Allergy

Development and Validation an Integrated Deep Learning Model to Assist Eosinophilic Chronic Rhinosinusitis Diagnosis: A Multicenter Study.

BACKGROUND: The assessment of eosinophilic chronic rhinosinusitis (eCRS) lacks accurate non-invasive preoperative prediction methods, relying primarily on invasive histopathological sections. This study aims to use computed tomography (CT) images and clinical parameters to develop an integrated deep learning model for the preoperative identification of eCRS and further explore the biological basis...

Broadly active intranasal influenza vaccine with a nanocomplex particulate adjuvant targeting mast cells and toll-like receptor 9.

Flumist is the only FDA-approved intranasal influenza vaccine. Although it has recently been approved for at-home use, it has significant limitations. These include reduced effectiveness in generating a protective immune response in patients with extensive influenza exposure, safety concerns due to its live attenuated virus formulation, and reduced efficacy due to viral drift/shift. To address thi...

Clinical prediction model by machine learning to determine the results of maternal dietary avoidance in food protein-induced allergic proctocolitis infants.

OBJECTIVE: The objective of this study was to investigate the factors associated with the results of maternal dietary avoidance in infants diagnosed w...

De Novo Design of Highly Stable Binders Targeting Dihydrofolate Reductase in Klebsiella pneumoniae.

The study aims to design novel therapeutic inhibitors targeting the DHFR protein of Klebsiella pneumoniae. However, challenges like bacterial resistan...

Predicting Immunotherapy Response in Unresectable Hepatocellular Carcinoma: A Comparative Study of Large Language Models and Human Experts.

Hepatocellular carcinoma (HCC) is an aggressive cancer with limited biomarkers for predicting immunotherapy response. Recent advancements in large lan...

ITGAV, a specific biomarker associated with the pathogenesis of idiopathic pulmonary fibrosis.

Objective Idiopathic pulmonary fibrosis (IPF), which radiologically/pathologically manifests mainly as usual interstitial pneumonia (UIP), is easily c...

Deciphering Shared Gene Signatures and Immune Infiltration Characteristics Between Gestational Diabetes Mellitus and Preeclampsia by Integrated Bioinformatics Analysis and Machine Learning.

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common and serious disorders of pregnancy that threaten maternal safety and perinatal ou...

A novel model for predicting immunotherapy response and prognosis in NSCLC patients.

BACKGROUND: How to screen beneficiary populations has always been a clinical challenge in the treatment of non-small-cell lung cancer (NSCLC) with imm...

Deciphering the Immunomodulatory Function of GSN Inflammatory Cancer-Associated Fibroblasts in Renal Cell Carcinoma Immunotherapy: Insights From Pan-Cancer Single-Cell Landscape and Spatial Transcriptomics Analysis.

The heterogeneity of cancer-associated fibroblasts (CAFs) could affect the response to immune checkpoint inhibitor (ICI) therapy. However, limited stu...

Efficacy of laryngeal mask epinephrine in neonatal resuscitation; an ovine study.

BACKGROUND: The efficacy of Laryngeal Mask Airway (LMA) epinephrine during neonatal resuscitation has not been studied. We hypothesize that LMA epinep...

From Multi-Omics to Visualization and Beyond: Bridging Micro and Macro Insights in CAR-T Cell Therapy.

Chimeric antigen receptor T (CAR-T) cell therapies, a cornerstone of immunotherapy, have demonstrated remarkable efficacy in treating hematological ma...

Precise Electromagnetic Modulation of the Cell Cycle and Its Applications in Cancer Therapy.

Precise modulation of the cell cycle via electromagnetic (EM) control presents a groundbreaking approach for cancer therapy, especially in the develop...

Breakthroughs and challenges of organoid models for assessing cancer immunotherapy: a cutting-edge tool for advancing personalised treatments.

Organoid models are powerful tools for evaluating cancer immunotherapy that provide a more accurate representation of the tumour microenvironment (TME...

Identification of pyroptosis-related gene S100A12 as a potential diagnostic biomarker for sepsis through bioinformatics analysis and machine learning.

Sepsis is a non-discriminatory inflammatory reaction that can result in a diverse array of organ dysfunctions, which can be fatal. Pyroptosis is a pro...

PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inference.

Peruvian cuisine has won numerous international awards, attracting tourists from around the world to Peru to experience its diverse culinary offerings...

Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.

BACKGROUND: The "gut-skin axis" has been proposed to play an important role in the development and symptoms of atopic dermatitis. Therefore, we have c...

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT i...

Artificial intelligence networks for assessing the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features: a systematic review and meta-analysis.

BACKGROUND AND AIM: Artificial intelligence (AI) networks offer significant potential for predicting immunotherapy outcomes in gastrointestinal cancer...

Can ChatGPT provide parent education for oral immunotherapy?

BACKGROUND: Oral Immunotherapy (OIT) has exhibited great potential in the treatment of food allergy. However, there is no global consensus on best pra...

Role of artificial intelligence in advancing immunology.

Artificial intelligence (AI) has revolutionized various biomedical fields, particularly immunology, by enhancing vaccine development, immunotherapies,...