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Reactive oxygen species (ROS) and reactive sulfur species (RSS) are involved in many physiological processes and act as collaborators with crosstalk. As an important member of gasotransmitters and RSS, hydrogen sulfide (H2S) carries out signaling functions at submicromolar levels because of its high reactivity. Mechanisms of dynamic regulation of ROS and H2S production are poorly understood, and the development of a highly selective and organelle-targeted chemical tool will advance the further understanding of H2S chemical biology and ROS/RSS crosstalk. Herein, we report a highly selective and sensitive, endoplasmic reticulum (ER)-targeted fluorescent probe (ER-BODIPY-NBD) for revealing cisplatin-induced H2S biogenesis for the first time. The probe demonstrates a 152-fold fluorescence enhancement at 520 nm after reaction with H2S to release a bright BODIPY product (quantum yield 0.36). The probe is highly selective toward H2S over biothiols, ER-targeted, and biocompatible. In addition, the probe was successfully employed to track H2S biogenesis in live cells via stimulation from exogenous hypochlorous acid and the drug cisplatin. [ABSTRACT FROM AUTHOR]

A growing of evidence has showed that patients with osteoarthritis (OA) had a higher coronavirus 2019 (COVID-19) infection rate and a poorer prognosis after infected it. Additionally, scientists have also discovered that COVID-19 infection might cause pathological changes in the musculoskeletal system. However, its mechanism is still not fully elucidated. This study aims to further explore the sharing pathogenesis of patients with both OA and COVID-19 infection and find candidate drugs. Gene expression profiles of OA (GSE51588) and COVID-19 (GSE147507) were obtained from the Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) for both OA and COVID-19 were identified and several hub genes were extracted from them. Then gene and pathway enrichment analysis of the DEGs were performed; protein–protein interaction (PPI) network, transcription factor (TF)-gene regulatory network, TF-miRNA regulatory network and gene-disease association network were constructed based on the DEGs and hub genes. Finally, we predicted several candidate molecular drugs related to hub genes using DSigDB database. The receiver operating characteristic curve (ROC) was applied to evaluate the accuracy of hub genes in the diagnosis of both OA and COVID-19. In total, 83 overlapping DEGs were identified and selected for subsequent analyses. CXCR4, EGR2, ENO1, FASN, GATA6, HIST1H3H, HIST1H4H, HIST1H4I, HIST1H4K, MTHFD2, PDK1, TUBA4A, TUBB1 and TUBB3 were screened out as hub genes, and some showed preferable values as diagnostic markers for both OA and COVID-19. Several candidate molecular drugs, which are related to the hug genes, were identified. These sharing pathways and hub genes may provide new ideas for further mechanistic studies and guide more individual-based effective treatments for OA patients with COVID-19 infection. [ABSTRACT FROM AUTHOR]

Objective: Patients with chronic ankle instability (CAI) may experience ankle force sense deficits due to mechanoreceptor injury and proprioceptive deafferentation in the affected ankles. This study aimed to systematically review the literature and investigate (1) whether patients with CAI have impaired force sense when compared with uninjured contralateral sides or healthy controls, and (2) which characteristics of CAI (e.g., any measurement of CAI symptoms, clinical questionnaires, or functional tests on the injured ankles) are correlated with force sense deficits. Type: Systematic review and meta‐analysis. Literature Survey: PubMed, Embase, Web of Science, Cochrane Library, Scopus, CINAHL, and SPORTDiscus were searched for ankle‐related, injury‐related, and force sense‐related terms from inception to February 2, 2022. Methodology: The following information was extracted from included articles: demographic data, sample size, selection criteria, methodology, force reproduction test outcomes, and correlations between force sense and other characteristics of CAI. Meta‐analyses were conducted for the force sense outcomes, and a narrative review was undertaken for the correlation between force sense deficits and other characteristics of CAI. Synthesis: Eight studies were included. The meta‐analyses revealed eversion force sense deficits of the injured ankles in absolute error (magnitude of force reproduction error) at 20% maximal voluntary isometric contractions (MVIC) (standardized mean difference [SMD] = 0.67, 95% confidence interval [CI] 0.23–1.11) and variable error (consistency of force reproduction) at 30% MVIC (SMD = 0.46, 95% CI 0.07–0.85), as compared with healthy controls. None of the included studies reported a significant correlation between these two deficits and other characteristics of CAI. Conclusions: Patients with CAI have eversion force sense deficits in the magnitude of force reproduction error at 20% MVIC and the consistency of force reproduction at 30% MVIC. [ABSTRACT FROM AUTHOR]

Virtual try-on technology has wide application and research value in promoting the informatization and intelligence of the clothing industry, and is one of the research hotspots of artificial intelligence in the field of intelligent clothing manufacturing. At present, virtual try-on mainly focuses on two-dimensional virtual try-on based on image generation. This paper provides a comprehensive overview of two-dimensional virtual try-on technology. It introduces and analyzes traditional virtual try-on, and categorizes and summarizes the main tasks, types, development process, and models of existing two-dimensional virtual try-on technology. It also discusses in detail the principles and related improvements of representative algorithms of various types. It summarizes the application of traditional virtual try-on and two-dimensional virtual try-on technology, and discusses the extension technology of two-dimensional virtual try-on technology. It summarizes and compares the benefits and drawbacks of using traditional and current virtual try-on technology, as well as summarizes and forecasts the field's future development. [ABSTRACT FROM AUTHOR]

Studying the impact of various factors on environmental perception is crucial because humans live in an environment where these factors interact and blend. The thermal-acoustic environment is the major factor that affects the overall perception of urban parks. This study focuses on urban parks in the subtropical region, with Xihu Park in Fuzhou, China, as the research area. Through measurements and questionnaires, this study explores the effects of the thermal-acoustic environment in urban parks on subjective evaluation (thermal assessment, acoustic assessment, and overall environmental assessment). The results reveal that: (1) a higher temperature significantly increases the sensation of heat and lowers thermal comfort, heat acceptance, and overall thermal environment evaluation scores. The type of sound source has a significant positive impact on thermal assessment, and the higher the ranking of the sound source type, the greater its positive impact on thermal assessment. (2) Regarding acoustic evaluation, higher sound pressure level is associated with more negative subjective ratings of loudness, harshness, intensity, and excitement. In contrast, positive sound sources can enhance comfort, preference, disorder, coordination, and overall soundscape evaluation. Additionally, temperature increases tend to result in more negative harshness, intensity, and coordination ratings. The interaction between temperature and sound pressure level also significantly affects subjective loudness, harshness, and intensity. (3) Overall environmental evaluation is also affected by temperature, with increasing temperatures leading to decreased comfort and satisfaction while increasing irritation. High sound pressure environments result in worse overall irritation ratings, while positive sound sources can significantly enhance overall comfort, irritation, and satisfaction ratings. Furthermore, the interaction between temperature and sound pressure level significantly impacts overall irritation and satisfaction ratings. These findings are significant for managing and improving the park's thermal environment and soundscape, providing a practical framework for landscape architects. [ABSTRACT FROM AUTHOR]

Many important machine learning applications involve regularized nonconvex bi-level optimization. However, the existing gradient-based bi-level optimization algorithms cannot handle nonconvex or nonsmooth regularizers, and they suffer from a high computation complexity in nonconvex bi-level optimization. In this work, we study a proximal gradient-type algorithm that adopts the approximate implicit differentiation (AID) scheme for nonconvex bi-level optimization with possibly nonconvex and nonsmooth regularizers. In particular, the algorithm applies the Nesterov's momentum to accelerate the computation of the implicit gradient involved in AID. We provide a comprehensive analysis of the global convergence properties of this algorithm through identifying its intrinsic potential function. In particular, we formally establish the convergence of the model parameters to a critical point of the bi-level problem, and obtain an improved computation complexity O ~ (κ 3.5 ϵ - 2) over the state-of-the-art result. Moreover, we analyze the asymptotic convergence rates of this algorithm under a class of local nonconvex geometries characterized by a Łojasiewicz-type gradient inequality. Experiment on hyper-parameter optimization demonstrates the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]

Betavoltaic batteries can meet long-term energy supply needs. However, due to the decay of the radioactive source, the output performance of battery will change over time, and the laws of this change require elucidation to aid the battery engineer. In this study, the influences of time on the apparent power density and β-energy spectrum of the 63 Ni source were clarified. Moreover, the structural parameters, including the p-region, n-region doping concentrations, and junction depth of GaN-based (hexagonal) p–n junction, were optimized, which are 2 × 1017 cm–3, 1014 cm–3, and 0.1 μm, respectively. In particular, the time-related performance trends were analyzed, and a formula for the maximum output power density deterioration was obtained, which can be used to evaluate the performance of 63 Ni GaN-based p–n junction betavoltaic battery within 200 years. The simulation results showed that the maximum output power density of battery after 50 years is 0.243 μW cm−2, which is only 60% of the initial value. In addition, the other output performances, namely, the short-circuit current density, open-circuit voltage, fill factor, and conversion efficiency are 0.096 μA cm−2, 2.67 V, 94.3%, and 20.5%, respectively. [ABSTRACT FROM AUTHOR]

Position detection is essential for precise contactless manipulation as it can play an important role in analyzing the behavior patterns and motion regularities of levitated objects. However, traditional detection methods have several limitations, such as finite feature representation, low detection accuracy, and poor adaptability, notably for small targets. To address these issues, this paper proposes an effective detector called RFRM-CenterNet, which is the first attempt to detect the location of levitated objects based on a convolutional neural network. First, a receptive field refinement module consisting of multi-stage parallel dilated convolutional layers is designed to detect small levitated objects. Then, to increase the feature representation capability, a feature fusion network is designed, which employs a parallel fusion of ResNet50 and a receptive field refinement module. In addition, an experimental system is constructed, and a dataset is established to train the model and verify the performance of the proposed method. The experimental results show that RFRM-CenterNet has better performance in detecting levitated objects than other detection methods. [ABSTRACT FROM AUTHOR]