Allergy

AI-driven cellular immunotherapy: transforming CAR-T engineering and translation.

Chimeric antigen receptor T (CAR-T) cell therapy has demonstrated remarkable success in hematologic malignancies but faces persistent challenges in solid tumors and broader clinical translation, including limited target specificity, heterogeneous tumor antigen expression, unpredictable functional outcomes, and complex manufacturing processes. Recent advances in artificial intelligence (AI) are beg...

Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.

T-cell receptor (TCR) cross-reactivity, whereby a single TCR recognizes multiple peptide-MHC (pMHC) ligands, is essential for immune surveillance but also represents a major safety challenge for TCR-based therapeutics because of severe off-target toxicities. Rapid advances in immune-repertoire sequencing, structural biology, and immunopeptidomics have accelerated computational efforts to character...

Deep Learning of CT Imaging Predicts PD-L1 Expression and Immunotherapy Response in Metastatic NSCLC: A Multi-Center Study.

Immune checkpoint inhibitors (ICIs) benefit only a subset of patients with metastatic non-small cell lung cancer (NSCLC), but current selection relies...

Mapping the TCR landscape: computational tools empowering translational immunology and therapy design.

T cell receptors (TCRs) are central to adaptive immunity, yet their vast sequence and structural diversity present a significant challenge to fully un...

Deep Learning vs. Traditional Machine Learning in the Diagnosis of Cutaneous Drug Eruptions: A Comparative Study with Explainable AI on Whole-Slide Images.

Histopathological diagnosis of cutaneous drug eruptions (CDEs) presents a challenge in dermatopathology due to morphological overlap and high inter-ob...

Exploration of key stress granule-related genes in chronic sinusitis based on transcriptomics.

Chronic rhinosinusitis with nasal polyps (CRSwNP) frequently induces the formation of intracellular stress granules (SGs). This study aims to identify...

Scalable multiplexed machine learning gas sensor chips for food classification.

Multiplexed gas sensor arrays combined with machine learning have unlocked previously inaccessible applications for scent-based sensing. Current platf...

Machine learning discriminates bacterial, fungal, and viral infections using temporal blood analyte dynamics in bottlenose dolphins (Tursiops truncatus).

OBJECTIVE: To determine underlying infectious disease as bacterial, fungal, or viral in origin from longitudinal assessment of biochemistry and hemato...

Allergic rhinitis in the elderly. In collaboration with ARIA guidelines.

Rhinitis in the elderly represents a unique challenge, due to specific clinical profiles, needs and expectations. Allergic rhinitis (AR) in the elderl...

Single-cell transcriptomic analysis reveals the T lymphocyte microenvironment and identifies HOPX as a hub gene in membranous nephropathy.

BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment....

Fatty acid synthesis therapy-induced senescence (FASTIS) in cancer cells.

Therapy-induced senescence (TIS) in cancer cells can be triggered by radiotherapy, chemotherapy, and certain targeted therapeutics. Here, we demonstra...

Advancing fungal sinusitis diagnosis: a radiomics and machine learning approach.

BACKGROUND: Differentiating fungal from chronic sinusitis remains a diagnostic challenge due to overlapping symptoms. OBJECTIVES: This study aims to e...

Single-cell multi-omics dissection of RevitalAge Markers uncovers age-dependent immunotherapy resistance and druggable targets in melanoma.

Aging-related molecular reprogramming profoundly influences melanoma progression and therapeutic sensitivity, yet underlying mechanisms remain poorly ...

Integrative spatiotemporal transcriptomics identifies a liver metastasis-related initial cell population associated with the SEMA3A-NRP1 axis in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy in which liver metastasis represents the principal determinant of po...

Cellular architecture and neighborhood-informed virtual spatial tumor profiling from histopathology.

The tumor microenvironment (TME) critically shapes disease progression and therapeutic resistance. However, a comprehensive understanding of its spati...

Transcriptomic profiling identifies immunotherapy-responsive phenotypes in microsatellite-stable metastatic colorectal cancer.

Conventional immune checkpoint inhibitors (ICIs) remain largely ineffective in microsatellite-stable metastatic colorectal cancer (MSS mCRC), where lo...

Clinically actionable classification tool for childhood and adult atopic dermatitis via explainable AI: a retrospective cross-sectional study optimizing diagnostic accuracy.

BACKGROUND: Despite the critical role of early identification in managing atopic dermatitis (AD), current studies are limited by the absence of adult-...

Drug-induced multisystem syndromes: An overlooked challenge in pharmacovigilance.

BackgroundDrug-Induced Multisystem Syndromes (DIMS) represent a clinically significant yet under-recognized group of delayed immune-mediated adverse d...

A novel computational framework for tumor-specific T cell antigen identification using a deep neural network.

Identifying tumor-specific T-cell antigens is essential for advancing cancer immunotherapy and enabling precision-driven, AI-assisted discovery. While...

Machine learning-based identification of basement membrane-related signature to predict recurrence and immunotherapy benefit in bladder cancer.

The basement membrane (BM) plays a critical role in regulating bladder cancer (BC) progression. However, a BM-related signature for predicting BC recu...