Allergy & Immunology

Artificial Intelligence Powered Audiomics: The Futuristic Biomarker in Pulmonary Medicine - A State-of-the-Art Review.

AI-driven "audiomics" leverages voice and respiratory sounds as non-invasive biomarkers to diagnose and manage pulmonary conditions, including COVID-19, tuberculosis, ILD, asthma, and COPD. By analyzing acoustic features, machine and deep learning enhance diagnostic accuracy and track disease progression. Key applications include cough-based TB detection, smartphone COVID-19 screening, and speech ...

Artificial intelligence-enabled precision medicine for inflammatory skin diseases

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine learning approaches offer opportunities to enhance the diagnosis and treatment of inflammatory skin diseases, including atopic dermatitis, psoriasis, hidradenitis suppurativa, and autoimmune connective tissue disease. This review examines the current landscape...

An oral norovirus vaccine generates mucosal immunity and reduces viral shedding in a phase 2 placebo-controlled challenge study.

There are currently no licensed vaccines for norovirus, a leading cause of epidemic and endemic gastroenteritis worldwide. Clinical advancement of pro...

Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.

Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen. Nevertheless, the diagnostic rate remains below 6...

Development and validation of a deep learning model for diagnosing neuropathic corneal pain via in vivo confocal microscopy.

Neuropathic corneal pain (NCP) is an underdiagnosed ocular disorder caused by aberrant nociception and hypersensitivity of corneal nerves, often resul...

Innovations in maternal-fetal dermatology: A focus on artificial intelligence-driven diagnostics, global disparities, and transformative care.

Pregnancy-associated dermatologic conditions emerge from intricate hormonal, immunologic, genetic, and environmental changes, often complicating mater...

Artificial intelligence-enabled precision medicine for inflammatory skin diseases.

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine learning app...

IntrinsicEdit: Precise generative image manipulation in intrinsic space

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. How...

Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer.

Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strateg...

Targeting high-risk multiple myeloma genotypes with optimized anti-CD70 CAR-T cells.

Despite the success of BCMA-targeting CAR-Ts in multiple myeloma, patients with high-risk cytogenetic features still relapse most quickly and are in u...

Identifying Mild-to-Moderate Atopic Dermatitis Using a Generic Machine Learning Approach: A Danish National Health Register Study.

Atopic dermatitis is a chronic skin disease, causing itching and recurrent eczematous lesions. In Danish national register data, adults with atopic de...

Characteristics of lung sounds in early infants using automated analysis.

UNLABELLED: A new lung sound analysis software program has been developed. It can automatically select a typical lung sound spectrogram and calculate ...

Integrating different approaches for the identification of new disruptors of HIV-1 capsid multimerization.

Human Immunodeficiency Virus (HIV) belongs to the Lentivirus genus, Retroviridae family, enveloped by a lipid bilayer within which the capsid protein ...

Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis.

BACKGROUND: CD8T cells, also known as cytotoxic T lymphocytes, play a key role in the tumor immune microenvironment (TME) and immune response. The aim...

Fusogenic Lipid Nanovesicles as Multifunctional Immunomodulatory Platforms for Precision Solid Tumor Therapy.

Although immunotherapy demonstrates considerable prospect in overcoming solid tumors, its clinical efficacy is limited by several factors, such as poo...

Enhancing pyrrolizidine alkaloid separation and detection: LC-MS/MS method development and integration of ion mobility spectrometry into the LC-HRMS workflow.

Pyrrolizidine alkaloids (PAs) are plant toxins occurring in different foodstuffs, including teas, herbal infusions and species. Additionally, PAs may ...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged hospitalization in asthma patients.

Dendritic cell-based microrobots for enhanced systemic antigen-specific immune tolerance.

Current immunotherapeutic approaches for autoimmune disorders primarily rely on the use of generalized immunosuppressive medications. However, most im...

Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) is a novel predictive biomarker for chemotherapy and immunotherapy response, as well as prognostic indicat...

Identification of genetic indicators linked to immunological infiltration in idiopathic pulmonary fibrosis.

This study employed bioinformatics to investigate potential molecular markers associated with idiopathic pulmonary fibrosis (IPF) and examined their c...