................................................................... 1
ESL in mechanotransduction .................................................................................................. 4
eNOS/NO/cGMP vasodilatory pathway ................................................................................. 5
ESL as a non-osmotic salt buffer ............................................................................................ 8
Salt-induced increases in oxidative stress impair endothelial function .................................. 9
Salt induces endothelial cell stiffening and glycocalyx damage .......................................... 12
Exercise-induced ESL damage .............................................................................................. 14
Damage to the ESL may liberate stored Na+ ........................................................................ 15
Effects of salt and exercise on immune response ................................................................. 15
Neutrophils ............................................................................................................................ 16
Monocytes and macrophages ................................................................................................ 17
Natural killer cells ................................................................................................................. 18
Exercise as an immune system adjuvant ............................................................................... 19
Objectives................................................................................................................................. 19
METHODS ................................................................................................................................... 20
Ethics ........................................................................................................................................ 20
Participants .............................................................................................................................. 20
Determining exercise capacity ............................................................................................... 20
Ventilatory threshold 1 ......................................................................................................... 21
Ventilatory threshold 2 ......................................................................................................... 24

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Experimental design ............................................................................................................... 26
Flow-mediated dilation ........................................................................................................... 27
Antibody titration ................................................................................................................... 30
Blood storage and preparation for flow cytometry ............................................................. 31
Flow cytometry ........................................................................................................................ 33
Gating strategy ........................................................................................................................ 34
Statistics ................................................................................................................................... 36
RESULTS ..................................................................................................................................... 36
Popliteal FMD ......................................................................................................................... 36
Brachial FMD .......................................................................................................................... 39
Changes in baseline artery diameters ................................................................................... 40
Flow cytometry of blood leukocyte populations ................................................................... 41
Cardiovascular fitness variables ............................................................................................ 44
DISCUSSION............................................................................................................................... 44
Local glycocalyx shedding exerts a greater influence on endothelial dysfunction than the
effects of high salt intake ........................................................................................................ 45
Inflammation response to exercise ........................................................................................ 49
Leukocytosis post-exercise ..................................................................................................... 50
Neutrophils .............................................................................................................................. 51
Monocytes and macrophages ................................................................................................. 54
Natural killer cells ................................................................................................................... 57
Limitations ............................................................................................................................... 60
Changes to baseline vessel diameter post-exercise ............................................................... 61
Exercise training inhibits pathways of salt-related dysfunction ........................................... 62
Dietary contributions to antioxidative capacity .................................................................... 63

v

CONCLUSIONS .......................................................................................................................... 63
LITERATURE CITED ................................................................................................................ 65
APPENDICES ............................................................................................................................. 78
Appendix 1 ............................................................................................................................... 78
Statistical analysis ................................................................................................................. 78
Abbreviations .......................................................................................................................... 87

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LIST OF FIGURES
Figure 1. Visual representation of the endothelial glycocalyx (left) and its major components
(right). Glycoproteins are seen attached to basal endothelial cells. GAG chains are seen branching
off from anchor proteoglycans and soluble proteoglycans which are incorporated with hyaluronic
acid (HA), endothelial cell superoxide dismutase (ec-SOD), and antithrombin-III (AT III). These
components form the endothelial glycocalyx that functions as a barrier between blood plasma and
the endothelium and exerts various roles in plasma and vessel wall homeostasis (Reitsma et al.
2007). .............................................................................................................................................. 2
Figure 2. The chemical structures of the main repeating disaccharide units and glycosidic bonds
in GAGs. GAGs shown include heparin/heparan sulfate, chondroitin sulfates, hyaluronic
acid/hyaluronan, and keratan sulfates. Hyaluronic acid stands out as the only GAG devoid of
sulfate groups. The chemical structures of keratan sulfates are not provided (Afosah and Al-Horani
2020). .............................................................................................................................................. 3
Figure 3. Diagram of NO pathway from synthesis to relaxation. NO prompts VSMC relaxation by
activating GPCRs, triggering PLC, leading to calcium release. Calcium and other cofactors
activate eNOS, producing NO. NO binds to sGC in VSMC, generating cGMP, which activates
PKG, promoting VSMC relaxation. Shear stress can also activate eNOS independently of GPCR
(da Silva et al. 2021). ...................................................................................................................... 7
Figure 4. Diagram of coupled versus uncoupled eNOS showing that uncoupled eNOS can generate
O2−., a highly toxic super radical. Uncoupled eNOS can subsequently contribute to the
development of various CVDs (Tran et al. 2022). ........................................................................ 10
Figure 5. Summary of the oxidative stress-related pathways that excess dietary salt can disrupt
causing endothelial dysfunction. Elevated dietary Na + levels increase O2- production by activating
NADPH oxidase and inhibiting SOD-1 and mitochondrial SOD (SOD-2). NO reacts readily with
O2-, preventing its diffusion into vascular smooth muscle. Although not shown, the resulting
ONOO− oxidizes BH4, which leads to uncoupling of eNOS, leading to further reductions in NO
and increases in O2−(Patik et al. 2021). ......................................................................................... 12
Figure 6. Comparing a healthy and damaged ESL, where damage to the eGC allows infiltration
of Na+ into endothelial cells causing decreased NO-mediated dilation and endothelial cell stiffness.
To the left, the healthy glycocalyx acts as a protective barrier between the plasma and the

vii

endothelial cell, buffering positively charged Na+. Conversely, elevated plasma Na+ levels on the
right result in glycocalyx damage, allowing increased Na+ access to ENaC on the endothelial
surface, consequently raising intracellular Na+ concentrations. In such instances, cellular stiffness
increases, and the conversion of shear stress into NO release is diminished (Patik et al. 2021). . 13
Figure 7. V̇CO2 over V̇O2 graph to identify VT1 through intersection points of linear components.
The intersection point of the two linear segments represents VT1. Each point is from breath-bybreath data collected during an incremental ramp exercise test using Quark CPET metabolic cart
(COSMED, Italy) .......................................................................................................................... 22
Figure 8. RQ over time to validate VT1 found on the V̇CO2/V̇O2 graph. The red line represents
the threshold RQ of 1.0. Once RQ begins increasing and is below 1.0, VT1 will have been reached.
....................................................................................................................................................... 23
Figure 9. General outline of the identification of the first and second ventilatory thresholds (VT1
and VT2) through cardiopulmonary exercise testing (CPET). This includes a focused examination
of parameters such as V̇O2 versus V̇CO2, VE/V̇CO2, VE/V̇O2, VE, and PETO2 and PETCO2 panels.
"Watt" symbolizes the rising resistance encountered in ramp incremental testing. Although not
shown, RQ over time may also be used for the determination of VT1, when it begins rising
signalling a shift from aerobic to anaerobic metabolism and achievement of VT1 (Anselmi et al.
2021). ............................................................................................................................................ 25
Figure 10. The screenshot of the CaroLab vessel wall tracking software illustrates several key
features. Red circles highlight: (A) the conversion factor, (B) vessel wall tracking guide points,
(C) the ruler tool used to determine the conversion factor, and (D) the average heart rate in beats
per minute over the testing period. ............................................................................................... 29
Figure 11. The stain index is the ratio of the separation between the positive population (red) and
the negative population (blue), divided by two times the standard deviation of the negative
population. MFI is the mean fluorescence intensity for positive and negative populations
(Kalser 2023). ............................................................................................................................... 31
Figure 12. A 1 mL aliquot of whole blood was lysed with red blood cell lysis buffer (10:1 ratio)
in a 15 mL centrifuge tube, followed by centrifugation at 300 g to pellet the peripheral blood
mononuclear cells (PBMCs). The lysed RBC layer was discarded, and the remaining pellet was
washed with 5 mL of fluorescence-activated cell sorting buffer (FACS). After resuspension and
incubation with Fc receptor blocker, the sample was stained with designated antibodies to identify

viii

leukocyte populations. Stained samples were incubated, resuspended, and analyzed using a flow
cytometer (Cytoflex, Beckman Coulter). ...................................................................................... 33
Figure 13. The flow cytometry gating strategy involved enumerating NK cell (CD56+), neutrophil
(CD66b+), and monocyte (CD14+) populations. The absence of negative populations for CD45+
resulted from the isolation of white blood cells during the blood preparation procedure. Gating for
two peaks within the CD56+ population was due to the presence of CD56+ bright and dim
subpopulations, representing distinct subsets of NK cells. ........................................................... 35
Figure 14. Exercise effects on popliteal artery flow-mediated dilation (n=4). Post-exercise
popliteal FMD was reduced by 2.6% (95% CI: 1.8 to 3.5%, p < 0.01), as determined by post hoc
analysis of exercise condition. Results are averaged over the levels of condition and time (n=4).
....................................................................................................................................................... 37
Figure 15. Effects of salt and sugar on popliteal FMD % including standard error bars. Results are
averaged over the levels of exercise. None displayed significance (p>0.05) (n=4). .................... 38
Figure 16. Brachial FMD % before and after a high salt diet and pre- and post-exercise showed
no significant differences (n=4). ................................................................................................... 39
Figure 17. Brachial artery FMD % before and after salt intake and sugar intake. Results are
averaged over the levels of exercise (n=4). .................................................................................. 40

ix

LIST OF TABLES
Table 1. Surface markers and fluorophores for immune cells. .................................................... 32
Table 2. Post Hoc comparison of pre- and post-exercise conditions found a significant mean
difference (n=4). ........................................................................................................................... 36
Table 3. Post Hoc comparison of condition and time displaying no significant differences (p>0.05)
(n=4).............................................................................................................................................. 37
Table 4. Mean percent dilation of the popliteal artery for, condition (salt or sugar), time (before or
after), and exercise (pre- and post-exercise) measured through FMD (n=4). ............................... 38
Table 5. Mean percent dilation of the brachial artery for, condition (salt or sugar), time (before or
after), and exercise (pre- and post-exercise) measured through FMD (n=4). ............................... 39
Table 6. Baseline artery diameters displayed in µm (n=4). ......................................................... 41
Table 7. Leukocyte cells/µL for, condition (salt or sugar), time (before or after), and exercise (preand post-exercise) measured through flow cytometry (n=4). ....................................................... 42
Table 8. Neutrophil cells/µL for, condition (salt or sugar), time (before or after), and exercise (preand post-exercise) measured through flow cytometry (n=4). ....................................................... 42
Table 9. Monocyte cells/µL for, condition (salt or sugar), time (before or after), and exercise (preand post-exercise) measured through flow cytometry (n=4). ....................................................... 42
Table 10. NK cells/µL for, condition (salt or sugar), time (before or after), and exercise (pre- and
post-exercise) measured through flow cytometry (n=4). .............................................................. 43
Table 11. Neutrophil percent of the total leukocyte population for, condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise) measured through flow cytometry (n=4).
....................................................................................................................................................... 43
Table 12. Monocyte percent of the total leukocyte population for, condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise) measured through flow cytometry (n=4).
....................................................................................................................................................... 43
Table 13. NK cell percent of the total leukocyte population for, condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise) measured through flow cytometry (n=4).
....................................................................................................................................................... 44
Table 14. Cardiovascular fitness variables (n=4). ........................................................................ 44

x

INTRODUCTION
The World Health Organization (WHO) (2023) recommends that the daily limit of salt
intake for adults should not exceed 2000 mg per day. On average, people consume over 4000 mg
of sodium (Na+) every day (WHO 2023). Na+ is a key cation in the extracellular fluid of the body
which contributes to the maintenance of plasma volume through osmotic effects, acid-base
balance, transmission of nerve impulses and normal cell function. However, excess Na+
consumption is linked to increased risk of cardiovascular disease (CVD), increased arterial blood
pressure (BP) and according to a meta-analysis conducted by Wang et al. (2020), the risk of CVD
increases by up to 6% with each additional gram of daily Na+ consumed. In 2023, the leading cause
of death in the United States was CVD, ahead of cancer (CDC, 2024). It is widely known that high
blood pressure (hypertension) causes CVD, contributes to kidney disease, and increases stroke
incidence (Strazzullo et al., 2009). In these diseases, the blood vessel wall, specifically the lining
called the endothelium, is the first site of dysfunction that leads to structural damage of the arterial
wall, atherosclerotic plaque formation, and potentially CVD (Widmer and Lerman, 2014).

Endothelial surface layer
The endothelium has a layer of complex sugar molecules on its surface called the
endothelial surface layer (ESL). The glycocalyx is a key component of the ESL that is anchored
by glycoproteins and proteoglycans, which form a system in which soluble molecules can further
incorporate into its structure (Reitsma et al. 2007). Glycoproteins and proteoglycans are considered
the “backbone” molecules of the glycocalyx (Figure 1). Glycoproteins connect the glycocalyx to
the endothelial cell membrane and function as endothelial cell adhesion molecules that play a
major role in cell recruitment from the bloodstream, and in cell signalling (Reitsma et al. 2007).

1

Figure 1. Visual representation of the endothelial glycocalyx (left) and its major components
(right). Glycoproteins are seen attached to basal endothelial cells. GAGs are seen branching off
from anchor proteoglycans and soluble proteoglycans which are incorporated with hyaluronic acid
(HA), endothelial cell superoxide dismutase (ec-SOD), and antithrombin-III (AT III). These
components form the endothelial glycocalyx that functions as a barrier between blood plasma and
the endothelium and exerts various roles in plasma and vessel wall homeostasis (Reitsma et al.
2007).
Glycoproteins’ general structure contains acidic oligosaccharides, such as heparan sulfate,
and terminal sialic acids, which contribute to the overall negative charge of the glycocalyx
(Weinbaum et al. 2007). In the eGC, sialic acids, such as N-acetylneuraminic acid (Neu5Ac), are
terminal residues on glycoproteins and glycolipids. The second components of the glycocalyx
“backbone” are the proteoglycans. While glycoproteins have shorter, branched oligosaccharide
chains and play roles in cell signaling and adhesion, proteoglycans have long, unbranched
glycosaminoglycans (GAG) chains, contributing to their structural support and regulation of
vascular permeability. Proteoglycans consist of a core protein to which sulphated GAGs are
covalently linked (Milusev et al. 2022). Variations in core proteins include their size, the number
of GAGs attached to them, and whether they are bound to the endothelial membrane (Reitsma et
2

al. 2007). Luminally, the glycocalyx is composed of soluble secreted proteoglycans and GAGs.
There are five groups of GAGs: heparan sulfate, chondroitin sulfate, dermatan sulfate, keratan
sulfate, and hyaluronan, all outlined in Figure 2 (Reitsma et al. 2007).

Figure 2. The chemical structures of the main repeating disaccharide units and glycosidic bonds
in GAGs. GAGs shown include heparin/heparan sulfate, chondroitin sulfates, hyaluronic
acid/hyaluronan, and keratan sulfates. Hyaluronic acid stands out as the only GAG devoid of
sulfate groups. The chemical structures of keratan sulfates are not provided (Afosah and Al-Horani
2020).
In the vasculature, heparan sulfate proteoglycans constitute around 90% of the total
proteoglycans within the glycocalyx, with chondroitin sulfate/dermatan sulfate being the second
most abundant (Oohira et al., 1983; Reitsma et al., 2007). Each GAG molecule can attach to the
proteoglycan anchors and be sulfated or acetylated to varying extents. The sulfation of GAGs is a
principal factor in determining the negative charge density of the molecule (Volpi 1999). The
composition

of

the

membrane-bound

mesh

of

proteoglycans,

glycoproteins,

and

glycosaminoglycans is dynamic. Additionally, the composition of associated plasma proteins and
soluble glycosaminoglycans undergoes constant replacement, with no distinct boundary between
locally synthesized and associated elements. Identifying clear compositional differences within the

3

glycocalyx, spanning from the endothelial membrane to the vascular lumen, is difficult. Instead, it
appears that the endothelial glycocalyx resembles a complicated, self-assembling mesh of various
polysaccharides (Reitsma et al. 2007). A dynamic equilibrium exists between the layer of soluble
components of the ESL and the flowing blood, continuously affecting the composition and
thickness of the glycocalyx. Several factors can influence the eGC including shear stress,
inflammation, diet, various disease and more. Regulated by endothelial cells, ESL volume and
composition are highly dependent on its local microenvironment in the vasculature (Reitsma et al.
2007).

ESL in mechanotransduction
One important function of the ESL is to detect alterations in blood flow and subsequently
regulate blood vessel diameter to accommodate changes in flow (Reitsma et al. 2007). The
endothelium, and thus the ESL, is in constant contact with mechanical forces caused by blood
flow, mainly characterized as shear stress. The glycocalyx plays a major role in the
mechanotransduction of shear stress signals to the endothelium (Pahakis et al. 2007). Experiments
conducted by Florian et al. (2003) and Foote et al. (2023) involved enzymatic degradation of
specific components of the glycocalyx using heparinase and neuraminidase. Their findings
revealed that degradation of these known glycocalyx components led to a significant decrease in
mechanotransduction, as evidenced by a marked reduction in nitric oxide (NO) production and
flow-dependent vasodilation.
The glycocalyx is initially involved in the mechanotransduction of shear stress within
blood vessels. Tarbell and Pahakis (2006) introduced a conceptual wind-in-the-trees model. This
model suggests that GAGs act as drag sensors, transferring force from shear stress to core proteins.

4

These core proteins then transmit the force to either the plasma membrane or the cytoskeleton
within the ESL. Weinbaum et al. (2003) further described that the forces dissipated across the
glycocalyx impose a torque on the stiff core proteins. This signal is then transmitted to the actin
cortical cytoskeleton via transmembrane domains, thus converting the sheer force into a
mechanically stimulated intracellular signal (Cosgun et al. 2020). Further supporting the role of
ESL in mechanotransduction, Dragovich et al. (2016) also concluded that shear-mediated NO
production was dependent on the presence of both heparan sulfate (HS) and hyaluronic acid (HA)
in the endothelial glycocalyx (eGC), as the removal of HS and/or HA lead to a significant decrease
in NO production.

eNOS/NO/cGMP vasodilatory pathway
In response to sheer stress on the endothelium, NO is produced by endothelium nitric oxide
synthase (eNOS). NO is a highly lipophilic, hyper-reactive, diffusible free radical gas with a
relatively short half-life in the blood (Qian and Fulton 2013). As a lipophilic, reactive gas, NO can
easily diffuse across multiple cellular membranes and interact with many different cellular and
extracellular targets including those involved in vasodilation (Qian and Fulton 2013). eNOS, a bidomain enzyme, homodimerizes to enable its enzymatic function. Each monomer comprises an Nterminal oxygenase domain with binding sites for L-Arg, heme, zinc, and tetrahydrobiopterin
(BH4), as well as a central calmodulin-binding region. Additionally, it contains a C-terminal
reductase domain with nicotinamide adenine dinucleotide phosphate (NADPH), flavin adenine
dinucleotide (FAD), and flavin mononucleotide (FMN) binding sites (Janaszak-Jasiecka et al.,
2023). NO synthesis occurs from L-arginine and molecular oxygen, with eNOS transferring
electrons from NADPH to the heme in the oxygenase domain (Förstermann and Sessa, 2012).

5

BH4, a crucial cofactor, binds to the oxygenase domain along with molecular oxygen and Larginine. Electrons from NADPH reduce and activate O 2 while oxidizing L-arginine to L-citrulline
and NO at the heme site (Förstermann and Sessa, 2012). Basically, O2 trades one of its oxygens
for nitrogen from L-arginine forming L-citrulline and NO.
NO freely diffuses into vascular smooth muscle cells and activates the guanylyl cyclase
(sGC)—cyclic guanosine monophosphate (cGMP) signalling pathway (Qian and Fulton 2013). In
this pathway, sGC is bound with high affinity to NO which catalyzes the formation of cGMP from
guanosine triphosphate (GTP). cGMP then activates downstream effector systems such as protein
kinases, phosphodiesterases, and ion channels. These effector systems stimulate the extrusion of
Ca2+ from the smooth muscle and cellular hyperpolarization to cause smooth muscle relaxation
and vasodilation of the blood vessel (Patik et al. 2021). Through this pathway, the ESL can sense
changes in blood flow and activate enzymes that release important vasodilators, like NO, that
adjust the size of the vessel according to the mechanical shear stress applied to it. However, eNOS
activation is preceded by many other cellular processes. As described in a review by Da Silva et
al. (2021), and illustrated in Figure 3, the endothelial relaxation response initiates when vasodilator
agents bind to membrane receptors on endothelial cells or through shear stress (which alternatively
triggers PI3K/AKT-dependent eNOS phosphorylation). Upon activation of membrane G-protein
coupled receptors (GPCR), phospholipase C (PLC) is activated, leading to increased
diacylglycerol (DAG) and inositol 1,4,5-trisphosphate (IP3) production. IP3 stimulates calcium
release from the cytoplasmic reticulum of the endothelial cell, elevating cytoplasmic Ca2+ levels.
This rise in Ca2+ activates calmodulin, which subsequently activates eNOS to produce NO. The
specific functions of active cGMP include phosphorylation of myosin light chain kinase (MLCK)

6

and activation of potassium channels and myosin light chain phosphatase (MLCP). Collectively,
these actions induce relaxation in vascular smooth muscle cells and causes vasodilation.

Figure 3. Diagram of NO pathway from synthesis to relaxation. NO prompts VSMC relaxation by
activating GPCRs, triggering PLC, leading to calcium release. Calcium and other cofactors
activate eNOS, producing NO. NO binds to sGC in VSMC, generating cGMP, which activates
PKG, promoting VSMC relaxation. Shear stress can also activate eNOS independently of GPCR
(da Silva et al. 2021).
Disruption of these processes, such as eNOS uncoupling and ESL damage, can lead to
endothelial dysfunction, which is the first step in CVD development (Gallo et al. 2022; Hadi et al.
2005; Widmer and Lerman 2014). One definition of endothelial dysfunction is an imbalance in
NO production and consumption, where consumption is favoured over production, leading to
reduced NO levels (Widmer and Lerman 2014). This can lead to an inability of the ESL to sense
changes in the blood vessel and regulate its diameter. Endothelial dysfunction can be attributed to
high oxidative stress and inflammation, which alter NO metabolism and can lead to global
vasoconstriction (Hadi et al. 2005; Jay Widmer and Lerman 2014). Transient dysfunction can also
be caused by mechanical shear stress or other factors that damage the sensory components of the

7

eGC (Kröpfl et al. 2021). Additionally, endothelial dysfunction is characterized by a shift towards
reduced vasodilation, smooth muscle cell proliferation, platelet adhesion and activation and
proinflammatory and prothrombic state within the arterial wall. This state favours all stages of
atherogenesis and increases CVD risk (Gallo et al. 2022).

ESL as a non-osmotic salt buffer
Another crucial role of the ESL in hypertension and inflammation is its function as a buffer
for dietary Na+, which helps maintain blood vessel function and vascular health (Reitsma et al.,
2007). The traditional two-compartment model of Na+ homeostasis, which involves regulation
through storage in plasma and kidney-mediated water retention and release, has been expanded to
incorporate Na+ storage beyond plasma levels. (Wenstedt et al. 2021). These alternate
compartments include the skin, muscle, and blood vessel wall which can vary in Na+ storage with
dietary intake. Na+ storage by the ESL is facilitated by the net negative charge of the glycocalyx,
which is determined by varying sulfation of GAGs. Negatively charged GAGs are thought to retain
passing Na+ through electrostatic interactions between the positive charge of Na+ and the negative
charge of the GAGs located in the eGC (Olde Engberink et al. 2014).
Several studies have investigated the relationship between GAG sulphation and synthesis,
and Na+ storage. GAGs in the ESL include heparan sulfate, chondroitin sulfate, dermatan sulfate,
keratan sulfate, and hyaluronan (Olde Engberink et al. 2014). Using differing Na+ loading
conditions in rats, Titze et al. (2004) found that non-osmotic Na+ storage correlated with specific
changes in GAG metabolism, where increasing skin Na+ was paired with increasing GAG content.
They also concluded that dietary NaCl loading coincided with increased chondroitin synthase
mRNA content in the skin, which is a key component of the GAG structure of the ESL (Djerbal et

8

al. 2017). In a human study by Selvarajah et al. (2017), dietary salt loading similarly increased Na+
storage in the skin. They noticed differences between sexes in salt storage and suggested that men's
thicker skin, potentially containing higher levels of dermal glycosaminoglycans, may act as a more
effective buffer for dietary Na+.
The role of the ESL in Na+ buffering has significant clinical implications in disease states
associated with ESL damage and salt intake. Diabetes mellitus and chronic kidney disease are
frequently linked with ESL damage and blood volume overload (Olde Engberink et al. 2019). This
suggests that ESL damage leading to the inability of the ESL GAGs to store Na+ may play a role
in maintaining normal volume regulation. In these diseases, the absence of Na+ storage manifests
as volume overload (Olde Engberink et al. 2019). Insights into Na+ regulation challenge our
understanding of blood pressure control and hypertension, especially regarding the impact of Na+
intake, known as Na+ sensitivity. Previous research mainly focused on renal function, assuming
impaired Na+ excretion as the cause of Na+ sensitivity. However, recent findings indicate a broader
regulation beyond the kidneys (Olde Engberink et al. 2019). The skin interstitium and extracellular
space are emerging as potential influencers of Na+ sensitivity. A disrupted or salt-overloaded ESL,
with diminished Na+ buffering capacity, permits increased Na+ transport into endothelial cells. This
impairs the endothelium, resulting in elevated reactive oxygen species (ROS), reduced antioxidant
defences, endothelial cell stiffening, and additional damage to the endothelial glycocalyx (Olde
Engberink et al., 2019; Patik et al., 2021).

Salt-induced increases in oxidative stress impair endothelial function
As mentioned previously, oxidative stress refers to an imbalance of ROS and antioxidant
activity. In particular, superoxide (O2−) can impair NO-mediated vasodilation by readily binding

9

NO, reducing its bioavailability and forming the free radical peroxynitrite (ONOO−) (Landmesser
et al. 2005; Patik et al. 2021). Both O2− and ONOO− can then oxidize the eNOS cofactor BH 4,
resulting in the uncoupling of eNOS and generation of O2− rather than NO. This increase in O2− and
ONOO− by eNOS uncoupling represents a positive feedback loop of endothelial impairment
through continuous removal of NO for vasodilation and accelerated production of O 2− from eNOS
uncoupling (Figure 4) (Tran et al. 2022).

Figure 4. Diagram of coupled versus uncoupled eNOS showing that uncoupled eNOS can generate
O2−., a highly toxic super radical. Uncoupled eNOS can subsequently contribute to the
development of various CVDs (Tran et al. 2022).
An increase in oxidative stress due to high salt has been found in many studies in rats and
humans. Lenda et al. (2000) found that an increase in ROS from a high Na+ diet-induced
endothelial dysfunction that was restored in the presence of the O2− scavenger superoxide
dismutase (SOD). In a human study by Jablonski et al. (2013) a low-Na+ diet significantly
increased brachial artery flow-mediated dilation (FMD), indicating improved endothelial function.
This was accompanied by increased NO and BH4 bioavailability and reduced oxidative stress.
They also found that supplementation with vitamin C, a well-established antioxidant, improved

10

brachial FMD potentially by restoring the redox balance and preventing oxidative stress-related
dysfunction. High salt intake has also been linked to the inhibition of antioxidant defences in the
endothelium, primarily through the reduced SOD protein expression. SODs catalyze the
dismutation of O2- into molecular oxygen and hydrogen peroxide (H 2O2). This process reduces
O2- levels, which can damage cells at high concentrations (Younus 2018). Typically studied in
rats, both activity and expression of SOD isoforms were reduced with high salt diets (Patik et al.
2021).
Several studies have also investigated the effects of a high-salt diet on NADPH oxidase
another contributor of O2-. NADPH oxidases are recognized as the primary generators of O 2- in the
vasculature. In various conditions like diabetes, hypertension, smoking, obesity, and aging, both
the increased expression and activity of NADPH oxidases exist. The activation of NADPH
oxidases plays a significant role in cardiovascular disease development (Janaszak-Jasiecka et al.
2023). Numerous studies suggest that high salt intake induced greater NADPH oxidase expression
(Guers et al. 2019; Kitiyakara 2003) or activity (Lenda and Boegehold 2002; Zhu et al. 2007) in
rat arteries contributing to increased oxidative stress. Various factors, including the exercise
immune response and excess dietary salt, can cause increased oxidative stress and redox
imbalances leading to ESL damage and endothelial dysfunction (Figure 5) (He et al. 2016; Patik
et al. 2021).

11

Figure 5. Summary of the oxidative stress-related pathways that excess dietary salt can disrupt
causing endothelial dysfunction. Elevated dietary Na+ levels increase O2- production by activating
NADPH oxidase and inhibiting SOD-1 and mitochondrial SOD (SOD-2). NO reacts readily with
O2-, preventing its diffusion into vascular smooth muscle. Although not shown, the resulting
ONOO− oxidizes BH4, which leads to uncoupling of eNOS, leading to further reductions in NO
and increases in O2−(Patik et al. 2021).

Salt induces endothelial cell stiffening and glycocalyx damage
High dietary Na+ intake may diminish NO release by altering the mechanical properties of
endothelial cells. Several studies have documented endothelial cell stiffening and ESL damage
when endothelial cells are exposed to elevated Na+ concentrations (Korte et al. 2011; Lenda et al.
2000; Oberleithner et al. 2011; Oberleithner et al. 2007; Olde Engberink et al. 2019; van Golen et
al. 2014). Oberleithner et al. (2007) cultured endothelial cells exposed to a Na+ bath which
increased stiffness and reduced NO release. Korte et al., (2011) expanded on Oberleithners 2007
study finding that this effect was caused by the opening of epithelial Na+ channels (ENaC), leading
to Na+ entry, and subsequent cell swelling and stiffening. Another study by Oberleithner et al.

12

(2011) demonstrated that prolonged exposure to high extracellular Na+ concentrations resulted in
a 50% reduction in eGC height and a 130% increase in ESL stiffness. Oberleithner et al. (2011)
also observed a reduction in heparan sulfate residues, a major component of the eGC, by 68%,
leading to eGC destabilization and collapse. These studies suggest that ESL damage may increase
Na+ entry into endothelial cells, potentially contributing to endothelial dysfunction and arterial
hypertension in individuals with high salt intake (Korte et al. 2011; Oberleithner et al. 2011;
Oberleithner et al. 2007). The combination of eGC damage and endothelial cell stiffening
diminishes the mechanotransduction of shear stress into NO release, further exacerbating
endothelial dysfunction (Patik et al. 2021). In summary, excess salt consumption can significantly
impair endothelial function by attenuating NO release and damaging the endothelial glycocalyx,
as shown in Figure 6.

Figure 6. Comparing a healthy and damaged ESL, where damage to the eGC allows infiltration
of Na+ into endothelial cells causing decreased NO-mediated dilation and endothelial cell stiffness.
To the left, the healthy glycocalyx acts as a protective barrier between the plasma and the
endothelial cell, buffering positively charged Na+. Conversely, elevated plasma Na+ levels on the
right result in glycocalyx damage, allowing increased Na+ access to ENaC on the endothelial
surface, consequently raising intracellular Na+ concentrations. In such instances, cellular stiffness
increases, and the conversion of shear stress into NO release is diminished (Patik et al. 2021).

13

Exercise-induced ESL damage
Exercise may be another factor that can transiently impair endothelial function, likely
through its systemic and local effects that degrade the ESL. Typically, a bout of exercise increases
blood flow to working muscles, whilst reducing blood flow to non-working tissues (Sarelius and
Pohl 2010). This increased blood flow usually dilates large and small arteries through the ESL's
ability to control the release of NO (Pahakis et al. 2007).
Endurance workouts or mainly aerobic exercise are widely recognized for triggering the
overproduction of ROS from heightened metabolism (He et al. 2016). This phenomenon leads to
oxidative stress and associated injuries. Studies suggest that endurance exercise can result in a 13–fold increase in O2− levels during muscle contraction (Sakellariou et al. 2013). The increase in
ROS resulting from exercise may lead to reductions in endothelial function through pathways
involving increases in oxidative stress. It should be noted, however, that regular or moderate
exercise has been shown to enhance antioxidant defence and endothelial function (He et al. 2016).
It is acute bouts of intense exercise that can transiently reduce endothelial function through the
overproduction of ROS (Higashi, 2015).
Exercise-induced increases in local blood flow have also been found to disrupt the ESL
through shear stress-induced glycocalyx damage. This disturbance can lead to transient reductions
in FMD when measured using the ultrasound technique. In fact, strenuous exercise impairs
endothelial function and researchers suggest that during exercise the ESL can be shed (Hahn et al.
2021; Steinach et al. 2022). Lee et al. (2019) found that after a cycling exercise at 70% VO2 max
for 45 minutes, glycocalyx components increased in the serum. They concluded that the increase
in serum concentrations of glycocalyx components may have been due to acute shedding caused
by increased blood flow in the vessels Grandys et al. (2023) similarly supported glycocalyx

14

shedding as a cause of a marked decrease in FMD in overtrained female track athletes who had
significantly higher serum concentrations of HA and syndecan-1 (SDC-1).

Damage to the ESL may liberate stored Na+
Once the ESL is shed, it may liberate stored Na+ from the ESL, enabling it to enter the
endothelium and induce endothelial dysfunction as described above (Patik et al. 2021).
Considering the important role of ESL GAGs in salt storage, and the potential degradation caused
by prolonged excess salt intake and acutely by strenuous exercise, exercise-induced damage to the
ESL may interact with the effects of excess salt, amplifying endothelial damage and dysfunction
(Hahn et al. 2021; Kröpfl et al. 2021; Olde Engberink et al. 2019; Steinach et al. 2022). Excess
salt damaging the ESL or local blood flow changes from exercise could allow greater transport of
salt directly into the endothelium, further exacerbating endothelial cell stiffening and disruption of
the eNOS/NO/cGMP dilation pathway (Korte et al. 2011; Oberleithner et al. 2011; Patik et al.
2021). The transient imbalance of ROS from exercise may independently cause endothelial
dysfunction by increasing oxidative stress-related disruption of the vasodilatory pathway.
Measuring endothelial dysfunction through FMD can allow us to quantify each of these factors
that may affect ESL and endothelial dysfunction, both individually and in conjunction with each
other. However, whether the blood flow directly causes ESL shedding or if other effects of
exercise, such as the activation of the immune system, trigger this process, remains unknown.

Effects of salt and exercise on immune response
Besides the effects of excess salt and exercise on endothelial damage, there are also
changes in circulating immune cell populations that occur immediately post-exercise and

15

following excessive salt loading (Li et al. 2022). It is well understood that during and immediately
after exercise, there are significant changes in the composition and number of blood leukocytes
(Peake et al. 2017). All major leukocyte subpopulations tend to increase in number during exercise
due to hemodynamic shear stress and/or catecholamines acting on leukocyte β2-adrenergic
receptors (Peake et al. 2017). These circulating immune cells include neutrophils, monocytes, and
lymphocytes, which undergo various alterations both during exercise and during periods of excess
salt loading. These alterations could affect their contributions to oxidative stress and, therefore,
endothelial dysfunction.

Neutrophils
Neutrophils experience suppressed activity with excess salt intake, including suppression
of degranulation, O2- production, phagocytosis, adhesion, and migration (Li et al. 2022). In human
neutrophils, Krampert et al. (2021) concluded that high salt prevented excessive ROS production,
which decreased their antimicrobial potential but curtailed ROS-mediated damage. This implies
that while salt may hinder neutrophils' ability to contribute to oxidative stress to combat pathogens
salt may also prevent damage to the ESL by hindering ROS production. Conversely, Mazzitelli et
al. (2022) reported that the effect of salt on neutrophil activity was dependent on exposure time.
Initially, neutrophils under high salt conditions were inhibited, showing a lack of response to
conventional agonists such as lipopolysaccharide (LPS), the chemotactic peptide fMLP, or
Zymosan. However, exposure to high concentrations of salt for longer periods resulted in the
activation of neutrophil inflammatory responses and an increased response to conventional
agonists.

16

While investigating the links between exercise-induced neutrophilia and blood oxidative
stress, Quindry et al. (2003) found significant blood oxidative stress immediately after maximal
intensity exercise. They also observed neutrophilia and a subsequent increase in neutrophilgenerated O2−. However, Quindry et al. (2003) stressed that other potential sources for oxidative
stress cannot be ruled out, limiting their findings. The effects of salt and exercise on neutrophil
activity in the context of oxidative stress are yet to be studied.

Monocytes and macrophages
A high salt diet can also increase circulating monocytes in mice and humans and induce
the formation of pro‐inflammatory human monocytes, which play a key role in the immune
response by promoting inflammation (Li et al. 2022; Austermann et al. 2022). These monocytes
are characterized by their ability to produce and release pro-inflammatory cytokines, such as
tumour necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6), NO
and ROS upon activation (Li et al. 2022; Austermann et al. 2022). Wenstedt et al. (2019)
demonstrated that a high salt diet increased C-C chemokine receptor type 2 (CCR2) expression on
monocytes in vitro and in vivo, coinciding with increased plasma monocyte chemoattractant
protein-1 (MCP-1), increased salt-induced transendothelial migration of monocytes, and increased
skin macrophage content. Wenstedt et al. (2019) also found macrophages demonstrated an increase
in pro-inflammatory phenotype after salt exposure. This pro-inflammatory priming of both
monocytes and macrophages, as well as CCR2, has been linked to the development of hypertension
and atherosclerosis, which is associated with ESL damage and endothelial dysfunction (Wenstedt
et al. 2019; Xiao and Harrison 2020). Further supporting the effects of high salt on macrophages,
Zhang et al. (2015) found that high salt can induce a shift in macrophage phenotype, characterized

17

by enhanced pro‐inflammatory and suppressed anti‐inflammatory gene expression. Wonner et al.
(2016) examined the exercise effects on monocytes and observed a significant mobilization of
CD14+CD16+ pro-inflammatory monocytes even after a small one-minute bout of strenuous
exercise. While reviewing the clinical impacts of Na+ storage, Olde Engberink et al. (2019)
described how monocytes, which seem attracted to high skin Na+ concentrations, play a crucial
regulatory role in Na+ homeostasis. They further explained that once in the skin, macrophages
modulate vascular endothelial growth factor-C (VEGF-C)–mediated cell increases of lymph
vessels, which is considered the principal process of mobilization of excessive Na+ from the skin.
Basically, macrophages control the growth of cells within lymph vessels in the skin, which helps
in eliminating excess Na+ from this tissue.

Natural killer cells
During and following exercise, Natural killer (NK) cell levels rise in peripheral blood. This
increase is attributed to the release of cytokines during muscle contraction, which promotes the
proliferation, maturation, and activation of NK cells (Quintana-Mendias et al., 2023). Additionally,
exercise induces the release of catecholamines, mobilizing epinephrine-dependent NK cells
(Quintana-Mendias et al., 2023). Moreover, heightened blood flow can stimulate circulating NK
cells by activating NK reservoirs located in the vascular endothelium (Quintana-Mendias et al.,
2023). Although the dysregulation of NK cell activation and development has been investigated
during high salt diets, their contribution to oxidative stress has yet to be reported.
The effects on immune cell populations vary depending on the cell type. While neutrophils
and macrophages may contribute to inflammation and oxidative stress during exercise and high
salt diets, there is less evidence regarding the role of NK cells in generating ROS (Quindry et al.

18

2003; Zhang et al. 2015). Monocytes might also play a crucial role in removing excess Na+ from
the skin, but it is unclear whether this process is enhanced or diminished during strenuous exercise
leading to monocytosis (Olde Engberink et al. 2019).
Exercise as an immune system adjuvant
During short-duration moderate to high-intensity workouts lasting less than 60 minutes,
tissue macrophages display antipathogen activity, and there is increased circulation of immune
components such as immunoglobulins, anti-inflammatory cytokines, neutrophils, NK cells,
cytotoxic T cells, and immature B cells (Nieman and Wentz 2019). These elements are crucial for
immune defence and metabolic health. Additionally, short-duration moderate exercise does not
lead to high levels of stress hormones or proinflammatory cytokines, unlike high-intensity or
prolonged exercise, which preserves immune cell function and reduces inflammation over time
(Nieman and Wentz 2019).
Objectives
In this study, we aim to investigate whether a high-salt diet induces endothelial dysfunction
and whether changes in blood flow that induce disruption of the endothelial surface layer can
exacerbate this dysfunction. To examine these mechanisms, we will use lower-body exercise as a
stimulus to induce local lower limb ESL disruption. Additionally, we will assess immune system
activation and endothelial function measures in the non-exercised upper limbs to identify whether
changes are immune-related or systemic. To achieve this, the strenuous exercise bout involving
cycling, which can stimulate a whole-body immune response characterized by an increase in
leukocyte cell counts and other inflammatory markers (Akhtari-Shojaei 2011). Cycling will
primarily increase blood flow to the legs whereas arm blood flow will remain relatively stable thus
localizing flow-induced ESL disruption to the legs. By comparing the dilation in the arms to that
19

in the legs before and after exercise, we can determine whether local blood flow and oxidative
stress or the immune response contribute to ESL disruption. Additionally, we will examine
whether the effects of salt exacerbate or blunt any observed endothelial dysfunction.

METHODS
Ethics
Ethics approval was granted by the Thompson Rivers University ethics committee. All
participants were informed of study procedures and risks and signed written consent forms to
partake in the study which were witnessed and signed by the investigators.

Participants
Participants were pre-screened to ensure they all met the inclusion criteria and completed
a Physical Activity Readiness + (PAR-Q+) (Bredin et al., 2013). Participants did not have a history
of cardiovascular disease, diabetes, blood-related diseases, or other cardiovascular risk factors.
Participants were non-smokers and did not have any known metabolic disorders. Before testing
was conducted, participants were instructed to avoid physical activity including cycling, running,
and resistance exercise 24 hours before testing.

Participants were also instructed to avoid

consumption of alcohol, marijuana, and any other non-prescription drugs 24 hours before testing.
Participants were additionally instructed to avoid caffeine and not eat four hours before testing on
the testing days.

Determining exercise capacity
Exercise capacity testing involved a graded exercise test on a cycle ergometer (Garmin
TacX cycle ergometer, Garmin Ltd. US). At the beginning of each Exercise capacity test, a gas

20

and volume calibration was performed according to the manufacturer's instructions on the Quark
CPET metabolic cart (COSMED, Italy). The ramp exercise bout involved a five-minute warm-up
at 50 Watts followed by an increased work rate of 25 watts per minute. The incremental ramp
exercise was controlled through TacX Bluetooth software (TacX cycle ergometer, Garmin Ltd.
US) to actively control resistance and monitor and record pedal speed. Participants maintained 70
rotations per minute (RPM) pedal cadence and continued the exercise bout until volitional fatigue.
Breath-by-breath data was measured and monitored using the Quark CPET metabolic cart
(COSMED, Italy) and analyzed to identify ventilatory thresholds (VT1 and VT2). VT1 and VT2
were identified using a modified V-slope method (Beaver et al. 1986). This method involved
analyzing plots of VE/V̇CO2, VE/V̇O2, V̇CO2/V̇O2, PETCO2 and PETO2, and respiratory quotient
(RQ) over time.

Ventilatory threshold 1
Ventilatory threshold 1 (VT1) was found by combining points on the graphs to find the
most likely wattage that resulted in achieving VT1. During incremental exercise below the VT1,
the amount of carbon dioxide (CO2) delivered to the lungs increases linearly with oxygen uptake
(V̇O2). However, once above the VT1, the rate of CO2 output (V̇CO2) starts to increase more
rapidly in relation to V̇O2 (Beaver et al., 1986; Solberg et al., 2005). This change in CO2 output
relative to O2 consumption can be seen graphically at the intersection point of the two linear
portions of the V̇CO2/V̇O2 curve (as seen in Figure 7). Additionally, this point can be crossreferenced with the RQ by time graph. RQ is the ratio of carbon dioxide produced to oxygen
consumed which provides insight into the metabolic substrates utilized during exercise (Kakutani
et al. 2018). As exercise intensity increases, there is a gradual increase in metabolism through

21

anaerobic pathways alongside aerobic pathways, characterized by an increase in RQ. The point at
which RQ begins to rise indicates a sharp increase in anaerobic metabolism as intensity increases
(Solberg et al. 2005). RQ over time can be used to validate the VT1 value found using the
V̇CO2/V̇O2 graph, where the VT1 must be achieved before RQ surpasses a value of 1.0. Figures 7
and 8 illustrate graphs derived from breath-by-breath data collected during an incremental ramp
exercise test to find VT1.

Figure 7. V̇CO2 over V̇O2 graph to identify VT1 through intersection points of linear components.
The intersection point of the two linear segments represents VT1. Each point is from breath-bybreath data collected during an incremental ramp exercise test using Quark CPET metabolic cart
(COSMED, Italy)

22

Figure 8. RQ over time to validate VT1 found on the V̇CO2/V̇O2 graph. The red line represents
the threshold RQ of 1.0. Once RQ begins increasing and is below 1.0, VT1 will have been reached.
Minute ventilation (VE) and PETO2 and PETCO2 graphs can also be used to find ventilatory
thresholds. VT1 estimations can be verified using the following criteria: 1) The VE/V̇O2 curve
begins to rise as the VE/V̇CO2 curve remains flat or decreases, 2) The PETCO2 curve is rising or
constant, while the PETO2 curve changes from declining or flat to rising. Estimates of VT1
generally fall between 45% and 65% of individuals measured V̇O2 max, which can also be used
as validation (Balady et al. 2010; Davis et al. 1976). Each participant's VT1 was used to calculate
the appropriate exercise prescription for subsequent testing sessions. Both individually and in
combination, these methods have undergone extensive review and testing to establish their
effectiveness in identifying VT1 (Beaver et al., 1986; Davis et al., 1976; Kakutani et al., 2018;
Solberg et al., 2005).

23

Ventilatory threshold 2
Ventilatory threshold 2 (VT2) marks the stage of incremental exercise characterized by a
rapid rise in VE compared to V̇O2 (Martini et al., 2022). This surge in VE, resulting from increased
respiratory rate and tidal volume, is driven by heightened CO 2 production due to hydrogen ion
accumulation with escalating exercise intensity (Martini et al., 2022). While VT1 can be identified
as the point where the VE/V̇O2 curve begins to rise as the VE/V̇CO2 curve remains flat or
decreases, VT2 is identified as the point where VE/V̇O2 and VE/V̇CO2 simultaneously increase.
VT2 can also be found by examining the V̇CO2/V̇O2 graph, where a third linear component may
appear beyond VT1, intersecting with the second component. However, in practice, identifying
this third component can be challenging (Martini et al., 2022). Using the PETCO2 over time graph
the deflection point of the curve where PETCO2 begins to decline can also establish VT2 (Anselmi
et al. 2021). Figure 9 illustrates the indices for VT1 and VT2.

24

Figure 9. General outline of the identification of the first and second ventilatory thresholds (VT1
and VT2) through cardiopulmonary exercise testing (CPET). This includes a focused examination
of parameters such as V̇O2 versus V̇CO2, VE/V̇CO2, VE/V̇O2, VE, and PETO2 and PETCO2 panels.
"Watt" symbolizes the rising resistance encountered in ramp incremental testing. Although not
shown, RQ over time may also be used for the determination of VT1, when it begins rising
signalling an increase in anaerobic metabolism and achievement of VT1 (Anselmi et al. 2021).
Generally, VT1 can be achieved within 1–3 minutes of incremental ramp testing, while
VT2 may take 10-15 minutes to reach (Rossiter 2011). The desired work rate was calculated as
the wattage value 1/3 between the wattage at VT1 and VT2, within the heavy exercise domain.
This work rate would cause glycocalyx shedding and immune system activation, but not
exhaustive levels of exertion for participants (Sapp et al. 2019; Schlagheck et al. 2020). Several
studies have demonstrated that moderate to high-intensity exercise was required to cause
glycocalyx shedding, oxidative stress, and immune response (He et al. 2016; Kröpfl et al. 2021;
Lee et al. 2019; Peake et al. 2017; Quindry et al. 2003; Quintana-Mendias et al. 2023; Steinach et
al. 2022; Wonner et al. 2016).

25

Experimental design
After completing exercise capacity testing, participants returned to the lab on four separate
days for experimental trials. In experimental session one, baseline readings were taken without salt
loading. Participants were then given salt or sugar pills (1.15 g) to be taken daily over two weeks.
Sugar pills served as the placebo, while salt pills constituted the experimental treatment. Whether
placebo or salt pills were given first was randomized for each participant. Participants gradually
increased salt intake to 13.8 g per day by consuming 12 pills daily. Experimental session two
occurred exactly two weeks after experimental session one, involving the same measurements.
Following experimental session two, a two-week washout period was implemented to return
participants to baseline levels. Experimental session three reassessed participants' baseline
variables. Subsequently, participants resumed salt or sugar pill intake for another two weeks.
Experimental session four marked the final testing day, with measurements identical to previous
days. Throughout the trial, participants maintained their regular diets and lifestyles. Salt pills were
designed to dissolve in the small intestine to minimize adverse effects, reducing the likelihood of
early release in the stomach and subsequent nausea. Participants were instructed to consume no
more than 3-4 pills at once and to take pills only after eating to mitigate nausea.
Experimental sessions involved continuous blood pressure recording, electrocardiogram
(ECG) measurements and ultrasound measurements to assess FMD of popliteal and brachial
arteries. Venous blood samples were obtained and analyzed through enzyme-linked
immunosorbent assay (ELISA) testing and flow cytometry. Blood pressure was measured using
photoplethysmography (PPG). This method of continuous non-invasive arterial pressure
monitoring (CNAP) uses the volume clamp technique in which an infrared light is shone through
the middle or fourth finger whilst a cuff inflates and deflates to keep blood volume constant. These

26

changes in cuff pressure are proportional to arterial blood pressure and calibrated to
oscillometrically obtained brachial blood pressure. Since light is absorbed by blood, changes in
blood flow can be detected by PPG sensors as changes in the intensity of light through the finger
cuffs. After participants were instrumented, they were instructed to lie in a supine position at rest
for approximately 20 minutes to ensure resting conditions. Once participants finished their rest
period, a baseline FMD was determined at the brachial, and popliteal arteries. Additionally, a
venous blood sample of 5 mL was obtained from an antecubital vein and placed in an EDTA tube.
An aliquot of 1 mL of blood was taken from the 5 mL sample for flow cytometry preparation and
the rest of the 4 mL were centrifuged at 2500 g for 10 minutes. Two hundred and fifty µL of plasma
was then distributed in six Eppendorf tubes to be analyzed for glycocalyx components. Once
baseline data collection was completed, the 45-minute exercise bout began at the previously
determined work rate (1/3 between VT1 and VT2). Immediately after exercise, blood was drawn
and FMD was assessed at the brachial and popliteal arteries.

Flow-mediated dilation
FMD was measured at the brachial and popliteal arteries using an EPIQ 5 Ultrasound
system (Phillips, US). The FMD protocol consisted of a baseline measurement of artery diameter
with no peripheral ischemia followed by an assessment of dilation after cuff deflation (Rosenberry
& Nelson, 2020). Recordings included 15 seconds of resting artery diameter, 15 seconds before
pressure cuff release, and two minutes immediately post-pressure cuff release. Ischemia of the
forearm or calf was induced downstream of the artery of interest by inflation of a blood pressure
cuff to >200 mmHg for five minutes. Releasing the pressure cuff triggers an immediate surge in
blood flow through the brachial or popliteal artery, initiating vasodilation in the blood vessels

27

(Rosenberry & Nelson, 2020). Ultrasound recordings were taken in 15- and 30-second durations.
Video clips were transferred using a USB to be analyzed through CaroLab software (Zahnd et al.
2017) and Microsoft Excel 2016 (Microsoft Corporation, 2016).
Using CaroLab software, arterial walls were identified and tracked throughout the video
clips to identify baseline vessel diameter and peak vessel diameter. Baseline diameter was
measured over 15 heart cycles and peak diameter was measured over 3 heart cycles. The number
of frames analyzed for 15 and 3 heart cycles was dependent on the heart rate (HR) of the participant
and the frames per second or refresh rate of the ultrasound recording (measured in Hz).

# 𝑜𝑓 𝑓𝑟𝑎𝑚𝑒𝑠 𝑓𝑜𝑟 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 = 𝐻𝑅 (𝑏𝑝𝑚) 𝑥

# 𝑜𝑓 𝑓𝑟𝑎𝑚𝑒𝑠 𝑓𝑜𝑟 𝑝𝑒𝑎𝑘 = 𝐻𝑅 (𝑏𝑝𝑚) 𝑥

1𝑚𝑖𝑛
𝑥 15 𝑐𝑦𝑐𝑙𝑒𝑠 𝑥 𝑟𝑒𝑓𝑟𝑒𝑠ℎ 𝑟𝑎𝑡𝑒 (𝐻𝑧)
60𝑠𝑒𝑐

1𝑚𝑖𝑛
𝑥 3 𝑐𝑦𝑐𝑙𝑒𝑠 𝑥 𝑟𝑒𝑓𝑟𝑒𝑠ℎ 𝑟𝑎𝑡𝑒 (𝐻𝑧)
60𝑠𝑒𝑐

Moreover, the measurements extracted from the video clips were calibrated to accurately
reflect the actual artery diameter utilizing the ruler tool within the CaroLab software. This involved
multiplying the diameter readings for both the popliteal and brachial arteries by a factor obtained
through the ruler tool. This adjustment compensated for inaccurate diameter readings that occurred
during the transfer of ultrasound clips from the ultrasound to CaroLab. Figure 10 shows CaroLab
software analysis of a brachial artery to determine changes in diameter. This includes rulerdetermined correction factor, blood vessel wall tracking, refresh rate (Hz), and HR (bpm) all
circled in red.

28

Figure 10. The screenshot of the CaroLab vessel wall tracking software illustrates several key
features. Red circles highlight: (A) the conversion factor, (B) vessel wall tracking guide points,
(C) the ruler tool used to determine the conversion factor, and (D) the average heart rate in beats
per minute over the testing period.
After transferring the diameter readings to Excel, the baseline diameter was determined by
averaging the diameter readings over 15 heart cycles. This baseline diameter was then multiplied
by the previously determined conversion factor. Next, the peak diameter was calculated by
averaging the highest diameter readings over three heart cycles following cuff release.
Subsequently, this peak diameter was multiplied by the conversion factor to obtain the true peak
vessel diameter. To quantify arterial response to FMD, relative percent dilation was calculated
using baseline and peak vessel diameters. These relative percent dilation values were determined
for pre- and post-exercise conditions under both control and salt-loaded conditions.

29

% 𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 =

𝑃𝑒𝑎𝑘 𝑑𝑖𝑎𝑚𝑒𝑡𝑒𝑟 − 𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑑𝑖𝑎𝑚𝑒𝑡𝑒𝑟
𝑥 100
𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑑𝑖𝑎𝑚𝑒𝑡𝑒𝑟

Antibody titration
Antibody titrations were conducted to determine the optimal amounts of each type of
fluorescent antibody per sample. In five tube arrays, each antibody was distributed in decreasing
concentrations into the tubes which contained equal amounts of a lysed and washed human blood.
Fluorescence was then measured using the flow cytometer for each tube of the array and the
staining index was calculated from the populations of leukocytes stained. Illustrated in Figure 11,
the stain index is defined as the ratio of the separation between the positive and negative
populations divided by two times the standard deviation (SD) of the negative population
(Kalser 2023).

𝑆𝑡𝑎𝑖𝑛 𝐼𝑛𝑑𝑒𝑥 =

𝑀𝐹𝐼𝑝𝑜𝑠 − 𝑀𝐹𝐼𝑛𝑒𝑔
2 𝑥 𝑆𝐷𝑛𝑒𝑔

The stain index was calculated for each volume of antibody used in the six tube arrays,
ranging from 0.25 µL to 5 µL. It was determined that 2.5 µL was the optimal antibody volume
for staining the cell populations of interest. This volume yielded an equivalent stain index
value to the BIORAD-recommended 5 µL, indicating optimal staining efficiency. The
Cytoflex flow cytometry software provided the mean fluorescence intensity (MFI) and SD
required for stain index calculations.

30

Figure 11. The stain index is the ratio of the separation between the positive population (red) and
the negative population (blue), divided by two times the standard deviation of the negative
population. MFI is the mean fluorescence intensity for positive and negative populations
(Kalser 2023).

Blood storage and preparation for flow cytometry
Once the participant’s blood was drawn in EDTA tubes, the blood was divided into 1 mL
and 4 mL aliquots, for flow cytometer leukocyte enumeration and glycocalyx components
respectively. Blood leukocyte analysis was conducted immediately to maintain the accuracy of
leukocyte counts (Greineder and Younger 2006; Sędek et al. 2020). Blood plasma used to
determine glycocalyx components was stored at -80C for later ELISA screening. A 1 mL aliquot
of whole blood was exposed to red blood cell lysis buffer in a 10:1 ratio in a 15 mL centrifuge
tube. After the addition of lysis buffer to the blood, it was rocked moderately for 10 minutes. After
10 minutes, or once the sample appeared clear, the sample was centrifuged at 300 g to pellet the
peripheral blood mononuclear cells (PBMCs). The lysed RBC layer was discarded. Next, the
sample was washed to remove cell fragments and residual plasma using 5 mL of fluorescence-

31

activated cell sorting buffer (FACS). For the wash step, the pellet was resuspended in 5 mL of
FACS, transferred to a 5 mL FACS tube, centrifuged, and the supernatant removed. Post-wash,
the pellet was resuspended again in 100 µL of FACS and treated with 5 μL of Fc receptor blocker.
The sample was incubated for 20 minutes at room temperature. Next, the sample was stained with
the designated antibodies to identify populations of leukocytes, neutrophils, monocytes, and NK
cells. Table 1 represents the markers and fluorophores selected to observe the immune cell
populations of interest.
Table 1. Surface markers and fluorophores for immune cells.
Surface
Marker

Fluorophore

Excitation

wavelength Emission

(nm)

(nm)

wavelength

Immune cell

CD45

FITC

497-499

516-519

Leukocyte

CD14

PacBlue

404-406

454-456

Monocyte

CD56

PE

564-566

575-576

NK cell

CD66b

APC

650-652

659-661

Granulocyte

Note: Wavelength ranges for fluorophores are for 99% excitation and emission and were found
using Biolegend’s spectra analyzer tool (Biolegend Inc, 2023).

The lysed and washed blood samples were stained by distributing 10 µL of a master mix
of antibodies containing 2.5 µL of each fluorescent antibody. Stained sample tubes were incubated
in the dark for 30 minutes. Samples were then diluted further in FACS buffer to bring the volume
to 1 mL. Each sample was then analyzed using a flow cytometer (Cytoflex, Beckman Coulter).
Figure 12 provides the general outline of blood preparation for flow cytometry.

32

Figure 12. A 1 mL aliquot of whole blood was lysed with red blood cell lysis buffer (10:1 ratio)
in a 15 mL centrifuge tube, followed by centrifugation at 300 g to pellet the peripheral blood
mononuclear cells (PBMCs). The lysed RBC layer was discarded, and the remaining pellet was
washed with 5 mL of fluorescence-activated cell sorting buffer (FACS). After resuspension and
incubation with Fc receptor blocker, the sample was stained with designated antibodies to identify
leukocyte populations. Stained samples were incubated, resuspended, and analyzed using a flow
cytometer (Cytoflex, Beckman Coulter).

Flow cytometry
Before each testing day, the Cytoflex Flow Cytometer was cleaned using the “daily clean”
function, which utilizes tubes of cleaning solution and deionized water. The system was then set
to the excitation wavelengths of each antibody fluorophore as described in Table 1. Pre- and postexercise tubes were analyzed. The final volume of each tube was 1 mL to ensure the cell
concentrations fell between 1-5 x 106 cells/µL. Each tube was set to display a maximum of
100,000 events. The "record" function was used to limit the sample volume to 1 mL, with a sample
speed of 60 µL/minute. Following the pre- and post-exercise samples, the backflush function was

33

employed, and deionized water was run through for 30 seconds to clear any residual sample from
the previous tube. After analyzing all tubes, the data was saved onto an external hard drive, and
the flow cytometer underwent another "daily clean" function.

Gating strategy
Once the samples were analyzed using the flow cytometer, a series of gating steps were
applied to quantify populations of the antibody-labeled immune cells. First, the sample data was
separated on a histogram of all events (cells) for CD45+ and CD45- populations thereby isolating
the general leukocyte cell population and non-leukocytes. The leukocyte population was then
plotted on a forward scatter and side scatter plot with forward scatter representing differences in
cell size and side scatter representing differences in granularity. This allowed three general
leukocyte populations to be identified: granulocytes, lymphocytes, and monocytes. Each
population was gated and a histogram representing the fluorescence intensity of events was
displayed in separate plots. For example, the granulocyte population was gated and a histogram of
the fluorescence intensity of the CD66b antibody marker was displayed. Two distinct peaks could
be identified, those that were CD66b+ cells and those that did not fluoresce and were considered
CD66b- cells. CD66b+ cells were recognized as the neutrophil population. The same strategy was
used for monocytes and natural killer cells. Using this gating strategy, the flow cytometer program
provided population distributions of cells/µL and the percent of each population among the entire
leukocyte population. The absence of CD45- cells is due to the blood preparation protocol's
leukocyte isolation procedure, where RBCs are lysed, and other cell debris is removed through
resuspension and centrifugation, resulting in a pellet containing only white blood cells. Regarding
the NK cell or CD56+ cell population, two peaks are observed, both of which are CD56+. One peak

34

represents CD56+ bright cells, while the other represents CD56+ dim cells. These bright and dim
CD56+ NK cells denote two distinct subpopulations of NK cells. However, analyzing these
subpopulations was beyond the scope of this study. Figure 13 displays the general outline of gating
to find each cell population. Combining this information with the testing timeline enabled us to
measure the counts of different immune cell populations before and after subjects underwent a
high salt diet, as well as before and after exercise.

Figure 13. The flow cytometry gating strategy involved enumerating NK cell (CD56+), neutrophil
(CD66b+), and monocyte (CD14+) populations. The absence of negative populations for CD45+
resulted from the isolation of white blood cells during the blood preparation procedure. Gating for
two peaks within the CD56+ population was due to the presence of CD56+ bright and dim
subpopulations, representing distinct subsets of NK cells.

35

Statistics
Statistics for FMD were performed using JASP (Version 0.17.1) software (JASP Team
2023). A 3-way repeated measure ANOVA was performed on FMD data separating conditions
of: pre- and post-exercise, before and after salt, and before and after control. For flow cytometry
data analysis, 3-way RM ANOVA was performed for the same repeated measures analyzing
cells/µL and percent of the total leukocyte population.

RESULTS
Popliteal FMD
Popliteal FMD before and after exercise was the only measure significantly different across
all conditions. Table 2 and Figure 14 show that post-exercise popliteal FMD was reduced by 2.7
% (95% CI: 1.8 to 3.5%, p < 0.01).
Table 2. Post Hoc comparison of pre- and post-exercise conditions found a significant mean
difference (n=4).
95% CI for Mean Difference
Mean Difference (%)
Pre

Post 2.654

Lower

Upper

SE

t

p

1.806

3.502

0.266 9.964 0.002

Note. Results are averaged over the levels of condition and time.

36

Figure 14. Exercise effects on popliteal artery flow-mediated dilation (n=4). Post-exercise
popliteal FMD was reduced by 2.6% (95% CI: 1.8 to 3.5%, p < 0.01), as determined by post hoc
analysis of exercise condition. Results are averaged over the levels of condition and time (n=4).

For all other comparisons of popliteal FMD, no other relationships such as those between
salt and sugar supplementation, showed any significant changes (Appendix 1). This can be seen in
Table 3 and Figure 15 which displays the lack of significant differences before and after high salt
intake, before and after sugar intake, and between after-salt and after-sugar conditions.
Table 3. Post Hoc comparison of condition and time displaying no significant differences (p>0.05)
(n=4).
Condition * Time
Salt, Before

Sugar, Before
Salt, After

Sugar, Before
Salt, After
Sugar, After
Salt, After
Sugar, After
Sugar, After

Mean Difference
1.096
0.614
0.575
-0.483
-0.521
-0.038

SE
0.851
0.929
1.033
1.033
0.929
0.851

t
1.288
0.661
0.557
-0.467
-0.561
-0.045

p
0.604
0.908
0.941
0.964
0.940
1.000

Note. Results are averaged over the levels of: exercise

37

Figure 15. Effects of salt and sugar on popliteal FMD % including standard error bars. Results are
averaged over the levels of exercise. None displayed significance (p>0.05) (n=4).
Mean values for popliteal FMD are reported below (Table 4). In Table 4, the exerciseinduced reductions in popliteal FMD are quite pronounced, and there may have been a slight trend
in FMD reduction after a high-salt diet, but this was not found to be significant (p=0.347)
(Appendix 1).
Table 4. Mean percent dilation of the popliteal artery for, condition (salt or sugar), time (before or
after), and exercise (pre- and post-exercise) measured through FMD (n=4).
Condition
Salt

Time
Before
After

Sugar

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N
4
4
4
4
4
4
4
4

Mean (%)
6.195
4.291
5.415
3.843
5.520
2.774
6.864
2.471

SD (%)
1.667
1.963
1.366
1.158
1.693
1.195
5.341
0.704

38

Brachial FMD
Brachial FMD remained unchanged across all conditions, including pre- and post-exercise
(Appendix 1). Table 5 displays the mean brachial FMD values for condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise).
Table 5. Mean percent dilation of the brachial artery for, condition (salt or sugar), time (before or
after), and exercise (pre- and post-exercise) measured through FMD (n=4).
Condition
Salt

Time
Before
After

Sugar

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N
4
4
4
4
4
4
4
4

Mean (%)
6.813
5.788
6.597
5.884
6.548
6.436
7.351
7.726

SD (%)
1.579
1.421
2.761
2.207
1.850
3.375
1.586
3.465

Figure 16 also displays the lack of any significant changes in brachial FMD before and after salt
treatment, and pre- and post-exercise.

Figure 16. Brachial FMD % before and after a high salt diet and pre- and post-exercise showed
no significant differences (n=4).

39

There was also no change in brachial FMD between salt and sugar conditions (Figure 17). The
statistical analysis for all variables for brachial FMD are shown in Appendix 1.

Figure 17. Brachial artery FMD % before and after salt intake and sugar intake. Results are
averaged over the levels of exercise (n=4).
Changes in baseline artery diameters
Baseline artery diameter of popliteal and brachial arteries did not change when comparing
HSD, control, and pre-treatment conditions (Appendix 1). Table 7 displays the mean baseline
diameters for pre- and post-exercise, brachial or popliteal arteries, and conditions of sugar
(placebo), baseline (none), or salt (HSD).

40

Table 6. Baseline artery diameters displayed in µm (n=4).
Exercise
Pre

Artery
Brachial

Popliteal

Post

Brachial

Popliteal

Condition
Sugar
Baseline 1
Salt
Baseline 2
Sugar
Baseline 1
Salt
Baseline 2
Sugar
Baseline 1
Salt
Baseline 2
Sugar
Baseline 1
Salt
Baseline 2

N
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4

Mean (µm)
3897.750
3781.500
3744.250
3865.500
5487.750
5889.000
5884.750
6039.000
3877.750
3808.750
3778.500
3935.500
5605.000
5555.500
5991.250
5216.000

SD (µm)
673.448
391.374
559.170
611.216
496.161
637.125
523.482
310.680
648.529
523.201
666.243
454.006
170.366
627.608
547.537
1755.325

Flow cytometry of blood leukocyte populations
Blood leukocyte populations generally remained stable across all conditions, with no
significant changes (p>0.05) observed in the counts of leukocytes, NK cells, and neutrophils per
microliter (Appendix 1). However, monocytes exhibited a mean decrease of 20.17 cells/µL (95%
CI: 2.31 to 38.04 cells/µL, p < 0.05) when comparing before and after salt intake and the control
condition (sugar). This difference was identified through data analysis shown in Appendix 1. The
percent of the total leukocyte population remained unchanged for all cell types across all
conditions (Appendix 1). Tables 6-9 display mean cells/µL and 10-12 display the mean percent of
the total leukocyte population for each analyzed condition.

41

Table 7. Leukocyte cells/µL for, condition (salt or sugar), time (before or after), and exercise (preand post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N Mean (cells/µL)
4 2967
4 2707
4 2442
4 2702
4 2827
4 2358
4 2292
4 2404

SD (cells/µL)
1428
1596
2177
2350
1700
1919
1441
1454

Table 8. Neutrophil cells/µL for, condition (salt or sugar), time (before or after), and exercise (preand post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre

N Mean (cells/µL)
4 2068

SD (cells/µL)
979

Post
Pre
Post
Pre
Post

4
4
4
4
4

1771
1615
1971
1969
1510

995
1409
1959
1173
1215

Pre

4 1598

1016

Post

4 1729

1074

Table 9. Monocyte cells/µL for, condition (salt or sugar), time (before or after), and exercise (preand post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N Mean (cells/µL)
4 161
4 161
4 130
4 117
4 157
4 149
4 149
4 152

SD (cells/µL)
110
141
135
125
116
154
114
129

42

Table 10. NK cells/µL for, condition (salt or sugar), time (before or after), and exercise (pre- and
post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N Mean (cells/µL)
4 126
4 141
4 95
4 73
4 125
4 137
4 111
4 94

SD (cells/µL)
153
181
125
81
154
185
118
85

Table 11. Neutrophil percent of the total leukocyte population for, condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N
4
4
4
4
4
4
4
4

Mean (%)
70.4
66.4
65.5
66.8
71.0
65.3
70.5
71.9

SD (%)
4.3
6.3
7.9
15
5.0
4.9
4.2
2.6

Table 12. Monocyte percent of the total leukocyte population for, condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N
4
4
4
4
4
4
4
4

Mean (%)
4.8
4.7
4.6
3.9
4.7
4.4
5.6
4.9

SD (%)
2.0
2.2
3.1
2.5
2.0
2.5
2.1
2.6

43

Table 13. NK cell percent of the total leukocyte population for, condition (salt or sugar), time
(before or after), and exercise (pre- and post-exercise) measured through flow cytometry (n=4).
Condition
Sugar

Time
Before
After

Salt

Before
After

Exercise
Pre
Post
Pre
Post
Pre
Post
Pre
Post

N
4
4
4
4
4
4
4
4

Mean (%)
3.3
4.3
2.9
3.0
3.3
4.3
3.5
3.3

SD (%)
3.7
3.9
3.8
2.1
3.7
3.9
3.2
2.3

Cardiovascular fitness variables
V̇O2 max values were calculated by averaging 30 seconds of V̇O2 breath-by-breath data at
peak work rate for each participant (Table 15). The single highest value of oxygen uptake is also
included in Table 15 represented by “V̇O2 peak”. Max heartrate, age, and self-reported
extracurricular activities are also included.
Table 14. Cardiovascular fitness variables (n=4).
V̇O2 max
(mL/min/kg)

V̇O2 peak
(mL/min/kg)

Max HR (bpm)

Age

Reported activities

Sex

28.44

35.07

198

22

Weight training, Soccer

Female

42.39

51.32

198

22

Soccer

Male

48.52

54.24

196

24

Rugby

Male

40.40

44.75

197

23

Weight training, Football

Male

DISCUSSION
The pathways of endothelial dysfunction from high salt intake are complex and involve
disruption of various biochemical pathways, alterations in the ESL’s physical properties, and,
potentially, changes in immune cell activity and recruitment. To determine the relationships among
salt, the ESL, and the immune system, we conducted experiments involving acute bouts of exercise
44

and after two weeks of high dietary salt intake. This approach allowed us to examine how high salt
intake affects the ESL and endothelial function when the glycocalyx is perturbed by exerciseinduced shear stress and immune system activation. Through FMD measurements and flow
cytometry analysis of specific leukocyte populations, we aimed to study these effects.

Local glycocalyx shedding exerts a greater influence on endothelial dysfunction than the
effects of high salt intake
The main finding of this study was that exercise reduced FMD solely in an artery that
supplies the exercising limbs, the popliteal artery (a relative decrease of 44%). This finding
supports the hypothesis of locally caused endothelial dysfunction from an acute bout of exercise.
Our testing also revealed no reduction in FMD responses when comparing pre- and post-exercise
measurements of the brachial artery. This suggests that the immediate impact of exercise,
particularly concerning the disturbance of NO-mediated dilation, primarily affected the popliteal
artery, which supplies blood to locally active skeletal muscles in the legs. There was no change in
FMD after the HSD at the popliteal or brachial arteries, suggesting that exercise's acute effects
may induce greater reductions than a HSD.
Local dysfunction pathways may involve heightened oxidative stress surrounding the
active skeletal muscle and/or damage to the eGC. ROS are generated predominantly by contracting
skeletal muscles during physical activity and can increase depending on exercise intensity (He et
al. 2016; McArdle et al. 2001; Zuo et al. 2015). These findings mirror the findings of Sakellariou
et al. (2013), who reported that exercise can result in a 1–3-fold increase in O2− levels in active
muscle groups. Potentially, these local increases in ROS could interfere with NO-mediated
vasodilation. O2- readily binds to NO forming ONOO-. This interaction reduces NO's availability

45

to promote vasodilation and interferes with eNOS NO production (Janaszak-Jasiecka et al. 2023).
Both O2- and ONOO- can oxidize BH4, a crucial cofactor in eNOS activity (Milstien and Katusic
1999). This oxidation leads to the production of O2- instead of NO, a phenomenon known as eNOS
uncoupling (Janaszak-Jasiecka et al. 2023). An imbalance of NO production from the increased
uncoupling of eNOS then leads to a depressed vasodilatory response to shear stress, as quantified
by FMD techniques (Janaszak-Jasiecka et al. 2023). It was also described by van Golen et al.
(2014) that ROS may contribute to endothelial dysfunction by damaging the eGC, which plays a
key role in the mechanotransduction of changes in blood flow to cause NO-mediated vasodilation
(Pahakis et al. 2007). Many of the proposed pathways of Na+-related dysfunction involve causing
oxidative stress, from increased NADPH activity and expression, as well as decreased SOD
activity and expression (Lenda and Boegehold 2002; Zhu et al. 2007; Kitiyakara 2003; Majerczak
et al. 2017; Guers et al. 2019). We suspect that the lack of change in FMD response in both the
popliteal and brachial arteries when on a HSD, alongside observing a decrease in the popliteal
artery with exercise, could be because salt may not disrupt endothelial function as much as exercise
does locally. We also did not find any differences between post-exercise FMD after HSD and after
no salt loading. This suggests that the release of Na+ stored in the ESL due to glycocalyx shedding
from exercise may not happen or, if it does, it may not cause significant endothelial dysfunction.
Locally influenced dysfunction is further supported by our finding of exercise-induced endothelial
dysfunction only in the popliteal artery and not the brachial artery.
The local effects of exercise may have caused greater dysfunction compared to the Na +related pathways of dysfunction and the systemic disruptions to dilation caused by exercise. Bike
exercise likely increased mechanical shear stress due to the heightened blood flow to the actively
working skeletal muscles in the legs (Sarelius and Pohl 2010). This increase in blood flow in the

46

legs compared to the arms may have caused greater shear stress and damage to the eGC in the
popliteal artery compared to the brachial artery. Additionally, local oxidative stress and exercise
by-products could have impaired vasodilation in the popliteal artery more so than the brachial
artery (Kröpfl et al. 2021; Nishiyama et al. 2017). The increased temperature of the working
muscles during exercise could further exacerbate these effects, leading to a more pronounced
suppression of vasodilation in the popliteal artery compared to the brachial artery (Chen et al.
2023). All of the above factors may have culminated in a reduced popliteal FMD after exercise,
but not brachial FMD.
It is well understood that the eGC plays a key role in the mechanotransduction of shear
stress to stimulate the eNOS/NO/cGMP vasodilatory pathway (Reitsma et al. 2007). We observed
that endothelial function was not significantly affected by the HSD we gave our participants. Also,
damage to the eGC preventing mechanotransduction may be more detrimental to endothelial
function than other pathways involving Na+, such as endothelial cell stiffening. Although excess
Na+ is known to contribute to increased systemic oxidative stress, our finding of unchanged FMD
post-HSD but a reduced FMD after exercise may suggest that locally produced ROS from exercise
causes a more disruptive increase in oxidative stress than a HSD does systemically. This
combination of local oxidative stress and shear stress could cause much greater damage to the eGC
and endothelial dysfunction than the systemic effects of a HSD and other Na+-related dysfunction
pathways.
Kröpfl et al. (2021) and Lee et al. (2019) both found eGC shedding by measuring
glycocalyx components in the serum after exercise similar to our exercise bout but did not quantify
endothelial dysfunction using FMD pre- and post-exercise. However, Ghiarone et al. (2018)
demonstrated when degrading the eGC enzymatically using neuraminidase, FMD was

47

significantly reduced in rats. Bar et al. (2019) also found that glycocalyx injury coincided with the
impairment of endothelium‐dependent vasodilation and NO‐dependent function. Grandys et al.
(2023) also provided support for glycocalyx degradation leading to reductions in FMD, observing
a marked decrease in FMD in overtrained female track athletes who had significantly higher serum
concentrations of HA and SDC-1, caused by ESL damage. However, this study was focused on
the systemic effects of overtraining on endothelial function, not necessarily the direct impact of
locally caused glycocalyx damage. Grandys et al. (2023) found correlations between catabolicanabolic hormone balance changes, eGC damage, and reduced FMD among overtrained athletes,
but did not specifically compare brachial and popliteal artery FMD after a bike exercise.
Specifically, they looked at intensive periods of exercise training (~13 hours per week) in elite
track athletes causing repeated instances of glycocalyx damage without sufficient time for repair.
This differed from our stimulus of single bouts of strenuous bike exercise, followed by immediate
testing of brachial and popliteal artery FMD. However, they suggested that the overtraining
response resembled exercise-induced acute changes in glycocalyx shedding markers. They cited
that increased glycocalyx shedding markers resulted from enhanced blood flow, decreased
antioxidative capacity, and increased ROS and cytokines.
Further investigation is needed to understand the specific local effects of exercise-induced
glycocalyx damage on endothelial dysfunction, particularly concerning FMD responses, as there
is limited human research in this area. The relative contributions of shear stress compared to ROS
in terms of glycocalyx damage could also be an area of investigation. Future studies are also
needed to compare the local and systemic effects of exercise at different intensities and modalities
concerning ESL integrity and endothelial dysfunction. This will provide insights into the relative

48

significance of glycocalyx damage compared to other pathways in post-exercise and post-HSD
endothelial dysfunction.

Inflammation response to exercise
Inflammation involves a series of cellular and molecular events that result in increased
body temperature, capillary dilation, and the production of soluble components in the blood
(Cerqueira et al. 2020). These responses, triggered by stressors and crucial for host defence and
tissue homeostasis, help eliminate harmful substances and damaged tissue among other functions
(Cerqueira et al. 2020). Acute moderate to high-intensity exercise induces a rise in proinflammatory cytokines followed by the release of anti-inflammatory cytokines that attenuate the
inflammatory response (Moldoveanu et al. 2001). Common markers of inflammation, such as Creactive protein (CRP) and TNF-α, have been shown to cause eGC damage and inhibit eNOS
activity (Devaraj et al., 2009; Qu et al., 2021). However, it is unlikely these markers were elevated
after our prescribed exercise session and probably did not contribute to the observed reduction in
popliteal FMD. Although IL-6 is consistently upregulated as a myokine released by working
skeletal muscles during exercise, TNF-α and CRP do not show consistent increases in the acute
exercise response (Petersen and Pedersen 2005). TNF-α and CRP only significantly increased well
after exercise or in response to much higher exercise intensities and durations (Cerqueira et al.
2020; Petersen and Pedersen 2005). The absence of CRP and TNF-α involvement in the
inflammation response to exercise is important as many studies that correlate inflammation with
glycocalyx damage/endothelial dysfunction focus on the effects of these cytokines specifically
(Devaraj et al. 2009; Hu et al. 2021; Qamirani et al. 2005; Sproston and Ashworth 2018; Tarbell
and Cancel 2016).

49

IL-6 is also unlikely to contribute to the exercise-induced dysfunction we observed.
Although locally working muscles will secrete IL-6, the effects of this cytokine are dependent on
the context of its release (Docherty et al. 2022). Initially thought of as a strictly pro-inflammatory
signalling molecule, IL-6 mainly has anti-inflammatory effects during exercise (Docherty et al.
2022). During exercise, IL-6 acts as a hormone-like molecule which mobilizes extracellular
substrates and/or augments substrate delivery to working muscle (Petersen and Pedersen 2005).
IL-6 also has anti-inflammatory effects. It stimulates the production of anti-inflammatory
cytokines interleukin-1 receptor antagonist (IL-1ra) and interleukin-10 (IL-10), inhibits TNF-α,
and induces the production of hepatocyte-derived acute-phase proteins, many of which have antiinflammatory properties (Petersen and Pedersen 2005).
The observation of endothelial dysfunction after exercise in the popliteal artery, but not in
the brachial artery, suggests that the systemic inflammatory response was not strong enough or not
conducive to causing eGC damage and endothelial dysfunction. This is expected considering the
low likelihood that the acute exercise bouts used in our study caused increases in TNF- α and CRP.
Additionally, IL-6 locally released in response to exercise confers anti-inflammatory and
metabolism-related effects during exercise, unrelated to its pro-inflammatory eGC damaging
activity in disease states (Docherty et al. 2022; Nash et al. 2022).

Leukocytosis post-exercise
Leukocytosis is a general increase in circulating white blood cells and is commonly
observed post-exercise. As early as 1932, this phenomenon was observed and is a fundamental
part of the exercise immune response (Edwards and Wood 1932; Rowbottom and Green 2000;
Sand et al. 2013). All major leukocyte subpopulations tend to increase in number during exercise

50

due to hemodynamic shear stress and/or catecholamines acting on leukocyte β2-adrenergic
receptors (Peake et al. 2017). From light to severe exercise intensities, all populations of immune
cells we analyzed have been shown to increase (Leicht et al. 2017; Tvede et al. 1993). While the
combined effects of a HSD and exercise are less understood, our findings of no increase in any
leukocyte population post-exercise are likely due to a small sample size with high variation, rather
than a physiological lack of immune activation from our exercise bout.

Neutrophils
Of the three leukocyte populations we wished to quantify for their changes pre- and postexercise and pre- and post-high salt intake, neutrophils were of particular interest. In a study on
neutrophils and exercise-induced oxidative stress, Quindry et al. (2003) demonstrated that intense
exercise prompts the migration of neutrophils to active skeletal muscles, possibly resulting in
heightened oxidative stress. Since endurance exercise performed above VT1 significantly boosts
the number of circulating neutrophils, it is conceivable that this neutrophilia can contribute to the
oxidative stress seen in the blood during high-intensity exercise (Quindry et al. 2003).
Local neutrophil recruitment begins in response to proteins released from injured muscle,
like creatine kinase (CK) and myoglobin (Brancaccio et al. 2010). This triggers the release of
cytokines, attracting more neutrophils and macrophages to the damaged area, where they become
activated (Lee et al. 2017). Neutrophil activation involves the assembly of NADPH-oxidase,
generating ROS and initiating a respiratory burst. These ROS, along with hypochlorous acid
(HOCl) produced by myeloperoxidase (MPO) activity, facilitate the phagocytosis of cellular debris
(Carrera-Quintanar et al. 2020). Ultimately, this process facilitates the removal of muscle debris
and tissue repair (Carrera-Quintanar et al. 2020; Patik et al. 2021). However, transiently, this acute

51

increase in ROS following exercise could potentially disrupt NO-mediated dilation and cause
damage to the eGC, resulting in endothelial dysfunction (Carrera-Quintanar et al. 2020; Patik et
al. 2021). Normally, to mitigate non-specific damage caused by the respiratory burst, neutrophils
possess an antioxidant system that is activated four to five hours after a bout of exercise (Tauler et
al. 2002). We did not see a change in neutrophil counts after exercise. This could have resulted
from a discrepancy between other studies concerning exercise modality, time of measurement, or
exercise intensity. Our exercise bout of concentric cycling in the heavy exercise domain (above
VT1, but below VT2) was also unlikely to cause muscle damage and increase CK production
(Ueda et al. 2020). Since muscle damage-induced neutrophil recruitment is unlikely to occur
during the exercise bout in our study, it is also unlikely that neutrophils contributed to the locally
reduced FMD in the popliteal artery. Supporting this, we found no increase in circulating
neutrophils immediately after exercise.
Neutrophilia is suggested to increase depending on the relative exercise intensity (Quindry
et al. 2003). Leicht et al. (2017) observed that neutrophilia was indeed blunted in an easy cycling
bout and epinephrine concentration was lower than at higher exercise intensities. However, the
idea that our exercise intensity was insufficient to invoke any neutrophil response is unlikely. Even
in the study by Leicht et al. (2017), easy cycling did increase neutrophil populations, just not to
the extent of higher intensities. Earlier work by Tvede et al. (1993) also supported an increase in
neutrophils at light, moderate, and severe bike exercise intensities. A more probable explanation
for the lack of change found in neutrophils after exercise is an insufficient sample size (n=4) and
high variation among samples.
In summary, although we did not find changes in populations of neutrophils after exercise
(most likely due to high variation and low sample size) it is unlikely neutrophils contributed to the

52

local endothelial dysfunction we observed in the popliteal artery due to insufficient muscle damage
caused by our exercise bout (Ueda et al. 2020). Future studies analyzing neutrophil responses to
exercise and contributions to endothelial dysfunction should include a larger participant pool,
monitor CK and other muscle damage markers, and track oxidative stress markers.
A HSD also did not affect counts of neutrophil populations and percentages of leukocytes.
Supporting our finding, a study by Yi et al. (2015) which measured leukocyte counts of healthy
participants found that neutrophil counts were unchanged across all levels of controlled salt intake
ranging from 6 g to 12 g per day. Changes in neutrophil counts are thus unlikely to contribute to
endothelial dysfunction during an HSD. However, numerous studies have found that a HSD does
have noticeable impacts on various neutrophil functions (Krampert et al. 2021; Li et al. 2022;
Mazzitelli et al. 2022; Jobin et al. 2020). In general, HSDs seem to have an immunodepressive
effect on neutrophils (Li et al. 2022). Krampert et al. (2021) found that in human neutrophils, ROS
production was attenuated as a result of a HSD, which caused a suppression of neutrophils’
antibactericidal activity. Li et al. (2022) outlined the impacts of high salt on neutrophils, including
suppressed degranulation and O2- production. Besides inhibiting key immune-related functions of
neutrophils, interactions with neutrophil ROS production could also modulate their contributions
to oxidative stress under HSDs. We did not observe a change in endothelial function from a HSD
in our participants. The attenuation of ROS production from neutrophils could have influenced the
unchanged FMD responses before and after high salt intake as well as the lack of brachial artery
dysfunction resulting from systemic post-exercise effects.
Neutrophil activity during and after exercise, as well as before and after a HSD, may play
a role in regulating oxidative stress, requiring further investigation (Carrera-Quintanar et al. 2020).
To better understand the effects of salt intake and exercise on endothelial function and the ESL,

53

ROS levels before and after a HSD and exercise should be monitored. This, along with studying
serum glycocalyx components affected by ESL damage and examining FMD responses, could
offer valuable insights into the impact of neutrophils and exercise-induced immune system
activation on vascular health and ESL integrity.

Monocytes and macrophages
Macrophages and monocytes are versatile immune cells crucial for various physiological
and pathological processes (Kloc and Kubiak 2022). They participate in phagocytosis, and antigen
presentation to T cells, and initiate adaptive immune responses essential for immune surveillance
and specific immune responses against pathogens. Both monocytes and macrophages secrete
cytokines such as TNF-α and interleukins, which regulate inflammation, immune responses, and
tissue repair (Austermann et al. 2022). Moreover, macrophages and monocytes modulate immune
responses by interacting with other immune cells, exhibiting both pro-inflammatory and antiinflammatory activities depending on the context (Kloc and Kubiak 2022). Furthermore,
monocytes differentiate into tissue-resident macrophages, which have specialized functions
tailored to their specific tissue environments, including the removal of excess Na+ from the skin
(Kloc and Kubiak 2022; Olde Engberink et al. 2019).
In our study, although we found a significant difference for the time condition, this meant
that the difference was before and after HSD and the placebo condition. This was most likely a
consequence of a relatively small sample size and a high coefficient of variation among
participants, not a depressive effect of both high salt intake and slightly increased sugar intake.
Although several studies have noted changes in circulating monocytes from high-sugar diets, the
supplementation of ~13.8 g of sugar per day over two weeks did not match the levels used in those

54

studies (Ma et al. 2022). Other studies also found different effects of salt. Contrary to our findings
of a mean decrease in monocytes, Yi et al. (2015) reported that a HSD of 12 g per day led to a
significantly higher number of immune cell monocytes compared to the same subjects on a lowersalt diet. Additionally, a correlation test by Yi et al. (2015) revealed a strong positive association
between salt intake levels and monocyte numbers. Wenstedt et al. (2019) similarly observed that
a HSD tended to increase the total number of circulating monocytes. Our study did not observe
any reduction in FMD following a HSD in both brachial and popliteal arteries, suggesting that the
HSD did not induce a shift in monocyte recruitment leading to endothelial dysfunction.
Other studies have shown that high salt intake can modulate monocyte activity, potentially
influencing endothelial function. Wenstedt et al. (2019) found that a HSD shifted monocytes
towards a pro-inflammatory phenotype, with higher CCR2 expression and increased IL-6 and
MCP-1 secretion. This led to a higher density of macrophages in the skin, possibly contributing to
endothelial dysfunction through greater activation and ROS production. Generally, a HSD can
increase circulating monocytes in mice and humans, as well as induce pro‐inflammatory human
monocytes. However, we did not observe this increase after a HSD. Thus, any influence of
monocytes and macrophages on endothelial function after high salt intake is likely due to a change
in function and retention in the skin rather than an increase in their number in circulation.
The lack of increase in circulating monocytes from concentric cycling at the intensity and
duration of our study is not unfounded. In a study by Tvede et al. (1993) that tested the effects of
different exercise intensities on leukocyte populations, it was found that a low- and moderateintensity bike exercise did not cause an immediate increase in monocytes post-exercise. Instead,
monocyte levels either increased one to two hours after exercise cessation (Tvede et al. 1993).
These findings further support the idea that exercise-induced increases in circulating monocyte

55

populations likely do not contribute to pathways causing endothelial dysfunction. Additionally. in
the context of systemic versus local differences in endothelial dysfunction after exercise, systemic
monocyte-related pathways of dysfunction were likely not present, since brachial FMD remained
unchanged after exercise and after HSD.
Strenuous exercise can cause a significant increase in circulating leukocytes, including
monocytes (Peake et al. 2017). These cells are believed to migrate partly from the marginal pool
of the bloodstream, which contains cells loosely adhered to or rolling on vascular endothelium.
The recruitment of these cells into the bloodstream is attributed to shear stress and may be mediated
by catecholamines (Peake et al. 2017). Strenuous exercise can cause muscle injuries, activating
neutrophils and macrophages through interferon-γ (IFN-γ), interleukin-1 (IL-1), and tumour
necrosis factor (TNF) (Steinbacher and Eckl 2015). These activated immune cells then produce
excessive ROS leading to endothelial dysfunction (Steinbacher and Eckl 2015). However, our
exercise bouts were unlikely to trigger these pathways, represented by the lack of increase found
in monocytes immediately post-exercise. Muscle damage is more likely to occur during eccentric
exercise as opposed to concentric bike exercise, especially at moderate to heavy intensities and
relatively short durations (Ueda et al. 2020). Since our bike exercise involved 45 minutes of
concentric cycling in the heavy exercise domain, it is unlikely that monocyte recruitment and
activation through muscle damage-related pathways occurred.
This lack of local recruitment of ROS-producing immune cells and lack of systemic
increases of monocyte populations immediately post-exercise suggests that the exercise immune
response in terms of monocyte recruitment is unlikely to contribute to the endothelial dysfunction
we observed and immediately post-exercise. Further, while exercise at high intensity and duration
may influence function and cause migration to damaged muscle tissue (Peake et al. 2017), our

56

exercise bout of 45 minutes of heavy-intensity concentric biking is unlikely to result in extensive
muscle damage (Ueda et al. 2020).
Several studies have effectively observed the inflammatory and anti-inflammatory
phenotypes of macrophages and monocytes using flow cytometry with expanded antibody panels
(Austermann et al. 2022; Wonner et al. 2016; Wenstedt et al. 2019). These techniques could serve
as valuable guidelines for future research investigating the impact of both exercise and high salt
intake on the roles of monocytes and macrophages in vascular damage. Additionally, observing
the contribution of ROS by monocytes and macrophages under exercise and HSD conditions may
also be useful to shed light on the relative contributions (or lack of) for these immune cells
concerning endothelial dysfunction.

Natural killer cells
Initially characterized as large granular lymphocytes capable of natural cytotoxicity against
tumour cells, NK cells have since been identified as a distinct lymphocyte lineage, possessing both
cytotoxic and cytokine-producing effector capabilities (Vivier et al. 2008). While NK cells are
crucial for combating viruses, it remains unclear whether a HSD influences the development and
functionality of NK cells and if this contributes to ESL damage. Our study did not show significant
changes in the absolute count or percentage of NK cells, however, their functions could still impact
endothelial dysfunction under a high-HSD and after exercise. Zeng et al. (2020) found that a HSD
in mice decreased NK cell counts in the spleen and lungs and increased ROS levels due to higher
NADPH-oxidase subunit expression. Krampert et al. (2021) similarly found that high salt
enhanced ROS production in NK cells. This increased ROS production may affect endothelial
function by disrupting NO-mediated vasodilation.

57

Systemic and local inflammatory responses from disease states can cause rapid loss of
glycocalyx and its activities, both directly and indirectly (Hu et al. 2021). NK cells contribute to
endothelial dysfunction when influenced by high salt intake and exercise. Pro-inflammatory
cytokines upregulate enzymes that degrade glycocalyx components (Shamloo et al. 2021). This
damage is triggered by TNF-α, bacterial lipopolysaccharides, and other cytokines, promoting the
release of metalloproteinases and heparinases (Hu et al. 2021; Tarbell and Cancel 2016). NK cells
secrete cytokines such as IFN-γ, TNF-α, and Granulocyte-Macrophage Colony-Stimulating Factor
(GM-CSF), contributing to this process (Paul and Lal 2017). Although the inflammation induced
by exercise differs from disease-state inflammation, it is unclear whether a HSD, either
independently or combined with exercise, may shift the inflammatory response toward glycocalyx
damage and endothelial dysfunction or if it has minimal effect on inflammation pathways
(Docherty et al. 2022; Petersen and Pedersen 2005; Qu et al. 2021; Sproston and Ashworth 2018).
Although a HSD and exercise can increase NK cell activity and cytokine levels, particularly
IFN-γ, which is linked to eGC damage (Rizvi et al. 2021; Quintana-Mendias et al. 2023; HaywoodWatson et al. 2011), we did not observe changes in NK cell counts or FMD after a HSD. This
suggests that NK cell contribution to inflammation was not affected by HSD. Exercise reduced
popliteal FMD only in the local working muscle, indicating a lack of systemic changes in NK cell
function. Future research should focus on specific changes in NK cell activity and function rather
than absolute counts and percentages of leukocytes when investigating NK cell influences on
endothelial function.
In summary, the investigation into leukocytosis post-exercise sheds light on the web of
interactions between exercise-induced immune responses and endothelial function. Leukocyte
populations, including neutrophils, monocytes, and NK cells, exhibit diverse responses to exercise

58

and HSDs and their implications for vascular health remain complex. The mobilization and
activation of neutrophils post-exercise may contribute to oxidative stress and potential endothelial
dysfunction. However, due to the lack of observed increases in neutrophils and likely insufficient
muscle damage caused by our exercise bout, neutrophils are unlikely to contribute to the local
popliteal dysfunction post-exercise. Alterations in monocyte populations post-exercise and posthigh salt intake likely do not influence inflammation-related pathways or oxidative stress and
therefore do not significantly affect endothelial function. Furthermore, the response of NK cells to
high salt and exercise may suggest a contribution of immune activation and endothelial
dysfunction. However, NK cells were not involved in the local dysfunction in our study and did
not cause systemic endothelial dysfunction either. Our findings suggest that the immune response
from exercise, given our specific intensity, duration, and modality, is unlikely to contribute to the
local or systemic endothelial dysfunction that we observed and is commonly found after exercise.
Additionally, a HSD was unlikely to cause a significant enough shift in immune cell function and
number to result in systemic disruptions to endothelial dysfunction. Further, if immune system
activation is involved, changes in function rather than absolute counts are likely responsible for
contributing to endothelial dysfunction. There is a need for further research to determine the
precise mechanisms linking exercise, salt intake, and immune responses to endothelial function.
Additional studies looking at different oxidative stress markers and alterations in leukocyte
function may offer greater insights into preventive strategies and therapeutic interventions for
preserving cardiovascular health.

59

Limitations
There were several limitations to our study. First, we did not control participants’ lifestyles
during the study period, which could have resulted in variable meals before testing sessions among
other influences. We also relied on self-reporting for pill consumption. This metric may not
accurately reflect each participant's specific Na+ consumption. To verify whether the HSD resulted
in higher levels of Na+ in our participants compared to when they were on washout and placebo
periods, we could use a combination of methods. These methods include 24-hour urine samples,
spot urine samples, and more detailed diet tracking or specific diet control. These measures could
help ensure a clear distinction between the conditions. Although we did not observe an increase in
any immune cell population, a reduction in blood plasma volume can affect hematocrit and
leukocyte measurements. Future research should consider this aspect in their analysis for more
accurate results.

Menstrual cycles
Another limitation of our study was not tracking the menstrual cycles of female
participants. Menstrual hormones influence processes like inflammation and eNOS activity (Reed
and Carr 2018; Harris et al. 2022; Chakrabarti et al. 2014). Gaskins et al. (2012) found significant
CRP variation across menstrual cycles, with hormone fluctuations affecting inflammation levels
(Wander et al. 2008). This could impact endothelial function by influencing inflammationmediated damage. Specific hormone cycles could also affect endothelial function. For instance,
estrogen has been shown to cause NO-dependent vasodilation, which could cause transient
increases or reductions to FMD responses through enhanced eNOS activity (Caulin-Glaser et al.
1997; Chambliss et al. 2000). Although our study only included one female participant,

60

minimizing any effect of menstrual cycles, future research including more female participants
should monitor and account for these variations.
Changes to baseline vessel diameter post-exercise
In our study, we observed a decrease in popliteal FMD after exercise. However, it’s possible
that these reductions are not solely attributed to ROS-mediated disruption, shear-induced shedding
of the eGC, or immune response-related factors (Dawson et al. 2013). Dawson et al. (2013)
outlined many of the factors that can influence post-exercise FMD measurements, including
changes in baseline artery diameter after exercise. Since calculating FMD involves finding the
percent difference between baseline and peak artery diameter, the effects of acute exercise on
baseline diameter may influence the FMD response. It is possible that alterations in baseline
diameter following acute exercise could pose a limitation when using FMD to assess endothelial
function immediately post-exercise (Dawson et al. 2013). Larger arteries, like the popliteal artery,
tend to exhibit lower FMD. Therefore, a reduction in FMD after exercise might not necessarily
indicate a decrease in vascular function itself but rather reflect a diminished dilator reserve, where
vasodilation may be challenging in an already dilated or stretched vessel (Gori et al. 2009).
However, studies by Birk et al. (2012) and Katayama et al. (2012) demonstrated that even after
statistically adjusting for changes in artery diameter, a notable decrease in FMD persisted
immediately after exercise. This suggests that alterations in baseline diameter alone do not entirely
explain endothelial dysfunction following exercise in all instances. When we examined the initial
baseline artery diameters in our study, we did not find any significant differences between the
diameters before and after exercise. If future studies with more participants do find significant
changes to baseline diameter post-exercise, these changes should be accounted for. Normalization
of FMD responses can be achieved through allometric scaling by dividing the peak percentage

61

change in diameter by the magnitude of the stimulus achieved with reactive hyperemia,
represented by shear stress (Pyke and Tschakovsky 2005).
Exercise training inhibits pathways of salt-related dysfunction
Studies have shown decreased FMD and NO production following HSD, but our study found
no such effects in either popliteal or brachial arteries. Exercise training may have countered the
harmful effects of high salt intake, through variations in participants’ pre-study activity levels.
Oxidative stress from HSD can disrupt the vasodilatory pathway and damage the ESL. Exercise
may mitigate this stress by enhancing antioxidant pathways and reducing vascular damage
(Higashi 2015). Enhanced antioxidative pathways from exercise may reduce ROS influence on
eNOS uncoupling and eGC damage. Exercise may also protect eGC from ROS-induced damage,
preserving shear-induced NO production and Na+ buffering capacity. Additionally, exercise may
increase glycocalyx thickness, further enhancing Na+ buffering (Schmitz et al. 2019; Selvarajah et
al. 2017). Participants with exercise training may thus resist oxidative stress from HSD better and
maintain endothelial function, explaining our study’s findings. Using breath-by-breath data
collected from exercise capacity testing, our participants displayed similar V̇O2 max values, and
max HR values to active and trained individuals in studies by Kulinski et al. (2014) and Caputo et
al. (2003). This suggests that our participant pool could have attained training adaptations prior to
participating in our study, giving them greater resistance to the effects of a HSD that otherwise
would cause reduced FMD. In addition to breath-by-breath data, our participants reported being
involved in regular weight training, and/or participation or past participation in competitive
football, rugby, and soccer. Future studies should consider participants’ activity levels when
investigating HSDs, exercise, and immune response effects on endothelial function.

62

Dietary contributions to antioxidative capacity
Participants were advised to maintain their normal diets during the study, but we did not
specifically control their diets, which could have led to variations in antioxidative capacity. This
factor may have contributed to our findings of unchanged endothelial function after a HSD. For
instance, a participant with increased consumption of vitamin C or vitamin E may be better
equipped to combat oxidative stress factors introduced by the HSD. Greaney et al. (2012) directly
determined the effect of antioxidants in restoring redox balance during an HSD, observing that
NO-mediated increases in skin blood flow were restored by local infusion of ascorbic acid (vitamin
C) in individuals consuming excess Na+. In an extensive review of antioxidants and oxidative
stress, Tan et al. (2018) concluded that antioxidants can disrupt the spread of free radicals by
preventing their formation, thereby reducing oxidative stress. While we do not propose that
exercise training or dietary antioxidants could fully eliminate dysfunction caused by these
pathways, they may have mitigated the effects to some extent, potentially explaining our
observation of unchanged endothelial function after the HSD

CONCLUSIONS
In our study, we found that exercise caused a significant reduction in popliteal FMD, but
not brachial FMD after a bout of cycling exercise at one-third work rate between VT1 and VT2.
We did not find a reduction in FMD or changes in immune cell populations after a HSD. While
unchanging immune cell counts are unexpected, it is unlikely that the exercise immune response
is likely to influence endothelial dysfunction. Based on the absence of reduced brachial FMD after
exercise and the absence of FMD reduction after high salt intake in popliteal and brachial arteries,
we propose that localized effects of exercise caused greater impairment of FMD compared to
systemic effects. Increases in blood flow and shear stress in specific active muscles, as well as

63

local release of ROS, lead to glycocalyx damage and endothelial dysfunction. These localized
forces may play a greater role in causing endothelial dysfunction compared to systemic pathways
related to oxidative stress, endothelial cell stiffening by high salt, and systemic immune system
activation. The bike exercise, targeting skeletal muscles in the leg, likely triggered an influx of
blood flow and shear stress, resulting in the shedding of glycocalyx components crucial for NOmediated dilation. ROS released locally from higher metabolism of active muscles may also have
caused glycocalyx damage and reduced NO-bioavailability. Consequently, these factors led to a
reduced popliteal artery FMD, but not brachial artery FMD, post-exercise. Our study had several
limitations, providing opportunities for future research. More extensive participant tracking of diet,
exercise, and menstrual cycles should be incorporated into studies with larger and more diverse
participant pools. Additionally, ELISA testing and an expanded panel of antibodies for flow
cytometry could help measure glycocalyx components, markers of inflammation and oxidative
stress, and immune cell by-products. Such measures could increase our understanding of the
intricate yet interconnected roles of salt intake, ESL integrity, and the immune response to
exercise, thereby increasing our understanding of endothelial function.

64

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77

APPENDICES
Appendix 1
Statistical analysis
Statistics from 3-way RM ANOVA performed on popliteal FMD data across conditions of exercise
(pre and post), time (before and after), and condition (salt and control) (n=4).
Within Subjects Effects
Cases
condition
Residuals
time
Residuals
exercise
Residuals
condition * time
Residuals
condition * exercise
Residuals
time * exercise
Residuals
condition * time * exercise
Residuals

Sum of Squares
2.239
11.163
0.017
14.470
56.352
1.703
2.576
6.234
6.706
18.620
0.864
42.555
1.960
11.285

df Mean Square
1 2.239
3 3.721
1 0.017
3 4.823
1 56.352
3 0.568
1 2.576
3 2.078
1 6.706
3 6.207
1 0.864
3 14.185
1 1.960
3 3.762

F
0.602

p
0.494

0.004

0.956

99.274

0.002

1.240

0.347

1.080

0.375

0.061

0.821

0.521

0.523

Note. Type III Sum of Squares.

78

Statistics from 3-way RM ANOVA performed on brachial FMD data across exercise (pre and
post), time (before and after), and condition (salt and control) (n=4).
Within Subjects Effects
Cases
condition
Residuals
time
Residuals
exercise
Residuals
condition * time
Residuals
condition * exercise
Residuals
time * exercise
Residuals
condition * time * exercise
Residuals

Sum of Squares
4.435
19.250
1.946
58.332
1.086
8.037
2.450
13.864
2.003
3.653
0.320
8.539
0.015
20.574

df Mean Square
1 4.435
3 6.417
1 1.946
3 19.444
1 1.086
3 2.679
1 2.450
3 4.621
1 2.003
3 1.218
1 0.320
3 2.846
1 0.015
3 6.858

F
0.691

p
0.467

0.100

0.772

0.406

0.570

0.530

0.519

1.645

0.290

0.112

0.760

0.002

0.966

Note. Type III Sum of Squares.

79

Statistics from 3-way repeated measures ANOVA analysis of leukocyte cells/µl across exercise
(pre and post), time (before and after), and condition (salt and control) (n=4).
Within Subjects Effects
Cases
condition

Sum of Squares
437776.602

df Mean Square
1 437776.602

Residuals

1.696×10+6

3

565382.652

time

519720.710

1

519720.710

Residuals

2.836×10

+6

3

945210.275

exercise

63829.859

1

63829.859

3

1.234×10

+6

Residuals

3.701×10

condition * time

857.601

+6

1

857.601

Residuals

2.228×10

+6

3

742583.456

condition * exercise

63710.221

1

63710.221

Residuals

185996.068

3

61998.689

time * exercise

607301.184

1

607301.184

+6

3

753710.499

Residuals

2.261×10

condition * time * exercise

1812.923

1

1812.923

Residuals

105211.173

3

35070.391

F
0.774

p
0.444

0.550

0.512

0.052

0.835

0.001

0.975

1.028

0.385

0.806

0.436

0.052

0.835

Note. Type III Sum of Squares.

80

Statistics from 3-way repeated measures ANOVA analysis of neutrophil cells/µl across exercise
(pre and post), time (before and after), and condition (salt and control) (n=4).
Within Subjects Effects
Cases

Sum of Squares

df Mean Square

F

p

condition

192750.644

1

192750.644

0.674

0.472

Residuals

858145.877

3

286048.626

time

82423.075

1

82423.075

0.101

0.772

Residuals

2.455×10

+6

3

818435.277

exercise

36234.993

1

36234.993

0.041

0.852

+6

3

877788.859
0.012

0.918

1.493

0.309

1.991

0.253

0.032

0.869

Residuals

2.633×10

condition * time

5164.583

1

5164.583

Residuals

1.246×10

+6

3

415205.699

condition * exercise

75220.599

1

75220.599

Residuals

151177.490

3

50392.497

time * exercise

772844.606

1

772844.606

+6

3

388226.868

Residuals

1.165×10

condition * time * exercise

2007.086

1

2007.086

Residuals

185771.068

3

61923.689

Note. Type III Sum of Squares

81

Statistics from 3-way repeated measures ANOVA analysis of monocyte cells/µl across exercise
(pre and post), time (before and after), and condition (salt and control) (n=4).
Within Subjects Effects
Cases
condition

Sum of Squares
768.026

df Mean Square
1 768.026

Residuals

7019.634

3

2339.878

time
Residuals

3256.043
756.585

1
3

exercise

168.040

Residuals

F
0.328

p
0.607

3256.043
252.195

12.911

0.037*

1

168.040

0.055

0.830

9180.379

3

3060.126

condition * time

2448.075

1

2448.075

1.367

0.327

Residuals

5374.058

3

1791.353

condition * exercise

32.542

1

32.542

0.096

0.777

Residuals

1017.406

3

339.135

time * exercise

3.207

1

3.207

0.002

0.968

Residuals

5202.066

3

1734.022

condition * time * exercise

317.709

1

317.709

1.882

0.264

Residuals

506.334

3

168.778

Note. Type III Sum of Squares. (*) denotes statistically significant change in monocytes per µl.

82

Statistics from 3-way repeated measures ANOVA analysis of NK cells/µl across exercise (pre and
post), time (before and after), and condition (salt and control) (n=4).
Within Subjects Effects
Cases
condition
Residuals

Sum of Squares
513.441
5063.633

df Mean Square
1 513.441
3 1687.878

F
0.304

p
0.620

time

12200.001

1

12200.001

0.874

0.419

Residuals
exercise
Residuals

41855.398
73.872
5901.641

3
1
3

13951.799
73.872
1967.214

0.038

0.859

condition * time

827.228

1

827.228

0.544

0.514

Residuals

4561.885

3

1520.628

condition * exercise

0.702

1

0.702

0.001

0.973

Residuals

1591.815

3

530.605

times * exercise

2313.700

1

2313.700

1.550

0.302

Residuals

4477.824

3

1492.608

condition * time * exercise

36.509

1

36.509

0.079

0.797

Residuals

1390.703

3

463.568

Note. Type III Sum of Squares.

83

Statistics from 3-way repeated measures ANOVA analysis of neutrophil proportion of the total
leukocyte population for, condition (salt or sugar), time (before or after), and exercise (pre- and
post-exercise) measured through flow cytometry (n=4).
Within Subjects Effects
Cases
condition
Residuals
time
Residuals
exercise
Residuals

Sum of Squares
0.005
0.020
1.205×10-4
0.030
0.002
0.021

df Mean Square
1 0.005
3 0.007
1 1.205×10-4
3 0.010
1 0.002
3 0.007

F
0.702

p
0.464

0.012

0.920

0.345

0.598

condition * time

0.006

1

0.006

0.731

0.455

Residuals

0.023

3

0.008

1

1.431×10-4

0.107

0.765

3.328

0.166

0.083

0.792

-4

condition * exercise

1.431×10

Residuals

0.004

3

0.001

time * exercise

0.008

1

0.008

Residuals

0.007

3

0.002

condition * time * exercise

2.022×10-4

1

2.022×10-4

Residuals

0.007

3

0.002

Note. Type III Sum of Squares.

84

Statistics from 3-way repeated measures ANOVA analysis of monocyte proportion of the total
leukocyte population for, condition (salt or sugar), time (before or after), and exercise (pre- and
post-exercise) measured through flow cytometry (n=4).
Within Subjects Effects
Cases

Sum of Squares

df Mean Square

condition

1.476×10-4

1

1.476×10-4

Residuals

4.503×10

-4

3

1.501×10

-4

1.003×10

-5

1

1.003×10-5

Residuals

7.937×10

-4

3

2.646×10

-4

exercise

1.575×10-4

1

1.575×10-4

Residuals

3.965×10-4

3

1.322×10-4

2.632×10

-4

1

2.632×10-4

3.256×10

-4

3

1.085×10

-4

2.661×10

-6

1

2.661×10-6

9.938×10

-5

3

3.313×10

-5

5.036×10

-5

1

5.036×10-5

1.647×10

-4

3

5.491×10

-5

2.180×10

-6

1

2.180×10-6

7.462×10

-5

3

-5

time

condition * time
Residuals
condition * time
Residuals
time * exercise
Residuals
condition * time * exercise
Residuals

2.487×10

F

p

0.983

0.394

0.038

0.858

1.192

0.355

2.425

0.217

0.080

0.795

0.917

0.409

0.088

0.787

Note. Type III Sum of Squares.

85

Statistics from 3-way repeated measures ANOVA analysis of NK cell proportion of the total
leukocyte population for, condition (salt or sugar), time (before or after), and exercise (pre- and
post-exercise) measured through flow cytometry (n=4).

Within Subjects Effects
Cases

Sum of Squares

df Mean Square

condition

4.262×10-5

1

4.262×10-5

Residuals

6.297×10

-4

3

2.099×10

-4

3.500×10

-4

1

3.500×10-4

3

4.986×10

-4

1

2.182×10-4

3

4.500×10

-4

1

4.324×10-5
-4

time
Residuals
exercise
Residuals
condition * time
Residuals
condition * time
Residuals
time * exercise
Residuals
treatment * time * exercise
Residuals

0.001
2.182×10

-4

0.001
4.324×10

-5

6.268×10

-4

3

2.089×10

4.130×10

-6

1

4.130×10-6

3.212×10

-4

3

1.071×10

-4

2.574×10

-4

1

2.574×10-4

5.666×10

-4

3

1.889×10

-4

4.186×10

-6

1

4.186×10-6

3.218×10

-4

3

-4

1.073×10

F

p

0.203

0.683

0.702

0.464

0.485

0.536

0.207

0.680

0.039

0.857

1.363

0.327

0.039

0.856

Note. Type III Sum of Squares.

86

Abbreviations
Abbreviation
Na+
CVD
BP
ESL
GAG
NO
HS
HA
eGC
eNOS
BH4
NADPH
FAD
FMN
sGC
cGMP
GTP
GPCR
PLC
DAG
IP3
MLCK
MLCP
ROS
O 2ONOOSOD
FMD
H 2O 2
ENaC
SDC-1
LPS
TNF-α
IL-1β
IL-6
CCR2
MCP-1

Definition
Sodium
Cardiovascular Disease
Blood Pressure
Endothelial Surface Layer
Glycosaminoglycan
Nitric Oxide
Heparan Sulfate
Hyaluronic Acid
Endothelial Glycocalyx
Endothelial Nitric Oxide Synthase
Tetrahydrobiopterin
Nicotinamide Adenine Dinucleotide Phosphate
Flavin Adenine Dinucleotide
Flavin Mononucleotide
Guanylyl Cyclase
Cyclic Guanosine Monophosphate
Guanosine Triphosphate
G-protein Coupled Receptors
Phospholipase C
Diacylglycerol
Inositol 1,4,5-trisphosphate
Myosin Light Chain Kinase
Myosin Light Chain Phosphotase
Reactive Oxygen Species
Superoxide
Peryoxynitrite
Superoxide Dismutase
Flow-mediated Dilation
Hydrogen Peroxide
epithelial Na+ Channels
Syndecan-1
Lipopolysaccharide
Tumour Necrosis Factor Alpha
Interleukin-1 Beta
Interleukin-6
C-C Chemokine Receptor Type 2
Monocyte Chemoattractant Protein-1

87

VEGF-C
NK cells
PAR-Q+
RQ
VT1
CO2
VO2
VCO2
VE
VT2
ECG
ELISA
PPG
CNAP
HR
CRP
IL-1ra
IL-10
CK
HOCl
MPO
IFN-γ
IL-1
TNF
GM-CSF

Vascular Endothelial Growth Factor-C
Natural Killer Cells
Physical Activity Readiness +
Respiratory Quotient
Ventilatory Threshold 1
Carbon Dioxide
Oxygen Uptake
Carbon Dioxide Output
Minute Ventilation
Ventilatory Threshold 2
Electrocardiogram
Enzyme-linked Immunosorbent Assay
Photoplethysmography
Continuous Non-invasive Arterial Pressure Monitoring
Heart Rate
C-reactive Protein
Interleukin-1 Receptor Antagonist
Interleukin-10
Creatine Kinase
Hypochlorous Acid
Myeloperoxidase
Interferon-γ
Interleukin-1
Tumour Necrosis Factor
Granulocyte-Macrophage Colony-Stimulating Factor

88