A fluorescence-based sweat test sensor in a proof-of-concept clinical study for COVID-19 screening diagnosis.

During the corona virus disease 2019 (COVID-19) pandemic period, rapid screening of covid-19 patients has been of great interest by developing a fluorescent sensor for complexation with nonanal, which is a marker for Covid-19 detection in sweat. Solid phase micro-extraction gas chromatography-mass spectrometry (SPME GC-MS) was initially used to quantify nonanal in armpit sweat samples based on an external calibration curve. A sample containing a nonanal content above the threshold of 1.04 µL is expected to be COVID-19 positive with a sensitivity and specificity of 87% and 89%, respectively, validated by comparison with RT-PCR results. For more practical applications, helicene dye-encapsulated ethyl cellulose, namely EC@dyeNH, was applied to screen 140 sweat samples collected from the foreheads of volunteers. The mixed sensor and sweat solution droplets were then visualized and imaged under blacklight. The COVID-19 positive droplets exhibited yellow fluorescence emission, the brightness of which could be measured by using ImageJ in the grey scale. With the optimum color intensity of >73 for positive results, the screening performance was observed with a sensitivity and specificity of 96% and 93%, respectively. The overall test time of this method is approximately less than 15 min. This alternative method offers a promising practical screening approach for the diagnosis of COVID-19 in sweat.

A Smart Wristband Integrated with an IoT-Based Alarming System for Real-Time Sweat Alcohol Monitoring.

Breathalyzer is a common approach to measuring blood alcohol concentration (BAC) levels of individuals suspected of drunk driving. Nevertheless, this device is relatively high-cost, inconvenient for people with limited breathing capacity, and risky for COVID-19 exposure. Here, we designed and developed a smart wristband integrating a real-time noninvasive sweat alcohol metal oxide (MOX) gas sensor with a Drunk Mate, an Internet of Thing (IoT)-based alarming system. A MOX sensor acquired transdermal alcohol concentration (TAC) which was converted to BAC and sent via the IoT network to the Blynk application platform on a smartphone, triggering alarming messages on LINE Notify. A user would receive an immediate alarming message when his BAC level reached an illegal alcohol concentration limit (BAC 50 mg%; TAC 0.70 mg/mL). The sensor readings showed a high linear correlation with TAC (R2 = 0.9815; limit of detection = 0.045 mg/mL) in the range of 0.10-1.05 mg/mL alcohol concentration in artificial sweat, achieving an accuracy of 94.66%. The sensor readings of ethanol in water were not statistically significantly different (p > 0.05) from the measurements in artificial sweat and other sweat-related solutions, suggesting that the device responded specifically to ethanol and was not affected by other electrolytes in the artificial sweat. Moreover, the device could continuously monitor TAC levels simulated in real-time in an artificial sweat testing system. With the integration of an IoT-based alarming system, the smart wristband developed from a commercial gas sensor presented here offers a promising low-cost MOX gas sensor monitoring technology for noninvasive and real-time sweat alcohol measurement and monitoring.

Night sweats (nocturnal hyperhidrosis) causing wrinkled (pruney) hands in a patient with SARS-CoV-2 infection.

We report the case of a 28-year-old female who developed severe night sweated on the ninth day of SARS-CoV-2 infection with wrinkling of the fingers and palms.

Recent Advances of Point-of-Care Devices Integrated with Molecularly Imprinted Polymers-Based Biosensors: From Biomolecule Sensing Design to Intraoral Fluid Testing.

Recent developments of point-of-care testing (POCT) and in vitro diagnostic medical devices have provided analytical capabilities and reliable diagnostic results for rapid access at or near the patient's location. Nevertheless, the challenges of reliable diagnosis still remain an important factor in actual clinical trials before on-site medical treatment and making clinical decisions. New classes of POCT devices depict precise diagnostic technologies that can detect biomarkers in biofluids such as sweat, tears, saliva or urine. The introduction of a novel molecularly imprinted polymer (MIP) system as an artificial bioreceptor for the POCT devices could be one of the emerging candidates to improve the analytical performance along with physicochemical stability when used in harsh environments. Here, we review the potential availability of MIP-based biorecognition systems as custom artificial receptors with high selectivity and chemical affinity for specific molecules. Further developments to the progress of advanced MIP technology for biomolecule recognition are introduced. Finally, to improve the POCT-based diagnostic system, we summarized the perspectives for high expandability to MIP-based periodontal diagnosis and the future directions of MIP-based biosensors as a wearable format.

Biomedical detection dogs for the identification of SARS-CoV-2 infections from axillary sweat and breath samples*.

A Polymerase Chain Reaction (PCR) test of a nasal swab is still the 'gold standard' for detecting a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, PCR testing could be usefully complemented by non-invasive, fast, reliable, cheap methods for detecting infected individuals in busy areas (e.g. airports and railway stations) or remote areas. Detection of the volatile, semivolatile and non-volatile compound signature of SARS-CoV-2 infection by trained sniffer dogs might meet these requirements. Previous studies have shown that well-trained dogs can detect SARS-CoV-2 in sweat, saliva and urine samples. The objective of the present study was to assess the performance of dogs trained to detect the presence of SARS-CoV-2 in axillary-sweat-stained gauzes and on expired breath trapped in surgical masks. The samples were provided by individuals suffering from mild-to-severe coronavirus disease 2019 (COVID-19), asymptomatic individuals, and individuals vaccinated against COVID-19. Results: Seven trained dogs tested on 886 presentations of sweat samples from 241 subjects and detected SARS-CoV-2 with a diagnostic sensitivity (relative to the PCR test result) of 89.6% (95% confidence interval (CI): 86.4%-92.2%) and a specificity of 83.9% (95% CI: 80.3%-87.0%)-even when people with a low viral load were included in the analysis. When considering the 207 presentations of sweat samples from vaccinated individuals, the sensitivity and specificity were respectively 85.7% (95% CI: 68.5%-94.3%) and 86.0% (95% CI: 80.2%-90.3%). The likelihood of a false-positive result was greater in the two weeks immediately after COVID-19 vaccination. Four of the seven dogs also tested on 262 presentations of mask samples from 98 subjects; the diagnostic sensitivity was 83.1% (95% CI: 73.2%-89.9%) and the specificity was 88.6% (95% CI: 83.3%-92.4%). There was no difference (McNemar's testP= 0.999) in the dogs' abilities to detect the presence of SARS-CoV-2 in paired samples of sweat-stained gauzes vs surgical masks worn for only 10 min. Conclusion: Our findings confirm the promise of SARS-CoV-2 screening by detection dogs and broaden the method's scope to vaccinated individuals and easy-to-obtain face masks, and suggest that a 'dogs + confirmatory rapid antigen detection tests' screening strategy might be worth investigating.

New method of screening for COVID-19 disease using sniffer dogs and scents from axillary sweat samples.

BACKGROUND: Early screening for COVID-19 is needed to limit the spread of the virus. The aim of this study is to test if the sniffer dogs can be successfully trained to identify subjects with COVID-19 for 'proof of concept' and 'non-inferiority' against PCR. We are calling this method, Dognosis (DN). METHODS: Four hundred and fifty-nine subjects were included, 256 (Group 'P') were known cases of COVID-19 (PCR positive, some with and some without symptoms) and 203 (Group 'C') were PCR negative and asymptomatic (control). Samples were obtained from the axillary sweat of each subject in a masked fashion. Two dogs trained to detect specific Volatile Organic Compounds for COVID-19 detection were used to test each sample. RESULTS: [DN] turned out positive (+) in all the cases that were PCR positive (100% sensitivity). On the other hand, [DN] turned positive (+) in an average of 12.5 cases (6.2%) that were initially PCR negative (apparent specificity of 93.8%). When the PCR was repeated, true specificity was 97.2%. These parameters varied in subgroups from 100% sensitivity and 99% specificity in symptomatic patients to 100% sensitivity and 93% specificity in asymptomatic patients. CONCLUSION: DN method shows high sensitivity and specificity in screening COVID-19 patients.

Reversible Hydration Composite Films for Evaporative Perspiration Control and Heat Stress Management.

Donning of personal protective equipment (PPE) in the healthcare sector has been intensified by the on-going COVID-19 pandemic around the globe. While extensive PPE provides protection, it typically limits moisture permeability and severely hinders the sweat evaporation process, resulting in greater heat stress on the personnel. Herein, a zinc-poly(vinyl alcohol) (Zn-PVA) composite film is fabricated by embedding a super-hygroscopic zinc-ethanolamine complex (Zn-complex) in the PVA matrix. By attaching the Zn-PVA composite film, the relative humidity (RH) inside the protective suit decreases from 91.0% to 48.2%. The reduced RH level, in turn, enhances evaporative cooling, hence bringing down the heat index from 64.6 to 40.0 °C at an air temperature of 35 °C, remarkably lowering the likelihood of heat stroke. The American Society for Testing and Materials tests conducted on a sweating manikin have also proven that the Zn-PVA composite films can significantly reduce the evaporative resistance of the protective suit by 90%. The low material cost, facile fabrication process, and reusability allow the Zn-PVA composition films to be readily available for healthcare workers worldwide. This application can be further extended to other occupations that are facing severe thermal discomfort and heat stress.

Identifying SARS-COV-2 infected patients through canine olfactive detection on axillary sweat samples; study of observed sensitivities and specificities within a group of trained dogs.

There is an increasing need for rapid, reliable, non-invasive, and inexpensive mass testing methods as the global COVID-19 pandemic continues. Detection dogs could be a possible solution to identify individuals infected with SARS-CoV-2. Previous studies have shown that dogs can detect SARS-CoV-2 on sweat samples. This study aims to establish the dogs' sensitivity (true positive rate) which measures the proportion of people with COVID-19 that are correctly identified, and specificity (true negative rate) which measures the proportion of people without COVID-19 that are correctly identified. Seven search and rescue dogs were tested using a total of 218 axillary sweat samples (62 positive and 156 negative) in olfaction cones following a randomised and double-blind protocol. Sensitivity ranged from 87% to 94%, and specificity ranged from 78% to 92%, with four dogs over 90%. These results were used to calculate the positive predictive value and negative predictive value for each dog for different infection probabilities (how likely it is for an individual to be SARS-CoV-2 positive), ranging from 10-50%. These results were compared with a reference diagnostic tool which has 95% specificity and sensitivity. Negative predictive values for six dogs ranged from ≥98% at 10% infection probability to ≥88% at 50% infection probability compared with the reference tool which ranged from 99% to 95%. Positive predictive values ranged from ≥40% at 10% infection probability to ≥80% at 50% infection probability compared with the reference tool which ranged from 68% to 95%. This study confirms previous results, suggesting that dogs could play an important role in mass-testing situations. Future challenges include optimal training methods and standardisation for large numbers of detection dogs and infrastructure supporting their deployment.

COVID-19 sniffer dog experimental training: Which protocol and which implications for reliable sidentification?

The introduction of trained sniffer dogs for COVID-19 detection could be an opportunity, as previously described for other diseases. Dogs could be trained to detect volatile organic compounds (VOCs), the whiff of COVID-19. Dogs involved in the study were three, one male and two females from different breeds, Black German Shepherd, German Shepherd, and Dutch Shepherd. The training was performed using sweat samples from SARS-CoV2 positive patients and from SARS-Cov2 free patients admitted at the University Hospital Campus Bio-medico of Rome. Gauze with sweat was collected in a glass jar with a metal top and put in metal boxes used for dog training. The dog training protocol was performed in two phases: the olfactory conditioning and the olfactory discrimination research. The training planning was focused on the switch moment for the sniffer dog, the moment when the dog was able to identify VOCs specific for COVID-19. At this time, the dog was able to identify VOCs specific for COVID-19 with significant reliability, in terms of the number of correct versus incorrect (p < 0.0001) reporting. In conclusion, this protocol could provide a useful tool for sniffer dogs' training and their introduction in a mass screening context. It could be cheaper and faster than a conventional testing method.

State of Sweat: Emerging Wearable Systems for Real-Time, Noninvasive Sweat Sensing and Analytics.

Skin-interfaced wearable systems with integrated colorimetric assays, microfluidic channels, and electrochemical sensors offer powerful capabilities for noninvasive, real-time sweat analysis. This Perspective details recent progress in the development and translation of novel wearable sensors for personalized assessment of sweat dynamics and biomarkers, with precise sampling and real-time analysis. Sensor accuracy, system ruggedness, and large-scale deployment in remote environments represent key opportunity areas, enabling broad deployment in the context of field studies, clinical trials, and recent commercialization. On-body measurements in these contexts show good agreement compared to conventional laboratory-based sweat analysis approaches. These device demonstrations highlight the utility of biochemical sensing platforms for personalized assessment of performance, wellness, and health across a broad range of applications.

A non-printed integrated-circuit textile for wireless theranostics.

While the printed circuit board (PCB) has been widely considered as the building block of integrated electronics, the world is switching to pursue new ways of merging integrated electronic circuits with textiles to create flexible and wearable devices. Herein, as an alternative for PCB, we described a non-printed integrated-circuit textile (NIT) for biomedical and theranostic application via a weaving method. All the devices are built as fibers or interlaced nodes and woven into a deformable textile integrated circuit. Built on an electrochemical gating principle, the fiber-woven-type transistors exhibit superior bending or stretching robustness, and were woven as a textile logical computing module to distinguish different emergencies. A fiber-type sweat sensor was woven with strain and light sensors fibers for simultaneously monitoring body health and the environment. With a photo-rechargeable energy textile based on a detailed power consumption analysis, the woven circuit textile is completely self-powered and capable of both wireless biomedical monitoring and early warning. The NIT could be used as a 24/7 private AI "nurse" for routine healthcare, diabetes monitoring, or emergencies such as hypoglycemia, metabolic alkalosis, and even COVID-19 patient care, a potential future on-body AI hardware and possibly a forerunner to fabric-like computers.

SARS-CoV-2 is not found in the sweat of COVID-19 positive patients.

BACKGROUND: As the SARS-CoV-2 virus made a pandemic all over the world, its transmission routes became significant. Transmission from human to human is known, but other possible routes are not determined well. AIMS: This study aimed to reveal the presence of SARS-CoV-2 virus in sweat. METHODS: This prospective study was conducted in a tertiary care education and training hospital. Fifty patients were included in this study. Skin disinfection was done with an alcohol-based solution. Swabs for RT-PCR (real-time reverse transcriptase polymerase chain reaction) were taken from forehead and axilla skin after sweating patients for 30 min. After collection of sweat, swabs were placed into 2 ml of sterile viral transport medium, then transported quickly to the microbiology laboratory. RESULTS: No SARS-CoV-2 virus was detected in RT-PCR of forehead and axilla swabs. CONCLUSION: This study showed that there is no transmission of SARS-CoV-2 virus via sweat. However, general precautions must be taken while doing interventional procedures.

Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study.

The aim of this proof-of-concept study was to evaluate if trained dogs could discriminate between sweat samples from symptomatic COVID-19 positive individuals (SARS-CoV-2 PCR positive) and those from asymptomatic COVID-19 negative individuals. The study was conducted at 2 sites (Paris, France, and Beirut, Lebanon), followed the same training and testing protocols, and involved six detection dogs (three explosive detection dogs, one search and rescue dog, and two colon cancer detection dogs). A total of 177 individuals were recruited for the study (95 symptomatic COVID-19 positive and 82 asymptomatic COVID-19 negative individuals) from five hospitals, and one underarm sweat sample per individual was collected. The dog training sessions lasted between one and three weeks. Once trained, the dog had to mark the COVID-19 positive sample randomly placed behind one of three or four olfactory cones (the other cones contained at least one COVID-19 negative sample and between zero and two mocks). During the testing session, a COVID-19 positive sample could be used up to a maximum of three times for one dog. The dog and its handler were both blinded to the COVID-positive sample location. The success rate per dog (i.e., the number of correct indications divided by the number of trials) ranged from 76% to 100%. The lower bound of the 95% confidence interval of the estimated success rate was most of the time higher than the success rate obtained by chance after removing the number of mocks from calculations. These results provide some evidence that detection dogs may be able to discriminate between sweat samples from symptomatic COVID-19 individuals and those from asymptomatic COVID-19 negative individuals. However, due to the limitations of this proof-of-concept study (including using some COVID-19 samples more than once and potential confounding biases), these results must be confirmed in validation studies.

Wearable electrochemical biosensors in North America.

Tremendous research and commercialization efforts around the world are focused on developing novel wearable electrochemical biosensors that can noninvasively and continuously screen for biochemical markers in body fluids for the prognosis, diagnosis and management of diseases, as well as the monitoring of fitness. Researchers in North America are leading the development of innovative wearable platforms that can comfortably comply to the human body and efficiently sample fluids such as sweat, interstitial fluids, tear and saliva for the electrochemical detection of biomarkers through various sensing approaches such as potentiometric ion selective electrodes and amperometric enzymatic sensors. We start this review with a historical timeline overviewing the major milestones in the development of wearable electrochemical sensors by North American institutions. We then describe how such research efforts have led to pioneering developments and are driving the advancement and commercialization of wearable electrochemical sensors: from minimally invasive continuous glucose monitors for chronic disease management to non-invasive sweat electrolyte sensors for dehydration monitoring in fitness applications. While many countries across the globe have contributed significantly to this rapidly emerging field, their contributions are beyond the scope of this review. Furthermore, we share our perspective on the promising future of wearable electrochemical sensors in applications spanning from remote and personalized healthcare to wellness.

Study presence of COVID-19 (SARS-CoV-2) in the sweat of patients infected with Covid-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease, which started in Wuhan, Chin, has now become a public health challenge in most countries around the world. Proper preventive measures are necessary to prevent the spread of the virus to help control the pandemic. Because, SARS-CoV-2 is new, its transmission route has not been fully understood. In this study, we aimed to investigate the presence of SARS-CoV-2 in the sweat secretion of COVID-19 patients. Sweat specimens of 25 COVID- 19 patients were collected and tested for SARS-CoV-2 RNA by Real-time Polymerase Chain Reaction (RT-PCR) method. After RNA extraction and cDNA amplification, all samples were examined for the presence of ORF-1ab and N genes related to COVID-19. Results annotated by Realtime PCR machines software based on Dynamic algorithm. The results of this study showed the absence of SARS-CoV-2 in the sweat samples taken from the foreheads of infected people. Therefore, it can be concluded that the sweat of patients with COVID- 19 cannot transmit SARS-CoV-2. However they can be easily contaminated with other body liquids.