Allergy

Modeling microbiome modulation of tumor metabolic networks to predict synergistic therapies.

Differences in microbiome composition profoundly influence drug response, yet methods to model the metabolic impact of microbes on host cells and therapeutics remain limited. We present a microbiome-aware computational framework combining machine learning and genome-scale metabolic models to predict combination therapies for colorectal cancer (CRC) in the presence of Fusobacterium nucleatum (Fn) a...

iHaptenAb: an integrated hapten-antibody database for rational hapten design and antibody discovery.

Antibodies targeting small molecules play indispensable roles in food safety, environmental monitoring, clinical diagnostics, and immunotherapy. The generation of such antibodies critically depends on hapten design. Although several generic antibody databases exist, an open resource that specifically integrates haptens and the corresponding antibody performance has remained unavailable, thereby li...

AI-driven dual-task prediction model for co-stratifying efficacy and toxicity in NSCLC immunotherapy.

While effective against non-small cell lung cancer (NSCLC), PD-1 inhibitors can induce immune-related adverse events (irAEs), occurring in up to 15.2%...

Cancer immunotherapy under immune pressure: Mechanisms of resistance and the shift toward precision immune engineering.

Cancer immunotherapy has transformed the treatment landscape across multiple malignancies; however, durable responses remain limited to a subset of pa...

Single-Atom Nanozymes for High-Efficiency Cancer Immunotherapy by Targeting Tumor Microenvironment.

Tumor immunotherapy has emerged as a transformative strategy for cancer treatment. However, its clinical efficacy remains limited by the immunosuppres...

Manual and automated capture of analgesic-responsive facial pain behaviors of unrestrained mice in a trigeminal neuralgia model.

Trigeminal neuralgia (TN), a devastating neuropathic pain condition, profoundly affects human well-being. Despite an initial response to carbamazepine...

AI-Driven Digital Tools for Atopic Dermatitis: A Scoping Review.

BACKGROUND: Atopic dermatitis (AD) affects around 20% of children and up to 10% of adults. Its fluctuating course, severe pruritus, and impact on slee...

HTS-Oracle v2: Prospective Ai-Guided Discovery and Experimental Validation of Small Molecule Modulators Across Multiple Targets.

High-throughput screening (HTS) remains the cornerstone of early phase small molecule discovery yet consistently underperforms against immunotherapy t...

Rational drug design for Alzheimer's disease: from approved therapies to next-generation clinical candidates and AI-guided innovation.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by multifactorial pathology, including amyloid-β (Aβ) aggregation, ...

CT radiomics machine learning for predicting treatment response in unresectable stage III-IV NSCLC: insights from dual chemo-immunotherapy and immunotherapy cohorts.

PURPOSE: The purpose of this study was to develop a machine learning model based on radiomic features extracted from baseline contrast-enhanced CT sca...

Bending-Stable Pressure Sensor Based on Natural Wood Nanofibers for Ultra-Low Detection Limit.

Flexible pressure sensors, essential for intelligent electronic skins, are valued for their versatility and integration. However, the inherent couplin...

Current status and challenges of immune checkpoint inhibitors in liver cancer: from monotherapy to combination strategies.

Hepatocellular carcinoma (HCC) has an extremely poor prognosis. The emergence of immune checkpoint inhibitors (ICIs) has fundamentally transformed the...

Integrated Identification of NAD⁺ Metabolism-Associated Candidate Genes.

Migraine is one of the most disabling neurological diseases globally; however, a significant proportion of patients do not respond to current treatmen...

Recent advances on AI-driven decoding of tertiary lymphoid structures in precision cancer immunotherapy.

Tertiary lymphoid structures (TLS) are organized ectopic immune aggregates within the tumor microenvironment and have been associated with prognosis a...

Identification of obesity risk factors in 3-12-year-old children and adolescents with prior respiratory tract infections via interpretable machine and deep learning models.

BACKGROUNDS AND OBJECTIVES: Childhood obesity and respiratory tract infections (RTIs) are 2 major global public health issues that frequently co-occur...

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating im...

Non-invasive prediction of dupilumab response in facial atopic dermatitis using early post-treatment reflectance confocal microscopy features.

BACKGROUND: Non-invasive prediction of the efficacy of dupilumab on facial lesions in patients with atopic dermatitis (AD) was unresolved. OBJECTIVE: ...

Automated Detection and Classification of Pollen Grains Using YOLO-Based Deep Learning Models.

Authentication of high-value honey, particularly from the biodiverse Anzer Valley, relies on melissopalynology to verify botanical origin. However, tr...

TSTScope Unifies Single-Cell Multi-Omics to Identify Functional T Cell States Predictive of Immunotherapy Response.

Immune checkpoint blockade (ICB) can produce durable responses in cancer, but reliable predictors of benefit are still lacking. CD8+ tumor-specific T ...

Prognostic risk modeling based on integrated multi-omics analysis identifies CRY2 as a key regulator in tumor immunity and patient survival in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) exhibits substantial metabolic heterogeneity. This study developed a robust prognostic signature integrating ferro...