AI-Assisted Identification of Primary and Secondary Metabolomic Markers for Postoperative Delirium.

Despite considerable investigative efforts, the molecular mechanisms of postoperative delirium (POD) remain unresolved. The present investigation employs innovative methodologies for identifying potential primary and secondary metabolic markers of POD by analyzing serum metabolomic profiles utilizing the genetic algorithm and artificial neural networks. The primary metabolomic markers constitute a combination of metabolites that optimally distinguish between POD and non-POD groups of patients.

Reconstruction and analysis of the gene regulatory network for cell wall function in Arabidopsis thaliana L. leaves in response to water deficit.

The plant cell wall represents the outer compartment of the plant cell, which provides a physical barrier and triggers signaling cascades under the influence of biotic and abiotic stressors. Drought is a factor that negatively affects both plant growth and development. Cell wall proteins (CWP) play an important role in the plant response to water deficit.

Gene networks for use in metabolomic data analysis of blood plasma from patients with postoperative delirium.

Postoperative delirium (POD) is considered one of the most severe complications, resulting in impaired cognitive function, extended hospitalization, and higher treatment costs. The challenge of early POD diagnosis becomes particularly significant in cardiac surgery cases, as the incidence of this complication exceeds 50 % in certain patient categories. While it is known that neuroinflammation, neurotransmitter imbalances, disruptions in neuroendocrine regulation, and interneuronal connections contribute significantly to the development of POD, the molecular, genetic mechanisms of POD in cardiac surgery patients, along with potential metabolomic diagnostic markers, remain inadequately understood.

Molecular-genetic pathways of hepatitis C virus regulation of the expression of cellular factors PREB and PLA2G4C, which play an important role in virus replication.

The participants of Hepatitis C virus (HCV) replication are both viral and host proteins. Therapeutic approaches based on activity inhibition of viral non-structural proteins NS3, NS5A, and NS5B are undergoing clinical trials. However, rapid mutation processes in the viral genome and acquisition of drug resistance to the existing drugs remain the main obstacles to fighting HCV.

Prioritization of potential pharmacological targets for the development of anti-hepatocarcinoma drugs modulating the extrinsic apoptosis pathway: the reconstruction and analysis of associative gene networks help.

Hepatocellular carcinoma (HCC) is a common severe type of liver cancer characterized by an extremely aggressive course and low survival rates. It is known that disruptions in the regulation of apoptosis activation are some of the key features inherent in most cancer cells, which determines the pharmacological induction of apoptosis as an important strategy for cancer therapy. The computer design of chemical compounds capable of specifically regulating the external signaling pathway of apoptosis induction represents a promising approach for creating new effective ways of therapy for liver cancer and other oncological diseases.