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VUStruct: A compute pipeline for high throughput and personalized structural biology.

Effective diagnosis and treatment of rare genetic disorders requires the interpretation of a patient's genetic variants of unknown significance (VUSs). Today, clinical decision-making is primarily guided by gene-phenotype association databases and DNA-based scoring methods. Our web-accessible variant analysis pipeline, VUStruct, supplements these established approaches by deeply analyzing the down...

Cost-effectiveness of latent tuberculosis infection screening using interferon-gamma release assays among migrants to Japan: a Markov modelling study incorporating social vulnerability and access barriers.

OBJECTIVE: This study aims to evaluate the cost-effectiveness of latent tuberculosis infection (LTBI) screening strategies using interferon-gamma release assays (IGRAs) among migrants, integrating social vulnerability and access barriers into the modelling framework to support more inclusive public health policy. DESIGN: A Markov state-transition model was constructed from a public healthcare paye...

Genetic variants and polygenic risk scores associated with paroxysmal atrial fibrillation in the Japanese population.

Early-stage diagnosis of paroxysmal atrial fibrillation (PAF) is challenging owing to its asymptomatic nature. However, the genetic factors underlying...

Decoding the neural mechanisms of salty peptide perception via electroencephalography and machine learning.

Excessive sodium intake poses major public health risks, driving the search for salt substitutes that preserve desirable flavor. Salty peptides have e...

An integrated microneedle device for skin interstitial fluid multiplexed detection and deep learning-based analysis of acute myocardial infarction biomarkers.

Acute myocardial infarction (AMI) remains difficult to diagnose rapidly outside hospital settings because current evaluation still relies mainly on el...

Regional mapping of soil heavy metals via a novel deep learning approach: A case study in the Yangtze River Delta, China.

Accurate regional mapping of soil heavy metals is increasingly supported by multi-source environmental covariates, yet predictive performance is often...

Engineered artificial antigen-presenting cells for tumor immunotherapy: Design strategies, clinical applications, and translational challenges.

Immunotherapy has long played a pivotal role in cancer treatment, and antigen-presenting cell (APC)-based immunotherapy represents a promising strateg...

Machine learning-based cardiovascular risk prediction in systemic lupus erythematosus: development and internal validation of a prognostic model.

BACKGROUND: Cardiovascular (CV) diseases are the leading cause of mortality in patients with systemic lupus erythematosus (SLE). While traditional ris...

Enhancing corporate bankruptcy prediction and customer relationship sustainability through CNN-based financial feature transformation.

Corporate bankruptcy prediction is essential for assessing companies' capacity to maintain sustainable customer relationships and service quality. Thi...

Predicting Prognosis for Gastric Cancer Patients Receiving Neoadjuvant Treatment With Body Composition-Based Deep Learning.

BACKGROUND: This study sought to develop an innovative body composition (BC)-based deep learning (DL) model to precisely evaluate survival in gastric ...

Overexpression of NMNAT3 suppresses melanoma progression by reprogramming NAD⁺ metabolism.

BACKGROUND: Melanoma represents a highly aggressive and metastatic form of malignant skin cancer. that remains challenging to treat clinically. Tumor ...

Estimating band importance for environmental sound recognition using deep learninga).

Environmental sound recognition (ESR) enables listeners to interpret complex acoustic environments, yet the frequency regions that support recognition...

Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.

Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite rec...

Template-Based Label Propagation for Mouse Brain MRI Skull Stripping.

Accurate skull stripping is an essential preprocessing step in mouse brain magnetic resonance imaging, particularly for reliable atlas registration an...

Balancing Speed and Sensitivity: Echo-Planar Accelerated MRI for ARIA-H Screening in Anti-Aβ Therapeutics.

The recent advent of anti-amyloid-β monoclonal antibodies has introduced new demands for MRI-based screening of amyloid-related imaging abnormalities,...

Quantifying Repetitive Hand Flapping Kinematics in Autistic and Non-Autistic Toddlers Using Video-Based Pose Estimation.

While repetitive behaviors such as hand flapping are associated with autism, non-autistic toddlers also exhibit this behavior (e.g., when excited), ma...

Multiparametric MRI-based Deep Learning and Radiomics for Evaluating Lymph Node Metastasis in Early-Stage Cervical Cancer.

Purpose To develop a multiparametric MRI-based radiomics model and deep learning-radiomics (DLR) fusion model for preoperative prediction of lymph nod...

Development and Internal Validation of a Machine Learning Model for Predicting Long-Term Opioid Therapy After Hip Fracture Surgery in Older, Opioid-Naïve Adults.

BACKGROUND: Long-term opioid therapy (LTOT) after hip fracture surgery is a common postoperative complication associated with adverse outcomes, yet to...

Integrating AI-enhanced kinase enrichment analysis (KEA) with geometric deep learning and federated learning for precision drug repurposing.

Artificial intelligence (AI) is reshaping drug repurposing by integrating systems biology with molecular design. Here, we present a unified framework ...

Microstate permutation complexity of EEG signals distinguishes minimally conscious state plus from minimally conscious state minus.

BACKGROUND: Accurately distinguishing minimally conscious state plus (MCS+) from minimally conscious state minus (MCS-) is critical for prognosis and ...