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.

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.

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.

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.