SSIM over MSE: A new perspective for video anomaly detection.

Video anomaly detection plays a crucial role in ensuring public safety. Its goal is to detect abnormal patterns contained in video frames. Most existing models distinguish the anomalies based on the Mean Squared Error (MSE), which is hard to align with human perception, resulting in discrepancies between model-detected anomalies and those recognized by humans.

Mutant Pattern of p53 as a Feasible Predictor of Distant Metastasis Following Curative Gastrectomy for Advanced-stage Gastric Cancer.

The TP53 mutation is a poor prognostic factor for malignant tumors in a number of organs. The present study primarily aimed to clarify the impact of the mutant pattern of p53 on the prognosis and recurrence of gastric cancer. : For this purpose, 519 patients who underwent radical gastrectomy for cancer were enrolled in the present study.

Perceived discrimination as a predictor of cyberbullying: the mediating role of self-esteem and moderating role of self-compassion.

With the popularity of the internet, cyberbullying has emerged as an increasingly serious social issue, particularly affecting college students' behavioral health. This study explores the relationship between perceived discrimination and cyberbullying, as well as the mediating role of self-esteem and the moderating role of self-compassion (SC) in this relationship. Using a longitudinal design, data were collected from 892 Chinese college students (414 females, 478 males) in two waves spanning 1 year.

Unified Knowledge-Guided Molecular Graph Encoder with multimodal fusion and multi-task learning.

The remarkable success of Graph Neural Networks underscores their formidable capacity to assimilate multimodal inputs, markedly enhancing performance across a broad spectrum of domains. In the context of molecular modeling, considerable efforts have been made to enrich molecular representations by integrating data from diverse aspects. Nevertheless, current methodologies frequently compartmentalize geometric and semantic components, resulting in a fragmented approach that impairs the holistic integration of molecular attributes.

Mechanistic insights into carbonate radical-driven reactions: Selectivity and the hydrogen atom abstraction route.

Carbonate radical (CO) is inevitably produced in advanced oxidation processes (AOPs) when addressing real-world aqueous environments, yet it often goes unnoticed due to its relatively lower reactivity. In this study, we emphasized the pivotal role of CO in targeting the elimination of contaminants by contrasting it with conventional reactive oxygen species (ROSs) and assessing the removal of sulfamethazine (SMT). Similar to singlet oxygen (O), CO shows a preference for electron-rich organic compounds.

Computational evaluation of interactive dynamics for a full transcatheter aortic valve device in a patient-specific aortic root.

Transcatheter aortic valve implantation (TAVI) has become a key treatment for severe aortic stenosis, especially for patients unsuitable for surgery. Since its introduction in 2002, TAVI has advanced significantly due to improvements in imaging, operator skills, and device engineering. Despite these innovations, challenges in device sizing and positioning remain, complicating outcome predictions.

PDG2Seq: Periodic Dynamic Graph to Sequence Model for Traffic Flow Prediction.

Traffic flow prediction is the foundation of intelligent traffic management systems. Current methods prioritize the development of intricate models to capture spatio-temporal correlations, yet they often neglect the exploitation of latent features within traffic flow. Firstly, the correlation among different road nodes exhibits dynamism rather than remaining static.

FASNet: Feature alignment-based method with digital pathology images in assisted diagnosis medical system.

Many important information in medical research and clinical diagnosis are obtained from medical images. Among them, digital pathology images can provide detailed tissue structure and cellular information, which has become the gold standard for clinical tumor diagnosis. With the development of neural networks, computer-aided diagnosis presents the identification results of various cell nuclei to doctors, which facilitates the identification of cancerous regions.

Comparative proteomic analysis between tumor tissues and intratumoral exosomes from lung adenocarcinoma patients identifies PAFAH1B3 as an exosomal protein key for initiating metastasis in lung adenocarcinoma.

Mounting evidence strongly indicates that exosomes are pivotal in the advancement of cancer, yet the overarching profile of exosomal proteins and their contribution to lung adenocarcinoma (LUAD) progression remain underexplored. In our investigation, we isolated exosomes from treatment-naive LUAD (n = 20) and paired normal adjacent tissues (NATs), and conducted integrated proteomic on the acquired exosomes and source tissues to ascertain origin characteristics and potential therapeutic targets of the exosomal proteins in LUAD. The omics data revealed the overall landscape of exosomal proteins from tissues in LUAD, underscoring the profound linkage between exosomal proteins and tumor metastasis.

Analyte-Induced Specific Regulation of Light-Responsive COF-Cu Nanozyme Activity for Ultrafast Thiram Colorimetric Sensing.

A light-responsive covalent-organic framework (COF) nanozyme, which integrates the advantages of the COF structure and light-stimulated nanozyme catalysis, is a class of sensing star materials with wide application prospects. However, the sensing methods based on light-responsive COF nanozymes are relatively single at present. Therefore, it is necessary to develop new sensing strategies to broaden its application in chemical sensing and achieve highly efficient detection.

The effect of pin distractor assistance on the reduction of fibular fractures in the treatment of ankle fracture: A retrospective case-control study.

This study will evaluate the therapeutic effect of pin distractor assisted reduction of fibular fracture on ankle fracture. A retrospective analysis was performed on 98 patients diagnosed as ankle fracture or pilon fracture. These patients were all combined with fibular fracture.

How the cognitive load of simulated driving affects the brain dynamics underlying auditory attention.

Objective: Distracted driving is a primary contributor to for motor vehicle crashes, the leading cause for injuries and fatalities for youth. Although attention and working memory clearly underlie driving abilities, few studies explore these functions on the brain-level under the cognitive load of driving. To understand the load driving has on auditory attention processing, we examined the differences in dynamic brain response to auditory stimuli during LOAD (while driving in a high-fidelity driving simulator) and No-LOAD conditions (seated in simulator, parked on the side of the road).

Impact of select actionable genomic alterations on efficacy of neoadjuvant immunotherapy in resectable non-small cell lung cancer.

Background: Neoadjuvant immune checkpoint inhibitors (ICIs) have improved survival outcomes compared with chemotherapy in resectable non-small cell lung cancer (NSCLC). However, the impact of actionable genomic alterations (AGAs) on the efficacy of neoadjuvant ICIs remains unclear. We report the influence of AGAs on treatment failure (TF) in patients with resectable NSCLC treated with neoadjuvant ICIs.

Intelligent cell images segmentation system: based on SDN and moving transformer.

Diagnosing diseases heavily relies on cell pathology images, but the extensive data in each manual identification of relevant cells labor-intensive, especially in regions with a scarcity of qualified healthcare professionals. This study aims to develop an intelligent system to enhance the diagnostic accuracy of cytopathology images by addressing image noise and segmentation issues, thereby improving the efficiency of medical professionals in disease diagnosis. We introduced an innovative system combining a self-supervised algorithm, SDN, for image denoising with data enhancement and image segmentation using the UPerMVit model.

Graph explicit pooling for graph-level representation learning.

Graph pooling has been increasingly recognized as crucial for Graph Neural Networks (GNNs) to facilitate hierarchical graph representation learning. Existing graph pooling methods commonly consist of two stages: selecting top-ranked nodes and discarding the remaining to construct coarsened graph representations. However, this paper highlights two key issues with these methods: (1) The process of selecting nodes to discard frequently employs additional Graph Convolutional Networks or Multilayer Perceptrons, lacking a thorough evaluation of each node's impact on the final graph representation and subsequent prediction tasks.

A comparative study on contamination profiles of liquid crystal monomers (LCMs) between outdoor and indoor dusts, and the assessment of health risk of human exposure.

Liquid crystal monomers (LCMs) are ubiquitous in various environmental samples, which has led to increasing concerns regarding their potential health risks to humans and wildlife. However, the comparison of the contamination patterns of LCMs between indoor and outdoor environments has rarely been studied. In this study, 35 LCMs were investigated in n = 55 dust samples collected from indoor (n = 20) and outdoor (n = 35) spaces in Yulin, Northwest China.

AKR1B1-dependent fructose metabolism enhances malignancy of cancer cells.

Fructose metabolism has emerged as a significant contributor to cancer cell proliferation, yet the underlying mechanisms and sources of fructose for cancer cells remain incompletely understood. In this study, we demonstrate that cancer cells can convert glucose into fructose through a process called the AKR1B1-mediated polyol pathway. Inhibiting the endogenous production of fructose through AKR1B1 deletion dramatically suppressed glycolysis, resulting in reduced cancer cell migration, inhibited growth, and the induction of apoptosis and cell cycle arrest.

Mediating Effect of Cognitive Reserve in the Relationship Between Physical Activity and Cognitive Function in Community-Dwelling Older Adults.

The aim of this study was to investigate the mediating effect of cognitive reserve (CR) on the association between physical activity and cognitive function in community-dwelling older adults. A total of 495 community-dwelling older adults were included in this cross-sectional study. The CR, cognitive function, physical activity, and the potential confounders were assessed.

Multiregional transcriptomic profiling provides improved prognostic insight in localized non-small cell lung cancer.

Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels.

The health action process approach to promote regular physical activity among people with disabilities: A hierarchical regression analysis.

Objective: People with disabilities continue to cope with high levels of stress, such as disability-related stress and sociopolitical stress. Helping people with disabilities engage in regular physical activity to improve health and reduce stress is more important than ever. This study evaluated demographic covariates, the health action process approach (HAPA) constructs (action self-efficacy, outcome expectancy, risk perception, intention/commitment, maintenance and recovery self-efficacy, and action and coping planning), and positive person-environment variables (autonomous motivation, resilience, hope, and social support) as motivators for regular physical activity in a sample of people with disabilities.