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. Our analysis revealed L-lactic acid, inositol, and methylcysteine as the most salient primary markers upon which the prediction accuracy of POD manifestation achieved AUC = 99%. The secondary metabolomic markers represent metabolites that exhibit perturbed correlational patterns within the POD group. We identified 54 metabolites as the secondary markers of POD, incorporating neurotransmitters such as gamma-aminobutyric acid (GABA) and serotonin. These findings imply a systemic disruption in metabolic processes in patients with POD. The deployment of gene network reconstruction techniques facilitated the postulation of hypotheses describing the role of established genomic POD markers in the molecular-genetic mechanisms of metabolic pathways dysregulation, and involving the identified primary and secondary metabolomic markers. This study not only expands the understanding of POD pathogenesis but also introduces a novel technology for the bioinformatic analysis of metabolomic data that could aid in uncovering potential primary and secondary markers in diverse research domains.

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. The adaptation mechanisms of the cell wall to water loss are of interest for identifying important genetic factors determining plant drought resistance and provide valuable information on biomarkers for further selection aimed at increasing the yield of crop plants. Using ANDSystem, a gene network describing the regulation of CWPs under water restriction conditions was reconstructed. The analysis of the gene network and the transcriptome data analysis allowed prioritizing transcription factors (TF) based on their enrichment of differentially expressed genes regulated by them. As a result, scores were calculated, acting as indicators of the association of TFs with water deficit. On the basis of the score values, eight most significant TFs were selected. The highest priority was given to the TF GBF3. CWPs were prioritized according to the criterion of summing up the scores of transcription factors regulating these genes. Among the most prioritized CWPs were the AT5G03350 gene encoding a lectin-like protein, AT4G20860 encoding BBE-like 22 required for the oxidation of cellulose degradation products, and AT4G37800 encoding xyloglucan endotransglucosy lase/hydrolase 7. Overall, the implemented algorithm could be used for prediction of regulatory interactions between transcription factors and target genes encoding cell wall proteins in plants.

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 in adequately understood. In this study, blood plasma was collected from a group of patients over 65 years old after cardiac surgery involving artificial circulation. The collected samples were analyzed for sphingomyelin content and quantity using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS) me thods. The analysis revealed four significantly different sphingomyelin contents in patients with POD compared to those who did not develop POD (control group). Employing gene network reconstruction, we perceived a set of 82 regulatory enzymes affiliated with the genetic coordination of the sphingolipid metabolism pathway. Within this set, 47 are assumed to be regulators of gene expression, governing the transcription of enzymes pivotal to the metabolic cascade. Complementing this, an additional assembly of 35 regulators are considered to be regulators of activity, degradation, and translocation dynamics of enzymes integral to the aforementioned pathway. Analysis of the overrepresentation of diseases with which these regulatory proteins are associated showed that the regulators can be categorized into two groups, associated with cardiovascular pathologies (CVP) and neuropsychiatric diseases (NPD), respectively. The regulators associated with CVP are expectedly related to the effects on myocardial tissue during surgery. It is hypothesized that dysfunction of NPD-associated regulators may specifically account for the development of POD after cardiac surgery. Thus, the identified regulatory genes may provide a basis for planning further experiments, in order to study disorders at the level of expression of these genes, as well as impaired function of proteins encoded by them in patients with POD. The identified significant sphingolipids can be considered as potential markers of POD.

Hepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSystem. Gene expression regulation was statistically significant. Gene network analysis identified four out of 70 HCC marker genes whose expression regulation by viral proteins may be associated with HCC: DNA-binding protein inhibitor ID – 1 (ID1), flap endonuclease 1 (FEN1), cyclin-dependent kinase inhibitor 2A (CDKN2A), and telomerase reverse transcriptase (TERT). It suggested the following viral protein effects in HCV/human protein heterocomplexes: HCV NS3(p70) protein activates human STAT3 and NOTC1; NS2-3(p23), NS5B(p68), NS1(E2), and core(p21) activate SETD2; NS5A inhibits SMYD3; and NS3 inhibits CCN2. Interestingly, NS3 and E1(gp32) activate c-Jun when it positively regulates CDKN2A and inhibit it when it represses TERT. The discovered regulatory mechanisms might be key areas of focus for creating medications and preventative therapies to decrease the likelihood of HCC development during HCV infection.

The study of molecular genetic mechanisms of plant responses to specific growth conditions and stress factors is a central focus of scientific research aimed at developing new valuable crop varieties, particularly rice and wheat. These factors include abiotic stresses (high or low temperatures, drought, salinity, soil metal contamination), biotic stresses (pathogens, pests), as well as plant responses to regulatory factors (fertilizers, hormones, elicitors, and other compounds). Modern research in plant genetics is based on the understanding that the formation of any phenotypic characteristics (molecular genetic, biochemical, physiological, morphological, etc.) is controlled by gene networks – groups of coordinately functioning genes interacting through their products (RNA, proteins, and metabolites). Previously, we developed the ANDSystem intelligent technology designed to extract knowledge from scientific publication texts for the reconstruction of gene networks in biology and biomedicine. In this work, using an adapted version of ANDSystem for plants, we created the SmartCrop knowledge base designed to address challenges related to studying molecular genetic mechanisms of genotype-phenotype-environment interactions for agriculturally valuable rice and wheat crops. SmartCrop is designed to assist researchers in solving tasks such as interpreting omics technology results (establishing connections between gene sets and biological processes, phenotypic traits, etc.); reconstructing gene networks describing relationships between molecular genetic objects and concepts in breeding, phenomics, seed production, phytopathology, diagnostics, protective agents, etc.; identifying regulatory and signaling pathways of plant responses to specific growth conditions and biotic and abiotic stresses; predicting candidate genes for genotyping; searching for markers for marker-assisted selection; and identifying potential targets for substances (including external factors) affecting plants to ensure timely and uniform germination, better vegetative growth, efficient nutrient uptake, and improved stress resistance.

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. However, at present, most of the studies are devoted to pharmacological effects on the internal (mitochondrial) apoptosis pathway. In contrast, the external pathway induced via cell death receptors remains out of focus. Aberrant gene methylation, along with hepatitis C virus (HCV) infection, are important risk factors for the development of hepatocellular carcinoma. The reconstruction of gene networks describing the molecular mechanisms of interaction of aberrantly methylated genes with key participants of the extrinsic apoptosis pathway and their regulation by HCV proteins can provide important information when searching for pharmacological targets. In the present study, 13 criteria were proposed for prioritizing potential pharmacological targets for developing anti-hepatocarcinoma drugs modulating the extrinsic apoptosis pathway. The criteria are based on indicators of the structural and functional organization of reconstructed gene networks of hepatocarcinoma, the extrinsic apoptosis pathway, and regulatory pathways of virus-extrinsic apoptosis pathway interaction and aberrant gene methylation-extrinsic apoptosis pathway interaction using ANDSystem. The list of the top 100 gene targets ranked according to the prioritization rating was statistically significantly (p-value = 0.0002) enriched for known pharmacological targets approved by the FDA, indicating the correctness of the prioritization method. Among the promising potential pharmacological targets, six highly ranked genes (JUN, IL10, STAT3, MYC, TLR4, and KHDRBS1) are likely to deserve close attention.