Search Results (4,067)

Physiologically based pharmacokinetic (PBPK) models are widely used in the context of personalized medicine, as they allow for the evaluation of dosing schedules and routes of administration by predicting absorption, distribution, metabolism and excretion (ADME) of drugs in biological systems. Traditionally, PBPK models have been developed and applied at the population level, enabling the characterization of predefined cohorts, which remains limited in supporting true precision dosing. In this review, we explored the increasingly common shift from population-based to individual PBPK modelling, where individuals are modelled as virtual twins (VTs). Through the inclusion of additional patient-specific data, such as demographic, physiological, phenotypic and genotypic information, models can be personalized, moving beyond traditional one-size-fits-all strategies. Overall, incorporating individual patient data (e.g., septic, psychiatric, cardiac, or neonatal populations) improves model performance. Physiological parameters, particularly renal function, show strong potential given their role in drug elimination, while demographic variables enhance predictive accuracy in certain studies. In contrast, the benefits of including cytochrome P450 (CYP) phenotypic and genotypic data remain inconsistent. We further emphasize methodologies used to evaluate model performance, with a focus on clinical validation through comparisons between predicted and observed concentration-time profiles. Key challenges, including limited sample sizes and data availability, that may compromise predictive precision, are also discussed. Finally, we highlight the potential integration of PBPK-based VTs into broader digital twin frameworks as a promising path toward clinical translation, while acknowledging the critical barriers that must be addressed to enable routine clinical implementation. Full article

Paeonia lactiflora is an important traditional Chinese medicine. Its core bioactive component, albiflorin, exhibits significant pharmacological activity, but its biosynthetic pathway remains unclear, severely limiting the targeted regulation and sustainable utilization of this compound. In this study, integrated transcriptomic and metabolomic analyses revealed that tissue specificity is a key factor driving metabolite accumulation. Weighted Gene Co-expression Network Analysis (WGCNA) identified a gene module significantly positively correlated with albiflorin content. From this module, key candidate genes were screened, including MYB and bHLH transcription factor genes as well as CYP450. The expression patterns of these candidate genes were subsequently validated by qRT-PCR, confirming a strong correlation between the transcriptomic and experimental data. These findings not only clarify the molecular basis for the tissue-specific accumulation of albiflorin and provide critical targets for elucidating its complete biosynthetic pathway but also lay a solid foundation for molecular breeding and quality improvement of Paeonia lactiflora. Full article

According to a previous study, in insects, cyp307A1 plays a central role in ecdysteroid synthesis, which is a member of the cytochrome P450 family. However, the function of cyp307A1 in crustaceans remains unclear. In this study, we explored the function of Eccyp307a1 in Exopalaemon carinicauda through a series of experiments. The sequence of Eccyp307a1 encoded 529 amino acids, and the protein was found to possess typical P450 domains and heme-binding sites. The mRNA of Eccyp307a1 was expressed at a higher level during the early stages of ovary development, but was expressed less during the mature stage. Furthermore, employing eyestalk ablation and RNAi experiments, we determined that Eccyp307a1 could be regulated by neuroendocrine factors and is essential for the normal initiation of ovary development. These findings provided insights into the gene function of Eccyp307a1 in early ovary development in E. carinicauda, and our study further elucidates the molecular mechanisms of ovary development in crustaceans. Full article

Spodoptera frugiperda is a highly destructive migratory pest of global concern that infests a wide range of crops, particularly maize, as well as rice and sugarcane, causing substantial economic losses in China. Since its invasion of China, S. frugiperda has experienced prolonged insecticide selection pressure, resulting in the accelerated evolution and increasing prevalence of resistance to specific insecticides. This study aimed to elucidate the role of cytochrome P450 monooxygenase (CYP) gene families in mediating resistance to chlorantraniliprole and to evaluate the efficacy of nanoparticle-mediated delivery systems combined with P450-specific synergists for controlling S. frugiperda. Toxicity bioassays conducted on field populations demonstrated that chlorantraniliprole still retained considerable insecticidal activity. Analyses of three detoxification enzyme activities revealed a significant elevation in cytochrome P450 activity, and expression profiling of candidate CYP genes was performed using quantitative real-time PCR (qPCR). Exposure to chlorantraniliprole resulted in a 2.53-fold upregulation of CYP4G75 expression. Furthermore, nano-agrochemical formulation assays showed that the combined application of LDHs-dsCYP4G75 and chlorantraniliprole exerted a significant synergistic effect, increasing mortality by 21.99% compared with either treatment applied alone. Overall, this study provides mechanistic insights into P450-mediated resistance and offers a promising strategy to reduce reliance on chemical insecticides, thereby contributing to the development of sustainable integrated pest management (IPM) programs. Full article

Sesame (Sesamum indicum L.) is a nutrient-rich oilseed crop whose improvement can be accelerated by unlocking untapped genetic variation in African landraces. We integrated a global meta-quantitative trait loci (QTL) analysis with a genome-wide association study (GWAS) of Ethiopian germplasm to identify molecular markers for plant height and seed coat color. Meta-analysis of eight available data sources revealed six conserved QTL hotspots on chromosomes 3, 4, 6, 8, 9, and 11. Subsequently, GWAS on 200 Ethiopian accessions, represented by 3683 SNPs, detected 36 significant associations, including novel loci on chromosomes 12 and 13 not reported in Asian-focused research. Candidate genes assigned to these loci implicated key hormonal and transcriptional mechanisms: brassinosteroid biosynthesis (CYP90B1) and ethylene signaling (AP2/ERF) probably regulate plant architecture, while transcription factors (WRKY23, DOF3.1, and SBP-like) modulate flavonoid pathways controlling seed coat pigmentation. Analyses of population structure revealed two distinct groups (K = 2), and linkage disequilibrium (LD) decayed rapidly (~190 kb), which allows fine-mapping. The present study presents validated molecular markers and candidate genes for marker-assisted selection in sesame breeding. Full article

Background/Objectives: Cytochrome P450 3A4 (CYP3A4) metabolizes approximately 30–50% of clinically used drugs; thus, accurate prediction of CYP3A4 inhibition is essential for early assessment of drug–drug interaction (DDI) risk and toxicity. This study evaluated an integrated artificial intelligence framework for predicting CYP3A4 inhibition (%) using a large, curated chemical dataset. Methods: A dataset of 23,713 compounds was compiled from the Korea Chemical Bank and multiple commercial and public databases. Vector-based machine learning (ML) models (LightGBM, XGBoost, CatBoost, and a weighted ML ensemble) and graph neural network (GNN) models (O-GNN with contrastive learning and manifold mixup (O-GNN + CL + Mixup), D-MPNN, GINE, and GATv2) were evaluated. Manifold mixup was applied during GNN training, and SMILES enumeration-based test-time augmentation was used at inference. The best-performing ML and GNN models were integrated using a weighted ensemble strategy. Model interpretability was examined using SHAP analysis for ML models and occlusion sensitivity analysis for O-GNN + CL + Mixup. Results: The weighted ML ensemble achieved the best performance among ML models (RMSE = 19.1031, Pearson correlation coefficient (PCC) = 0.7566); the O-GNN + CL + Mixup model performed the best among GNN models (RMSE = 20.1002, PCC = 0.7265). The hybrid model achieved improved predictive accuracy (RMSE = 19.0784, PCC = 0.7570). External validation on 100 newly generated experimental data points confirmed generalizability (Custom Metric = 0.8035). Conclusions: This study demonstrated that integrating ML and GNN models with data augmentation strategies improves the robustness and interpretability of CYP3A4 inhibition prediction and established a practical framework for metabolic screening and DDI risk assessment. Full article

Salt stress is a severe threat to medicinal plants, adversely affecting their growth, yield, and quality. As a key antioxidant tripeptide, glutathione (GSH) confers salinity stress resilience in plants. However, how GSH shapes the plant tolerance to salt stress remains a mystery, especially in medicinal plants, including Pogostemon cablin. In this study, we investigated the regulatory effects of exogenous GSH on P. cablin seedlings under salt conditions. The results showed that GSH significantly improved seedling quality under both normal and salt conditions, evidenced by the increased shoot and root dry weight, plant height, and root length. Moreover, GSH effectively protected the photosynthetic system against salt-mediated damage via raised chlorophyll a, chlorophyll b, carotenoids, quantum yield of photosystem II [Y (II)], and PSII maximum efficiency (Fv/Fm). Furthermore, GSH stimulated the antioxidant defense system, including GSH, AsA, SOD, CAT, APX, POD, and GR, to restrain salt-induced malondialdehyde production and ROS burst. In addition, GSH treatment promoted the biosynthesis of secondary metabolites, including total polyphenol and flavonoid. RNA-seq analysis revealed that the activation of the flavonoid biosynthetic pathway significantly enhanced salt tolerance in P. cablin. Notably, several key regulatory genes within this pathway, including PAL, 4CL, C4H, CHI, ANS, F3′H, and CYP93, were significantly upregulated 24 h following GSH application under salt conditions. Therefore, exogenous GSH alleviates salt-induced oxidative stress in P. cablin via enhancing the antioxidant defense system and flavonoid biosynthetic activation. These findings provide valuable insights into the dual defense strategies of GSH for conferring salt resistance in plants. Full article

Flaveria trinervia (Spreng) C. Mohr is a plant traditionally used in Mexican medicine. In this study, gas chromatography–mass spectrometry (GC–MS) combined with network pharmacology was employed to characterize volatile and semi-volatile metabolites from F. trinervia leaves and to explore their potential system-level mechanisms of action in inflammatory and tumor-related disorders. A dual extraction strategy (hexane/dichloromethane and acetone/chloroform) was applied, followed by GC–MS-based compound identification. Putative molecular targets were predicted using established pharmacological databases, and protein–protein interaction networks were constructed to identify topological features and enriched biological pathways. A total of 11 bioactive compounds were tentatively identified with an identity level of ≥80%, with seven shared between both extracts, including phytol, germacrene D, caryophyllene oxide, pinene isomers, squalene, and 2,2′:5′,2″-terthiophene, metabolites previously reported to exhibit antioxidant, anti-inflammatory, and cytotoxic activities. Network topology analysis identified ESR1, RXRA/B/G, NCOA2, and CYP19A1 as central nodes, reflecting convergence on signaling axes involved in apoptosis, cell proliferation, immune modulation, and transcriptional regulation pathways. Functional enrichment analysis revealed significant associations with KEGG pathways related to immune modulation, neuroendocrine regulation, and cancer-associated pathways. Collectively, these findings suggest a multitarget biological and multipathway pharmacological profile for F. trinervia, consistent with previously reported biological activities. The concordance between in silico predictions and existing experimental evidence strengthens the pharmacological relevance of the identified metabolites and supports their prioritization for further experimental validation, including mechanistic and pharmacokinetic studies, in metabolic, immune, neurological, and cancer-related contexts. Full article

Hepatic osteodystrophy (HOD) is a frequent complication of chronic liver disease, marked by impaired osteogenesis and elevated fracture risk, particularly under sustained alcohol exposure. Bone morphogenetic proteins (BMPs), which play a crucial role in maintaining bone homeostasis, are dysregulated in alcoholic liver disease. Specifically, decreased BMP2 and increased BMP13 have been linked to impaired osteogenesis and cartilage-like shifts in bone progenitors. A human in vitro system that recapitulates this hepatic BMP imbalance is needed to dissect mechanisms and identify targets. To address this, we established a long-term human three-dimensional liver–bone co-culture model that integrates hepatocytes (HepaRG), hepatic stellate cells (LX-2), and human umbilical vein endothelial cells (HUVECs) with bone scaffolds seeded with osteoblast precursors (SCP-1) and osteoclast precursors (THP-1). This study aimed to characterize the effects of chronic 50 mM alcohol exposure on hepatic fibrogenic activation and BMP ligand secretion, and to investigate the associated BMP-responsive signaling involved in bone cell lineage differentiation and functional activity. The results demonstrated alcohol-induced hepatic CYP2E1 activation and fibrogenic remodeling with EMT signatures, as well as a decrease in BMP2 and an increase in BMP13, without affecting BMP9. Liver-derived factors activated both canonical and non-canonical BMP signaling in bone progenitors, reduced osteoblast activity and mineralization, preserved osteoclast TRAP activity, and shifted the lineage toward chondrogenesis (SOX9↑, RUNX2↓). Notably, this BMP profile and skeletal phenotype reflect clinical observations in chronic liver disease, indicating that the model recapitulates key in vivo pathological features. This human liver micro-organoid co-culture reproduces alcohol-induced hepatic BMP dysregulation and downstream bone defects, offering an organoid-centric, microengineered platform for mechanistic studies and BMP-targeted therapeutic screening in HOD. Full article

Fetal growth restriction (FGR) is a major contributor to perinatal morbidity and mortality, most commonly arising from placental dysfunction, with increasing evidence implicating aberrant DNA methylation in its pathogenesis. To identify robust epigenetic alterations associated with FGR, we analyzed placental chorionic villi from an in-house early-onset FGR cohort and compared them with a publicly available dataset (GSE100197). DNA methylation profiling was performed using Illumina EPIC (in-house) and 450K (public) arrays, processed with identical normalization and quality-control pipelines, including adjustment for gestational age and estimation of placental cell-type composition. Differentially methylated positions (DMPs) were identified using linear regression models, revealing 10,427 DMPs in the in-house cohort and 7467 in the public dataset, with 108 shared DMPs showing consistent direction of change across both cohorts. Promoter-associated DMPs were mapped to genes involved in angiogenesis, morphogenesis, immune regulation, and transcriptional control, including EPHA1, ANGPTL6, ITGAX, BCL11B, and CYP19A1, while additional novel candidates such as SLC39A12, YEATS4, and MIR515 family members were also identified. Functional annotation suggests that these methylation changes may influence pathways essential for placental vascular development and structural organization. Overall, this cross-cohort comparison highlights reproducible epigenetic signatures of FGR and underscores the need for standardized approaches to clarify the molecular mechanisms underlying placental insufficiency. Full article

This study compares the chemical composition, antimicrobial effects, and antibiotic-potentiating capacity of three Lauraceae essential oils (EO): Cryptocarya agathophylla (CAEO), Litsea cubeba (LCEO), and Laurus nobilis (LNEO). Gas chromatography–mass spectrometry (GC–MS) analysis revealed distinct chemotypes: CAEO and LCEO were dominated by oxygenated monoterpenes, while LNEO contained the highest levels of monoterpene hydrocarbons. Antibacterial testing against nine bacterial strains showed strain-dependent growth suppression trends, while true minimum inhibitory concentrations (MICs) were reached only in selected cases. EO–ampicillin interactions were evaluated using MIC-based checkerboard criteria, whereas OD-derived inhibition parameters were used exclusively to describe sub-MIC potentiation trends. In combination assays, LNEO exhibited the most pronounced potentiating effects against Streptococcus pyogenes, Shigella flexneri, and Haemophilus influenzae, while CAEO and LCEO showed moderate or strain-dependent enhancement. Hierarchical clustering highlighted distinct oil- and strain-specific interaction profiles. Overall, although CAEO displayed stronger intrinsic antibacterial effects when tested alone, LNEO emerged as the most effective potentiator of ampicillin activity in a strain-dependent manner. The effects of the major compounds identified in the Lauraceae EO were assessed in silico against protein targets of some microorganisms using the AutoDock software version 4.2.6. The docking scores revealed binding affinities of the bioactive compounds towards Dpr protein (4.3–5.8 kcal/mol), DNA gyrase (4.7–7.1 kcal/mol), mono- diacylglycerol lipase (4.4–6.2 kcal/mol), CYP51 (5.8–8.0 kcal/mol), phage-encoded quorum sensing anti-activator (5.8–8.0 kcal/mol) and Chondroitin ABC lyase I (4.8–6.3 kcal/mol). Two (2) hit compounds (α-Citral, β-Citral) were finely defined by strong hydrophobic and hydrophilic interactions with the bacterial and fungal protein targets, respectively. Full article

Abdominal aortic aneurysm (AAA) is a fatal vascular disorder driven by immune dysregulation and extracellular matrix (ECM) degradation, yet its molecular mechanisms remain unclear. This study investigated the mechanistic role of ID1 in AAA using an integrative multi-omics and machine learning approach. Two bulk transcriptomic datasets (GSE232911 and GSE183464) were analyzed through differential expression, WGCNA, and three machine learning algorithms (LASSO, Random Forest, and SVM-RFE), followed by immune infiltration analysis via ssGSEA and CIBERSORT. ID1 and CYP4B1 were identified by all three machine learning algorithms, but only ID1 showed stable downregulation and consistent discriminatory ability across independent datasets. (AUC = 0.939 and 0.868). Functional enrichment and immune deconvolution linked low ID1 expression to enhanced adaptive immune signaling, increased M1 macrophages, γδ T cells, and memory B cells, and reduced neutrophil and mast cell activity. Single-cell RNA sequencing (GSE226492) confirmed endothelial- and fibroblast-specific ID1 downregulation in AAA. These findings identify ID1 as a candidate gene associated with vascular immune remodeling and extracellular matrix–related pathways, providing a basis for future mechanistic investigation in AAA. Full article

As a typical halogenated hydrocarbon environmental pollutant, 1,2-dichloroethane (1,2-DCE) exhibits clinically confirmed hepatotoxicity with incompletely understood mechanisms. This study integrated network toxicology, molecular docking, and in vitro experiments to investigate necroptosis in 1,2-DCE-induced liver injury. Computational analysis predicted involvement of the aryl hydrocarbon receptor (AHR)/cytochrome P450 1A1 (CYP1A1) pathway, and molecular docking suggested potential binding between 1,2-DCE and AHR (−6.5 kcal/mol). CCK-8 assays showed that 1,2-DCE reduced THLE-2 hepatocyte viability in a concentration-dependent manner. Notably, 1,2-DCE triggered rapid AHR nuclear translocation within 1 h and transiently upregulated CYP1A1 at both the transcriptional and protein levels (3–6 h). Further studies revealed elevated intracellular reactive oxygen species (ROS) at 24 h. After 48 h exposure, CYP1A1 expression was significantly suppressed, accompanied by activation of necroptosis markers, including increased lactate dehydrogenase (LDH) release, enhanced propidium iodide (PI) staining, and elevated phosphorylation of receptor-interacting protein kinase 3 (RIPK3) and mixed lineage kinase domain-like protein (MLKL). These findings reveal a dual-phase mechanism: an early adaptive stress response via the AHR-CYP1A1 axis, followed by pathway dysfunction and transition to necroptosis, suggesting AHR as a potential target for intervening in 1,2-DCE-induced hepatotoxicity. Full article

Background/Objectives: SLC13A5 encodes a sodium–citrate cotransporter implicated in early-onset epileptic encephalopathy and metabolic brain dysfunction, yet its developmental regulation and molecular context in the human brain remain incompletely defined. Methods: Leveraging human developmental transcriptomes from the Evo-Devo resource, we delineated tissue trajectories and network context for SLC13A5 across the fetal–postnatal life. Results: In the cerebrum, SLC13A5 expression rises from late fetal stages to peak in the first postnatal year and then declines into adulthood, while cerebellar levels increase across the lifespan; liver shows a fetal decrease followed by sustained postnatal upregulation. A transcriptome-wide scan identified extensive positive and negative associations with SLC13A5, and a signed weighted gene co-expression network analysis (WGCNA) built on biweight midcorrelation placed SLC13A5 in a large module. The module eigengene tracked brain maturation (Spearman rho = 0.802, p = 8.62 × 10⁻⁶) and closely matched SLC13A5 abundance (rho = 0.884, p = 2.73 × 10⁻⁶), with a significant partial association after adjusting for developmental rank (rho = 0.672, p = 6.17 × 10⁻⁴). Functional enrichment converged on oxidative phosphorylation and mitochondria. A force-directed subnetwork of the top intramodular members (|bicor| > 0.6) positioned SLC13A5 adjacent to a densely connected nucleus including CYP46A1, ITM2B, NRGN, GABRD, FBXO2, CHCHD10, CYSTM1, and MFSD4A. Conclusions: Together, these results define a developmentally tuned, mitochondria-centered program that co-varies with SLC13A5 in the human brain across the lifespan. It may provide insights to interrogate age-dependent phenotypes and therapeutic avenues for disorders involving citrate metabolism. Full article

Personalized anesthesia has emerged as a key direction in modern perioperative medicine, driven by advances in molecular biology, analytical technologies, and digital monitoring. Traditional physiological parameters often fail to detect early stages of organ dysfunction, whereas molecular biomarkers provide earlier and more sensitive insight into inflammation, oxidative stress, neurotoxicity, and renal or hepatic injury. Inflammatory markers such as IL-6, CRP, and PCT indicate early immune activation, while oxidative stress biomarkers, including 8-isoprostanes and malondialdehyde, quantify metabolic imbalance and ischemia–reperfusion injury. Neurotoxicity biomarkers such as S100β, NSE, and GFAP allow early detection of subclinical cerebral injury, whereas kynurenine-pathway metabolites reflect neuroinflammation and the risk of postoperative cognitive dysfunction. Renal biomarkers such as NGAL, KIM-1, and cystatin C detect acute kidney injury significantly earlier than creatinine, and miR-122 holds strong potential as an early marker of hepatocellular injury. Genetic and epigenetic biomarkers—including polymorphisms in CYP2D6, CYP3A4/5, RYR1, OPRM1, and COMT, as well as microRNA-based signatures—enable individualized drug dosing and optimization of anesthetic strategies. Meanwhile, digital biomarkers such as EEG-derived indices, HRV, and NIRS provide continuous real-time physiological monitoring and can integrate with AI-based algorithms for predictive, adaptive anesthesia management. Although no single biomarker meets all criteria for an ideal clinical indicator, combining molecular, genetic, and digital biomarkers represents the most promising pathway toward fully personalized, safe, and outcome-optimized perioperative care. Full article