The reproducibility of closed-pouch sweat collection and thermoregulatory responses to exercise?heat stress

Reliability of a 60-min treadmill running protocol in the heat: The journal Temperature toolbox

We determined the reliability of a 60-min treadmill protocol in the heat when spaced >4 weeks apart, longer than the test-retest duration of 1 week found in the literature. Nine unacclimated, trained males (age: 31 ± 8 y; VO2peak: 60 ± 6 ml∙kg-1∙min-1) undertook a 15 min self-paced time-trial pre-loaded with 45 min of running at 70% of individual ventilatory threshold (11.2 ± 0.3 km∙h-1) in 30 ± 1°C (53 ± 5% relative humidity). They repeated this following 40 ± 14 and 76 ± 26 days, with pre-trial standardization of diet and exercise for 48 h. When considering trial 1 as a familiarization, change in core temperature (∆Tcore) during the first 45 min (∆2.0 ± 0.2°C) between trials 2 and 3 yielded bias and 95% limits of agreement (LoA) of -0.10 ± 0.43°C, standard error of measurement (SEM) of 0.13°C and intraclass correlation coefficient (ICC) of 0.75, more reliable than measures of baseline Tcore (36.9 ± 0.2°C; LoA: -0.23 ± 0.90°C; SEM: 0.22°C; ICC: 0.03) and Tcore at 45 min during exercise (38.9 ± 0.4°C; LoA: 0.32 ± 1.12°C; SEM: 0.28°C; ICC: 0.15). The coefficient of variation (CV) between trials 2 and 3 for distance run during the 15 min time-trial was 2.1 ± 2.0% with LoA of 0.001 ± 0.253 km and SEM of 0.037 km. This protocol is reliable spaced ~5 weeks apart when considering the most commonly accepted limit of <5% CV for performance, reinforced by reliability of the ΔTcore being 0.1 ± 0.4°C.

The effect of sweat sample storage condition on sweat content

Due to time and logistical constraints sweat samples cannot always be analyzed immediately. The purpose of this study was to investigate the effect of storage temperature and duration on sweat electrolyte and metabolite concentrations. Twelve participants cycled for 60 min at 40 W.m⁻² in 33°C and 65% RH. Using the absorbent patch technique, six sweat samples were collected from the posterior torso. Sweat from the six samples was mixed, divided again over six samples and placed in sealed vials. Sweat sodium, chloride, potassium, ammonia, lactate and urea concentrations in one sample were determined immediately. Two samples were stored at room temperature (~25°C, 42% RH) for 7 and 28 days respectively. The remaining samples were frozen at −20°C for 1 h, 7 or 28 days respectively before analysis. Sweat sodium, chloride, potassium and urea concentrations were not affected by storage temperature and duration. Sweat lactate decreased (−1.8 ± 1.8 mmol.L⁻¹, P = 0.007) and ammonia concentrations increased (5.1 ± 3.9 mmol.L⁻¹, P = 0.017) after storage for 28 days at 25°C only. The storage temperature and duration did not affect sodium, chloride, potassium and urea concentrations. However, sweat samples should not be stored for longer than 7 days at 25°C to obtain reliable sweat lactate and ammonia concentrations. When samples are frozen at −20°C, the storage duration could be extended to 28 days for these components.

A Case-Series Observation of Sweat Rate Variability in Endurance-Trained Athletes

Adequate fluid replacement during exercise is an important consideration for athletes, however sweat rate (SR) can vary day-to-day. The purpose of this study was to investigate day-to-day variations in SR while performing self-selected exercise sessions to evaluate error in SR estimations in similar temperature conditions. Thirteen endurance-trained athletes completed training sessions in a case-series design 1x/week for a minimum 30 min of running/biking over 24 weeks. Body mass was recorded pre/post-training and corrected for fluid consumption. Data were split into three Wet-Bulb Globe Thermometer (WBGT) conditions: LOW (<10 °C), MOD (10–19.9 °C), HIGH (>20 °C). No significant differences existed in exercise duration, distance, pace, or WBGT for any group (p > 0.07). Significant differences in SR variability occurred for all groups, with average differences of: LOW = 0.15 L/h; MOD = 0.14 L/h; HIGH = 0.16 L/h (p < 0.05). There were no significant differences in mean SR between LOW-MOD (p > 0.9), but significant differences between LOW-HIGH and MOD-HIGH (p < 0.03). The assessment of SR can provide useful data for determining hydration strategies. The significant differences in SR within each temperature range indicates a single assessment may not accurately represent an individual’s typical SR even in similar environmental conditions.

The Impact of Nutritional Supplementation on Sweat Metabolomic Content: A Proof-of-Concept Study

Sweat is emerging as a prominent biosource for real-time human performance monitoring applications. Although promising, sources of variability must be identified to truly utilize sweat for biomarker applications. In this proof-of-concept study, a targeted metabolomics method was applied to sweat collected from the forearms of participants in a 12-week exercise program who ingested either low or high nutritional supplementation twice daily. The data establish the use of dried powder mass as a method for metabolomic data normalization from sweat samples. Additionally, the results support the hypothesis that ingestion of regular nutritional supplementation semi-quantitatively impact the sweat metabolome. For example, a receiver operating characteristic (ROC) curve of relative normalized metabolite quantities show an area under the curve of 0.82 suggesting the sweat metabolome can moderately predict if an individual is taking nutritional supplementation. Finally, a significant correlation between physical performance and the sweat metabolome are established. For instance, the data illustrate that by utilizing multiple linear regression modeling approaches, sweat metabolite quantities can predict VO₂ max (p = 0.0346), peak lower body Windage (p = 0.0112), and abdominal circumference (p = 0.0425). The results illustrate the need to account for dietary nutrition in biomarker discovery applications involving sweat as a biosource.

Rate normalization for sweat metabolomics biomarker discovery

As the demand for real-time exercise performance feedback increases, excreted sweat has become a biosource of interest for continuous human performance assessment. For sweat to truly fulfill this requirement, analyte concentrations must be normalized to adequately assess day-to-day differences within and among individuals. In this manuscript, data are presented highlighting the use of accurate localized sweat rate as a means for ion and global metabolomic data normalization. The results illustrate large sweat rate variability among individuals over the course of two distinct exercises protocols. Furthermore, the data show sweat rate is not symmetrical at similar locations among right and left forearms of individuals (p = 0.0007). Sweat ion conductivity analysis suggest overall sweat rate normalization reduces variability collectively among ion values and participants with principal component analysis showing 77.8% of variation in the data set attributable to sweat rate normalization. Global metabolomic analysis of sweat illustrated overall rate normalization increases the variability among test subjects with 72.7% of the variation explained by sweat rate normalization. Finally, overall rate normalized metabolomic features of sweat significantly correlated (ρ ≥ 0.7, ρ ≤ -0.7) with measured performance metrics of the individual, establishing the potential for sweat to be used as a biosource for performance monitoring. Collectively, these data illustrate the importance of accurate localized sweat rate determination, for analyte data normalization, in support for the use of sweat in biomarker discovery efforts to predict human performance.

Physiological mechanisms determining eccrine sweat composition

Purpose

The purpose of this paper is to review the physiological mechanisms determining eccrine sweat composition to assess the utility of sweat as a proxy for blood or as a potential biomarker of human health or nutritional/physiological status.

Methods

This narrative review includes the major sweat electrolytes (sodium, chloride, and potassium), other micronutrients (e.g., calcium, magnesium, iron, copper, zinc, vitamins), metabolites (e.g., glucose, lactate, ammonia, urea, bicarbonate, amino acids, ethanol), and other compounds (e.g., cytokines and cortisol).

Results

Ion membrane transport mechanisms for sodium and chloride are well established, but the mechanisms of secretion and/or reabsorption for most other sweat solutes are still equivocal. Correlations between sweat and blood have not been established for most constituents, with perhaps the exception of ethanol. With respect to sweat diagnostics, it is well accepted that elevated sweat sodium and chloride is a useful screening tool for cystic fibrosis. However, sweat electrolyte concentrations are not predictive of hydration status or sweating rate. Sweat metabolite concentrations are not a reliable biomarker for exercise intensity or other physiological stressors. To date, glucose, cytokine, and cortisol research is too limited to suggest that sweat is a useful surrogate for blood.

Conclusion

Final sweat composition is not only influenced by extracellular solute concentrations, but also mechanisms of secretion and/or reabsorption, sweat flow rate, byproducts of sweat gland metabolism, skin surface contamination, and sebum secretions, among other factors related to methodology. Future research that accounts for these confounding factors is needed to address the existing gaps in the literature.

Electronic supplementary material

The online version of this article (10.1007/s00421-020-04323-7) contains supplementary material, which is available to authorized users.

Reliability of a wearable sweat rate monitor and routine sweat analysis techniques under heat stress in females

INTRODUCTION

The aim of the study was to evaluate the reliability of five different sweat analysis techniques which measure; whole body sweat rate [WBSR], local sweat rate [LSR] (via technical absorbent [TA] method and KuduSmart^® monitor), sweat conductivity [SC] and sweat gland activation [SGA] in a female population when exercising moderately under heat stress.

METHODS

Fourteen females (age; 26 ± 7 years, body mass; 66.5 ± 7.6 kg, height; 167.1 ± 6.4 cm) completed a preliminary threshold walking test (to determine exercise intensity) and two main trials, separated by 2 days. Main trials consisted of 30-min seated rest in the environmental chamber (35 °C, 50% relative humidity) in an upper body sauna-suit, before its removal, and walking at a moderate intensity (4 metabolic equivalents) for 30-min (speeds ranged from 4.8 to 6.5 km h^-1). WBSR was measured via nude mass pre and post exercise. The TA and Tegaderm patches (for sweat sodium chloride) were placed on the back, forearm and chest for the entire 60-min, replicated for all participants for both trials. SGA was assessed following the 60-min trial and the KuduSmart® monitor was placed on the left arm for the 30-min of exercise.

RESULTS

WBSR, LSR methods and SC demonstrated no difference between trials (p > 0.05), good agreement (within limits), strong correlations (r ≥ 0.88) and low typical error of measurements [TEM] (< 0.04 L min^-1, 0.13 mg min^-1 cm^-2 and 8 mmol L^-1, respectively). SGA method showed moderate intra-class correlation (r = 0.80), with high TEM (5 glands) and large limits of agreement.

CONCLUSION

Sudomotor function is reliable, as demonstrated by good reliability, small TEM and strong correlations. The use of these sweat techniques is appropriate and practical in females who are exercising at moderate intensity under heat stress, and so, may aid future interventions. SGA shows larger variation and should be used with caution.

A new occupational heat tolerance test: A feasibility study

Heat tolerance tests identify those susceptible to heat illnesses and monitor heat adaptations. Currently, tolerance tests do not replicate the uncompensable heat strain environments experienced in some occupations. In addition, tests can take up to 2 h to complete, and cannot offer intra and inter individual comparisons, due to the use of a fixed exercise intensity. This study aimed to assess the validity and reliability of a new heat occupational tolerance test (HOTT: 40 min at 6 W kg^-1 metabolic heat production, 50 °C 10% RH, in protective clothing) to the standard heat tolerance test (HTT: 2 h walk at 5 km h^-1 1% gradient, 40 °C 40% RH, in shorts and t-shirt). Eighteen participants (age: 21 ± 3 yrs, body mass: 81.3 ± 5.9 kg) completed trials to assess the validity and/or reliability of the HOTT. Peak rectal temperature (T_re) displayed strong agreement and low measurement error (0.19 °C) between HTT (38.7 ± 0.4 °C) and HOTT (38.6 ± 0.4 °C). Strong agreement was also displayed for physiological and perceptual measures between the two HOTT trials, including peak T_re (38.5 ± 0.4 °C vs. 38.5 ± 0.4 °C) and peak heart rate (182 ± 20 b min^-1 vs. 182 ± 21 b min^-1). The HOTT is the first tolerance test that assesses individuals' responses whilst wearing protective clothing in high temperatures. It can consistently identify individuals' levels of heat tolerance within a reduced time frame. In addition, it allows for participant monitoring over time and comparisons between individuals to be made. A continuum based approach is recommended when assessing individuals' responses to the HOTT.

The proteomic and metabolomic characterization of exercise-induced sweat for human performance monitoring: A pilot investigation

Sweat is a biofluid with several attractive attributes. However, investigation into sweat for biomarker discovery applications is still in its infancy. To add support for the use of sweat as a non-invasive media for human performance monitoring, volunteer participants were subjected to a physical exertion model using a treadmill. Following exercise, sweat was collected, aliquotted, and analyzed for metabolite and protein content via high-resolution mass spectrometry. Overall, the proteomic analysis illustrates significant enrichment steps will be required for proteomic biomarker discovery from single sweat samples as protein abundance is low in this medium. Furthermore, the results indicate a potential for protein degradation, or a large number of low molecular weight protein/peptides, in these samples. Metabolomic analysis shows a strong correlation in the overall abundance among sweat metabolites. Finally, hierarchical clustering of participant metabolite abundances show trends emerging, although no significant trends were observed (alpha = 0.8, lambda = 1 standard error via cross validation). However, these data suggest with a greater number of biological replicates, stronger, statistically significant results, can be obtained. Collectively, this study represents the first to simultaneously use both proteomic and metabolomic analysis to investigate sweat. These data highlight several pitfalls of sweat analysis for biomarker discovery applications.

Sweating Rate and Sweat Sodium Concentration in Athletes: A Review of Methodology and Intra/Interindividual Variability

Athletes lose water and electrolytes as a consequence of thermoregulatory sweating during exercise and it is well known that the rate and composition of sweat loss can vary considerably within and among individuals. Many scientists and practitioners conduct sweat tests to determine sweat water and electrolyte losses of athletes during practice and competition. The information gleaned from sweat testing is often used to guide personalized fluid and electrolyte replacement recommendations for athletes; however, unstandardized methodological practices and challenging field conditions can produce inconsistent/inaccurate results. The primary objective of this paper is to provide a review of the literature regarding the effect of laboratory and field sweat-testing methodological variations on sweating rate (SR) and sweat composition (primarily sodium concentration [Na⁺]). The simplest and most accurate method to assess whole-body SR is via changes in body mass during exercise; however, potential confounding factors to consider are non-sweat sources of mass change and trapped sweat in clothing. In addition, variability in sweat [Na⁺] can result from differences in the type of collection system used (whole body or localized), the timing/duration of sweat collection, skin cleaning procedure, sample storage/handling, and analytical technique. Another aim of this paper is to briefly review factors that may impact intra/interindividual variability in SR and sweat [Na⁺] during exercise, including exercise intensity, environmental conditions, heat acclimation, aerobic capacity, body size/composition, wearing of protective equipment, sex, maturation, aging, diet, and/or hydration status. In summary, sweat testing can be a useful tool to estimate athletes’ SR and sweat Na⁺ loss to help guide fluid/electrolyte replacement strategies, provided that data are collected, analyzed, and interpreted appropriately.

Sweat Sodium, Potassium, and Chloride Concentrations Analyzed Same Day as Collection Versus After 7 Days Storage in a Range of Temperatures

The purpose of this study was to determine the effect of storage temperature on sodium ([Na⁺]), potassium ([K⁺]), and chloride ([Cl^-]) concentrations of sweat samples analyzed 7 days after collection. Using the absorbent patch technique, 845 sweat samples were collected from 39 subjects (32 ± 7 years, 72.9 ± 10.5 kg) during exercise. On the same day as collection (PRESTORAGE), 609 samples were analyzed for [Na⁺], [Cl^-], and [K⁺] by ion chromatography (IC) and 236 samples were analyzed for [Na⁺] using a compact ion-selective electrode (ISE). Samples were stored at one of the four conditions: -20 °C (IC, n = 138; ISE, n = 60), 8 °C (IC, n = 144; ISE, n = 59), 23 °C (IC, n = 159; ISE, n = 59), or alternating between 8 °C and 23 °C (IC, n = 168; ISE, n = 58). After 7 days in storage (POSTSTORAGE), samples were reanalyzed using the same technique as PRESTORAGE. PRESTORAGE sweat electrolyte concentrations were highly related to that of POSTSTORAGE (intraclass correlation coefficient: .945-.989, p < .001). Mean differences (95% confidence intervals) between PRESTORAGE and POSTSTORAGE were statistically, but not practically, significant for most comparisons: IC [Na⁺]: -0.5(0.9) to -2.1(0.9) mmol/L; IC [K⁺]: -0.1(0.1) to -0.2(0.1) mmol/L; IC [Cl^-]: -0.4(1.4) to -1.3(1.3) mmol/L; ISE [Na⁺]: -2.0(1.1) to 1.3(1.1) mmol/L. Based on typical error of measurement results, 95% of the time PRESTORAGE and POSTSTORAGE sweat [Na⁺], [K⁺], and [Cl^-] by IC analysis fell within ±7-9, ±0.6-0.7, and ±9-13 mmol/L, respectively, while sweat [Na⁺] by ISE was ±6 mmol/L. All conditions produced high reliability and acceptable levels of agreement in electrolyte concentrations of sweat samples analyzed on the day of collection versus after 7 days in storage.

Body map of regional vs. whole body sweating rate and sweat electrolyte concentrations in men and women during moderate exercise-heat stress

This study determined the relations between regional (REG) and whole body (WB) sweating rate (RSR and WBSR, respectively) as well as REG and WB sweat Na⁺ concentration ([Na⁺]) during exercise. Twenty-six recreational athletes (17 men, 9 women) cycled for 90 min while WB sweat [Na⁺] was measured using the washdown technique. RSR and REG sweat [Na⁺] were measured from nine regions using absorbent patches. RSR and REG sweat [Na⁺] from all regions were significantly ( P < 0.05) correlated with WBSR ( r = 0.58-0.83) and WB sweat [Na⁺] ( r = 0.74-0.88), respectively. However, the slope and y-intercept of the regression lines for most models were significantly different than 1 and 0, respectively. The coefficients of determination ( r²) were 0.44-0.69 for RSR predicting WBSR [best predictors: dorsal forearm ( r² = 0.62) and triceps ( r² = 0.69)] and 0.55-0.77 for REG predicting WB sweat [Na⁺] [best predictors: ventral forearm ( r² = 0.73) and thigh ( r² = 0.77)]. There was a significant ( P < 0.05) effect of day-to-day variability on the regression model predicting WBSR from RSR at most regions but no effect on predictions of WB sweat [Na⁺] from REG. Results suggest that REG cannot be used as a direct surrogate for WB sweating responses. Nonetheless, the use of regression equations to predict WB sweat [Na⁺] from REG can provide an estimation of WB sweat [Na⁺] with an acceptable level of accuracy, especially using the forearm or thigh. However, the best practice for measuring WBSR remains conventional WB mass balance calculations since prediction of WBSR from RSR using absorbent patches does not meet the accuracy or reliability required to inform fluid intake recommendations. NEW & NOTEWORTHY This study developed a body map of regional sweating rate and regional (REG) sweat electrolyte concentrations and determined the effect of within-subject (bilateral and day-to-day) and between-subject (sex) factors on the relations between REG and the whole body (WB). Regression equations can be used to predict WB sweat Na⁺ concentration from REG, especially using the forearm or thigh. However, prediction of WB sweating rate from REG sweating rate using absorbent patches does not reach the accuracy or reliability required to inform fluid intake recommendations.

Measurement of sodium concentration in sweat samples: comparison of 5 analytical techniques

Sweat sodium concentration (SSC) can be determined using different analytical techniques (ATs), which may have implications for athletes and scientists. This study compared the SSC measured with 5 ATs: ion chromatography (IChr), flame photometry (FP), direct (DISE) and indirect (IISE) ion-selective electrode, and ion conductivity (IC). Seventy sweat samples collected from 14 athletes were analyzed with 5 instruments: the 883 Basic IC Plus (IChr, reference instrument), AAnalyst 200 (FP), Cobas 6000 (IISE), Sweat-Chek (IC), and B-722 Laqua Twin (DISE). Instruments showed excellent relative (intraclass correlation coefficient (ICC) ≥ 0.999) and absolute (coefficient of variation (CV) ≤ 2.6%) reliability. Relative validity was also excellent between ATs (ICC ≥ 0.961). In regards to the inter-AT absolute validity, compared with IChr, standard error of the estimates were similar among ATs (2.8-3.8 mmol/L), but CV was lowest with DISE (3.9%), intermediate with IISE (7.6%), and FP (6.9%) and highest with IC (12.3%). In conclusion, SSC varies depending on the AT used to analyze samples. Therefore, results obtained from different ATs are scarcely comparable and should not be used interchangeably. Nevertheless, taking into account the normal variability in SSC (∼±12%), the imprecision of the recommendations deriving from FP, IISE, IC, and DISE should have trivial health and physiological consequences under most exercise circumstances.

The reliability of a heat acclimation state test prescribed from metabolic heat production intensities

Acclimation state indicates an individual's phenotypic response to a thermally stressful environment, where changes in heat dissipation capacity are determined during a heat acclimation state test (HAST). Variations in thermoregulatory and sudomotor function are reported while exercising at intensities relative to maximal oxygen uptake. This inter-individual variation is not true when intensity is prescribed to elicit a fixed rate of metabolic heat production (Ḣprod). This study investigated the reliability of peak Tre and two composite measures (sweat gain and sweat setpoint) derived from indices of thermosensitivity during a HAST prescribed from Ḣprod intensities. Fourteen participants (mean±SD; age 23±3 years, stature 174±7cm, body mass 75.0±9.4kg, body surface area 1.9±0.1m(2), peak oxygen consumption [V̇O2peak] 3.49±0.53Lmin(-1)) completed a lactate threshold-V̇O2peak test and two duplicate Ḣprod HASTs on a cycle ergometer. The HAST consisted of three, 30-min periods of exercise at fixed Ḣprod intensities relative to body mass (3, 4.5 and 6Wkg(-1)), within hot dry conditions (44.7±1.8°C and 18.1±4.7% relative humidity). Peak Tre (38.20±0.36 vs. 38.16±0.42°C, p=0.54), sweat setpoint (36.76±0.34 and 36.79±0.38°C, p=0.68) and sweat gain (0.37±0.14 and 0.40±0.18gs(-1)°C(-1), p=0.40) did not differ between HASTs. Typical error of measurement (TEM), coefficient variation (CV) and intra-class coefficient of correlation (ICC) were 0.19°C, 0.5% and 0.80 for peak Tre, 0.21°C, 0.6% and 0.65 for sweat setpoint and 0.09gs(-1)°C(-1), 28% and 0.68 for sweat gain, respectively. The use of fixed Ḣprod intensities relative to body mass is a reliable method for measuring Tre and ascertaining sweat setpoint during a HAST, whereas, sweat gain displays greater variability. A Ḣprod HAST appears sufficiently reliable for quantifying heat acclimation state, where TEM in peak Tre and sweat setpoint are small enough to identify physiologically meaningful improvements post-intervention.

Regional variations in transepidermal water loss, eccrine sweat gland density, sweat secretion rates and electrolyte composition in resting and exercising humans

Literature from the past 168 years has been filtered to provide a unified summary of the regional distribution of cutaneous water and electrolyte losses. The former occurs via transepidermal water vapour diffusion and secretion from the eccrine sweat glands. Daily insensible water losses for a standardised individual (surface area 1.8 m2) will be 0.6-2.3 L, with the hands (80-160 g.h-1) and feet (50-150 g.h-1) losing the most, the head and neck losing intermediate amounts (40-75 g.h-1) and all remaining sites losing 15-60 g.h-1. Whilst sweat gland densities vary widely across the skin surface, this same individual would possess some 2.03 million functional glands, with the highest density on the volar surfaces of the fingers (530 glands.cm-2) and the lowest on the upper lip (16 glands.cm-2). During passive heating that results in a resting whole-body sweat rate of approximately 0.4 L.min-1, the forehead (0.99 mg.cm-2.min-1), dorsal fingers (0.62 mg.cm-2.min-1) and upper back (0.59 mg.cm-2.min-1) would display the highest sweat flows, whilst the medial thighs and anterior legs will secrete the least (both 0.12 mg.cm-2.min-1). Since sweat glands selectively reabsorb electrolytes, the sodium and chloride composition of discharged sweat varies with secretion rate. Across whole-body sweat rates from 0.72 to 3.65 mg.cm-2.min-1, sodium losses of 26.5-49.7 mmol.L-1 could be expected, with the corresponding chloride loss being 26.8-36.7 mmol.L-1. Nevertheless, there can be threefold differences in electrolyte losses across skin regions. When exercising in the heat, local sweat rates increase dramatically, with regional glandular flows becoming more homogeneous. However, intra-regional evaporative potential remains proportional to each local surface area. Thus, there is little evidence that regional sudomotor variations reflect an hierarchical distribution of sweating either at rest or during exercise.

Biological and analytical variation of the human sweating response: implications for study design and analysis

Appropriate quantification of analytical and biological variation of thermoregulatory sweating has important practical utility for research design and statistical analysis. We sought to examine contributors to variability in local forearm sweating rate (SR) and sweating onset (SO) and to evaluate the potential for using bilateral measurements. Two women and eight men (26 ± 9 yr; 79 ± 12 kg) completed 5 days of heat acclimation and walked (1.8 l/min VO(2)) on three occasions for 30 min in 40°C, 20% RH, while local SR and SO were measured. Local SR measures among days were not different (2.14 ± 0.72 vs. 2.02 ± 0.79 vs. 2.31 ± 0.72 mg·cm(2)·min(-1), P = 0.19) nor was SO (10.47 ± 2.54 vs. 10.04 ± 2.97 vs. 9.87 ± 3.44 min P = 0.82). Bilateral SR (2.14 ± 0.72 vs. 2.16 ± 0.71 mg·cm(2)·min(-1), P = 0.56) and SO (10.47 ± 2.54 vs. 10.83 ± 2.48 min, P = 0.09) were similar and differences were ≤ 1 SD of day-to-day differences for a single forearm. Analytical imprecision (CV(a)), within (CV(i))-, and between (CV(g))-subjects' coefficient of variation for local SR were 2.4%, 22.3%, and 56.4%, respectively, and were 0%, 9.6%, and 41%, respectively, for SO. We conclude: 1) technologically, sweat capsules contribute negligibly to sweat measurement variation; 2) bilateral measures of SR and SO appear interchangeable; 3) when studying potential factors affecting sweating, changes in SO afford a more favorable signal-to-noise ratio vs. changes in SR. These findings provide a quantitative basis for study design and optimization of power/sample size analysis in the evaluation of thermoregulatory sweating.

Surface contamination artificially elevates initial sweat mineral concentrations

Several sweat mineral element concentrations decline with serial sampling. Possible causes include reduced dermal mineral concentrations or flushing of surface contamination. The purpose of this study was to simultaneously sample mineral concentrations in transdermal fluid (TDF), sweat, and serum during extended exercise-heat stress to determine if these compartments show the same serial changes during repeat sampling. Sixteen heat-acclimated individuals walked on a treadmill (1.56 m/s, 3.0% grade) in a 35°C, 20% relative humidity (RH), 1 m/s wind environment 50 min each hour for 3 h. Mineral concentrations of Ca, Cu, Fe, K, Mg, Na, and Zn were measured each hour from serum, sweat from upper back (sweat pouch) and arm (bag), and TDF from the upper back. Sites were meticulously cleaned to minimize surface contamination. Mineral concentrations were determined by spectrometry. TDF remained stable over time, with exception of a modest increase in TDF [Fe] (15%) and decrease in TDF [Zn] (-18%). Likewise, serum and pouch sweat samples were stable over time. In contrast, the initial arm bag sweat mineral concentrations were greater than those in the sweat pouch, and [Ca], [Cu], [Mg], and [Zn] declined 26-76% from initial to the subsequent samples, becoming similar to sweat pouch. Nominal TDF mineral shifts do not affect sweat mineral concentrations. Arm bag sweat mineral concentrations are initially elevated due to skin surface contaminants that are not removed despite meticulous cleaning (e.g., under fingernails, on arm hair), then decrease with extended sweating and approach those measured from the scapular region.

Effect of heat acclimation on sweat minerals

PURPOSE

This study examined the impact of 10 d of exercise-heat acclimation on sweat mineral concentrations.

METHODS

Eight male subjects walked on a treadmill at 3.5 mph, 4% grade for 100 continuous minutes or until rectal temperature reached 39.5 degrees C on 10 consecutive days in an environmental chamber set at 45 degrees C, 20% relative humidity. Arm sweat samples were collected during the first 30 min of exercise-heat stress on days 1 and 10 using a polyethylene arm glove.

RESULTS

Final core temperature and HR values were significantly lower (P < 0.05) on day 10 versus day 1. Whole-body sweating rates increased by approximately 6% (P = 0.12). Sweat sodium concentration on day 10 (36.22 +/- 7.22 mM) was significantly lower than day 1 (54.49 +/- 16.18 mM) (P < 0.05). Sweat mineral concentrations of calcium (approximately 29%), copper (approximately 50%), and magnesium (approximately 43%) were also significantly lower on day 10 versus day 1 of heat acclimation (P < 0.05). A trend for lower sweat iron (approximately 75%; P = 0.07) and zinc (approximately 23%; P = 0.10) concentrations were observed from day 1 to day 10. The estimated hourly sweat mineral losses (arm concentration x whole-body sweat rate) were reduced for calcium (approximately 27%), copper (approximately 46%), and magnesium (approximately 42%) (P < 0.05), but not iron (75%) or zinc (approximately 16%) (P > 0.05), from day 1 to day 10.

CONCLUSION

Exercise-heat acclimation conserves arm sweat mineral concentrations and possibly whole-body sweat losses of calcium, copper, and magnesium, and may reduce sweat iron and zinc concentrations.

Dissolution of materials in artificial skin surface film liquids

The dissolution of chemical constituents from jewelry, textiles, cosmetics, drugs, industrial chemicals, and particles in direct and prolonged contact with human skin is often assessed in vitro using artificial skin surface film liquids (SSFL). To provide meaningful results, the composition of artificial SSFL should accurately mimic human sweat and sebum, and the conditions of the in vitro test system should accurately reflect in vivo skin conditions. We summarized the reported composition of human SSFL and compared it to 45 different formulations of artificial sweat and 18 formulations of artificial sebum (studies published from 1940 to 2005). Conditions of in vitro dissolution test systems were reviewed and compared to in vivo skin conditions. The concentrations of individual constituents and pH of artificial sweat and concentrations of artificial sebum constituents are not always within ranges reported for human SSFL. Nearly all artificial SSFL lack many of the constituents in human SSFL. To develop a comprehensive model SSFL, we propose a standard SSFL, modified from the two best published sweat and sebum formulations. Little is known concerning the influence of test system conditions on dissolution, including SSFL temperature, container material composition, agitation, and physicochemical properties of the test article on dissolution. Thus, both a need and an opportunity exist for standardizing the composition of artificial SSFL and in vitro dissolution test methodologies. To standardize in vitro dissolution test systems, we recommend: maintaining artificial SSFL at a biologically relevant temperature appropriate to the human activity being modeled, carefully selecting test and sample storage containers to avoid bias in dissolution measurements, accounting for friction between a test article and skin in a biologically plausible manner, and physicochemical characterization of the test article or material to better understand mechanisms of dissolution and potential mechanisms of toxic action of dissolved material. More accurate modeling and better understanding of chemical dissolution from articles in contact with the skin will ultimately improve risk decision making, thereby protecting even the most susceptible persons from adverse health effects resulting from skin exposure.