Electrochemical Trifluoromethylation/1,5-HAT Reaction of -Cyanamide Alkenes: Synthesis of Trifluoromethylated Cyclic Amidines and -Acryloylpyrrolidin-2-one Derivatives.

The electrochemical trifluoromethylation/1,5-HAT of -cyanamide alkenes with CFSONa has been achieved to construct trifluoromethylated cyclic amidines and -acryloylpyrrolidin-2-one derivatives. This transformation was performed with readily available starting materials under mild conditions and required neither oxidants nor transition metal catalysts, exhibiting high atom economy.

Development of the International Classification of Functioning, Disability and Health (ICF) core set for stroke survivors in community-based rehabilitation settings in Hong Kong.

Purpose: This study aimed to develop an ICF core set for assessing stroke survivors in community-based rehabilitation settings in Hong Kong.

Material And Methods: A three-round Delphi process which involved 39 multidisciplinary experts in community-based rehabilitation services was conducted to reach consensus on a preliminary version of ICF core set for stroke survivors. The initial questionnaire included 130 second-level ICF categories while the panel was invited to suggest additional categories.

Kinship verification via correlation calculation-based multi-task learning.

Previous studies have demonstrated that metric learning approaches yield remarkable performance in the field of kinship verification. Nevertheless, a prevalent limitation of most existing methods lies in their over-reliance on learning exclusively from specified types of given kin data, which frequently results in information isolation. Although generative-based metric learning methods present potential solutions to this problem, they are hindered by substantial computational costs.

Enhancing fake news detection with transformer-based deep learning: A multidisciplinary approach.

The widespread dissemination of fake news presents a critical challenge to the integrity of digital information and erodes public trust. This urgent problem necessitates the development of sophisticated and reliable automated detection mechanisms. This study addresses this gap by proposing a robust fake news detection framework centred on a transformer-based architecture.

NU-1000/Cu Nanocomposite-Immobilized Organophosphate Hydrolase for the Cascade Conversion of Methyl Parathion to 4-Aminophenol.

Effective degradation and detoxification of the highly toxic organophosphate pesticide methyl parathion (MP) are important for pollution treatment and sustainable development. Enzymatic hydrolysis of MP by organophosphate hydrolase (OPH) is an effective way. However, hydrolytic product 4-nitrophenol (4-NP) remains environmentally hazardous.

Scenario simulation analysis of urbanization spatial pattern optimization promoting regional coordinated development: A case study of Guizhou, China.

This research delves into the optimization of urbanization spatial patterns in Guizhou Province, China. The findings reveal that with regional coordinated development as the central objective and the optimization of urbanization spatial patterns as the strategic focus, a research framework encompassing "temporal and spatial evolution of urbanization - identification and summation of pain points and difficulties - scenario simulation and optimization - strategic goal selection" is utilized to specifically tackle issues pertaining to urbanization spatial patterns. Through the construction of diverse scenarios and rigorous research analysis, an implementation pathway is derived, advocating for "strengthening the central region of Guizhou, fostering urban agglomeration development, reinforcing developmental support points, and promoting regional coordinated development.

STmiR: A Novel XGBoost-based framework for spatially resolved miRNA activity prediction in cancer transcriptomics.

MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.

Long sequence temporal knowledge tracing for student performance prediction via integrating LSTM and informer.

Knowledge tracing can reveal students' level of knowledge in relation to their learning performance. Recently, plenty of machine learning algorithms have been proposed to exploit to implement knowledge tracing and have achieved promising outcomes. However, most of the previous approaches were unable to cope with long sequence time-series prediction, which is more valuable than short sequence prediction that is extensively utilized in current knowledge-tracing studies.

High Prevalence of Macrolide-resistant ptxP3-prn150 Bordetella pertussis in Jiangsu Province, China, 2024.

Background: A significant surge in pertussis cases since early 2023 has raised serious public health concerns. To investigate the potential mechanisms contributing to this increased prevalence, we collected throat swab specimens from children exhibiting pertussis symptoms and conducted detailed molecular characterization.

Methods: All Bordetella pertussis (B.

KG-MACNF: A nonlinear cross-modal fusion model for predicting drug-target interactions via multi-relational embedding and fine-grained structure.

Drug-target interaction (DTI) prediction is essential for the development of novel drugs and the repurposing of existing ones. However, when the features of drug and target are applied to biological networks, there is a lack of capturing the relational features of drug-target interactions. And the corresponding multimodal models mainly depend on shallow fusion strategies, which results in suboptimal performance when trying to capture complex interaction relationships.

Efficacy and mechanism of high-purity HAMCC combined with CGF in promoting the repair of radiation-induced skin and soft tissue damage.

Radiotherapy, a prevalent and effective treatment for various malignancies, often causes collateral damage to normal skin and soft tissues in the irradiated area. To address this, we developed a novel approach combining SVFG-modified adipose-derived high-activity matrix cell clusters (HAMCC) with concentrated growth factors (CGF) to enhance regeneration and repair of radiation-induced skin and soft tissue injuries. Our study included cellular assays, wound healing evaluations, and histological analyses.

Prediction of modal parameters for thin-walled blade milling process considering material removal effect.

Accurate prediction of time-varying dynamic parameters during the milling process is a prerequisite for chatter-free cutting of thin-walled parts. In this paper, a matrix iterative prediction method based on weighted parameters is proposed for the time-varying structural modes during the milling of thin-walled blade structures. The thin-walled blade finite element model is established based on the 4-node plate element, and the time-varying dynamic parameters of the workpiece during the cutting process can be obtained by modifying the thickness of the nodes through the constructed mesh element finite element model It is not necessary to re-divide the mesh elements of the thin-walled parts at each cutting position, thus improving the calculation efficiency of the dynamic parameters of the workpiece.

Cultural heritage of the Qin-Shu Ancient Road in Shaanxi: Spatial distribution characteristics and influencing factors.

This study investigates the spatial and temporal distribution and the influencing factors of 579 cultural heritage sites along the Qin-Shu Ancient Road in Shaanxi Province, employing kernel density estimation, buffer analysis, and geographic detectors. Three key findings emerge: (1) The spatial pattern is characterized by a "line-belt-core" structure, with a belt-like aggregation along the Xi'an-Baoji-Hanzhong axis. Core concentrations are found in Xi'an (181 sites), Hanzhong (159 sites), and Ankang (122 sites), with secondary concentrations in Baoji (72 sites) and Shangluo (36 sites).

Unveiling additive effects on molecular packing and charge transfer in organic solar cells: an AIMD and DFT study.

Additive assisted strategies play a crucial role in optimizing the morphology and improving the performance of organic solar cells (OSCs), yet the molecular-level mechanisms remain unclear. Here, we employ molecular dynamics (AIMD) and density functional theory (DFT) to elucidate the influence of typical additives of 1,8-diiodooctane (DIO) and 3,5-dichlorobromobenzene (DCBB) on molecular packing, electronic structures, and charge transport. It can be observed that both additives can enhance the stacking properties of the donor and acceptor materials, yet they have different effects on the local electrostatic environment.

Impact of digital technology on herders' grassland leasing-in decisions in Inner Mongolia, China.

Against the backdrop of grassland ecological degradation, grassland transfer has become a crucial pathway for optimizing livestock resource allocation and promoting sustainable pastoral development. Based on survey data from 383 herder households in the farming-pastoral ecotone of Inner Mongolia, China, this study applies Heckman models, mediation models, and moderation models to examine the impact of digital technology on herders' grassland leasing-in decisions and the underlying mechanisms. The results indicate that digital technology significantly increases both the probability and the scale of grassland leasing-in among herders.

Integrative network toxicology and molecular docking reveal 4-Nonylphenol's multifaceted mechanisms in breast cancer pathogenesis.

Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.

Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.

Development efficiency of green logistics in Guangdong province based on Super-SBM and GML index.

Under China's national sustainability strategy, the logistics industry is confronted with the imperative of high-quality green development. Given its status as the leading economic province and a national logistics hub, investigating green logistics development in Guangdong province holds paramount strategic importance. To comprehensively evaluate green logistics development efficiency of 21 cities in Guangdong from 2016 to 2022, this study employed the super-efficiency slacks-based measure model (Super-SBM) with undesirable outputs, the Global Malmquist-Luenberger (GML) productivity index and a four-quadrant analysis based on static and dynamic efficiency.

1p-Enh-regulated CYP4B1 alleviates NNK-induced heart failure and lung cancer via the STAT3 pathway.

Heart failure (HF) and lung cancer (LC) often coexist, yet their shared molecular mechanisms are unclear. We analyzed transcriptome data from the NCBI Gene Expression Omnibus (GEO) database (GSE141910, GSE57338) to identify 346 HF‑related differentially expressed genes (DEGs), then combined weighted gene co-expression network analysis (WGCNA) pinpointed 70 hub candidates. Further screening of these 70 hub candidates in TCGA lung cancer cohorts via LASSO, Random Forest, and multivariate Cox regression suggested CYP4B1 as the only independent prognostic marker.

Competency of triage nurse in the emergency department: A scoping review protocol.

Introduction: Triage is an essential strategy to mitigate crowding and guarantee patients' safety in emergency departments. To improve the quality of triage in emergency departments, Nurses should be equipped with the necessary competencies. Therefore, this review aims to synthesize available evidence on the competency elements required for triage nurses in emergency departments and to identify factors that influence their competency development.

Construct prediction models for low muscle mass with metabolic syndrome using machine learning.

Background: Metabolic syndrome (MetS) and sarcopenia are major global public health problems, and their coexistence significantly increases the risk of death. In recent years, this trend has become increasingly prominent in younger populations, posing a major public health challenge. Numerous studies have regarded reduced muscle mass as a reliable indicator for identifying pre-sarcopenia.

How data assets influence enterprise persistent innovation: Evidence from China.

This study investigates the impact of data assets on enterprise persistent innovation using panel data from Chinese A-share listed firms from 2011 to 2022. The results indicate that data assets significantly enhance both the inputs and outputs of enterprise persistent innovation, with the findings remaining robust under endogeneity tests. Mediation analysis reveals that data assets influence enterprise persistent innovation through three key channels: process innovation, business innovation, and technological innovation.

Cognitive load suppresses explicit learning while sparing implicit learning in visuomotor adaptation.

Limiting cognitive resources negatively impacts motor learning, but its cognitive mechanism is still unclear. Previous studies failed to differentiate its effect on explicit (or cognitive) and implicit (or procedural) aspects of motor learning. Here, we designed a dual-task paradigm requiring participants to simultaneously perform a visual working memory task and a visuomotor rotation adaptation task to investigate how cognitive load differentially impacted explicit and implicit motor learning.

Comprehensive analysis of disulfidptosis-related genes in pulmonary hypertension through machine learning and immune infiltration: Spotlight on USP32 and ZNF655 as key regulators.

Background: Disulfidptosis, a novel cellular death manner, has yet to be fully explored within the context of pulmonary arterial hypertension (PAH). This study aims to identify genes implicated in PAH that are involved in disulfidptosis.

Method: Based on data from the GEO database, this study employed co-expression analysis, Weighted Gene Co-Expression Network Analysis (WGCNA), hub gene identification, and Gene Set Enrichment Analysis (GSEA) to uncover genes associated with PAH and disulfidptosis.

Kidney stone disease increases the risk of cardiovascular events.

Introduction: Kidney stone disease is associated with numerous cardiovascular risk factors. However, the findings across studies are non-uniformly consistent, and the control of confounding variables remains suboptimal. This study aimed to investigate the association between kidney stone and cardiovascular disease.