Although it is widely accepted that cancer-derived extracellular vesicles (EVs) carry DNA cargo, the association of cell-free circulating DNA (cfDNA) and EVs in plasma of healthy humans remains elusive. Using a physiological exercise model, where EVs and cfDNA are synchronously released, we aimed to characterize the kinetics and localization of DNA associated with EVs. EVs were separated from human plasma using size exclusion chromatography or immuno-affinity capture for CD9⁺, CD63⁺, and CD81⁺ EVs. DNA was quantified with an ultra-sensitive qPCR assay targeting repetitive LINE elements, with or without DNase digestion. This model shows that a minute part of circulating cell-free DNA is associated with EVs. During rest and following exercise, only 0.12% of the total cfDNA occurs in association with CD9⁺/CD63⁺/CD81⁺EVs. DNase digestion experiments indicate that the largest part of EV associated DNA is sensitive to DNase digestion and only ~20% are protected within the lumen of the separated EVs. A single bout of running or cycling exercise increases the levels of EVs, cfDNA, and EV-associated DNA. While EV surface DNA is increasing, DNAse-resistant DNA remains at resting levels, indicating that EVs released during exercise (ExerVs) do not contain DNA. Consequently, DNA is largely associated with the outer surface of circulating EVs. ExerVs recruit cfDNA to their corona, but do not carry DNA in their lumen.

This study aimed to examine the skin temperature (Tsk) variations in five regions of interest (ROI) to assess whether possible disparities between the ROI's Tsk could be associated with specific acute physiological responses during cycling. Seventeen participants performed a pyramidal load protocol on a cycling ergometer. We synchronously measured Tsk in five ROI with three infrared cameras. We assessed internal load, sweat rate, and core temperature. Reported perceived exertion and calves' Tsk showed the highest correlation (r = -0.588; p < 0.01). Mixed regression models revealed that the heart rate and reported perceived exertion were inversely related to calves' Tsk. The exercise duration was directly associated with the nose tip and calf Tsk but inversely related to the forehead and forearm Tsk. The sweat rate was directly related to forehead and forearm Tsk. The association of Tsk with thermoregulatory or exercise load parameters depends on the ROI. The parallel observation of the face and calf Tsk could indicate simultaneously the observation of acute thermoregulatory needs and individual internal load. The separate Tsk analyses of individual ROI appear more suitable to examine specific physiological response than a mean Tsk of several ROI during cycling.

Background: Physical activity alleviates chronic stress. The latest research suggests a relationship between resilience and physical fitness. Beneficial adaptations of the hypothalamic-pituitary-adrenal axis, sympathetic nervous system, endocannabinoid system, and tryptophan pathway, which are induced by an active lifestyle, are considered to be conducive to resilience. However, detailed knowledge on the molecular link between the effects of acute and chronic physical exercise and improved resilience to stress in humans is missing. Moreover, the relationship between innate and acquired aerobic capacity and resilience is poorly understood. Objective: The aim of this study is to implement a human exercise intervention trial addressing the following main hypotheses: a high innate aerobic capacity is associated with high resilience to stress, and web-based physical exercise training improves aerobic capacity of physically inactive adults, which is accompanied by improved resilience. In this setting, we will analyze the relationship between resilience parameters and innate and acquired aerobic capacity as well as circulating signaling molecules. Methods: A total of 70 healthy, physically inactive (<150 minutes/week of physical activity) adults (aged 18-45 years) will be randomly assigned to an intervention or control group. Participants in the intervention group will receive weekly training using progressive endurance and interval running adapted individually to their remotely supervised home training performance via web-based coach support. A standardized incremental treadmill exercise test will be performed before and after the intervention period of 8 weeks to determine the innate and acquired aerobic capacity (peak oxygen uptake). Before and after the intervention, psychological tests and questionnaires that characterize parameters implicated in resilience will be applied. Blood and saliva will be sampled for the analysis of cortisol, lactate, endocannabinoids, catecholamines, kynurenic acid, and further circulating signal transducers. Statistical analysis will provide comprehensive knowledge on the relationship between aerobic capacity and resilience, as well as the capacity of peripheral factors to mediate the promoting effects of exercise on resilience. Results: The study was registered in October 2019, and enrollment began in September 2019. Of the 161 participants who were initially screened via a telephone survey, 43 (26.7%) fulfilled the inclusion criteria and were included in the study. Among the 55% (17/31) of participants in the intervention group and 45% (14/31) of participants in the control group who completed the study, no serious adverse incidents were reported. Of 43 participants, 4 (9%) withdrew during the program (for individual reasons) and 8 (19%) have not yet participated in the program; moreover, further study recruitment was paused for an indeterminate amount of time because of the COVID-19 pandemic. Conclusions: Our study aims to further define the physiological characteristics of human resilience, and it may offer novel approaches for the prevention and therapy of mental disorders via an exercise prescription. International Registered Report Identifier (IRRID): DERR1-10.2196/29712

Infrared thermography is increasingly applied in sports science due to promising observations regarding changes in skin’s surface radiation temperature ( $T_{sr}$ ) before, during, and after exercise. The common manual thermogram analysis limits an objective and reproducible measurement of $T_{sr}$ . Previous analysis approaches depend on expert knowledge and have not been applied during movement. We aimed to develop a deep neural network (DNN) capable of automatically and objectively segmenting body parts, recognizing blood vessel-associated $T_{sr}$ distributions, and continuously measuring $T_{sr}$ during exercise. We conducted 38 cardiopulmonary exercise tests on a treadmill. We developed two DNNs: body part network and vessel network, to perform semantic segmentation of 1 107 855 thermal images. Both DNNs were trained with 263 training and 75 validation images. Additionally, we compare the results of a common manual thermogram analysis with these of the DNNs. Performance analysis identified a mean IoU of 0.8 for body part network and 0.6 for vessel network. There is a high agreement between manual and automatic analysis (r = 0.999; p $< $ 0.001; T-test: p = 0.116), with a mean difference of 0.01 $^\circ$ C (0.08). Non-parametric Bland Altman’s analysis showed that the 95% agreement ranges between - 0.086 $^\circ$ C and 0.228 $^\circ$ C. The developed DNNs enable automatic, objective, and continuous measurement of $T_{sr}$ and recognition of blood vessel-associated $T_{sr}$ distributions in resting and moving legs. Hence, the DNNs surpass previous algorithms by eliminating manual region of interest selection and form the currently needed foundation to extensively investigate $T_{sr}$ distributions related to non-invasive diagnostics of (patho-)physiological traits in means of exercise radiomics.