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Physiology

UB study finds memory deficits resulting from epigenetic changes in Alzheimer’s disease can be reversed – UB Now: News and views for UB faculty and…

Memory loss associated with Alzheimers disease (AD) may be able to be restored by inhibiting certain enzymes involved in abnormal gene transcription, according to a preclinical study by UB researchers. The findings could pave the way toward new treatments for Alzheimers disease.

The paper was published Dec. 9 in Science Advances.

By treating AD mouse models with a compound to inhibit these enzymes, we were able to normalize gene expression, restore neuronal function and ameliorate cognitive impairment, says senior author Zhen Yan, SUNY Distinguished Professor in the Department of Physiology and Biophysics in the Jacobs School of Medicine and Biomedical Sciences at UB.

Alzheimers disease alters the expression of genes in the prefrontal cortex, a key region of the brain controlling cognitive processes and executive functions.

By focusing on gene changes caused by epigenetic processes (those that are not related to changes in DNA sequences) such as aging, the UB researchers were able to reverse elevated levels of harmful genes that cause memory deficits in AD.

The current research extends the work the UB team reported in 2019 in the journal Brain, in which they were able to reverse the loss or downregulation of genes beneficial to cognitive function in AD.

In this new paper, the UB team reports that it has reversed the upregulation of genes involved in impairing cognitive function.

Yan explains that transcription of genes is regulated by an important process called histone modification, where histones, the proteins that help package DNA into chromosomes, are modified to make that packaging looser or tighter. The nature of the packaging, in turn, controls how genetic material gains access to a cells transcriptional machinery, which can result in the activation or suppression of certain genes.

Yan says researchers found that H3K4me3, a histone modification called histone trimethylation at the amino acid lysine 4, which is linked to the activation of gene transcription, is significantly elevated in the prefrontal cortex of people with AD and mouse models of the disease.

That epigenetic change, she says, is linked to the abnormally high level of histone-modifying enzymes that catalyze the modification known as H3K4me3.

The UB researchers found that when the AD mouse models were treated with a compound that inhibits those enzymes, they exhibited significantly improved cognitive function.

This finding points to the potential of histone modifying enzyme-targeted drugs for AD treatment, which may have broad and powerful impact, Yan says.

In making that discovery, the UB team also identified a number of new target genes, including Sgk1 as a top-ranking target gene of the epigenetic alteration in AD. Sgk1 transcription is significantly elevated in the prefrontal cortex of people with AD and in animal models with the disorder.

Yan says researchers found that abnormal histone methylation at Sgk1 contributes to its elevated expression in AD. Interestingly, the upregulation of Sgk1 is also strongly correlated with the occurrence of cell death in other neurodegenerative diseases, including Parkinsons disease and amyotrophic lateral sclerosis, she says.

Sgk1 encodes an enzyme activated by cell stress, which plays a key role in numerous processes, such as regulating ion channels, enzyme activity, gene transcription, hormone release, neuroexcitability and cell death. The researchers found it is highly connected to other altered genes in AD, suggesting it may function as a kind of hub that interacts with many molecular components to control disease progress.

In this study, we have found that administration of a specific Sgk1 inhibitor significantly reduces the dysregulated form of tau protein that is a pathological hallmark of AD, restores prefrontal cortical synaptic function, and mitigates memory deficits in an AD model, she says. These results have identified Sgk1 as a potential key target for therapeutic intervention of AD, which may have specific and precise effects.

Yans UB co-authors are Qing Cao, postdoctoral fellow and first author; Wei Wang, research scientist; Jamal Williams, a doctoral candidate in UBs neuroscience program; Fengwei Yang, bioinformatics specialist; and Zi Jun Wang, postdoctoral fellow.

Funding for the research came from Yans grants from the National Institute on Aging of the National Institutes of Health.

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UB study finds memory deficits resulting from epigenetic changes in Alzheimer's disease can be reversed - UB Now: News and views for UB faculty and...

Physiology

Technology a Key for Assessing Couples and Improving Therapy – Psych Congress Network

During a keynote session presented on Wednesday at the Evolution of Psychotherapy virtual event, John Gottman, PhD, and Julie Gottman, PhD, co-creators of the Gottman Institute shared with attendees how they have used technology not only to better assess the problems that are causing couples to seek therapy, but to also help them address and overcome those issues.

The Gottman Institute conducted an international study of more than 40,000 couplesincluding heterosexual, gay, lesbian and other coupleswho were entering therapy. Questions in the survey covered 10 areas:

Participant answers were fed into research-based algorithms and a summary of outcomes was generated. Findings from the study were published in the Journal of Marital and Family Therapy. What the Gottmans found in their research was nearly all couples are having serious problems around conflict (particularly with regards to criticism, defensiveness, contempt and stonewalling), trauma stemming from individuals primary family growing up (especially among gay and lesbian couples) is often a trigger for conflict, and overall, more powerful intervention tools are needed, especially during the COVID-19 pandemic.

To that end, Dr. John Gottman said, the institute created Gottman Connect, a telehealth platform that connects couples to a therapist either together at home or from separate locations. The telehealth intervention starts with an assessment, which is a step often skipped by many therapists, often because they dont know what to assess or how to conduct an assessment or they feel assessments can be intimidating for clients, Dr. John Gottman said. With the Connect platform, however, the institute has found couples enjoy quizzes, assessment is expected and adds credibility among clients, plus it gives direction and focus for therapy. Assessments pinpoint strengths and challenges of relationships, plus co-morbidities. The platforms Love Lab component reveals interaction dynamics within a couple and measure physiology.

Ultimately, the platform generates two reports: One for the therapist and one for the couple. The clinicians report includes essential co-morbidities and detailed treatment recommendations. The couples report includes relationship-level information and can be used in feedback sessions.

Dr. Julie Gottman then highlighted six intervention tools also included within the platform that can.

The point of all of the interventions is that they empower the therapists of any orientation, she said. There are many tools on this platform, but whatever orientation you bring into the session is honored as the central part of the therapy. These interventions can serve as supplements or, if you like, the main part of therapy.

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Technology a Key for Assessing Couples and Improving Therapy - Psych Congress Network

Physiology

Skin-interfaced microfluidic system with personalized sweating rate and sweat chloride analytics for sports science applications – Science Advances

Abstract

Advanced capabilities in noninvasive, in situ monitoring of sweating rate and sweat electrolyte losses could enable real-time personalized fluid-electrolyte intake recommendations. Established sweat analysis techniques using absorbent patches require post-collection harvesting and benchtop analysis of sweat and are thus impractical for ambulatory use. Here, we introduce a skin-interfaced wearable microfluidic device and smartphone image processing platform that enable analysis of regional sweating rate and sweat chloride concentration ([Cl]). Systematic studies (n = 312 athletes) establish significant correlations for regional sweating rate and sweat [Cl] in a controlled environment and during competitive sports under varying environmental conditions. The regional sweating rate and sweat [Cl] results serve as inputs to algorithms implemented on a smartphone software application that predicts whole-body sweating rate and sweat [Cl]. This low-cost wearable sensing approach could improve the accessibility of physiological insights available to sports scientists, practitioners, and athletes to inform hydration strategies in real-world ambulatory settings.

Advances in materials science, mechanics design, and miniaturized electronics serve as the foundations for emerging classes of thin, soft skin-interfaced devices for multifunctional sensing of physiological status and processes (1, 2). Biochemical analysis of sweat in situ represents a promising pathway for enabling intermittent and continuous monitoring of sweat loss and composition, which is important for maintaining proper hydration and electrolyte balance, particularly in athletic contexts (3). Precise, real-time measurements of sweat dynamics (i.e., local sweating rate and local total sweat volume) and sweat biomarkers require wearable chemical systems capable of continuous capture and analysis of sweat and transmission of the resulting information locally to the user or remotely to health professionals (4, 5). A critical requirement for the broad adoption of such wearable systems is in the ability to reliably collect and measure analytes with minimal contamination. Conventional technologies for sweat collection have relied on absorbent pads, gauzes, and centrifuge systems, with the need for external laboratory instruments for analysis. These approaches support basic performance and physiology studies within controlled laboratory settings, but they are not suitable for real-time and ambulatory deployments.

The specific focus of the current work is on human performance and athletics, where body fluid and electrolyte deficits accrued through sweat loss during physical activity and heat stress increase cardiovascular strain, which, in turn, could lead to impairment of physical and cognitive performance (610). Because of the considerable variation in sweating rate (~0.5 to 3 liters/hour) and sweat electrolyte concentrations [sodium ([Na+]) and chloride ([Cl]) ~10 to 100 mM] (11, 12), personalized fluid replacement strategies based on individual sweat profiles are recommended (9, 13). Whole-body sweat loss is typically estimated via the measurement of change in body mass before and after exercise while also accounting for any fluid intake and/or urine loss during the test session. The reference technique for whole-body measurement of sweat electrolyte concentrations is the washdown procedure (1416). Such approaches are lengthy, retrospective, and require athlete and practitioner adherence to tight quality control procedures. Thus, there has been recent interest in regional techniques to estimate whole-body sweating rate and electrolyte loss. Still, assessing sweat profiles using established regional sweat collection and analysis techniques is a slow, labor-intensive process and impractical for ambulatory use. For example, hygrometry is considered the gold standard technique for measuring regional sweating rate, but ventilated sweat capsules require specialized, wired equipment, and controlled laboratory conditions (16). Furthermore, established gravimetric-based techniques such as filter paper, sweat pouches, and plastic sweat collectors are not conducive to real-world applications such as on-field sports training (16). While the absorbent patch technique has been widely used with athletes to measure sweat electrolyte concentrations (11, 1719), the required post-collection harvesting and expensive benchtop analysis of sweat is impractical for the general population and precludes real-time feedback to the wearer.

The accurate measurement of sweat dynamics requires the effective isolation of sweat from the skin and the surrounding environment to seal the sweat from contaminants. Skin-like, lab-on-a-chip microfluidic platforms are, therefore, of particular interest, because of their ability to collect, route, and chemically analyze precise, microliter volumetric samples of sweat released from well-defined regions of the skin. The integration of microfluidics directly with the surface of the skin supports many important operations in fluidic manipulation of sweat for precise capture, storage, volumetric measurement, and chemical analysis. The development of wearable systems that can monitor biomarkers in situ via electrochemical sensors represents a promising pathway for continuous monitoring of sweat, whereby sweat is routed to sensing electrodes that interface to recording electronics, power supply systems, and radio communication hardware (4, 2024). Colorimetric biochemical sensors provide a unique set of advantages in this context including methods of multianalyte analysis (5), hybrid operation (23), and time-correlated sampling (25, 26) all in low-cost (27) and waterproof form factors (28). A key feature of colorimetric sensing is a readout mode that provides data directly to the user or study administrator via the naked eye or quantitatively via image capture with a smartphone after calibrating for environmental lighting conditions (29). A set of additional technical requirements for wearable sweat sensors involves the use of physical designs, which align with conventional manufacturing workflows. Roll-to-roll manufacture is one option (30) and has been used in a pilot study for sweat monitoring of 40 subjects (20). However, the utility of wearable sweat sensors to track sweating rate and sweat electrolyte loss has yet to be demonstrated in a large, diverse cohort in uncontrolled environments.

The primary objective of this work was to determine the clinical validity of a roll-to-roll manufacturable, skin-interfaced wearable microfluidic device with colorimetric sensors and a smartphone image processing platform in measuring regional sweating rate and sweat [Cl]. The absorbent sweat patch technique was used as the reference method since it has been established as a reliable measure of regional sweating rate and sweat [Cl] and is the well-accepted method for individualized sweat electrolyte testing in the field (16). Another objective of this study was to develop algorithms to predict whole-body sweating rate and whole-body sweat [Cl] in a large clinical study (312 athletes), which is an important step in using skin-interfaced wearable microfluidic devices to help determine individualized fluid-electrolyte replacement needs.

The wearable microfluidic patch technology introduced here involves multilayered stacks of thin-film polymers that contain intricate microfluidic channels created using laser and die cutting techniques. The network of microchannels and assay wells are created using roll-to-roll processing of polymeric rolls of materials, allowing for rapid (~1000 patches/min) and low-cost manufacturing of soft conformal microfluidic constructs, as an alternative to silicone-based mold casting techniques. The microfluidic channels are composed of hydrophobic polymeric materials that route sweat by exploiting the natural pressure associated with eccrine sweat excretion. Figure 1A shows the multilayered microfluidics, dye and bioassay reservoirs, the top graphics layer with color reference stripes, and a subjacent skin adhesive layer, which collectively define the low-modulus features of the flexible sticker-like patch. Microchannel 1 has the capacity to collect ~130 l of sweat from a defined sweat collection region (38.5 mm2 and 7 mm diameter). An orange dye mixes with sweat to make propagation along the channel highly visible, allowing rapid assessment and measurement of sweat volume (Fig. 1A, inset). In contrast, microchannel 2 has a smaller capacity (~30 l) and collection area (12.6 mm2 and 4 mm diameter) designed to support a colorimetric reaction between excreted sweat entering the microchannel and deposited chemical reagents for analysis of [Cl]. Figure 1B shows a representative example of the microfluidic patch (without the top graphics layer) skin-mounted on the ventral forearm before exercise begins. During exercise, microchannels 1 and 2 capture and mix sweat as shown in Fig. 1C. The spatial extent of orange sweat capture in microchannel 1 and the purple color intensity in microchannel 2 provide a measure of local sweat excretion volume and sweat [Cl], respectively. Figure 1D shows an optical image of the microfluidic patch on another subject with defined vein contours on the ventral forearm. The microfluidic patch intimately conforms to the surface of the skin without causing irritation around curvilinear regions or in the presence of heavy sweat excretion. The thin geometry (~680 m) and low bending stiffness of the device support mechanical deformations (Fig. 1E), aiding wearability during intense physical activities.

(A) Exploded view illustration of microfluidic patch and its subassembly layers. (Insets) Magnified images of the reference colors in the top graphics layer (top) and deposited assays in the embedded layer (bottom). (B) Optical image of microfluidic patch on the ventral forearm before exercise (unfilled) (scale bar, 1 cm). (C) Optical image of microfluidic patch showing sweat filling in microchannels 1 and 2 (scale bar, 1 cm). (D) Optical image of microfluidic patch (zoom-out view) showing the device filling as sweat is excreted on the forearm. (E) Optical images of microfluidic patch under slight bending (left) and extreme bending (right) (scale bar, 1 cm). (F) Optical image of a cyclist wearing a microfluidic patch and an absorbent patch on opposing arms during exercise on a stationary bicycle in controlled laboratory environment. (G) Close-up image of a microfluidic patch and an absorbent patch taken during exercise. (H to K) Optical images of subjects wearing a microfluidic patch and an absorbent patch during different sports (basketball, soccer, track and field, and tennis) under uncontrolled environmental conditions. Photo credit: Stephen Lee, Epicore Biosystems.

The colorimetric sensing strategy used in the microfluidic patch provides quantitative assessment of regional sweat loss, sweating rate, and sweat [Cl] in real-world settings. To characterize the accuracy of this sensing approach in demanding and intense exercise scenarios, the microfluidic patch performance was assessed in comparison to conventional sweat analysis techniques using absorbent patches for collection of sweat and subsequent benchtop gravimetry (for sweat volume) and ion chromatography (for sweat [Cl]) techniques. Figure 1F shows a subject exercising on a cycle ergometer while instrumented with a microfluidic patch (left forearm) and absorbent patch (right forearm). The magnified image of the forearms in Fig. 1G highlights the visual nature of the microfluidic patch compared to the absorbent patch. In addition to controlled activities in a laboratory, microfluidic patch performance was compared with absorbent patches in uncontrolled environments and across different physically demanding sports, including lacrosse, basketball (Fig. 1H), soccer (Fig. 1I), track and field (Fig. 1J), and tennis (Fig. 1K).

Digital image capture and analysis with a smartphone enable simple and rapid assessment of instantaneous sweating rate and sweat [Cl] from the microfluidic patch in ambulatory settings. Custom software uses the smartphone camera to capture and analyze the microfluidic patch as shown in Fig. 2A. This technique enables detection of the microfluidic patch boundary in the image frame, as well as the positions of the microchannels and reference color markers (Fig. 2B). The reference color markers allow ambient light correction and white balancing in real time, thereby eliminating the effects of variable lighting conditions (e.g., daylight, shadows, and cloudy environments). Upon recognition of the microfluidic patch landmarks, the software application detects the orange color in microchannel 1 and computes collected sweat volume based on the spatial distribution of the orange color and the three-dimensional patch geometry (Fig. 2C). Following correction of the measured colors using the reference markers, the intensity of the purple color in microchannel 2 is measured in CIELAB color space relative to the patch background across multiple regions of interest (Fig. 2, D and E). Light absorption varies monotonically with the concentration of the colorimetric assay according to the Beer-Lambert law. Since this concentration, in turn, is proportional to [Cl] of collected sweat, [Cl] can be estimated from the color intensity. This technique measures local sweat volume and sweat [Cl] with a resolution of 0.01 L and 0.1 mM, respectively.

(A) Person photographing the patch on users arm with the smartphone application. (B) Automated detection of patch boundaries and critical features. Colored outlines denote boundaries of detected patch features. (C) Image is mapped to known patch shape for volume measurement. (D) Measured CIELAB colors for the chloride channel (blue), nearby patch background (red), and difference after color correction (purple). The purple line shows the vector of the expected color difference. The gray lines show the effect of color correction on the center four grid boxes. (E) Color vector length maps monotonically to chloride concentration (average vector length from Fig. 2D is denoted in red). Photo credit: Alexander J. Aranyosi, Epicore Biosystems.

To test the accuracy of the microfluidic patch and the accompanying software, the microfluidic patch and absorbent patches were used to measure regional sweating rate (Fig. 3A) and sweat [Cl] (Fig. 3B) from competitive athletes during on-field/court sports training under varied environmental and ambient lighting conditions (n = 43 subjects). Microfluidic patch results were significantly correlated with absorbent patch data for both regional sweating rate (r = 0.83, P < 0.0001) and sweat [Cl] (r = 0.84, P < 0.001). When the outlier data point with a high regional sweating rate and high regional sweat [Cl] is removed from Fig. 3 (A and B), the Pearson correlations remain statistically significant (r = 0.73 and r = 0.82, respectively; P < 0.001). While the microfluidic patch sweating rate was higher than that of the absorbent patch (1.42 0.60 versus 1.04 0.33 mg/cm2 per minute, P < 0.0001), there was no difference in sweat [Cl] between the microfluidic and absorbent patches (21.4 14.1 versus 20.0 12.4 mM, P = 0.11). The strong correlation between the microfluidic and absorbent patches, which represent two different methodologies, demonstrates the robustness of the microfluidic patch across a diverse group of athletes.

(A) Regional sweating rate measurements and (B) regional sweat chloride concentration under varying environmental and ambient lighting conditions (n = 43 subjects). Assumptions for homogeneity of variance of the absorbent patch sweat chloride concentration were not met (B). Therefore, the inset of (B) shows the scatterplot and correlation analysis results of raw microfluidic sweat chloride concentration versus log-transformed absorbent patch sweat chloride concentration. Note that when the outlier data point with a high regional sweating rate and high regional sweat [Cl] is removed from (A) and (B), the Pearson correlations remain statistically significant (r = 0.73 and r = 0.82, respectively; P < 0.001).

There were originally 55 participants in this study. Data from one subject were excluded because the absorbent patch was on the skin too long and became oversaturated. Eleven subjects data (20%) were excluded from analysis because of the following microfluidic device failures: (i) Sweat did not advance far enough in microchannel 2 by the end of exercise (n = 5), (ii) the patch delaminated or fell off (n = 4), or (iii) clouding or backflow in microchannel 1 occurred likely from physical impact to the patch during training (n = 2). Therefore, the final dataset was n = 43 (fig. S1).

To examine the relation between regional and whole-body sweat, subjects wore microfluidic patches and absorbent patches in a controlled laboratory environment where whole-body sweat measurements were also collected. Microfluidic patch results (n = 45 subjects) were significantly correlated with the absorbent patch for both regional sweating rate (r = 0.90, P < 0.0001; Fig. 4A) and sweat [Cl] (r = 0.93, P < 0.0001; Fig. 4B). Microfluidic patch sweating rate was significantly higher than that of the absorbent patch (1.99 1.22 versus 1.55 0.68 mg/cm2 per minute, P < 0.0001), as was observed in on-field/court sports (Fig. 3). There was no difference in sweat [Cl] between the microfluidic and absorbent patches (37.8 23.3 versus 36.7 23.7 mM, P = 0.32).

(A) Regional sweating rate data and (B) regional sweat chloride concentration measured during cycling on a stationary bicycle (n = 45 subjects).

Figure 5 (A and B) shows scatterplots of microfluidic regional sweating rate versus whole-body sweating rate under controlled laboratory conditions (n = 45 subjects). Whole-body sweating rate data are expressed in body surface areanormalized (milligrams per square centimeter per minute, r = 0.71, P < 0.0001; Fig. 5A) and absolute (liters per hour, r = 0.73, P < 0.0001; Fig. 5B) values. Means SD body surface areanormalized whole-body sweating rate was 0.82 0.22 mg/cm2 per minute, and absolute sweating rate was 0.95 0.32 liters/hour. When the outlier data point with a high microfluidic patch sweating rate is removed from Fig. 5 (A and B), the Pearson correlation results remain statistically significant (r = 0.70 and r = 0.71, respectively; P < 0.0001).

(A) Microfluidic regional versus whole-body sweating rate, expressed relative to body surface area (milligrams per square centimeter per minute). (B) Microfluidic regional versus whole-body sweating rate, with whole-body sweating rate expressed in absolute terms (liters per hour). (C) Microfluidic regional sweat chloride concentration versus whole-body sweat chloride concentration. (D) Whole-body sweat chloride concentration versus whole-body sweat sodium concentration. (E) Whole-body sweat chloride concentration model showing predicted versus measured whole-body sweat chloride concentration. (F) Metrics for the model predicting whole-body sweat chloride concentration from microfluidic sweat chloride concentration. Note that when the outlier data point with a high microfluidic patch sweating rate is removed from (A) and (B), the Pearson correlation results remain statistically significant (r = 0.70 and r = 0.71, respectively; P < 0.0001).

The results shown in Fig. 5 (A and B) suggest that the correlation between microfluidic and whole-body sweating rate is similar regardless of whether or not the data are normalized to body surface area. Therefore, all whole-body sweating rate models hereafter are focused on the prediction of sweating rate in absolute terms (liters per hour) for ease of practical interpretation.

Figure 5C includes a scatterplot of microfluidic regional sweat [Cl] versus whole-body sweat [Cl] under controlled laboratory conditions (n = 45 subjects: r = 0.93, P < 0.0001). A scatterplot of whole-body sweat [Cl] versus whole-body sweat [Na+] under controlled laboratory conditions (n = 45 subjects: r = 0.99, P < 0.0001) is shown in Fig. 5D. Whole-body sweat [Cl] was 41.3 16.5 mM (means SD), and whole-body sweat [Na+] was 41.8 15.5 mM. Establishing the relation between whole-body sweat [Cl] and [Na+] is relevant because published recommendations for electrolyte replacement are based on sweat Na+ losses (9, 13). The results suggest that there is a strong relation between whole-body sweat [Cl] and [Na+] [r2 = 0.98, concordance correlation coefficient (CCC) = 0.99, mean absolute agreement (MAE) = 2 mM, and root mean square error (RMSE) = 2 mM]. Figure 5E shows predicted versus measured whole-body sweat [Cl] using the model established via the simple linear regression analysis (depicted in Fig. 5C). Prediction model metrics are also shown in Fig. 5F for whole-body sweat [Cl] (r2 = 0.86, CCC = 0.92, MAE = 5 mM, and RMSE = 6 mM).

In this study, there were originally 49 participants. Data from 4 subjects (8%) were excluded from analysis because sweat did not advance far enough in the microfluidic patch channel 2 by the end of exercise (n = 3) or the microfluidic patch delaminated (n = 1). Therefore, the final dataset was n = 45 (fig. S2).

Reliability of the microfluidic and absorbent patch methods for measuring regional sweating rate and sweat [Cl] under controlled laboratory conditions (n = 12) are shown in Table 1. Coefficients of variation (CVs) were similar between methods for sweating rate (CV = 9% for both methods) and sweat [Cl] (microfluidic CV = 12% and absorbent patch CV = 13%). Whole-body sweating rate was not different between days (1.07 0.50 and 1.09 0.49 liters/hour, P = 0.47), and the CV was 4%.

A model was derived to predict whole-body sweating rate from microfluidic regional sweating rate data in recreational to competitive athletes (n = 312) of various team and individual sports tested under a range of environmental conditions (Fig. 6). Inputs to the model included microfluidic regional sweating rate and various factors related to subject characteristics (body mass and sex), environment (air temperature), and exercise conditions (type of sport, energy expenditure, and exercise duration). Figure 6A shows results with the model that includes all seven input factors (r2 = 0.74, CCC = 0.85, MAE = 0.13 liters/hour, and RMSE = 0.18 liters/hour). Figure 6B shows results for a six-factor model (all inputs except energy expenditure) (r2 = 0.63, CCC = 0.77, MAE = 0.16 liters/hour, and RMSE = 0.21 liters/hour). In this study, means SD microfluidic sweating rate was 1.25 0.79 mg/cm2 per minute, and whole-body sweating rate was 0.92 0.33 liters/hour.

(A) Whole-body sweating rate results with a seven-factor model including microfluidic regional sweating rate, body mass, sex, air temperature, type of sport, exercise duration, and energy expenditure (n = 312 subjects) across various team and individual sports. (B) Whole-body sweating rate results with a six-factor model including all of the above except energy expenditure (n = 312 subjects).

There were originally 346 participants in this study. Eleven subjects data were excluded because of equipment issues in obtaining energy expenditure in the field. Data from 23 subjects (7%) were excluded from analysis because of the following microfluidic patch failures: (i) Sweat did not advance far enough in microchannel 2 by the end of exercise (n = 9), (ii) the patch delaminated or fell off (n = 10), or (iii) backflow in microchannel 1 likely from physical impact to the patch during training (n = 4). Therefore, the final dataset was n = 312 (fig. S3).

Systematic studies were conducted to compare the wearable microfluidic platform with standard techniques for sweat testing. The main finding was that regional sweating rate and sweat [Cl] data from the microfluidic patch were significantly correlated with those of the standard absorbent patch technique during ~90 min of exercise under varying environmental and ambient lighting conditions. Furthermore, we investigated the test-retest (day-to-day) reliability of the microfluidic device, which is a requisite step in any methodological validation process. The CVs for the microfluidic device were similar to that of the reference techniques for both sweating rate (9%) and sweat [Cl] (12 to 13%) in the present study. These CVs were also consistent with previous research investigating day-to-day variability in forearm sweating rate and electrolyte concentrations (12, 16). This work improves upon previous feasibility studies with similar devices (5) and advances the field by demonstrating validation in hundreds of athletes (n = 312), not only in a controlled setting but also in competitive athletes during live on-field/court training for several sports.

Actionable hydration feedback from the microfluidic patch requires estimating whole-body sweating rate and sweat [Cl] from the regional measurements. To this end, robust models based on microfluidic patch results and other available information were developed for implementation into a smartphone application. The good agreement between predicted and measured whole-body sweating rate (r2 = 0.74, CCC = 0.85) and sweat [Cl] (r2 = 0.86, CCC = 0.92) provides additional validation of microfluidic patch measurements and enables personalized fluid-electrolyte intake recommendations for athletes (12). Results suggest that the mean absolute error of the prediction models are 0.13 liters/hour (or 14%) for whole-body sweating rate and 5 mmol (or 13%) for whole-body sweat [Cl].

Figure 7 presents a schematic flow of the system operation that uses the wearable microfluidic platform in combination with a smartphone application to determine sweat profile results and personalized hydration recommendations. This system improves on time-intensive and laborious conventional sweat analysis methods and consists of (i) placement of a soft microfluidic patch on an easily accessible area of the body (left ventral forearm), (ii) passive sweat collection and reaction with colorimetric assays, (iii) image capture of colorimetric responses with a smartphone, (iv) image analysis via computer vision and application of predictive algorithms, (v) generation of sweat profiles, and (vi) development of personalized hydration strategies for (vii) optimizing post-workout rehydration and fluid intake during future exercise sessions.

(A) The user applies the sweat patch on their left ventral forearm after cleaning and drying the skin surface. (B) Passive sweat collection and reaction with the colorimetric assays as the athlete completes their workout. (C) After exercise, the user takes an image of the patch via the smartphone application. (D) The application processes the patch results, pulls in other inputs (body mass and sex from the users profile, type of sport, exercise duration, weather data, and energy expenditure), and applies algorithms. (E) Sweat profile results, including whole-body sweating rate, whole-body sweat loss, and whole-body sweat sodium loss, are displayed on the screen (example shown is for a 90-min session). (F) Personalized fluid intake recommendations are provided on the basis of the users sweat profile. (G) User follows recommendations to properly rehydrate immediately after workout and properly hydrate during their next workout of similar intensity, duration, and environment.

To standardize testing across the large population of subjects and multiple trials, we used a set of best practices developed for the microfluidic patch that were applicable to both controlled laboratory and uncontrolled environments. For adequate adhesion of the microfluidic patch to the skin, it is critical that the skin is clean, free of skin-care products (lotions, sunscreen, etc.), and dry before device application. In addition, while we successfully tested athletes in the field (trials 1 and 3) without having to shave the patch site, it is prudent for individuals with high hair follicle density on their ventral forearm to shave the area before patch application. While wearing the patch, the user is instructed to avoid physically probing the microfluidic channels (e.g., from towel drying the skin) or peeling the patch from the skin (e.g., contact sports), which could lead to device failures.

Future research is needed to corroborate the validity of the microfluidic sweat patch and broaden its utility even further. As noted above, the microfluidic patch could not measure sweat [Cl] in a small percentage of subjects (<10%) because sweat did not advance far enough in microchannel 2 to initiate the colorimetric reaction. Research is planned to enlarge the collection area of future versions of the microfluidic patch to accommodate low sweat flow rates (0.4 mg/cm2 per minute). In addition, while the exercise duration in the present studies (up to ~1.5 to 2 hours) was representative of typical workouts by recreational and trained athletes (e.g., running for fitness or training, team sport practice for soccer, basketball, etc.), the results may not be applicable to endurance events lasting longer than 1.5 to 2 hours. Therefore, future research with a focus on longer duration testing is needed to confirm the validity of the microfluidic patch during exercise that extends beyond 1.5 to 2 hours. Other potential avenues of future research with this device include validation and algorithm development for patch application to the right forearm and other regions of the body and for a broader range of environmental conditions and additional types of sports/physical activities.

In conclusion, the microfluidic patch enables real-time assessment of sweating rate and sweat [Cl] under field conditions with no need for specialized expertise or laboratory tools. Collection of sweating rate and sweat electrolyte loss data using this low-cost wearable sensing approach could improve the accessibility of physiological insights available to sports scientists, practitioners, and athletes to inform hydration strategies in real-world settings, with applications not only in athletic performance and fitness but also in military readiness and clinical medicine.

A series of trials was carried out to compare the wearable microfluidic platform with standard techniques for sweat testing. The objective of trial 1 was to compare the microfluidic patch and absorbent patch results for regional sweating rate and sweat [Cl] during on-field/court sports training. In trial 2a, the objectives were (i) to compare the microfluidic patch and absorbent patch results for regional sweating rate and sweat [Cl] and (ii) to determine the relation between the microfluidic patch and whole-body sweating rate and sweat [Cl]. The objective of trial 2b was to determine the day-to-day CV of the microfluidic patch in measuring regional sweating rate and sweat [Cl]. Last, in trial 3, the objective was to develop a whole-body sweating rate predictive model.

This research (clinical trial identifier: NCT04240951) was approved by the Sterling Institutional Review Board (IRB) (Atlanta, GA) for the protection of human study participants (Sterling IRB ID: 6004). Each participant and his/her parent or guardian (for subjects under 18 years) were informed of the experimental procedures and associated risks before providing written informed consent. Figures S1 to S3 show the CONSORT flow diagrams for study enrollment, participant exclusion, and data exclusion details for trials 1, 2, and 3, respectively. In total, data from 312 subjects (194 males and 118 females; 15 to 45 years) were analyzed. Participants ranged from recreationally active to highly trained athletes competing in individual or team sports. Table S1 provides summary data of subject characteristics for each trial.

Standard laser and die cutting techniques, which support roll-to-roll manufacturing processes, enabled fabrication of wearable microfluidic devices. Briefly, a five-layer stack of thin-film elastic polymers formed the microfluidic channels, the top graphics layer, and patterned skin adhesive layer. Pressure-sensitive adhesive served as the intermediate to bond the individual layers together. Inlet windows and windows in the adhesive layer created openings to define the two sweat collection regions interfacing with the skin. For colorimetric analysis, a dehydrated colored dye (~4 l) was deposited in microchannel 1 to measure regional sweat volume and sweating rate. The dye dissolves into sweat as it passes, creating an orange streak whose front can be measured to determine collected sweat volume. Microchannel 2 was prepared with a Cl-sensitive bioassay consisting of a 5-l volume of a mixture of silver chloranilate and polyhydroxyethylmethacrylate (pHEMA; Sigma-Aldrich, MO, USA) in methanol (2%, w/v) placed near the inlet region of the microchannel for Cl detection. The pHEMA creates a hydrogel that stabilizes the insoluble silver chloranilate. As sweat passes through the hydrogel, the Cl reacts with silver chloranilate to produce silver chloride, which precipitates out, and soluble chloranilic acid is carried with the sweat and produces a purple color with a concentration-dependent intensity.

Photos of microfluidic patches were captured using a smartphone (iPhone 8, Apple Inc.) and digital single-lens reflex (DSLR) camera (EOS 6D, Canon Inc.). Images were captured at the time of absorbent patch removal, at the end of exercise, and wherever possible at earlier times during exercise. RAW images were used for processing to eliminate artifacts introduced by normalization, compression, and other preprocessing steps. Traditional computer vision algorithms identified the locations of relevant features including the patch outline, color swatches, and filled regions of microchannel 1. Features on the graphics layer allowed patch orientation to be determined, after which the patch outline and filled regions of microchannel 1 were fed into a computational model of the patch to determine filled volume. Normalized sweating rate was computed from this volume, the collection area defined by the patch adhesive, and the elapsed time from exercise start to photo capture. The color swatches were used to derive a mapping from the image color space to a known color space for Cl measurement. The colors of regions along microchannel 2 and corresponding background regions alongside were measured and mapped to this known color space. The intensity of purple within microchannel 2 relative to the patch background was then used to determine [Cl]. These methods were validated by comparing them to measurements performed manually from the same images. Additional processing details are described in fig. S4.

Each trial applied the following methods for measuring regional sweating rate (trials 1, 2, and 3) and regional sweat [Cl] (trials 1 and 2). Sweat was collected from the right and left ventral forearms with an absorbent patch (Tegaderm+Pad, 3M, St. Paul, MN; pad size, 11.9 cm2) and the wearable microfluidic patch, respectively. This was deemed a fair comparison between methods since several previous studies have reported no significant bilateral differences in forearm sweating rate and sweat electrolyte concentrations (12, 3134). The CV between the left and right ventral forearms is ~12 to 13%, while the day-to-day CV in ventral forearm sweating rate and sweat [Cl] is ~9 to 13% (12).

Before patch application, the ventral forearms were rinsed with deionized water and wiped dry with electrolyte-free gauze (10 10 cm, Thermo Fisher Scientific, Waltham, MA). For optimal patch adhesion to the skin in the laboratory study (trial 2), the ventral forearms were also shaved if needed to remove hair (~20% of subjects). For ecological validity, the ventral forearms were not shaved in the field testing. However, during field testing, an elastic net dressing (Surgilast, Derma Sciences, Princeton, NJ) was put on the right forearm to ensure that the absorbent patch remained adhered to the skin. Absorbent patches were removed upon moderate sweat absorption but before saturation as determined by visual inspection (patch time on skin was 39 to 112 min for trial 1 and 12 to 71 min for trial 2). Upon removal, the absorbent pad was immediately separated from the Tegaderm using clean forceps and placed in an air-tight plastic tube (Sarstedt Salivette). Regional sweating rate (in milligrams per square centimeter per minute) was measured gravimetrically on the basis of the mass of sweat absorbed in the pad (to the nearest 0.001 g using an analytical balance; Mettler Toledo Balance XS204, Columbus, OH), the pad surface area, and the duration that the patch was on the skin. Sweat from the absorbent patch was extracted via centrifuge and subsequently analyzed for [Cl] in duplicate by ion chromatography (Dionex ICS-3000).

For trials 1, 2, and 3, whole-body sweating rate was calculated from the difference in pre- to post-exercise body mass, corrected for food/fluid intake, urine/stool loss, respiratory water loss, and weight loss due to substrate oxidation (35), divided by exercise duration. Whole-body sweat [Na+] and [Cl] were measured in trial 2a, and details of this methodology are described below. Recovery of electrolytes using the whole-body washdown procedures was measured during six mock trials using a 2-liter solution of artificial sweat. Recovery of Na+ and Cl was 102 to 103%, which suggests effective detection of electrolytes in the whole-body washdown collection system. The day-to-day CV for whole-body sweat [Na+] and [Cl] in this study (trial 2b) was 8 to 10%.

Additional experimental procedures for each trial are described below. Table S2 provides a summary of descriptive data related to the exercise conditions, environment, and physiological outcome measures in each trial. Experimental procedures for the reference techniques used to measure regional and whole-body sweating rate and sweat [Cl] have been described in more detail in previous publications (11, 12).

Trial 1. Sweat was collected with the microfluidic and absorbent patches from 43 subjects (15 males and 28 females; 17 1 year old; 64.3 10.4 kg) from five sports (tennis, soccer, lacrosse, basketball, and track and field) during on-the-field/court, coach-led training sessions (22 to 34C, 50 to 82% relative humidity). All sports were outdoors with the exception of basketball. Body mass was measured before and after exercise to the nearest 0.01 kg on a digital platform scale (Mettler Toledo ICS425s-BC300, Columbus, OH) while subjects wore minimal clothing (i.e., compression shorts/sports bra). Subjects were asked to towel dry before each body mass measurement. Subjects were allowed to consume water, a 6% carbohydrate-electrolyte solution, and sports nutrition products ad libitum during training. All drink bottles and nutrition products were massed before consumption, and the drink bottles and remaining food (or in many cases, the empty food wrapper) were massed after consumption (to the nearest 1 g; Ohaus CS2000, Pine Brook, NJ). When necessary, athletes urine loss during exercise was collected using a preweighed beaker/container and later massed (to the nearest 1 g; Ohaus CS2000, Pine Brook, NJ). Each participants energy expenditure during exercise was estimated using a Global Positioning System device (STATSports APEX Team Series, Newry, Ireland).

Trial 2a. Subjects cycled on an ergometer (Velotron SRAM, Pro, Chicago, IL) at moderate intensity [(159 43 W; 62 6% maximal oxygen uptake (VO2max); 82 5% maximal heart rate (HRmax)] for 90 min in a climate-controlled chamber (32C, 25 to 50% relative humidity). Heart rate was monitored using telemetry (Polar Electro RS400; Lake Success, NY), and power output (watts) and cadence were recorded every 10 min. Energy expenditure (kilocalorie) was calculated from the cycling work rate (36). Subjects were provided a commercially available 6% carbohydrate-electrolyte solution to drink ad libitum during exercise. Immediately before and after exercise, nude body mass was recorded using a digital platform scale (KCC300 platform and IND439 reader; Mettler Toledo, Columbus, OH) to the nearest 0.01 kg. Subjects were asked to towel dry before each body mass measurement.

The whole-body washdown method was used to determine sweat [Na+] and sweat [Cl] from the entire body (16, 37). Before exercise, subjects whole bodies were rinsed with 5.0 liters of deionized water using a compression sprayer (model 010PEXG, Gilmour, Somerset, PA) and then dried with electrolyte-free paper towels (Wypall L-40, Kimberly-Clark, Irving, TX). Next, subjects donned compression shorts/sport bra and a heart rate monitor that had been previously rinsed with deionized water to remove any electrolytes and air-dried. Subjects did not wear socks or shoes during the trial. During exercise, care was taken to avoid sweat drippage. Two front (lower body, 2.9 to 3.1 m/s and upper body, 2.3 to 3.0 m/s) fans and one rear (1.5 to 2.0 m/s) fan were used to promote evaporative cooling. Subjects were given an electrolyte-free paper towel to absorb sweat from their face, neck, front torso, and arms. While double-gloved, study investigators wiped the subjects back with an electrolyte-free paper towel to prevent dripping of sweat. The cycle ergometer seat and handlebars were covered with a plastic bag.

At the end of the 90 min of cycling exercise, the subjects stepped off the ergometer and directly into the washdown chamber that was positioned next to the cycle ergometer. The post-exercise washdown chamber consisted of a bale bag (Farm Bag Film Division, Glenford, OH) inside a steel frame (1.6 meters by 0.8 meters by 0.9 meters). The shorts/sport bra, heart rate monitor strap, and paper towels used to wipe the subjects sweat were hung to air dry. Next, the nude subject was rinsed thoroughly with deionized water (using a compression sprayer, N-80; Tabor Tools, Kibbutz Beit Rimon, Israel) to ensure removal of all sweat electrolytes from the skin and hair. Five liters of deionized water was prepared, of which a 200-ml sample was separated into aliquots for pre-rinse analysis, and the remaining 4.8 liters was used for rinsing the subject. After rinsing, the subject dried off with electrolyte-free paper towels and stepped out of the washdown chamber. The heart rate monitor and subjects shorts/sport bra and all paper towels, gauze, elastic netting, Tegaderm part of the patches, and investigators outer gloves that touched the subject during exercise were put in the bottom of the bale bag (with the post-rinse deionized water). After the contents collected at the bottom of the bale bag were thoroughly mixed, a post-rinse sample was collected for electrolyte analysis (via ion chromatography; Dionex ICS-3000) (37). Whole-body sweat [Na+] and [Cl] were determined from dilution calculations based on the measured [Na+] and [Cl] in the post-rinse solution, the known volume of deionized water added to the bale bag (4.8 liters), and sweat loss.

Trial 2b. A subset of 12 subjects (8 males and 4 females) in trial 2a completed two additional trials (under standardized conditions) 2 to 8 days apart (at the same time of day) to determine the day-to-day reliability of regional sweating rate and sweat [Cl] measured with the microfluidic patch and absorbent patch. To ensure consistency between trials, the subjects reported to the laboratory after abstaining from caffeine, alcohol, and vigorous exercise for 24 hours and food for 2 hours. In addition, subjects were asked to consume a consistent diet in the 48 hours preceding each trial and record all food and fluid intake in that time frame. Diets were analyzed using Nutribase Software (NB19Pro+, CyberSoft Inc.; Phoenix, AZ). Subjects were asked to drink 500 ml of water 2 hours before the trials. A urine sample was collected for the assessment of baseline urine specific gravity (USG; Atago Pen Refractometer, 3741-E03, Tokyo, Japan).

Subjects cycled on an ergometer (Velotron SRAM, Pro, Chicago, IL) at moderate intensity for 90 min in a climate-controlled chamber. Dietary analysis confirmed that energy (5404 2576 versus 5166 2303 kcal, P = 0.55), water (7.2 4.1 versus 7.2 3.5 liters, P = 0.99), and Na+ intake (7457 2915 versus 7082 2543 mg, P = 0.56) were consistent in the 48 hours leading up to each trial. There was no difference in baseline USG (1.013 0.010 versus 1.010 0.010, P = 0.21) or body mass (75.96 13.68 versus 75.88 13.76 kg, P = 0.77) between trials. All experimental procedures for measuring regional sweating rate, regional sweat [Cl], and whole-body sweating rate were the same as in trial 2a. Fluid intake during exercise (0.891 0.469 versus 0.890 0.473 liters, P = 0.85) and net fluid balance (1.18 0.93 versus 1.21 0.93%, P = 0.43) were consistent between trials. As expected, there were also no differences in absolute workload (160 45 versus 162 47 W, P = 0.21), relative intensity (63 5 versus 64 6% maximal oxygen uptake, P = 0.20; 82 5 versus 82 5% maximal heart rate, P = 0.38), or environmental conditions (32.0 0.1 versus 31.9 0.1C, P = 0.24; 51 1 versus 51 1% relative humidity, P = 0.12) between trials.

Trial 3. Microfluidic regional sweating rate and whole-body sweating rate were measured in 312 subjects (194 males and 118 females) to develop a whole-body sweating rate prediction equation. All subjects in trial 1 (n = 43) and trial 2 (n = 45) were included in this dataset. Data were collected in the field (n = 198) and laboratory (n = 114) in a variety of athletes (43 to 150 kg, 15 to 45 years) and environmental conditions (21 to 35C, 25 to 82% relative humidity, wind 0 to 7 m/s). In the field, energy expenditure was estimated using a Global Positioning System device (STATSports APEX Team Series). See tables S1 and S2 for more details. Experimental procedures in the field and laboratory were the same as described above for trials 1 and 2, respectively.

Analyses were carried out using Statistical Analysis Software version 9.4 (SAS Institute, Cary, NC), Minitab 17 Statistical Software (Minitab, State College, PA), and JMP Pro version 15.1 (SAS Institute, Cary, NC). The significance level for all statistical tests was set at = 0.05. Shapiro-Wilk tests were conducted to assess normality of the data, and Levenes tests were used to assess homogeneity of variance. Data are shown as means SD. Paired t tests were used to determine mean differences between microfluidic and absorbent patch measures of regional sweating rate and sweat [Cl]. To determine the intramethod test-retest reliability, paired-sample t tests and CVs were used.

Pearson product-moment correlations were conducted to determine the relations between the microfluidic patch and absorbent patch and between regional and whole-body measures of sweating rate and sweat [Cl]. In instances of deviation from normality or homogeneity of variance, data were natural log-transformed to meet assumptions before analyses (Fig. 3B). Where natural log transformation did not resolve deviation from normal distribution, nonparametric Spearman correlation analysis was conducted (Fig. 4B).

Multiple regressions with diagnostic tests on residuals were used to develop prediction models for whole-body sweat [Cl] and whole-body sweating rate. The prediction strength of regression models was assessed via coefficients of determination (r2) (38). Quantitative agreement between predicted and measured was assessed using the CCC, which measures the degree of departure between x-axis and y-axis values relative to perfect concordance, or the line of identity (39). A CCC > 0.80 is considered very good agreement (40). Prediction model error was quantified using mean absolute error, mean absolute percentage error, and RMSE.

ACSM, ACSMs Guidelines for Exercise Testing and Prescription (Lippincott Williams & Wilkins, ed. 9, 2014), 456 pp.

J. R. Thomas, J. K. Nelson, Measuring research variables, in Research Methods in Physical Activity, J. R. Thomas, J. K. Nelson, Eds. (Human Kinetics, ed. 4, 2001), pp. 181200.

Acknowledgments: We thank the following for assistance with data collection: R. Reale, K. Dalrymple, M. King, K. Luhrs, and B. Sopena. We thank P. De Chavez and S. Qu for statistical analysis support and J. Stofan for support with study conceptualization and supervision. We also thank S. Chen for benchtop testing of sweat microfluidic patches. Funding: This study was funded by the Gatorade Sports Science Institute, a division of PepsiCo Inc. The views expressed in this manuscript are those of the authors and do not necessarily reflect the position or policy of PepsiCo Inc. We also acknowledge funding support provided by the Querrey Simpson Institute for Bioelectronics at Northwestern University. Author contributions: Study conceptualization: L.B.B., J.M.C., J.A.R., and R.G.; methodology: L.B.B., K.A.B., A.J.R., C.T.U., T.J.R., J.B.M., A.J.A., S.P.L., and R.G.; data collection: K.A.B., K.A.L., M.L.A., S.D.B., A.J.R., R.P.N., J.L.B., T.J.R., A.J.A., M.S.S., and W.L.; data curation: L.B.B.; formal analysis: L.B.B.; project administration: L.B.B.; supervision: J.M.C.; writingoriginal draft preparation: L.B.B., J.T.R., J.A.R., and R.G.; writingreview and editing: J.A.R., J.T.R., and J.M.C.; manuscript visualization/data presentation: L.B.B., J.B.M., A.J.A., M.S.S., S.P.L., and W.L. Competing interests: L.B.B., K.A.B., K.A.L., M.L.A., S.D.B., A.J.R., R.P.N., J.L.B., C.T.U., and J.M.C. are employed by PepsiCo R&D. T.J.R. was an employee of PepsiCo R&D at the time of data collection and is now with Therabody. R.G., S.P.L., A.J.A., M.S.S., J.B.M., W.L., and J.A.R. are cofounders and/or employees of Epicore Biosystems Inc., a company that develops epidermal microfluidic devices. The views expressed in this manuscript are those of the authors and do not necessarily reflect the position or policy of PepsiCo Inc. J.A.R. is an inventor on a patent related to this work filed by the University of Illinois (no. 10736551, filed 11 August 2015, published 11 August 2020). J.A.R. is an inventor on a patent related to this work filed by Northwestern University (no. 10653342, filed 17 June 2016, published 19 May 2020). J.B.M., S.P.L., A.J.A., and R.G. are inventors on a patent application related to this work filed by Epicore Biosystems Inc. (PCT/US18/43430, filed 25 July 2017, published 24 July 2018). The authors declare that they have no other competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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Skin-interfaced microfluidic system with personalized sweating rate and sweat chloride analytics for sports science applications - Science Advances

Physiology

Five Johns Hopkins faculty named to National Academy of Inventors – The Hub at Johns Hopkins

ByHub staff report

Five Johns Hopkins faculty members have been elected as fellows of the National Academy of Inventors, a prestigious distinction that recognizes and honors the creators or co-developers of outstanding inventions that have made a difference in society. These professors join the more than 4,000 current fellows of the academy, which features members of more than 250 institutions worldwide.

The honorees from Johns Hopkins are:

Ramalingam Chellappa, who joined the Hopkins Department of Biomedical Engineering and the Department of Electrical and Computer Engineering as a Bloomberg Distinguished Professor earlier this year. Chellappa's work has shaped the field of facial recognition technology, and he is known as an expert in machine learning. At Hopkins he contributes to the Mathematical Institute for Data Science and the Center for Imaging Science.

Valina Dawson, a professor of neurology, neuroscience, and physiology in the School of Medicine, and co-director of the Neuroregeneration and Stem Cell Programs in the Institute for Cell Engineering. The lab aims to discover and describe the cell signaling pathways that contribute to neuron survival and death in Parkinson's disease and strokes. In her work, Dawson has discovered new therapies to treat neurological disorders, and established new neurological targets for patients' recovery processes.

Sharon Gerecht, professor of chemical and biomolecular engineering, and director of the Johns Hopkins Institute for NanoBioTechnology. Gerecht is an internationally recognized expert in vascular and stem cell biology and a member of the National Academy of Medicine. Together with her research group, she studies the interactions between stem cells and their microenvironments with the long-term goal of engineering artificial cell microenvironments.

Carol Greider, a professor in the Department of Molecular Biology and Genetics. In 2009, Grieder shared the Nobel Prize in Physiology or Medicine with Elizabeth Blackburn and Jack Szostak for their work on telomeres and telomerase, an enzyme that maintains protective "caps" on the ends of chromosomes. She studies the roles these enzymes play in cancer and age-related degenerative disease.

Nitish Thakor, a professor in the Department of Biomedical Engineering. Thakor conducts research on neurological instrumentation, biomedical signal processing, micro and nanotechnologies, neural prosthesis, and neural and rehabilitation techniques. Director of the Laboratory for Neuroengineering, Thakor also serves as director of the NIH Training Grant on Neuroengineering. Currently, he is developing a next-generation neurally controlled upper limb prosthesis alongside a multi-university consortium funded by DARPA.

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Five Johns Hopkins faculty named to National Academy of Inventors - The Hub at Johns Hopkins

Physiology

Emulate Announces Lung-Chip Technology Used by US Army to Study Effects of COVID-19 – PRNewswire

BOSTON, Dec. 8, 2020 /PRNewswire/ --Emulate, Inc., a leading provider of advanced in vitro models, today announced that its Alveolus Lung-Chip is being used by the U.S. Army to understand how the SARS-CoV-2 virus interacts with lung cells. With funding from the FY20 Coronavirus Aid, Relief, and Economic Security (CARES) Act, researchers at the U.S. Army Combat Capabilities Development Command (DEVCOM) Chemical Biological Center are using Emulate Lung-Chips to observe intracellular interactions and better understand the role of proteins within lung cells on disease processes.

Emulate Lung-Chip models recreate key aspects of pulmonary physiology by incorporating multiple primary cell types in distinct epithelial and vascular channels in a lung-specific dynamic microenvironment which can mimic tissue-to-tissue interactions, extracellular matrix, immune cell components and mechanical forces. They are ideal for studies looking at viral infection and pathogenesis and efficacy testing.

"In the past, the closest researchers could get to something like this was by introducing a virus into animals and then dissect them. With this, there is no need for animals in performing toxicological research," said Dan Angelini, Ph.D., a Center research biologist, in an Army press release. "For example, we can observe which specific lung cells engaged the virus and allowed it to cross the cell membrane. We can then track the actions of the virus inside the infected cell both recording the virus' mechanisms of pathogenesis and the timing of the damage it causes."

The Alveolus Lung-Chip combines primary human alveolar epithelial cells with primary human microvascular lung endothelial cells. Cells are seeded onto the chips which have been coated with extracellular matrix. A mechanical strain is applied and then air is introduced into the epithelial cell channel. This creates a unique microenvironment which maintains phenotype and functionality of the endothelial and epithelial cells enabling scientists to develop more representative understandings of disease processes and drug responses. These characteristics make it an ideal model for studying the underlying mechanisms of SARS-CoV-2 viral infection.

"Historically technologies for in vitro modelling have been slow to innovate, contributing to a high failure rate in drug development and a limited understanding of human physiological response," said Jim Corbett, CEO of Emulate, Inc. "Advanced in vitro models, such as Organ-Chips from Emulate, are showcasing more predictive outcomes than 2D modeling and animal studies. We are excited the Army is embracing these new technological advances and applying them toward understanding SARS-CoV-2 viral infection and taking critical steps to impact this global health crisis."

The Lung-Chip is part of a complete Human Emulation System from Emulate, which includes chips, instrumentation and hardware. For more information, visit https://www.emulatebio.com/blog/webinar-lung-chip-viral-infection-covid-19

About Emulate, Inc.Emulate Inc.is a privately held company that creates advanced in vitro models for understanding how diseases, medicines, chemicals, and foods affect human health. Our lab-ready Human Emulation System includes three components: Zo Culture Module, Organ-Chips, and analytical software applications. The platform provides a window into the inner workings of human biology and diseaseoffering researchers a new technology designed to predict human response with greater precision and detail than conventional cell culture or animal-based experimental testing. Each of Emulate's proprietary Organ-Chipsincluding the liver, intestine, and kidneycontains tiny hollow channels lined with tens of thousands of living human cells and tissues and is approximately the size of an AA battery. An Organ-Chip is a living, microengineered environment that recreates the natural physiology and mechanical forces that cells experience within the human body. Our founding team pioneered the Organs-on-Chips technology at the Wyss Institute for Biologically Inspired Engineering at Harvard University. Emulate holds the worldwide exclusive license from Harvard University to a robust and broad intellectual property portfolio for the Organs-on-Chips technology and related systems. For more information, please visit emulatebio.com.

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Physiology

Uncovering the Mind-Body Connection of Touch – UANews

By Brittany Uhlorn, BIO5 Institute

Tuesday

Humans are born with the language of touch, and physical connection is essential to our development, growth and survival throughout life.

An infant requires the protective embrace of a parent or caretaker to fully develop, learn trust, and make connections. University of Arizona researcher Dr. Katalin Gothard, born and trained as a medical doctor in Romania, interacted with infants who lacked that physical connection while training at an orphanage during her pediatric clerkship. Due to dictatorial policies in Romania, many orphanages were bursting with unwanted babies while suffering from lack of funds and staff. Because of scarce resources and the goal to keep the children alive, workers prioritized medical needs like preventing malnutrition and infection.

Though she and the staff did their best to keep the children physically healthy, Gothard didn't fully understand the impact that the lack of touch would have on the orphans until she began to study the mind-body connection as a scientist in the United States.

"All those antibiotics and all that nutrition did not make them happier adults," said Gothard, a UArizona professor of physiology and member of the university's BIO5 Institute. "Picking them up, holding them and tickling them would have been much more important."

Though initially educated as a medical doctor, Gothard was also trained as a neuroscientist. Observing the toll of mental and emotional hardships caused in part by the oppressive regime in Romania inspired her to change career paths from medicine to science.

"I strongly believe that there's no human suffering that compares to the suffering that our own mind can inflict on us," she said. "There's no physical disease that compares to the pain and misery and hopelessness of a mental disease."

Gothard now dedicates herself to understanding how physical sensations and experiences affect our emotions. For more than 20 years, the physician-turned-scientist has focused on the amygdala, the almond-shaped mass within the brain, as the critical center of this mind-body dialogue.

In 2019, she and colleagues discovered cells in the amygdala that responded not just to sights and sounds, but also touch something that had never before been shown.

In the moment of the discovery, Gothard felt a strong pull from her earlier days at the orphanage to investigate those touch-responsive brain cells.

"One day we found cells that respond to touch, and it was irresistible. I thought, 'Does that mean that I could work on something that takes me back to those years at the orphanage when I was ignorant, and I didn't know what these babies really needed?'" she said. "It was one of those things in life that you cannot say no to. It walks into your life and you know that from that day on your life will change."

Physical Versus Emotional Responses to Touch

Though we know that a handshake forms a connection, a hug brings comfort and a touch from a stranger feels uncomfortable, scientists and physicians have yet to determine the neural mechanisms behind these mind-body processes. With a $2.1 million grant from National Institutes of Health, a team of trainees led by Gothard and her co-investigator Andrew Fuglevan, a professor of neuroscience and physiology, is seeking to understand how the brain interprets the social, emotional and physical determinants of touch.

Gothard's lab examines the differences in brain activity between gentle grooming on the cheek and a pesky puff of air on the forehead. The researchers observed that the response to the physical aspects of touch when and where occurs much faster than the response to the emotional and social components, like whether the touch was pleasant or from a familiar person.

They also compared the influences of the various touch parameters on emotional state and found that although the objective parameters of touch are processed first, the social aspects were more important in influencing amygdala activity and resulting emotional states.

"If you receive a gentle caress from a person that is not welcome even though the pressure on your skin, the sweep speed, the temperature of the hand might be exactly the same as a welcomed touch your amygdala will say, 'I don't like this,'" Gothard said.

With these findings, Gothard realized the emotional and social consequences of touch, combined with our expectations, outrank the physical.

She and her team found that recipient heart rate at the time of touch correlated with emotional response: When the touch was a positive experience, both the heart rate and amygdala activity slowed, but when the touch was negative, heart rate and amygdala activity both increased. She now aims to find the link between touch and changes to markers in the body, including heart rate, as this causal factor might also be the direct link between touch and changes to amygdala circuitry.

"The more we understand about the brain, the more humble we become about how little insight we have on what's happening inside that dark cranial box," she said.

COVID-19 Causing Touch Deprivation

Gothard hopes her work will one day inform not only the ways humans normally process touch, but also how these circuits can go awry in people with mental illnesses such as social anxiety or schizophrenia, in which the response to touch is more complex. The research may also help to explain how a lack of touch during infancy such as that experienced by orphans leads to attachment disorders later in life.

Implications for Gothard's work further extend to the deprivation of touch during the COVID-19 pandemic. While Gothard stands by the recommendations of social distancing to mitigate the spread of disease, she believes that social isolation during the pandemic will have major, lasting mental health ramifications.

"We are in the middle of uncertainty. What you want in the middle of uncertainty is a hug, but you can't do that right now," she said.

Since physical touch is currently scarce, especially for the elderly and for those who live alone, it's important to find ways to pacify the brain's craving for touch, Gothard said.

She recommends massaging the scalp during hair washing or stimulating the body through physical movement and exercise with the sunshine and breeze. Mind-body scans, such as those often used in yoga and other mindfulness practices, can also help substitute physical touch.

Although these substitutes help to meet the need for physical connection, Gothard said, they cannot fully replace the language of touch we were born to give and receive.

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Uncovering the Mind-Body Connection of Touch - UANews

Physiology

Communication’s Lindsey Aloia Honored with Early Career Award for Prolific Research – University of Arkansas Newswire

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Lindsey Aloia

Lindsey Aloia, associate professor of communication in the Fulbright College of Arts and Sciences, was recently honored with the 2020 Janice Hocker Rushing Early Career Research Award from the Southern States Communication Association.

This award honors untenured, assistant professors with no more than five years in the academy thatare SSCA members who demonstrate exceptional scholarly ability through research and publication.

Aloia's research is prolific. Aloia has published 24 manuscripts, three book chapters, a special journal issue introduction, and has two manuscripts accepted and in production, with seven manuscripts under review.

In addition, she has secured a book contract with Oxford University Press as the lead editor of a handbook on physiology of interpersonal interactions and physiological outcomes of interpersonal communication. Also, Aloia has presented her research findings at 31 regional, national, and international conferences resulting in multiple awards for top papers, articles, and a top dissertation award.

Aloia's work focuses on elucidating the causes and consequences of verbal aggression and in interpersonal communication associations, specifically how qualities of interpersonal interactions, as well as individuals, shape the use of and reactions to verbally aggressive experiences.

In her work, she considers consequential communication to illuminate the emotional well-being, cognitive fitness, physiological health, and behavioral implications of verbal aggression.

In his letter of nomination, Robert Brady, former chair for the Department of Communication, noted "Lindsey joined the communication department at the University of Arkansas in her first assistant professor position in 2015 and immediately impressed me with her exceptional scholarly ability."

He added, "I believe that Lindsey's innovative, theoretically motivated, and rigorous research, combined with her methodological prowess and commitment to the Southern States communication Association make her a strong candidate for the Janice Hocker Rushing Early Career Research Award."

For more information about the Janice Hocker Rushing Early Career Research Award, visit the SSCA online.

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Communication's Lindsey Aloia Honored with Early Career Award for Prolific Research - University of Arkansas Newswire

Physiology

Evaluation of Pulmonary Function Tests Among Pregnant Women of Differe | IJWH – Dove Medical Press

Yosef Eshetie Amare,1 Diresibachew Haile2

1Department of Biomedical Sciences, Institute of Medicine and Health Sciences, Debre Berhan University, Debre Berhan, Ethiopia; 2Department of Physiology, College of Medicine and Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia

Correspondence: Yosef Eshetie AmareDepartment of Biomedical Sciences, Institute of Medicine and Health Sciences, Debre Berhan University, EthiopiaTel +251910966364Email yophy2006@gmail.com

Introduction: Pregnancy is characterized by a sequence of dynamic physiological changes that impact multiple organ system functions and is associated with various changes in pulmonary anatomy and physiology. Precise knowledge of the pulmonary function test parameters helps to understand and manage the course and outcome of pregnancy leading to safe delivery. It also helps to avoid misdiagnosis and unnecessary interventions. The aim of this study was to evaluate the effect of normal pregnancy on pulmonary function tests among pregnant women in Debre Berhan Referral Hospital, Ethiopia.Methods: A total of 176 study participants (first, second, and third trimester; and control) were involved under a comparative cross-sectional study design and convenience sampling technique. Anthropometric data, oxygen saturation of arterial blood, and pulmonary function tests were measured. Data were tabulated and statistically analyzed using SPSS version 20.0 statistical software. Means of all parameters were compared using one-way ANOVA followed by Tukeys post hoc multiple comparison test. Statistical significance was preset at a p-value of less than 0.05.Results: Mean of FVC for the controls, first, second, and third trimesters was 2.59 0.26, 2.13 0.15, 1.93 0.27, and 1.90 0.11 liters, respectively. Except for FEV1%, the mean values of FVC, FEV1, PEFR, and FEF 25 75% in the pregnant group (all the three trimesters) were significantly decreased from the controls (P< 0.05). Strong negative correlation was seen between SaO2 and RR (r= 0.865; P < 0.01). As the pregnancy progressed from first to the third trimester, dynamic pulmonary function tests (FVC, FEV1, FEF25-75%, and PEFR) were dropped and the respiratory rate increased.Conclusion: The results had shown the tendency of obstructive pattern while pregnancy becoming advanced. We have observed also a remarkable decline of SaO2 in pregnant women that might be counterbalanced by raised respiratory rate.

Keywords: pregnancy, high altitude, FVC, trimester, oxygen saturation

This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License.By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

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Evaluation of Pulmonary Function Tests Among Pregnant Women of Differe | IJWH - Dove Medical Press

Physiology

Seymour native, husband prepare to open chiropractic practice – Seymour Tribune

With seven years of college behind her, MacKenzie Ryczek is ready to apply what she learned.

The 25-year-old Seymour native and her husband, Nick Ryczek, graduated from the first and largest college of chiropractic Oct. 23.

That wrapped up MacKenzies postsecondary journey, which started with earning a Bachelor of Arts in science with a major in biology and minor in kinesiology and integrative physiology from Hanover College in 2017 and a Doctorate of Chiropractic from Palmer College of Chiropractic this year.

Now, she and Nick are making an adjustment in opening their own business, New Wave Chiropractic, in Greenwood in the spring of 2021.

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I am most looking forward to being able to serve the community, MacKenzie said. Its not a secret that people are getting sicker, yet we are spending the most on health care out of any other country. I want to be a part of the change that is needed to get people back to being healthy. Now more than ever, people are in need of a health change.

MacKenzie said she was in seventh grade when she decided she wanted to attend Palmer.

I have always wanted to be in the health field to help people, but I wanted to do something other than prescribe medications, she said. Chiropractic is about helping people find the root cause of their health concerns and heal them from the inside out.

She graduated from Seymour High School in 2013 before going on to Hanover to earn her undergraduate degree.

I feel that my education from Seymour and Hanover prepared me very well for graduate school, MacKenzie said. Not only the type of classes I took, but the amount of effort the classes required really made me prioritize my education.

The process of applying to chiropractic school included an application with two academic references, an essay and a phone interview.

No specific undergraduate degree is required, but you do have to have a certain amount of science-based classes in order to start the program, MacKenzie said.

Palmer was the only chiropractic school she visited as a prospective student and the only school she wanted to attend. The main campus is in Iowa, and other schools are in San Jose, California, and Port Orange, Florida.

I wanted to go to Palmer in Davenport, Iowa, because it was the first chiropractic college and so much history lives there, she said of the worlds first chiropractic school that was established in 1897.

At Palmer, MacKenzie said she received an excellent education and made many lifelong friends who are now valuable colleagues.

During her first trimester, she joined a club called AMPED, or Advanced Mentorship Program for Entrepreneurial Development.

This group met every week to train on communication, leadership and various business principles to prepare you for opening a practice after graduation, she said. I attended countless conferences and leadership retreats with this organization that has prepared me so much for what I am doing right now.

Making the grade was important to MacKenzie, and that showed by being named to the deans list eight times at Palmer.

I focused on learning and retaining as much information as I could during the classes to prepare for the five parts of chiropractic board exams, she said.

October was a big month because she and Nick were married Oct. 3 and followed that up 20 days later with graduation.

She and Nick met at Palmer.

We were in the same graduating class and had almost every class together for over three years, MacKenzie said. The intensity and demanding nature of going to school at Palmer can put strain on relationships, so it was nice to be able to share that stress and experience with Nick. Being able to graduate together made it easy for us to focus on the same goals right after graduation.

Nick, a Wisconsin native, said it wasnt until his early undergraduate years he realized he wanted to be a chiropractor.

I always knew I wanted to go into health care and help people, but I didnt exactly know where I fit into that until I was introduced to chiropractic, he said. The natural approach of chiropractic really spoke to me, and from that point on, I knew I wanted to go to chiropractic school and practice this amazing form of healing.

Nick said he was lucky to meet MacKenzie at Palmer.

Chiropractic school is pretty tough, so having her to go through everything with me was amazing, Nick said. We were able to keep each other going through the hard times and celebrate the good times together.

The ceremony Oct. 23 was MacKenzies third graduation. Her parents, James Harvey II and Tracy Harvey of Seymour, were in attendance.

It meant so much to be able to walk across the stage and be ceremonially promoted to doctor, she said. I have been in school since 2013 receiving a higher education. This is the first time in my life that I dont have a class to attend or an assignment to do. It feels surreal that I have finally accomplished what I set out to do many years ago.

Getting married and graduating in the same month was almost like running a marathon, she said.

It took a lot of planning and tons of phone calls to be able to graduate with my new last name, she said. It was nice to be able to celebrate the entire month of October with friends and family on our accomplishments.

MacKenzie decided she wanted to open her own practice after she joined AMPED.

This group really gave me the courage and determination to do that, she said. After Nick and I started dating, I brought him into the group and shared my goals and dreams, and I was lucky that he had the same goals, and everything just seemed to work out.

They chose Greenwood for several reasons.

I am very familiar with the area, its really close to Indianapolis but not as busy, its a very family-oriented town and it is going through some major growth, as well, MacKenzie said. We visited Greenwood a few times to just drive around, and it really felt like home.

The Ryczeks will be the only chiropractors and plan to have at least two employees at the start and hire more as they grow.

They are certified in Torque Release Technique, an instrument-based system of analyzing the spine that allows them to make adjustments as gentle and specific as possible. They also are trained to see pregnant women, infants and children of all ages.

Were so excited to start this chapter of our lives and be able make a huge impact on the health of our community, Nick said of opening the practice.

MacKenzie hopes her success story inspires others to pursue their dreams and work toward achieving them.

I hope to serve as an example in that you can do anything you set your mind to, she said. It doesnt matter where you come from, how strange anyone thinks your dream is. You can do whatever you are determined to do. It just takes effort, and it may take a ton of time, but it is so worth it in the end.

Ryczek file

Name: MacKenzie Ryczek

Age: 25

Hometown: Seymour

Residence: Greenwood

Education: Seymour High School (2013); Hanover College (Bachelor of Arts in science with a major in biology and minor in kinesiology and integrative physiology, 2017); Palmer College of Chiropractic (Doctorate of Chiropractic, 2020)

Occupation: Chiropractor

Family: Husband, Nick Ryczek; parents, James Harvey II and Tracy Harvey

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Seymour native, husband prepare to open chiropractic practice - Seymour Tribune