Pulmonology

Stem loop binding protein promotes SARS-CoV-2 replication via -1 programmed ribosomal frameshifting.

The -1 programmed ribosomal frameshifting (-1 PRF) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for keeping the balance between pp1a and pp1ab polyproteins. To date, the host factors influencing this process remain poorly understood. Using RNA pull-down assays combined with mass spectrometry screening, we discovered five host proteins interacting with -1 PRF RNA, incl...

Automatic Discovery and Optimal Generation of Amorphous High-Entropy Electrocatalysts.

Amorphous materials are ubiquitous in nature and are widely used for many industrial applications, including catalysis, energy storage, and environmental science. However, significant challenges remain in designing and optimizing amorphous high-entropy materials because of the lack of well-defined structure-activity relationships. Here, we use synthesis systems to discover and optimize amorphous h...

Artificial intelligence-based quantitative bone marrow pathology analysis for myeloproliferative neoplasms.

The evaluation of bone marrow pathology is essential for diagnosing and classifying myeloproliferative neoplasms (MPNs). However, morphological assess...

Dendritic cell dysfunction, including impaired IL-12 production, is associated with chronic pulmonary aspergillosis.

BACKGROUND: Growing evidence links immune dysfunction, notably impaired IFNγ production, to chronic pulmonary aspergillosis (CPA), but understanding o...

Clinical Utility of Pulmonary Function Testing in Assessing Longitudinal Outcomes of Deployed Veterans with Preserved Spirometry.

Deployment to the Southwest Asia Theater of Military Operations is associated with new-onset respiratory symptoms, yet commonly-used parameters on pul...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

The kidney is a target organ for the dysregulated host response to infection that defines sepsis, and acute kidney injury (AKI) is often an early mani...

Early prediction of bronchopulmonary dysplasia: comparison of modelling methods, development and validation studies.

BACKGROUND: Machine-learning methods are gaining in popularity to predict medical events but their added value to other methods is still to be determi...

CT-based deep learning model for improved disease-free survival prediction in clinical stage I lung cancer: a real-world multicenter study.

OBJECTIVES: To develop a deep learning (DL) model for predicting disease-free survival (DFS) in clinical stage I lung cancer patients who underwent su...

A strategy for the automatic diagnostic pipeline towards feature-based models: a primer with pleural invasion prediction from preoperative PET/CT images.

BACKGROUND: This study aims to explore the feasibility to automate the application process of nomograms in clinical medicine, demonstrated through the...

Multiscale-fusion models with genomic, topological and pathomic features to predict response to radiation therapy for non-small cell lung cancer patients.

Artificial intelligence models with biomarkers to predict treatment responses to radiation would be necessary to maximise the treatment outcomes of in...

Machine Learning-Driven COVID-19 Hospitalization Forecasting: From Theory to Practice in a Major Northeastern Academic Medical Center.

BACKGROUND: Predicting seasonal and emerging waves of respiratory viruses is crucial for effective public health responses. Despite significant effort...

Artificial Intelligence in Chronic Disease Management for Aging Populations: A Systematic Review of Machine Learning and NLP Applications.

As China's elderly population grows rapidly and the aging society arrives, the number of elderly patients with chronic diseases (mainly including chro...

Predicting Stroke-Associated Pneumonia in Acute Ischemic Stroke: A Machine Learning Model Development and Validation Study with CBC-Derived Inflammatory Indices.

PURPOSE: Stroke-associated pneumonia (SAP), a critical complication of ischemic stroke, significantly worsens outcomes. Our aim was to identify SAP ri...

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Un...

Artificial Intelligence Quantitation of Steatosis on Frozen Section Preimplant Slides Correlates with Some Liver Transplant Outcomes.

Introduction.Increased steatosis on preimplant liver frozen section is associated with delayed graft function and primary nonfunction. Efforts to stan...

Next-Generation Sequencing-Based Testing Among Patients With Advanced or Metastatic Nonsquamous Non-Small Cell Lung Cancer in the United States: Predictive Modeling Using Machine Learning Methods.

BACKGROUND: Next-generation sequencing (NGS) has become a cornerstone of treatment for lung cancer and is recommended in current treatment guidelines ...

Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report.

BACKGROUND: The rapid advancements in natural language processing, particularly the development of large language models (LLMs), have opened new avenu...

Implementation costs and cost-effectiveness of ultraportable chest X-ray with artificial intelligence in active case finding for tuberculosis in Nigeria.

Availability of ultraportable chest x-ray (CXR) and advancements in artificial intelligence (AI)-enabled CXR interpretation are promising developments...

Machine Learning Driven Synthesis of Cobalt Oxide Entrapped Heteroatom-Doped Graphitic Carbon Nitride for Enhanced Oxygen Evolution Reaction.

Developing highly efficient electrocatalysts for the oxygen evolution reaction is hindered by sluggish multi-electron kinetics, poor charge transfer e...

Improving lung cancer diagnosis and survival prediction with deep learning and CT imaging.

Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment are crucial for improving patients' survival outcomes. In thi...