Deep Learning-based Segmentation of Cervical Posterior Longitudinal Ligament Ossification in CT Images and Assessment of Spinal Cord Compression: A Two-center Study.

Objective: This study aims to develop a fully automated, CT-based deep learning（DL） model to segment ossified lesions of the posterior longitudinal ligament (OPLL) and to measure the thickness of the ossified material and calculate the cervical spinal cord compression factor.

Materials And Methods: A total of 307 patients were enrolled, with 260 patients from Shanghai Changzheng Hospital, And 47 patients from the Traditional Chinese Medicine Hospital of Southwest Medical University. CT images were used to manually segment the OPLL by four experienced radiologists.

Association between mixed exposure to dioxins and dioxin-like polychlorinated biphenyls and obesity among U.S. adults.

Backgrounds: Previous studies have suggested the potential links between dioxins or dioxin-like polychlorinated biphenyls (DL-PCBs) and obesity. However, the combined effects of dioxins and DL-PCBs on obesity are still unclear.

Methods: Nine kinds of dioxins and DL-PCBs were measured among 852 adults using the National Health and Nutrition Examination Survey (NHANES) from 2003-2004.

The m6A demethylase ALKBH5 is a novel epigenetic regulator of aortic valve calcification.

Aims: Calcific aortic valve disease (CAVD) is a common heart valve disease with significant clinical consequences. The mechanisms that drive the pathogenesis of CAVD remain to be fully elucidated. N6-methyladenosine (m6A), the most prevalent RNA epigenetic regulator, has recently been implicated in cardiovascular disease, but its role in CAVD has yet to be investigated.

Association between oral health-related behaviors and quality of life of adolescents among three provinces in Northwest China.

Objective: To assess the oral health-related quality of life (OHRQoL) of adolescents in Northwest China, and to explore the relationship between sociodemographic characteristics, oral health-related behaviors and OHRQoL.

Methods: A cross-sectional survey of adolescents aged 12-15 years in Shaanxi, Gansu province and Ningxia Hui Autonomous Region of Northwest China was conducted by stratified cluster random sampling. Oral examinations were performed with World Health Organization (WHO) standards, and the condition of crowns and periodontal was recorded.

The role of epigenetic regulation in pancreatic ductal adenocarcinoma progression and drug response: an integrative genomic and pharmacological prognostic prediction model.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with poor prognosis. Epigenetic dysregulation plays a crucial role in PDAC progression, but its comprehensive landscape and clinical implications remain unclear.

Methods: We integrated single-cell RNA sequencing, bulk RNA sequencing, and clinical data from multiple public databases.

Cytoplasmic Aggregates of Splicing Factor Proline-Glutamine Rich Disrupt Nucleocytoplasmic Transport and Induce Persistent Stress Granules.

Splicing factor proline-glutamine rich (SFPQ), a multifunctional RNA-binding protein (RBP), shows cytoplasmic colocalisation with stress granule (SG) markers; however, the causative relationship and mechanism underlying this coalescence of SFPQ aggregates and SGs remain unclear. In this study, we demonstrate that SFPQ lacking its nuclear localisation sequence spontaneously forms cytoplasmic aggregates that abnormally incorporate immature RNA and induce persistent SGs. mRNA profiling showed that SFPQ mislocalisation induced extensive changes in RNA processing, with a subset of alternatively spliced transcripts associated with nucleocytoplasmic transport.

Recognition of parasitic helminth eggs via a deep learning-based platform.

Introduction: Accurate and rapid diagnosis is crucial for the effective treatment of parasitosis. Traditional etiological methods, especially microscopic examination, are time-consuming, labor-intensive, and prone to false or missed detections. In response to these challenges, this study explores the use of artificial intelligence (AI) for the detection and classification of human parasite eggs through the YOLOv4 deep learning object detection algorithm.

Long-term survival and failure patterns in inoperable early-stage non-small cell lung cancer following stereotactic body radiotherapy: a single-institution retrospective study.

This study is to analyse the failure patterns and long-term survival after stereotactic body radiotherapy (SBRT) in patients with T1-3N0M0 inoperable non-small cell lung cancer (NSCLC). Early-stage NSCLC patitents who received SBRT at Zhejiang Cancer Hospital from January 2012 to September 2018 were retrospectively analyzed. The primary endpoint were the patterns of disease progression, which were divided into local recurrence, regional failure, and distant metastasis.

Ferroptosis in Osteoarthritis: Towards Novel Therapeutic Strategy.

Osteoarthritis (OA) is a chronic, degenerative joint disease primarily characterised by damage to the articular cartilage, synovitis and persistent pain, and has become one of the most common diseases worldwide. In OA cartilage, various forms of cell death have been identified, including apoptosis, necroptosis and autophagic cell death. Ever-growing observations indicate that ferroptosis, a newly-discovered iron-dependent form of regulated cell death, is detrimental to OA occurrence and progression.

Visible Light-Promoted and Catalyst-Controlled α-Aminoalkylation and α-Diaminoalkylation of Morita-Baylis-Hillman Acetates with -Methyl Arylamines: Divergent Synthesis of -Containing Alkyl Acrylates and γ,γ-Diaminobutyl Esters.

Visible light-promoted α-aminoalkyl radical-triggered α-aminoalkylation and α-diaminoalkylation of Morita-Baylis-Hillman acetates with -methyl arylamines to synthesize -containing alkyl acrylates and γ,γ-diaminobutyl esters was reported. Photoinduced α-aminoalkylation is carried out with Na-eosin Y as an organophotocatalyst at room temperature under metal- and oxidant-free conditions. In particular, the α-diaminoalkylation is performed via α-aminoalkyl radical addition/elimination followed by a catalyst-controlled selective α-aminoalkyl radical addition strategy in one step under the [Ir(dtbbpy)(bpy))]PF/KF catalytic system.

A Meta-analysis of the Regulation of Low-Density Lipoprotein Cholesterol and Proprotein Convertase Subtilisin-Kexin Type 9 with Inclisiran.

Objective: This study aimed to systematically evaluate the regulation of low-density lipoprotein cholesterol (LDL-C) and proprotein convertase subtilisin-kexin type 9 (PCSK9) with inclisiran using a meta-analysis.

Methods: A comprehensive search of PubMed, Embase, the Cochrane Library, and Web of Science was conducted for randomized controlled trials of inclisiran published up to April 2024. Stata software was used for statistical analysis of outcome indicators from the included studies.

MRI-Negative Temporal Lobe Epilepsy: A Study of Brain Structure in Adults Using Surface-Based Morphological Features.

Background: This research aimed to delve into the cortical morphological transformations in patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE-N), seeking to uncover the neuroimaging mechanisms behind these changes.

Methods: A total of 29 individuals diagnosed with TLE-N and 30 healthy control participants matched by age and sex were selected for the study. Using the surface-based morphometry (SBM) technique, the study analyzed the three-dimensional-T1-weighted MRI scans of the participants' brains.

log-RRIM: Yield Prediction via Local-to-global Reaction Representation Learning and Interaction Modeling.

Accurate prediction of chemical reaction yields is crucial for optimizing organic synthesis, potentially reducing time and resources spent on experimentation. With the rise of artificial intelligence (AI), there is growing interest in leveraging AI-based methods to accelerate yield predictions without conducting in vitro experiments. We present log-RRIM, an innovative graph transformer-based framework designed for predicting chemical reaction yields.

Influence of speed and line spacing on aerodynamic forces in high speed train passing in tunnels.

As train speeds increase, the aerodynamic effects generated during the passage of high-speed trains in tunnels become more pronounced. This article investigates the influence of line spacing on the aerodynamic forces during the passage of high-speed trains in tunnels at different speeds. The research methodology is based on the three-dimensional transient compressible Reynolds-averaged Navier-Stokes (RANS) equations and the k-ω Shear Stress Transport (SST) turbulence model, using overset grid technology to simulate the train passing process in the tunnel.