Allergy

Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristics in bladder cancer. In this study, we comprehensively evaluated the TME invasion pattern of bladder cancer in 1,889 patients, defined three differen...

Applications of Machine and Deep Learning in Adaptive Immunity.

Adaptive immunity is mediated by lymphocyte B and T cells, which respectively express a vast and diverse repertoire of B cell and T cell receptors and, in conjunction with peptide antigen presentation through major histocompatibility complexes (MHCs), can recognize and respond to pathogens and diseased cells. In recent years, advances in deep sequencing have led to a massive increase in the amount...

Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Multi-domain proteins are not only formed through natural evolution but can also be generated by recombinant DNA technology. Because many fusion prote...

Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.

Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortun...

Deep learning approach to skin layers segmentation in inflammatory dermatoses.

Monitoring skin layers with medical imaging is critical to diagnosing and treating patients with chronic inflammatory skin diseases. The high-frequenc...

Host-dependent molecular factors mediating SARS-CoV-2 infection to gain clinical insights for developing effective targeted therapy.

Coronavirus disease 2019 (COVID-19), a recent viral pandemic that first began in December 2019, in Hunan wildlife market, Wuhan, China. The infection ...

Automated severity scoring of atopic dermatitis patients by a deep neural network.

Scoring atopic dermatitis (AD) severity with the Eczema Area and Severity Index (EASI) in an objective and reproducible manner is challenging. Automat...

Personalized prediction of early childhood asthma persistence: A machine learning approach.

Early childhood asthma diagnosis is common; however, many children diagnosed before age 5 experience symptom resolution and it remains difficult to id...

Accuracy of Algorithms to Identify People with Atopic Dermatitis in Ontario Routinely Collected Health Databases.

TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties.

Immunotherapy is a research area with great potential in drug discovery for cancer treatment. Because of the capacity of tumor antigens to activate th...

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the ...

Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification m...

Automated detection of mouse scratching behaviour using convolutional recurrent neural network.

Scratching is one of the most important behaviours in experimental animals because it can reflect itching and/or psychological stress. Here, we aimed ...

MATHLA: a robust framework for HLA-peptide binding prediction integrating bidirectional LSTM and multiple head attention mechanism.

BACKGROUND: Accurate prediction of binding between class I human leukocyte antigen (HLA) and neoepitope is critical for target identification within p...

Effects of Neurodynamic Mobilizations on Pain Hypersensitivity in Patients With Hand Osteoarthritis Compared to Robotic Assisted Mobilization: A Randomized Controlled Trial.

OBJECTIVE: To evaluate the effectiveness of the neurodynamic mobilization techniques compared with passive robotic physiologic movement in patients wi...

Quantitative analysis of blood cells from microscopic images using convolutional neural network.

Blood cell count provides relevant clinical information about different kinds of disorders. Any deviation in the number of blood cells implies the pre...

Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images.

This study aimed to use computed tomography (CT) images to assess PD-L1 expression in non-small cell lung cancer (NSCLC) and predict response to immu...

Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.

BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a sm...

Recombinant human hyaluronidase PH20-mediated dermal spreading activity in mice is not altered by steroids, antihistamines, or salicylic acid.

OBJECTIVES: Drug-drug interaction studies for hyaluronidase safety assessments have evaluated only animal-derived enzyme preparations. We therefore se...

Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis.

Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagnostic regimes rely on allergy testing, exposure spe...