COVID-19

Multifaceted profiling of virus-specific CD8 T cells reveals distinct immune signatures against cytomegalovirus infection states during pregnancy.

Anti-cytomegalovirus (CMV) serological testing, including the IgG avidity index (AI), is used to assess CMV infection phases during pregnancy. However, little is known about anti-CMV cellular immunity during pregnancy, particularly its relation to serological diagnosis. Herein, using MHC-dextramer single-cell RNA sequencing and flow cytometry, we characterized IE1 and pp65 CMV-antigen specific CD8...

Engineering TCR-controlled fuzzy logic into CAR T cells enhances therapeutic specificity.

Chimeric antigen receptor (CAR) T cell immunotherapy represents a breakthrough in the treatment of hematological malignancies, but poor specificity has limited its applicability to solid tumors. By contrast, natural T cells harboring T cell receptors (TCRs) can discriminate between neoantigen-expressing cancer cells and self-antigen-expressing healthy tissues but have limited potency against tumor...

Detecting implicit biases of large language models with Bayesian hypothesis testing.

Despite the remarkable performance of large language models (LLMs), such as generative pre-trained Transformers (GPTs), across various tasks, they oft...

Ivermectin performance against equine strongylids: Efficacy, egg reappearance periods, and fecal egg counting method comparison.

Equine strongylids are ubiquitous and can cause severe health issues. Anthelmintic resistance is widely common in cyathostomin parasites, and recent s...

DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants.

BACKGROUND: A significant challenge in precision medicine is confidently identifying mutations detected in sequencing processes that play roles in dis...

Enhancing student-centered walking environments on university campuses through street view imagery and machine learning.

Campus walking environments significantly influence college students' daily lives and shape their subjective perceptions. However, previous studies ha...

MIST: An interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis.

Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune ...

101 Machine Learning Algorithms for Mining Esophageal Squamous Cell Carcinoma Neoantigen Prognostic Models in Single-Cell Data.

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the digestive tract, characterized by a high recurrence ra...

Prediction of COVID-19 mortality using machine learning strategies and a large-scale panel of plasma inflammatory proteins: A cohort study.

OBJECTIVE: To apply machine learning algorithms to generate models capable of predicting mortality in COVID-19 patients, using a large platform of pla...

5-5-5 ABRT (Dose of 5 Gy per Fraction for up to 5 Fractions Over 5 Weeks Adaptive Bridging Radiation Therapy)-Artificial Intelligence Enters the CAR (-T) (Chimeric Antigen Receptor-T) in Relapsed/Refractory Large B Cell Lymphoma.

PURPOSE: Bridging radiation therapy (BRT) is effective for local control in patients with relapsed or refractory large B cell lymphoma who are undergo...

A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.

Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichmen...

Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.

BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer patients can facilitate timely adjustment of treatmen...

Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm.

In the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis t...

Machine learning in point-of-care testing: innovations, challenges, and opportunities.

The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine ...

Electrocardiographic Discrimination of Long QT Syndrome Genotypes: A Comparative Analysis and Machine Learning Approach.

Long QT syndrome (LQTS) presents a group of inheritable channelopathies with prolonged ventricular repolarization, leading to syncope, ventricular tac...

AI feedback and workplace social support in enhancing occupational self-efficacy: a randomized controlled trial in Japan.

As AI is expected to take on the role of providing workplace feedback to employees in the future, understanding how AI and humans can complement effec...

Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning.

Highly concentrated antibody solutions are necessary for developing subcutaneous injections but often exhibit high viscosities, posing challenges in a...

Identification of biomarkers associated with M1 macrophages in the ST-segment elevation myocardial infarction through bioinformatics and machine learning approaches.

ST-segment elevation myocardial infarction (STEMI) is considered a critical cardiac condition with a poor prognosis. Shortly after STEMI occurs, the i...

Taking the 3Rs to a higher level: replacement and reduction of animal testing in life sciences in space research.

Human settlements on the Moon, crewed missions to Mars and space tourism will become a reality in the next few decades. Human presence in space, espec...

Detection of antibodies in suspected autoimmune encephalitis diseases using machine learning.

In our study, we aim to predict the antibody serostatus of patients with suspected autoimmune encephalitis (AE) using machine learning based on pre-co...