Genetics

Rapid identification of Litopenaeus vannamei pathogenic bacteria: a combined approach using surface-enhanced Raman spectroscopy (SERS) and deep learning.

Pathogenic bacterial infections are one of the leading causes of mortality in Litopenaeus vannamei, seriously affecting the economic efficiency of the shrimp aquaculture industry. However, traditional pathogen detection methods, such as the polymerase chain reaction (PCR), have drawbacks, including complex procedures and long processing times. Raman spectroscopy provides valuable biomolecular feat...

Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.

Trait Genome-to-Phenome (G2P) dimensionality and "breeding context" combine to influence the realised prediction skill of different whole genome prediction (WGP) methods. Theory and empirical evidence both suggest there is likely to be "No Free Lunch" for prediction-based breeding. Ensembles of diverse sets of G2P models provide a framework to expose and investigate the high G2P dimensionality of ...

Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.

Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor ...

Divide-and-conquer strategy with engineered ossification center organoids for rapid bone healing through developmental cell recruitment.

Current approaches for bone repair predominantly target localized delivery of growth factors that are aimed at the coupling of angiogenesis and osteog...

5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.

At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyopathy (SCM) in clinical practice. This study focuse...

DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads.

The advent of single-cell sequencing has revolutionized the study of cellular dynamics, providing unprecedented resolution into the molecular states a...

Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by high morbidity and poor prognosis. The complex mo...

Tracing the evolutionary pathway of SARS-CoV-2 through RNA sequencing analysis.

The COVID-19 pandemic, driven by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has underscored the need to understand the virus's ...

Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis.

This study developed an immune-related long non-coding RNAs (lncRNAs)-based prognostic signature by integrating multi-omics data and machine learning ...

Computational Strategies to Enhance Vitamin B Biosynthesis Potential of Microbes.

Vitamin B is a vital nutrient for the normal functioning of many metabolic processes. It has a characteristic corrinoid ring structure with a cobalt i...

Uncovering key markers and therapeutic targets for renal fibrosis in diabetic kidney disease through bulk and single-cell RNA sequencing.

BACKGROUND: Diabetic kidney disease (DKD) is the major cause of chronic kidney failure, with tubulointerstitial fibrosis playing a crucial role in dis...

D-optimal candexch algorithm-enhanced machine learning UV-spectrophotometry for five-analyte determination in novel anti-glaucoma formulations and ocular fluids: four-color sustainability framework with NQS assessment and UN-SDG integration.

The novel anti-glaucoma ophthalmic preparation containing latanoprost, netarsudil, and benzalkonium chloride has posed a significant challenge due to ...

Unraveling the oxidative stress landscape in diabetic foot ulcers: insights from bulk RNA and single-cell RNA sequencing data.

BACKGROUND: Oxidative stress plays a crucial role in the development of diabetic foot ulcers (DFU). However, its underlying mechanisms are not fully u...

Precise metabolic dependencies of cancer through deep learning and validations.

Cancer cells exhibit metabolic reprogramming to sustain proliferation, creating metabolic vulnerabilities absent in normal cells. While prior studies ...

MPNN-CWExplainer: An enhanced deep learning framework for HIV drug bioactivity prediction with class-weighted loss and explainability.

AIMS: Human Immunodeficiency Virus (HIV) remains a critical global health concern due to its impact on the immune system and its progression to Acquir...

Deep Learning Discovers New Morphological Features while Predicting Genetic Alterations from Histopathology of Papillary Thyroid Carcinoma.

Papillary thyroid carcinoma (PTC) is the most common malignant tumor of the endocrine system. mutations occur in 40-60%, mutations in 10-15%, and d...

Identification of proliferating neural progenitors in the adult human hippocampus.

Continuous adult hippocampal neurogenesis is involved in memory formation and mood regulation but is challenging to study in humans. Difficulties find...

Direct Modeling of DNA and RNA Aptamers with AlphaFold 3: A Promising Tool for Predicting Aptamer Structures and Aptamer-Target Interactions.

Aptamers, single-stranded nucleic acids that fold into unique three-dimensional shapes, bind selectively to non-nucleotide target molecules, making th...

Exploring the impact of neutrophils on lung adenocarcinoma using Mendelian randomization and transcriptomic study.

Tumor immune microenvironment plays a crucial role in determining the prognosis of lung adenocarcinoma (LUAD), with the interaction of immune cells wi...

Machine learning-based identification of wastewater treatment plant-specific microbial indicators using 16S rRNA gene sequencing.

Effluent released from municipal wastewater treatment plants reflects the microbial communities responsible for degrading and removing contaminants wi...