Physiological temperature varies temporally and spatially. Accurate and real‐time detection of localized temperature changes in biological tissues regardless of large deformation is crucial to understand thermal principle of homeostasis, to assess sophisticated health conditions, and further to offer possibilities of building a smart healthcare and medical system. Additionally, continuous temperature mapping in flexible and stretchable formats opens up many other potential areas, such as artificially electronic skins and reflection of emotional changes. This review exploits a comprehensive investigation onto recent advances in flexible temperature sensors, stretchable sensor networks, and platforms constructed in soft and compliant formats for wearable physiological monitoring. The most recent examples of flexible temperature sensors are first discussed regarding to their materials, structures, electrical and mechanical properties; temperature sensing network technologies in new materials and structural designs are then presented based on platforms comprised of multiple physical sensors and stretchable electronics. Finally, wearable applications of the sensing network are described, such as detection of human activities, monitoring of health conditions, and emotion‐related bodily sensations. Conclusions are made with emphasis on critical issues and new trends in the field of wearable temperature sensor network technologies.

Background:The risk factors for adverse events of Coronavirus have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR

BackgroundFamily-based intervention is essential for adolescents with behavioral problems. However, limited data are available on the relationship between family-based factors and adolescent internet addiction (AIA). We aimed to examine this relationship using a representative sample of Shanghai adolescents.MethodsIn October 2007, a total of 5122 adolescents were investigated from 16 high schools via stratified-random sampling in Shanghai. Self-reported and anonymous questionnaires were used to assess parent-adolescent interaction and family environments. AIA was assessed by DRM-52 Scale, developed from Young’s Internet-addiction Scale, using seven subscales to evaluate psychological symptoms of AIA.ResultsAdjusting for adolescents’ ages, genders, socio-economic status, school performances and levels of the consumption expenditure, strong parental disapproval of internet-use was associated with AIA (vs. parental approval, OR = 2.20, 95% CI: 1.24-3.91). Worse mother-adolescent relationships were more significantly associated with AIA (OR = 3.79, 95% CI: 2.22-6.48) than worse father-adolescent relationships (OR = 1.76, 95% CI: 1.10-2.80). Marital status of “married-but-separated” and family structure of “left-behind adolescents” were associated with symptoms of some subscales. When having high monthly allowance, resident students tended to develop AIA but commuter students did not. Family social-economic status was not associated with the development of AIA.ConclusionsThe quality of parent-adolescent relationship/communication was closely associated with the development of AIA, and maternal factors were more significantly associated with development of AIA than paternal factors. Family social-economic status moderated adolescent internet-use levels but not the development of AIA.

Inbred C57BL/6J mice displayed large individual variations in weight gain when fed a high‐fat diet (HFD). The objective of this study was to examine whether this predominantly nongenetic variability could be predicted by relevant baseline features and to explore whether variations in these significant features were influenced during pregnancy and/or lactation. Fat mass (FM), fat‐free mass (FFM), food intake (FI), resting metabolic rate (RMR), physical activity (PA), and body temperature (Tb) were all evaluated at baseline in 60 mice (aged 10–12 weeks) before HFD feeding. Regression analyses showed that baseline FM was a strong positive predictor of weight gain between 4 and 16 weeks of HFD. Baseline PA was negatively associated with weight gain at week 8, 12, and 16, and baseline FFM had a positive effect at week 12 and 16. In a second experiment, 40 female mice were mated and litter sizes (LS) were manipulated on day 3 of lactation. Weaning weight and postweaning growth rate (GR) had positive impacts on FM and FFM at age 9 weeks (FM, P = 0.001; FFM, P < 0.001: n = 97). Lactation LS had a negative effect on weaning weight and a positive effect on postweaning GR. In conclusion, our results show that obesity induced by HFD was associated with a higher baseline FM, a higher baseline FFM and a lower baseline PA level before the exposure of HFD. Two of these traits (FM and FFM) were influenced by lactation LS via weaning weight and postweaning GR.

No abstract