Genetics

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in trauma-induced coagulopathy.

Despite advancements in trauma care, uncontrolled hemorrhage and trauma-induced coagulopathy (TIC) remain the leading causes of preventable deaths after trauma. Understanding the genetic underpinnings and molecular mechanisms of TIC is crucial for developing effective diagnostic and therapeutic strategies. This study employed a comprehensive bioinformatics approach to elucidate the genetic landsca...

Interpretability-guided RNA N-methyladenosine modification site prediction with invertible neural networks.

As one of the most common and abundant post-transcriptional modifications, N-methyladenosine (mA) has been extensively studied for its essential regulatory role in gene expression and cell functions. The location of mA RNA modification sites, however, remains a challenging problem, because of the inability to characterize mA modified sites at a multi-scale level in their native RNA context. Here, ...

Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning.

Genome sequencing from wastewater enables accurate and cost-effective identification of SARS-CoV-2 variants. However, existing computational pipelines...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorectal cancer owing to its potential to improve surgic...

Predicting the Effects of Charge Mutations on the Second Osmotic Virial Coefficient for Therapeutic Antibodies via Coarse-Grained Molecular Simulations and Deep Learning Methods.

The impact of various charge mutations on the second osmotic virial coefficient was examined for three model therapeutic monoclonal antibodies (MAbs) ...

From combination early detection to multicancer testing: shifting cancer care toward proactive prevention and interception.

Identifying the presence of tumors at a very early stage or deciphering the process underlying their development can enable the interception of pro-ma...

AQP9 and IFITM1 as drivers of immune infiltration and tumor progression in IBD-associated colorectal cancer: from computational insights to experimental validation.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract associated with an increased risk of colorectal canc...

Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning.

Spinal cord injury (SCI) is a severe neurological disorder, with glucocorticoids like methylprednisolone commonly used for treatment. However, their e...

Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.

Kidney transplantation is the optimal treatment for end-stage renal disease (ESRD), but acute rejection (AR) remains a major factor affecting graft su...

Dynamicasome-a molecular dynamics-guided and AI-driven pathogenicity prediction catalogue for all genetic mutations.

Advances in genomic medicine accelerate the identification of mutations in disease-associated genes, but the pathogenicity of many mutations remains u...

Whole‑exome evolutionary profiling of osteosarcoma uncovers metastasis‑related driver mutations and generates an independently validated predictive classifier.

BACKGROUND: Osteosarcoma is the most common primary malignant bone tumor, with high invasiveness and metastatic potential and a poor prognosis in pati...

Predicting the impact of climate warming on soil quality using bacteria and machine learning.

In the context of global warming, a substantial portion of global soil is in a state of degradation, which poses a significant threat to biodiversity ...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contri...

Liposome-encapsulated AICAR hydrogel regulates macrophage metabolic reprogramming via SIK1 activation to alleviate osteoarthritis.

BACKGROUND: Osteoarthritis (OA), the most prevalent joint disorder, is characterized by a complex etiology and a lack of safe and effective therapeuti...

Early transcriptional responses reveal cell type-specific vulnerability and neuroprotective mechanisms in the neonatal ischemic hippocampus.

Neonatal hypoxic-ischemic (H-I) brain injury, a leading cause of neurodevelopmental disabilities, severely affects the metabolically active and neurog...

Combination of machine learning and protein‑protein interaction network established one ATM‑DPP4‑TXN ferroptotic diagnostic model with experimental validation.

Ferroptosis and lethal sepsis are interlinked, although this association remains largely unknown to clinical panels. Sepsis is characterized by dysfun...

Leveraging machine learning and single-cell RNA sequencing strategies to develop a risk prognosis scoring based on liquid-liquid phase separation feature genes in pediatric hepatoblastoma.

BACKGROUND: Considerable evidence highlights the intricate association between liquid-liquid phase separation (LLPS) and tumorigenesis, progression, a...

Advancements in Tuberculosis Diagnostics: An Update.

Tuberculosis (TB) is one of the major life-threatening diseases caused by a single pathogen which has become a social menace owing to its high resista...

Decoding disease-specific ageing mechanisms through pathway-level epigenetic clock: insights from multi-cohort validation.

BACKGROUND: Ageing is a multifactorial process closely associated with increased risk of chronic diseases. While epigenetic clocks have advanced agein...

Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene.

Genetic disorders commonly share features such as developmental delays, cognitive impairment, and behavioral challenges, yet many conditions also pres...