Allergy

Multiparametric MRI-Based Deep Learning and Radiomics for Predicting Progression-Free Survival Benefit in Patients with Hepatocellular Carcinoma Treated with Immunotherapy and Targeted Therapy Plus Transarterial Chemoembolization: A Bicentric Study.

RATIONALE AND OBJECTIVES: The non-invasive biomarkers for predicting progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC) treated with immunotherapy and molecular targeted therapy combined with transarterial chemoembolization (IMT-MTT-TACE) are urgently needed to identify individuals who are likely to benefit from this treatment regimen. This study aims to develop a non-...

Nanoengineering of Exosomal Surfaces for Precision Targeting and Payload Delivery at the Molecular Level.

Exosomes, nano-sized extracellular vesicles secreted by almost all cell types, have emerged as biologically compatible vehicles for targeted drug delivery, gene therapy, and molecular diagnostics. Their innate ability to traverse biological barriers and deliver diverse cargoes with minimal immunogenicity has catalyzed intense interest in their therapeutic exploitation. However, the intrinsic heter...

Strategies of AI-Driven CAR-T Cell Therapy Towards Solid Tumours.

Chimeric antigen receptor (CAR)-T cell immunotherapy shows significant success in hematologic malignancies. However, it faces critical challenges in s...

Clinical Factors Associated With Current Relevance in Allergic Contact Dermatitis: Development of Predictive Models Based on Data From the Spanish Contact Dermatitis Register (REIDAC).

BACKGROUND: Current relevance of positive patch-test reactions guides management in allergic contact dermatitis (ACD), yet its clinical predictors and...

The consensus molecular subtypes of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) lacks a standardized classification system, resulting in inconsistent clinical management and a suboptimal p...

The value of artificial intelligence combined with multimodal data analysis in tumor immunotherapy and targeted therapy.

The advent of immunotherapy and targeted therapy has revolutionized oncology treatment in recent years, marking a transformative shift toward precisio...

Novel Lipid Nanoparticle (LNP) Delivery Systems Enabling the Advancement of RNA Therapeutics.

Lipid nanoparticle (LNP)-mRNA technology has profoundly transformed the biomedical landscape, establishing itself as a highly versatile and powerful p...

An odyssey of monoclonal gammopathies: focusing on precursors and the progression from MGUS and SMM to multiple Myeloma, with a brief overview of novel therapeutic strategies.

Monoclonal gammopathies span a continuum from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to overt...

Comparison of machine learning methods in forecasting and characterizing the birch and grass pollen season.

The primary approach to the treatment of seasonal allergic diseases involves minimizing exposure to allergens and initiating early personalized therap...

Nuclear medicine in predicting hepatocellular carcinoma response.

Immune checkpoint inhibitors and anti-angiogenic targeted therapies have improved outcomes in hepatocellular carcinoma (HCC), but responses remain het...

The 487-gene expression profile test guides systemic therapy selection to improve outcomes for patients with atopic dermatitis: Results from a prospective trial.

BACKGROUND: Current atopic dermatitis (AD) therapy selection does not account for molecular drivers of disease, contributing to inadequate disease con...

Predictors of sensitivity to immune therapies in classic Hodgkin lymphoma.

Immune checkpoint blockade, particularly programmed cell death protein 1 inhibition, has redefined the management of classic Hodgkin lymphoma (cHL), a...

Advancements and challenges in CAR-NK cell therapy for cancer treatment.

Chimeric antigen receptor natural killer (CAR-NK) cell therapy is an emerging cancer treatment offering advantages over CAR-T therapy, including reduc...

Exploratory identification of COL1A1 as a potential gene linking endocrine-disrupting chemicals and lung adenocarcinoma: a bioinformatics and machine learning analysis.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are common environmental pollutants that affect human health. These chemicals have been linked to th...

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunotherapy is heterogeneous. Machine learning can integrat...

Molecular Stratification of Antiphospholipid Syndrome Through Integrative Analysis of the Whole-Blood RNA Transcriptome.

OBJECTIVE: Antiphospholipid syndrome (APS) is a thromboinflammatory disorder characterized by clinical and mechanistic heterogeneity that complicates ...

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...

Automating classification of treatment responses to combined targeted therapy and immunotherapy in HCC.

Tyrosine kinase inhibitor (TKI) combined with immunotherapy regimens are now widely used for treating advanced hepatocellular carcinoma (HCC), but the...

Improving machine-learning development in allergology: bridging the gap between open-access and cohort-based databases.

PURPOSE OF REVIEW: The advent of high-throughput data generation and artificial intelligence has transformed allergy research. Open-access database (O...

AI Co-Scientists Move to the Front Lines of Cancer Research.

Artificial intelligence systems are beginning to function as "co-scientists" in cancer research, generating drug candidates, prioritizing immunotherap...