Vibrational spectroscopy at electrolyte/electrode interfaces with graphene gratings.

Microscopic understanding of physical and electrochemical processes at electrolyte/electrode interfaces is critical for applications ranging from batteries, fuel cells to electrocatalysis. However, probing such buried interfacial processes is experimentally challenging. Infrared spectroscopy is sensitive to molecule vibrational signatures, yet to approach the interface three stringent requirements have to be met: interface specificity, sub-monolayer molecular detection sensitivity, and electrochemically stable and infrared transparent electrodes. Here we show that transparent graphene gratings electrode provide an attractive platform for vibrational spectroscopy at the electrolyte/electrode interfaces: infrared diffraction from graphene gratings offers enhanced detection sensitivity and interface specificity. We demonstrate the vibrational spectroscopy of methylene group of adsorbed sub-monolayer cetrimonium bromide molecules and reveal a reversible field-induced electrochemical deposition of cetrimonium bromide on the electrode controlled by the bias voltage. Such vibrational spectroscopy with graphene gratings is promising for real time and in situ monitoring of different chemical species at the electrolyte/electrode interfaces

EVIL: Evidential Inference Learning for Trustworthy Semi-supervised Medical Image Segmentation

Recently, uncertainty-aware methods have attracted increasing attention in semi-supervised medical image segmentation. However, current methods usually suffer from the drawback that it is difficult to balance the computational cost, estimation accuracy, and theoretical support in a unified framework. To alleviate this problem, we introduce the Dempster-Shafer Theory of Evidence (DST) into semi-supervised medical image segmentation, dubbed Evidential Inference Learning (EVIL). EVIL provides a theoretically guaranteed solution to infer accurate uncertainty quantification in a single forward pass. Trustworthy pseudo labels on unlabeled data are generated after uncertainty estimation. The recently proposed consistency regularization-based training paradigm is adopted in our framework, which enforces the consistency on the perturbed predictions to enhance the generalization with few labeled data. Experimental results show that EVIL achieves competitive performance in comparison with several state-of-the-art methods on the public dataset

Mechanisms connecting square dance to sleep quality among middle-aged and older Chinese females: serial mediation roles of social support and depressive symptoms

BackgroundSquare dance is gaining increasing popularity among middle-aged and older Chinese women who are also at high risk of sleep disturbance. Although previous studies have shown exercise could improve sleep quality, the association between square dance and sleep quality remains to be discussed, and even less is known about the potential mechanism underlying this association.PurposeThis study aims to investigate the relationship between square dance and sleep quality and test if social support and depressive symptoms together play a serial mediating role in the influence of square dance on sleep quality.MethodsA cross-sectional study was conducted among 549 middle-aged and older Chinese females from September to December 2020 in Shao Yang City, Hunan Province of China, with ethics approval granted (SYU [2020]002). Square dance involvement was assessed by three questions about the time participants spent in square dance. Social support, depressive symptoms, and sleep quality were measured using the Pittsburgh Sleep Quality Index (PSQI), Social Support Self-Rating Scale (SSRS), and 9-item Patient Health Questionnaire (PHQ-9), respectively. The serial mediation model was analyzed by the bootstrapping method to assess whether social support and depressive symptoms mediate the relationship between square dance and sleep quality.ResultsTwo-thirds of the participants had high involvement in square dance and most reported a moderate and high level of social support (98.54%). The prevalence of depressive symptoms and sleep disturbance was 19.49 and 26.78%, respectively. The serial mediation model showed a significant association between square dance and sleep quality, which was fully mediated by social support and depressive symptoms in a serial model (total effect c = −0.114, 95%CI = −0.227 to −0.001; direct effect c’ = −0.036, 95% CI = −0.138 to 0.065; total indirect effect ab = −0.077, 95% CI = -0.139 to-0.016).ConclusionOur study extends the understanding of how square dance is associated with sleep quality through the serial mediating roles of social support and depressive symptoms. It provides crucial implications for developing square dance interventions to improve sleep quality among middle-aged and older Chinese females

The therapeutic effects of low-intensity pulsed ultrasound in musculoskeletal soft tissue injuries: Focusing on the molecular mechanism

Musculoskeletal soft tissue injuries are very common and usually occur during both sporting and everyday activities. The intervention of adjuvant therapies to promote tissue regeneration is of great importance to improving people’s quality of life and extending their productive lives. Though many studies have focused on the positive results and effectiveness of the LIPUS on soft tissue, the molecular mechanisms standing behind LIPUS effects are much less explored and reported, especially the intracellular signaling pathways. We incorporated all research on LIPUS in soft tissue diseases since 2005 and summarized studies that uncovered the intracellular molecular mechanism. This review will also provide the latest evidence-based research progress in this field and suggest research directions for future experiments

TAGAP expression influences CD4+ T cell differentiation, immune infiltration, and cytotoxicity in LUAD through the STAT pathway: implications for immunotherapy

BackgroundT-cell Activation GTPase Activating Protein (TAGAP) plays a role in immune cell regulation. This study aimed to investigate TAGAP’s expression and its potential impact on CD4+ T cell function and prognosis in lung adenocarcinoma (LUAD).MethodsWe analyzed TAGAP expression and its correlation with immune infiltration and clinical data in LUAD patients using multiple datasets, including The Cancer Genome Atlas (TCGA-LUAD), Gene Expression Omnibus (GEO), and scRNA-seq datasets. In vitro and in vivo experiments were conducted to explore the role of TAGAP in CD4+ T cell function, chemotaxis, and cytotoxicity.ResultsTAGAP expression was significantly lower in LUAD tissues compared to normal tissues, and high TAGAP expression correlated with better prognosis in LUAD patients. TAGAP was positively correlated with immune/stromal/ESTIMATE scores and immune cell infiltration in LUAD. Single-cell RNA sequencing revealed that TAGAP was primarily distributed in CD4+/CD8+ T cells. In vitro experiments showed that TAGAP overexpression enhanced CD4+ T cell cytotoxicity, proliferation, and chemotaxis. Gene Set Enrichment Analysis (GSEA) indicated that TAGAP was enriched in the JAK-STAT signaling pathway. In vivo experiments in a xenograft tumor model demonstrated that TAGAP overexpression suppressed tumor growth and promoted CD4+ T cell cytotoxicity.ConclusionsTAGAP influences CD4+ T cell differentiation and function in LUAD through the STAT pathway, promoting immune infiltration and cytotoxicity. This study provides a scientific basis for developing novel LUAD immunotherapy strategies and exploring new therapeutic targets

KM-FCM: A fuzzy clustering optimization algorithm based on Mahalanobis distance

The traditional fuzzy clustering algorithm uses Euclidean distance as the similarity criterion, which is disadvantageous to the multidimensional data processing. In order to solve this situation, Mahalanobis distance is used instead of the traditional Euclidean distance, and the optimization of fuzzy clustering algorithm based on Mahalanobis distance is studied to enhance the clustering effect and ability. With making the initialization means by Heuristic search algorithm combined with k-means algorithm, and in terms of the validity function which could automatically adjust the optimal clustering number, an optimization algorithm KM-FCM is proposed. The new algorithm is compared with FCM algorithm, FCM-M algorithm and M-FCM algorithm in three standard data sets. The experimental results show that the KM-FCM algorithm is effective. It has higher clustering accuracy than FCM, FCM-M and M-FCM, recognizing high-dimensional data clustering well. It has global optimization effect, and the clustering number has no need for setting in advance. The new algorithm provides a reference for the optimization of fuzzy clustering algorithm based on Mahalanobis distance

SBTAnalyzer: A data processing software package for single-bacterium tracking microscopy at material surfaces

Single-bacterium tracking is a powerful microscopy method for quantitative studying bacterial motility. This method requires analysis tools that can be used for microscopy video processing and extracting trajectories from the videos. In this paper, we report a software with capability of handling the above two requirements. Moreover, we have applied the developed software to a single-bacterium tracking study for Escherichia coli moving near glass surfaces. By performing video processing and bacterial trajectory extraction in an automated and convenient way, our proposed approach can greatly help single-bacterium tracking studies and could be listed as one of the useful tools for related quantitative investigations