Allergy & Immunology

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. : The clinical data of 143 NEC neonates in the Zhujiang Hospital of Southern Medical University from October 2010 to October 2022 were collected, wher...

Machine Learning-Based Biomarker Discovery from Serum Trace Elements and Biochemical Parameters in Patients with Nasal Polyps.

Nasal polyps (NP) are benign mucosal outgrowths associated with chronic inflammation that can significantly reduce quality of life. This study aimed to evaluate changes in inflammation, oxidative stress, and trace element homeostasis in NP patients and to identify potential non-invasive diagnostic biomarkers. A total of 22 patients with NP and 19 healthy individuals were included in the study. Ser...

From dairy to plant products: Understanding their structural fingerprints with X-rays.

Global interest in milk alternatives increases rapidly due to health awareness, their allergen-friendliness, and concerns about sustainability. While ...

Advances in vaccine adjuvant development and future perspectives.

Use of highly purified antigens to improve vaccine safety has led to reduced immunogenicity and efficacy, resulting in the need for adjuvants to incre...

Cancer vaccines and the future of immunotherapy.

Vaccines have had a major impact on the control of infectious disease, most recently by helping to combat the COVID-19 pandemic. Prophylactic cancer v...

HAPIR: a refined Hallmark gene set-based machine learning approach for predicting immunotherapy response in cancer patients.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet the response rate remains limited, with only about 30% of solid tumor pa...

Machine Learning Characterization of Immunometabolism in the Tumor Microenvironment and Immunotherapy Responses in Bladder Cancer.

Immune dysregulation and metabolism reprogramming are implicated in bladder cancer (BLCA), the relationships between immunometabolism (IMB) and BLCA r...

Microglial pruning of glycinergic synapses disinhibits spinal PKCγ interneurons to drive pain hypersensitivity in mice.

Microglial activation is linked to neuroinflammation in neuropathic pain. Recently, microglia-mediated synaptic pruning has received mounting attentio...

Digital health tools in the management of allergic rhinitis: a systematic review.

BACKGROUND: Allergic rhinitis (AR) is an IgE-related condition that causes problems for patients and adds stress to healthcare systems everywhere. Tho...

Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.

Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this wor...

Semi-automated high content analysis of pollen performance using tubetracker.

TubeTracker provides a method to partially automate analysis of pollen tube growth using live imaging. Pollen function is critical for successful plan...

Advances in molecular pathology and therapy of non-small cell lung cancer.

Over the past two decades, non-small cell lung cancer (NSCLC) has witnessed encouraging advancements in basic and clinical research. However, substant...

Machine learning-based model for acute asthma exacerbation detection using routine blood parameters.

BACKGROUND: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings w...

Substrate Specificity of the Organic Cation Transporters MATE1 and MATE2K and Functional Overlap with OCT1 and OCT2.

The multidrug and toxin extrusion proteins MATE1 and MATE2K may determine the pharmacokinetics and drug-drug interactions of many drugs. However, thei...

Deep learning-based quantification of eosinophils and lymphocytes shows complementary prognostic effects in colorectal cancer patients.

The immune microenvironment of colorectal cancer is a major component of the disease and influences not only tumor progression and patient outcome but...

Pretreatment Multi-sequence Contrast-Enhanced MRI to Predict Response to Immunotherapy in Unresectable Hepatocellular Carcinoma Using Transformer: A Multicenter Study.

Targeted combined immunotherapy (TCI) has shown certain antitumor effects in patients with unresectable hepatocellular carcinoma(uHCC), but only a su...

Integrated machine learning based on cuproptosis and RNA methylation regulators to explore the molecular model of prostate cancer and provide novel insights to immunotherapy.

As a highly prevalent tumor in males, prostate cancer (PCa) needs newly developed biomarkers to guide prognosis and treatment. However, few researche...

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Un...

Robust Multiclass Feature Selection for the Authentication of Honey Botanical Origin via Nontargeted LC-MS Analysis.

Honey is one of the most frequently frauded foods due to the high market price of certain kinds of monofloral honey. Traditional authentication method...

Deep learning and inflammatory markers predict early response to immunotherapy in unresectable NSCLC: A multicenter study.

Immune checkpoint inhibitors (ICIs) demonstrate substantial interpatient variability in clinical efficacy for unresectable non-small cell lung cancer ...