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Wearable sensors have recently attracted extensive interest not only in the field of healthcare monitoring but also for convenient and intelligent human-machine interactions. However, challenges such as wearable comfort, multiple applicable conditions, and differentiation of mechanical stimuli are yet to be fully addressed. Herein, we developed a breathable and waterproof electronic skin (E-skin) that can perceive pressure/strain with nonoverlapping signals. The synergistic effect from magnetic attraction and nanoscaled aggregation renders the E-skin with microscaled pores for breathability and three-dimensional microcilia for superhydrophobicity. Upon applied pressure, the bending of conductive microcilia enables sufficient contacts for resistance decrease, while the stretching causes increased resistance due to the separation of conductive materials. The optimized E-skin exhibits a high gauge factor of 7.747 for small strain (0-80%) and a detection limit down to 0.04%. The three-dimensional microcilia also exhibit a sensitivity of -0.0198 kPa

Many patients after sphincter-preserving surgery experienced anorectal functional disturbances which were known as low anterior resection syndrome (LARS). Although many studies investigated LARS, there was inconsistency of their assessment tools and results. The aim of this systematic review was to elucidate the incidence and risk factors of LARS by a validated tool—LARS score. A systematic literature search in Pubmed, Embase, and Cochrane Library was conducted in April 2020. Studies investigating patients who were evaluated by LARS score 1 year after their sphincter-preserving surgery due to rectal cancer were included. Meta-analysis of incidence was conducted using the double arcsine method. Meta-analysis of each risk factor was conducted using a random effects model. A total of 50 studies were included. The pooled incidence of major LARS was 44% (95% CI 40–48%; I2 = 88%; 36 studies). Long course neoadjuvant radiotherapy (OR 2.89, 95% CI 2.06–4.05; I2 = 47%; P

Objectives. There have been no fully validated tools for the rapid identification of surgical patients at risk of intraoperative hypothermia. The objective of this study was to validate the performance of a previously established prediction model in estimating the risk of intraoperative hypothermia in a prospective cohort. Methods. In this observational study, consecutive adults scheduled for elective surgery under general anesthesia were enrolled prospectively at a tertiary hospital between September 4, 2020, and December 28, 2020. An intraoperative hypothermia risk score was calculated by a mobile application of the prediction model. A wireless axillary thermometer was used to continuously measure perioperative core temperature as the reference standard. The discrimination and calibration of the model were assessed, using the area under the receiver operating characteristic curve (AUC), Hosmer–Lemeshow goodness-of-fit test, and Brier score. Results. Among 227 participants, 99 (43.6%) developed intraoperative hypothermia, and 10 (4.6%) received intraoperative active warming with forced-air warming. The model had an AUC of 0.700 (95% confidence interval [CI], 0.632–0.768) in the overall cohort with adequate calibration (Hosmer–Lemeshow χ2 = 13.8, P = 0.087 ; Brier score = 0.33 [95% CI, 0.29–0.37]). We categorized the risk scores into low-risk, moderate-risk, and high-risk groups, in which the incidence of intraoperative hypothermia was 23.0% (95% CI, 12.4–33.5), 43.4% (95% CI, 33.7–53.2), and 62.7% (95% CI, 51.5–74.3), respectively ( P for trend

Background and aim Malignant mesothelioma (MM), being a rare and aggressive carcinoma, can barely be cured. Incidence of this cancer will keep climbing up in the next few decades since its major carcinogen, asbestos, is still in use in many countries. Unfortunately, prognosis of MM is unsatisfactory principally due to poor early diagnosis as a result of its long latency period and ambiguous symptoms. Lipids are known to contribute to cellular structure, signaling, and energy storage, and are widely reported to be related with tumorigenesis. Therefore, we aim to discover novel lipid biomarkers by plasma-based lipidomics that may improve MM diagnosis. Methods Plasma samples from 25 MM patients and 32 healthy controls (HCs) were collected and analysed using a high-throughput liquid chromatography-mass spectrometry (LC-MS). Univariate and multivariate analyses were subsequently performed to visualize the separation trend between two groups and to screen for differential feature ions. Ions were annotated using LipidSearch 4.2 and their enriched pathways were detected on LIPEA. Receiver operating curves (ROC) were used for analysing each annotated lipid’s diagnostic value. Survival analyses were performed to investigate each lipid’s prognostic value. Results In supervised partial least squares discriminant analysis (PLS-DA), clear separation between MM and HC groups was observed. A total of 34 differential lipids were annotated, among which 5 upregulated and 29 downregulated. Levels of plasma triacylglycerols (TGs) were higher in smoking versus non-smoking patients, and lower in female versus male patients. The top six lipids possessing highest diagnostic value included two phosphatidylethanolamines (PEs), two phosphatidylcholines (PCs) and two ceramides. Moreover, elevated circulating TG levels were associated with poorer survival, whereas increased monohexosylceramide (Hex1Cer) might be beneficial. Conclusions Our study revealed differentially expressed lipid patterns in MM and HC. PC, PE, and ceramides showed outstanding diagnostic performance, while TG and Hex1Cer exhibited significant prognostic values. Nevertheless, more studies should verify these trends as well as further investigating underlying mechanisms.

COVID-19 is an acute respiratory disease caused by SARS-CoV-2, which has high transmissibility. People infected with SARS-CoV-2 can develop symptoms including cough, fever, pneumonia and other complications, which in severe cases could lead to death. In addition, a proportion of people infected with SARS-CoV-2 may be asymptomatic. At present, the primary diagnostic method for COVID-19 is reverse transcription-polymerase chain reaction (RT-PCR), which tests patient samples including nasopharyngeal swabs, sputum and other lower respiratory tract secretions. Other detection methods, e.g., isothermal nucleic acid amplification, CRISPR, immunochromatography, enzyme-linked immunosorbent assay (ELISA) and electrochemical sensors are also in use. As the current testing methods are mostly performed at central hospitals and third-party testing centres, the testing systems used mostly employ large, high-throughput, automated equipment. Given the current situation of the epidemic, point-of-care testing (POCT) is advantageous in terms of its ease of use, greater approachability on the user's end, more timely detection, and comparable accuracy and sensitivity, which could reduce the testing load on central hospitals. POCT is thus conducive to daily epidemic control and achieving early detection and treatment. This paper summarises the latest research advances in POCT-based SARS-CoV-2 detection methods, compares three categories of commercially available products, i.e., nucleic acid tests, immunoassays and novel sensors, and proposes the expectations for the development of POCT-based SARS-CoV-2 detection including greater accessibility, higher sensitivity and lower costs.

Background Malignant mesothelioma (MM) is a rare and highly aggressive cancer. Despite advances in multidisciplinary treatments for cancer, the prognosis for MM remains poor with no effective diagnostic biomarkers currently available. The aim of this study was to identify plasma metabolic biomarkers for better MM diagnosis and prognosis by use of a MM cell line-derived xenograft (CDX) model. Methods The MM CDX model was confirmed by hematoxylin and eosin staining and immunohistochemistry. Twenty female nude mice were randomly divided into two groups, 10 for the MM CDX model and 10 controls. Plasma samples were collected two weeks after tumor cell implantation. Gas chromatography-mass spectrometry analysis was conducted. Both univariate and multivariate statistics were used to select potential metabolic biomarkers. Hierarchical clustering analysis, metabolic pathway analysis, and receiver operating characteristic (ROC) analysis were performed. Additionally, bioinformatics analysis was used to investigate differential genes between tumor and normal tissues, and survival-associated genes. Results The MM CDX model was successfully established. With VIP > 1.0 and P-value < 0.05, a total of 23 differential metabolites were annotated, in which isoleucine, 5-dihydrocortisol, and indole-3-acetamide had the highest diagnostic values based on ROC analysis. These were mainly enriched in pathways for starch and sucrose metabolism, pentose and glucuronate interconversions, galactose metabolism, steroid hormone biosynthesis, as well as phenylalanine, tyrosine and tryptophan biosynthesis. Further, down-regulation was observed for amino acids, especially isoleucine, which is consistent with up-regulation of amino acid transporter genes SLC7A5 and SLC1A3 in MM. Overall survival was also negatively associated with SLC1A5, SLC7A5, and SLC1A3. Conclusion We found several altered plasma metabolites in the MM CDX model. The importance of specific metabolic pathways, for example amino acid metabolism, is herein highlighted, although further investigation is warranted.