Genetics

Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is a common cause of cancer-related deaths worldwide, and accurate EGFR genotyping is crucial for optimal treatment outcomes. Conventional methods for identifying the EGFR genotype have several limitations. Therefore, we proposed a deep learning model using non-invasive CT images to predict EGFR mutation status with robustness and generalizability.

Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.

This study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT). A total of 1280 patients with NSCLC who underwent contrast-enhanced CT scans and EGFR mutation testing before treatment were selected for the final study. Regions of interest...

Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges.

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identi...

Historical perspective and future directions: computational science in immuno-oncology.

Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastati...

Identification and verification of diagnostic biomarkers based on mitochondria-related genes related to immune microenvironment for preeclampsia using machine learning algorithms.

Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality worldwide. Preeclampsia is linked to mitochondrial dysfunction...

Differences in the microbiome of the small intestine of Leghorn lines divergently selected for antibody titer to sheep erythrocytes suggest roles for commensals in host humoral response.

For forty generations, two lines of White Leghorn chickens have been selected for high (HAS) or low (LAS) antibody response to a low dose injection of...

Development and application of an indirect ELISA and nested PCR for the epidemiological analysis of among pigs in China.

INTRODUCTION: () is an important opportunistic and zoonotic pathogen which is associated with many diseases in humans and animals. However, the patho...

Simultaneous detection of human norovirus GI, GII and SARS-CoV-2 by a quantitative one-step triplex RT-qPCR.

BACKGROUND: There are many similarities in the clinical manifestations of human norovirus and SARS-CoV-2 infections, and nucleic acid detection is the...

Advancing genome editing with artificial intelligence: opportunities, challenges, and future directions.

Clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing (GED) technologies have unlocked exciting possibilities for und...

Novel B-DNA dermatophyte assay for demonstration of canonical DNA in dermatophytes: Histopathologic characterization by artificial intelligence.

We describe a novel assay and artificial intelligence-driven histopathologic approach identifying dermatophytes in human skin tissue sections (ie, B-D...

The buccal micronucleus cytome assay: New horizons for its implementation in human studies.

In this report we provide a summary of the presentations and discussion of the latest knowledge regarding the buccal micronucleus (MN) cytome assay. T...

Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer.

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, genetic subtypes, and mutations associated with CR...

Refining mutanome-based individualised immunotherapy of melanoma using artificial intelligence.

Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in...

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas.

Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment...

mediated green synthesis of silver and gold nanoparticles for enhanced biological applications.

The present study investigated the synthesis and biological applications of green, economical, and multifunctional silver and gold nanoparticles (TSAg...

Mining and rational design of psychrophilic catalases using metagenomics and deep learning models.

A complete catalase-encoding gene, designated soiCat1, was obtained from soil samples via metagenomic sequencing, assembly, and gene prediction. soiCa...

Prediction of protein structure and AI.

AlphaFold, an artificial intelligence (AI)-based tool for predicting the 3D structure of proteins, is now widely recognized for its high accuracy and ...

Deciphering complex antibiotic resistance patterns in through whole genome sequencing and machine learning.

INTRODUCTION: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenge...

TSCA-Net: Transformer based spatial-channel attention segmentation network for medical images.

Deep learning architectures based on convolutional neural network (CNN) and Transformer have achieved great success in medical image segmentation. Mod...

Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation.

Protein mutations can significantly influence protein solubility, which results in altered protein functions and leads to various diseases. Despite tr...