Analysis of Blood Pressure Status and Influencing Factors Among 7218 Emergency Department Nurses: An Observational Cross-Sectional Study.

As frontline healthcare workers, emergency department nurses face high levels of urgency in their work and are exposed to a high risk of contingencies. Their blood pressure status and influencing factors require close attention. This study employed a census method and conducted a cross-sectional survey in 11 cities in Hebei Province from November 2016 to July 2018, measuring blood pressure and collecting questionnaires on influencing factors.

Prediction of protein structural changes mediated by NS-SNPs in antibiotic resistance determinants in Streptococcus pneumoniae.

Streptococcus pneumoniae (S. pneumoniae) is a gram-positive bacterium, which is a human pathogen that colonises the human nasopharyngeal region. The evolution of its resistance to many antibiotics has become a major clinical and public health problem.

Enlarged Data Sets and Innovative Applicability Domain Characterization Empower ML Models to Reliably Bridge hERG Binding Data Gaps in Diverse Chemicals.

Chemicals may cause cardiotoxicity by binding to the K channel encoded by the human -related gene (hERG). Given the ever-increasing number of chemicals, developing models to efficiently fill the hERG binding affinity data gap is more desirable than conducting time-consuming experimental tests. However, previous data sets with limited chemical space hindered the development of models with high prediction accuracy and broad applicability domains (ADs).

Datt-AVP: Antiviral Peptide Prediction by Sequence-Based Dual Channel Network With Attention Mechanism.

With the frequent outbreak of viral pandemics, the search for efficient antiviral drugs has become an urgent task. Antiviral peptides (AVPs) have been proven to prevent the infection of host cells by viruses. This study proposes a novel tool called Datt-AVP for AVP prediction based on the peptide sequences.

Use of Modified YOLOv5 Algorithm in the Differential Diagnosis of Colonic Crohn's Disease and Ulcerative Colitis on CTE Images.

Inflammatory bowel disease (IBD) is an immune-mediated disorder characterized by intestinal inflammation and includes two subtypes: Crohn's disease (CD) and ulcerative colitis (UC). The computed tomography manifestations of colonic CD (cCD) and UC are similar, and differential diagnosis is challenging. Our study aimed to investigate the feasibility of using a modified YOLOv5 algorithm for differentiating between cCD and UC on computed tomography enterography (CTE) images.

Integrative single-cell and spatial transcriptomics uncover ELK4-mediated mechanisms in + tumor cells driving gastric cancer progression, metabolic reprogramming, and immune evasion.

Background: Globally, gastric cancer (GC) stands as the fifth most prevalent form of malignant neoplasm and represents a significant contributor to mortality associated with oncological conditions. Despite advancements in therapeutic strategies for GC, the outcomes for patients with advanced stages of the disease continue to be unfavorable, largely due to tumor heterogeneity and the challenges posed by resistance to therapeutic agents. Metabolic reprogramming is pivotal in driving the advancement of GC, contributing to the development of resistance to pharmacological treatments and facilitating the cancer's ability to evade immune surveillance.

Construction and validation of a nomogram model for cognitive impairment in heart failure patients.

Background: Patients with heart failure face a significantly elevated risk of cognitive impairment, yet clinical recognition remains inadequate-particularly among younger individuals and those with mild symptoms, leading to frequent underdiagnosis. The increasing prevalence among younger patients further worsens prognosis. This study aims to develop a tool to aid clinicians in the early identification of high-risk individuals and support informed clinical decision-making.

The Value of Intracranial Hemodynamic Parameters Derived From Phase-Contrast MRI in Predicting Severe Acute Mountain Sickness.

Background: Severe acute mountain sickness (sAMS) impacts the quality of life in individuals rapidly ascending to high altitudes. Intracranial hemodynamics are pathophysiologically linked to sAMS and may assist in identifying individuals susceptible to sAMS.

Purpose: To explore the predictive value of intracranial hemodynamic parameters for sAMS prior to rapid high-altitude exposure in normal subjects.

Surgical Refinement in Porcine Renal Autotransplantation - Flattening the Learning Curve in an Established Training Program.

Introduction: Complex animal models, such as the porcine renal autotransplantation (pRaTx) model, provide an excellent platform for translational research. The pRaTx model is challenging, offering many possibilities to refine surgical procedures and optimize learning curves and outcomes. In this study, we described the critical initial steps toward flattening the learning curve in pRaTx.

Machine Learning Models Based on Enlarged Chemical Spaces for Screening Carcinogenic Chemicals.

Machine learning (ML) models for screening carcinogenic chemicals are critical for the sound management of chemicals. Previous models were built on small-scale datasets and lacked applicability domain (AD) characterization that is necessary for regulatory applications of the models. In the current study, an enlarged dataset containing 1697 compounds (940 carcinogens and 757 non-carcinogens) was curated and employed to construct screening models based on 12 types of molecular fingerprints, four ML algorithms, and two graph neural networks.

Nucleic acid spheres for treating capillarisation of liver sinusoidal endothelial cells in liver fibrosis.

Liver sinusoidal endothelial cells (LSECs) lose their characteristic fenestrations and become capillarized during the progression of liver fibrosis. Mesenchymal stem cell (MSC) transplantation can reverse this capillarization and reduce fibrosis, but MSC therapy has practical limitations that hinder its clinical use. Here, with the help of artificial intelligence (AI), we show that MSCs secrete a microRNA (miR-325-3p) that helps restore LSEC fenestrations (tiny pores) by modulating their cytoskeleton, effectively reversing capillarization.

Consensus Modeling Strategies for Predicting Transthyretin Binding Affinity from Tox24 Challenge Data.

Transthyretin (TTR) is a key transporter of the thyroid hormone thyroxine, and chemicals that bind to TTR, displacing the hormone, can disrupt the endocrine system, even at low concentrations. This study evaluates computational modeling strategies developed during the Tox24 Challenge, using a data set of 1512 compounds tested for TTR binding affinity. Individual models from nine top-performing teams were analyzed for performance and uncertainty using regression metrics and applicability domains (AD).

Spatial layout characteristics of Northern Wei Luoyang: A spatial humanities analysis of the "Record of the Monasteries of Luoyang".

This paper explores the urban spatial structure and social stratification of Northern Wei Dynasty Luoyang City, based on Record of the Monasteries of Luoyang. Adopting a spatial humanities approach, the study integrates quantitative approaches, including the application of geographic information systems (GIS) for spatial analysis and complex network analysis. The findings indicate that the spatial organization of Northern Wei Luoyang was primarily concentrated within and around the inner city.

ChatOCT: Embedded Clinical Decision Support Systems for Optical Coherence Tomography in Offline and Resource-Limited Settings.

Optical Coherence Tomography (OCT) is a critical imaging modality for diagnosing ocular and systemic conditions, yet its accessibility is hindered by the need for specialized expertise and high computational demands. To address these challenges, we introduce ChatOCT, an offline-capable, domain-adaptive clinical decision support system (CDSS) that integrates structured expert Q&A generation, OCT-specific knowledge injection, and activation-aware model compression. Unlike existing systems, ChatOCT functions without internet access, making it suitable for low-resource environments.

Phenacetin[3]Arenes: Mannich-Type Macrocyclization, Unique Structure, Versatile Functionalization, and Strong Allosteric Binding.

This work introduces a novel N-CH₂-C macrocyclization pathway, diverging from the conventional C-CH₂-C linkages prevalent in macrocyclic arenes. This approach involves a one-pot condensation of - Phenacetin and its homologs with formaldehyde, yielding phenacetin[3]arenes (Ph[3]s) in yields up to 25.9%.

Exploring brain dysfunction in IBD: A study of EEG-fMRI source imaging based on empirical mode diagram decomposition.

Patients with inflammatory bowel disease (IBD) often suffer from mood disorders and cognitive decline, which has prompted research into abnormalities in emotional brain regions and their functional analysis. However, most IBD studies only focus on single-modality neuroimaging technologies. Due to a limited spatiotemporal resolution, it is unfeasible to fully explore deep brain source activities and accurately evaluate the brain functional connectivity.

Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis.

Invasiveness is a key indicator of tumor malignancy and is often linked to poor prognosis in breast cancer (BC). To explore the diverse characteristics of invasive cells, single-cell RNA sequencing (scRNA-seq) data from three ductal carcinoma stages were analyzed, classifying samples into invasion and non-invasion groups. Nine genes (MCTS1, PGK1, PCMT1, C8orf76, TMEM242, QPRT, SLC16A2, AFG1L, and SPINK8) were identified as key discriminators between these groups.

An interpretable radiomics-based machine learning model for predicting reverse left ventricular remodeling in STEMI patients using late gadolinium enhancement of myocardial scar.

Objectives: To evaluate the added value of the late gadolinium enhancement (LGE)-scar radiomics features in predicting reverse left ventricular remodeling (r-LVR) in ST-segment elevation myocardial infarction (STEMI) patients using machine learning (ML).

Materials And Methods: This retrospective study included 105 STEMI patients who underwent CMR within 7 days and 5 months post-percutaneous coronary intervention (PCI) on 1.5-T or 3.

Therapeutic Targets for Gastric Cancer: Mendelian Randomization and Colocalization Analysis.

Background: Gastric cancer (GC) is one of the most prevalent malignancies in the world. Most patients are diagnosed at advanced stages of the disease, primarily attributable to the insidious nature of early symptoms and the infrequent occurrence of routine screening. Further biomarkers are still needed for more comprehensive analysis, targeted prognostication, and effective treatment strategies.

Factors influencing community demand for assisted partner services for HIV in western Kenya: a multilevel qualitative analysis.

Objectives: This study explores factors affecting community-level demand for assisted partner services (APS) and HIV testing services (HTS) in western Kenya.

Design: This is a multilevel qualitative analysis conducted as part of the APS Scale-up Study, a hybrid type 2 implementation-effectiveness study of APS integrated within routine HTS. For this analysis, in-depth phone interviews assessed demand for APS and factors influencing decisions to participate in APS.

In situ osteogenic activation of mesenchymal stem cells by the blood clot biomimetic mechanical microenvironment.

Blood clots (BCs) play a crucial biomechanical role in promoting osteogenesis and regulating mesenchymal stem cell (MSC) function and fate. This study shows that BC formation enhances MSC osteogenesis by activating Itgb1/Fak-mediated focal adhesion and subsequent Runx2-mediated bone regeneration. Notably, BC viscoelasticity regulates this effect by modulating Runx2 nuclear translocation.

Imaging characteristics of brain microstructure and cerebral perfusion in Crohn's disease patients with anxiety: A prospective comparative study.

Background: Anxiety is a common comorbidity in patients with Crohn's disease (CD). Data on the imaging characteristics of brain microstructure and cerebral perfusion in CD with anxiety are limited.

Aim: To compare the imaging characteristics of brain microstructure and cerebral perfusion among CD patients with or without anxiety and healthy individuals.

Isolation, Identification, and Fermentation Optimization of Phytase-Producing Bacteria and Their Effects on Soybean Seedlings.

Phosphorus in soil mostly exists in complex compounds such as phytic acid, which reduces the effectiveness of phosphorus and limits agricultural production. Phytase has the activity of hydrolyzing phytate into phosphate. The mineralization of phytate in soil by phytase secreted by microorganisms is an effective way to improve the utilization rate of phytate.

Transfer Learning with a Graph Attention Network and Weighted Loss Function for Screening of Persistent, Bioaccumulative, Mobile, and Toxic Chemicals.

methods for screening hazardous chemicals are necessary for sound management. Persistent, bioaccumulative, mobile, and toxic (PBMT) chemicals persist in the environment and have high mobility in aquatic environments, posing risks to human and ecological health. However, lack of experimental data for the vast number of chemicals hinders identification of PBMT chemicals.

A comparative analysis of anthropometric indices for diagnosing obstructive sleep apnea among American Adults.

The occurrence of obstructive sleep apnea (OSA) syndrome is related to not only the overall obesity, but also the local distribution of fat. Therefore, we introduced anthropometric indicators to comprehensively assess the risks associated with obesity, including body mass index (BMI), which is used to assess the overall obesity, together with waist circumference (WC), body roundness index (BRI), visceral adiposity index (VAI) and lipid accumulation product (LAP), all of which reflect fat distribution. This cross-sectional study analyzed data from the 2005-2008 and 2015-2018 NHANES cycles, comprising 8966 participants.