Allergy & Immunology

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to co...

Feature selection enhances peptide binding predictions for TCR-specific interactions.

INTRODUCTION: T-cell receptors (TCRs) play a critical role in the immune response by recognizing specific ligand peptides presented by major histocompatibility complex (MHC) molecules. Accurate prediction of peptide binding to TCRs is essential for advancing immunotherapy, vaccine design, and understanding mechanisms of autoimmune disorders.

Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.

Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Therefore, it is imperative to develop sophisticated t...

Analysis of the sensitization activity of leaves protein.

The determination of allergenic proteins in leaves, which is the main components of immune activity, has enabled the development of a more effective ...

Unpaired Dual-Modal Image Complementation Learning for Single-Modal Medical Image Segmentation.

OBJECTIVE: Multi-modal MR/CT image segmentation is an important task in disease diagnosis and treatment, but it is usually difficult to acquire aligne...

Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.

BACKGROUND: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in bra...

Computational biology and artificial intelligence in mRNA vaccine design for cancer immunotherapy.

Messenger RNA (mRNA) vaccines offer an adaptable and scalable platform for cancer immunotherapy, requiring optimal design to elicit a robust and targe...

Cellular Senescence in Hepatocellular Carcinoma: Immune Microenvironment Insights via Machine Learning and In Vitro Experiments.

Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell c...

Immunological composition of human milk before and during subclinical and clinical mastitis.

Mastitis, an inflammatory condition affecting more than 25% of breastfeeding women, is usually associated with reduced milk secretion, pain, and disco...

Leveraging Deep Learning for Immune Cell Quantification and Prognostic Evaluation in Radiotherapy-Treated Oropharyngeal Squamous Cell Carcinomas.

The tumor microenvironment plays a critical role in cancer progression and therapeutic responsiveness, with the tumor immune microenvironment (TIME) b...

Automatic machine learning accurately predicts the efficacy of immunotherapy for patients with inoperable advanced non-small cell lung cancer using a computed tomography-based radiomics model.

PURPOSE: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomar...

DeepDrug as an expert guided and AI driven drug repurposing methodology for selecting the lead combination of drugs for Alzheimer's disease.

Alzheimer's Disease (AD) significantly aggravates human dignity and quality of life. While newly approved amyloid immunotherapy has been reported, eff...

Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning.

In the production sector, the usefulness of predictive systems as a tool for management and decision-making is well known. In the agricultural sector,...

HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates.

The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective tr...

Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods.

BACKGROUND: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is...

Assessing ChatGPT's accuracy and reliability in asthma general knowledge: implications for artificial intelligence use in public health education.

BACKGROUND: Integrating Artificial Intelligence (AI) into public health education represents a pivotal advancement in medical knowledge dissemination,...

The role of mitophagy-related genes in prognosis and immunotherapy of cutaneous melanoma: a comprehensive analysis based on single-cell RNA sequencing and machine learning.

Mitophagy, the selective degradation of mitochondria by autophagy, plays a crucial role in cancer progression and therapy response. This study aims to...

A novel machine learning-based immune prognostic signature for improving clinical outcomes and guiding therapy in colorectal cancer: an integrated bioinformatics and experimental study.

Immune cells are pivotal components in the tumor microenvironment (TME), which can interact with tumor cells and significantly influence cancer progre...

The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading.

We developed an AI system capable of automatically classifying anterior eye images as either normal or indicative of corneal diseases. This study aims...

Advancing precision cancer immunotherapy drug development, administration, and response prediction with AI-enabled Raman spectroscopy.

Molecular characterization of tumors is essential to identify predictive biomarkers that inform treatment decisions and improve precision immunotherap...