Allergy

In vitro selection of DNA aptamers and their integration in a competitive voltammetric biosensor for azlocillin determination in waste water.

The uncontrolled usage of veterinary antibiotics has led to their widespread pollution in waterways and milk products. Potential impact of antibiotic residues on the environment and human health such as increased antibiotic resistance of microorganisms and triggering allergic reactions in humans have been reported. In this work, we developed a highly selective and sensitive voltammetric aptasensor...

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks.

The importance of T cells in immunotherapy has motivated developing technologies to improve therapeutic efficacy. One objective is assessing antigen-induced T cell activation because only functionally active T cells are capable of killing the desired targets. Autofluorescence imaging can distinguish T cell activity states in a non-destructive manner by detecting endogenous changes in metabolic co-...

Efficient expression of EpEX in the cytoplasm of using thioredoxin fusion protein.

Recombinant epithelial cell adhesion molecule extracellular domain (EpEX) has a high potential as a candidate for passive and active immunotherapy as ...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vaccine-related anaphylaxis from plain-text clinical n...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation...

Deep learning for pollen allergy surveillance from twitter in Australia.

BACKGROUND: The paper introduces a deep learning-based approach for real-time detection and insights generation about one of the most prevalent chroni...

Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry.

Imaging flow cytometry (IFC) produces up to 12 spectrally distinct, information-rich images of single cells at a throughput of 5,000 cells per second....

White blood cells detection and classification based on regional convolutional neural networks.

White blood cells (WBC) are important parts of our immune system and they protect our body against infections by eliminating viruses, bacteria, parasi...

DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity.

Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen prediction focus on the binding between human leukocyte ...

DeepTetrad: high-throughput image analysis of meiotic tetrads by deep learning in Arabidopsis thaliana.

Meiotic crossovers facilitate chromosome segregation and create new combinations of alleles in gametes. Crossover frequency varies along chromosomes a...

Dietary reference values for sodium.

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) derived dietary reference values (...

Identifying Phenotypes of Atopic Dermatitis in a Longitudinal United States Cohort Using Unbiased Statistical Clustering.

Precise Pollen Grain Detection in Bright Field Microscopy Using Deep Learning Techniques.

The determination of daily concentrations of atmospheric pollen is important in the medical and biological fields. Obtaining pollen concentrations is ...

Safety of viable embryonated eggs of the whipworm as a novel food pursuant to Regulation (EU) 2015/2283.

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver an opinion on...

Future of Radiotherapy in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as associated Epstein-Barr virus infection and high radio...

Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters.

Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambr...

IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment.

Wart disease (WD) is a skin illness on the human body which is caused by the human papillomavirus (HPV). This study mainly concentrates on common and ...

Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data.

Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global ...

Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Pollen.

Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of a...

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.

Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical ...