Search Results (2,880)

Gatifloxacin (GTFX), a fourth-generation fluoroquinolone, causes metabolic disturbances in mammals, but its hepatotoxic mechanisms in aquatic vertebrates remain unclear. This study investigated whether GTFX induces liver injury in zebrafish larvae through oxidative stress or alternative pathways. Larvae at 3 days post-fertilization were exposed to 0.2–2.3 mg/mL GTFX for 48 h. Liver morphology, histopathology, intracellular reactive oxygen species (ROS), and expression of lipid metabolism (pparg) and xenobiotic biotransformation genes (cyp1a, cyp1b1) were assessed. GTFX exposure caused concentration-dependent reductions in liver area, increased hepatic opacity, delayed yolk sac absorption, and hepatocyte swelling with cytoplasmic vacuolization. Despite these structural changes, ROS levels did not differ significantly from those of controls. In contrast, transcriptional analysis revealed significant upregulation of pparg, cyp1a, and cyp1b1, indicating disrupted lipid homeostasis and enhanced detoxification responses. Acute high-dose GTFX exposure induced a metabolism-associated hepatotoxic response in zebrafish larvae, which occurred without a statistically significant change in bulk ROS levels. Together, these findings offer mechanistic insight into fluoroquinolone-associated liver injury. Full article

Assessing genetic structure is important for conserving endangered freshwater fishes inhabiting fragmented river systems. Pseudopungtungia nigra, a Korean endemic species, occurs in several isolated drainages, but its mitochondrial population structure has not been fully evaluated. In this study, we analyzed mitochondrial cytochrome b (cytb) sequences from 80 individuals across eight populations to examine genetic diversity, haplotype composition, and population differentiation. A total of 25 haplotypes were detected, indicating relatively high diversity at the species level. However, diversity was uneven among populations: the Mangyeonggang (MG) population contained only two haplotypes, both of which were not found in the other populations, and showed the lowest haplotype and nucleotide diversity among the sampled populations. Multiple analyses, including pairwise differentiation, haplotype network reconstruction, principal coordinates analysis, and AMOVA, consistently identified MG as the most divergent population. The mitochondrial pattern was also concordant with previously reported microsatellite-based structure, supporting a major division between MG and the remaining populations. These findings indicate that P. nigra preserves substantial diversity overall, whereas the MG population showed a restricted and population-specific cytb haplotype composition. This study provides a genetic basis for defining conservation units and for guiding restoration and management strategies in this endangered species. Full article

Background: Paracetamol is widely used for acute pain management in orthopedic trauma; however, interindividual variability in analgesic response remains insufficiently understood. Cytochrome P450 2E1 (CYP2E1), a key enzyme involved in paracetamol metabolism and the formation of the toxic metabolite N-acetyl-p-benzoquinone imine (NAPQI), may contribute to this variability. This study aimed to investigate the relationship between CYP2E1 gene polymorphisms and the analgesic efficacy of paracetamol in patients with lower extremity fractures. Methods: A total of 127 patients with lower extremity fractures and 100 healthy controls were included. All patients received 1000 mg of intravenous paracetamol. Pain intensity was assessed using the Visual Analog Scale (VAS) at baseline and at 30, 60, and 120 min after administration. Genotyping of CYP2E1 polymorphisms (*1A, *5B, *6, and *7B) was performed using PCR-RFLP. Differences in the VAS scores and analgesic response were analyzed according to genotype. Results: Paracetamol administration resulted in a significant reduction in pain scores at all time points (p < 0.001). Patients carrying the CYP2E15B variant exhibited significantly higher VAS scores and a weaker early analgesic response compared to non-carriers (p ≤ 0.001). Similarly, CYP2E11A carriers demonstrated higher pain scores across all time points (p < 0.05), although the magnitude of effect was less pronounced. No significant differences were observed for the CYP2E16 variant. Due to low frequency, CYP2E17B could not be reliably analyzed. Conclusions: Paracetamol is an effective analgesic in patients with lower extremity fractures; however, CYP2E1 polymorphisms may modulate individual pain perception and early analgesic response. In particular, the *5B and, to a lesser extent, *1A variants are associated with higher pain scores. These findings support the potential role of pharmacogenetic approaches in personalized pain management. Full article

Introduction: A genetic algorithm (GA)-based approach was designed to predict drug–drug interactions (DDIs) triggered by cytochrome P450 3A (CYP3A) inhibition or induction in horses. Methods: Area under the concentration-time curve ratios (AUCRs), obtained from published in vivo DDI studies in horses, were used to compute the following parameters: (1) the contribution ratio (CR), i.e., the fraction of the substrate dose metabolized via the CYP3A pathway, and (2) the interacting drug’s inhibitory potency or inducing efficacy (IR or IC, respectively). Results: AUCRs for 9 substrates, 12 inhibitors, and 1 inducer of equine CYP3A were predicted and validated with the developed method. More than 96% of predictions fell within the commonly accepted range of 50–200% of observed values. Conclusions: The proposed GA-based method may be a useful tool to estimate possible clinically relevant DDIs when co-administration of a CYP3A substrate and a CYP3A-interacting drug is anticipated. Full article

Background/Objectives: Cytochrome P450 enzymes (CYP2D6, CYP2C19, CYP3A4) play a key role in interindividual variability in cardiovascular drug metabolism. This study aimed to describe metabolizer phenotype distributions in a Turkish emergency cardiac cohort and across diagnostic categories. Methods: This retrospective descriptive pharmacogenomic study included 250 patients. Genotyping was performed using TaqMan assays for CYP2D6 (*2, *4, *10, *41), CYP2C19 (*2, *17), and CYP3A4 (*22, *1B). Phenotypes were assigned according to CPIC guidelines. CYP2D6 copy-number variation was not assessed. Results: Non-normal metabolizer phenotypes were observed in 55.6% (CYP2D6), 84.4% (CYP2C19), and 30.4% (CYP3A4) of patients. For CYP2D6, normal (44.4%) and intermediate (42.0%) metabolizers predominated. For CYP2C19, intermediate metabolizers were most frequent (36.0%), followed by normal (22.8%), rapid (17.2%), poor (14.8%), and ultra-rapid metabolizers (9.2%). CYP3A4 showed predominantly normal activity (69.6%). Phenotype distributions varied across diagnoses without clear clustering. Conclusions: A high prevalence of CYP2D6 and CYP2C19 variability with predicted functional relevance based on CPIC was observed, whereas CYP3A4 activity was more stable. These findings provide descriptive pharmacogenomic data to support future genotype-guided cardiovascular therapy studies. Full article

Although the effectiveness of plant-derived essential oils (EOs) against several insect pests is well-documented, their high volatility presents a challenge. In this study, the potential to enhance the insecticidal activity of Satureja hortensis L. EO, an accessible natural agent, through nanoemulsification was assessed against the cosmopolitan pest Spodoptera frugiperda (J. E. Smith, 1797). The nanoemulsion of the EO (NEEO) was prepared using Tween 80 as the emulsifying agent and high-intensity ultrasonication. Oral bioassays indicated that the NEEO was more toxic (LC₅₀ = 0.922%) than the pure EO (LC₅₀ = 1.186%). Sublethal exposure to LC₃₀ of the NEEO caused evident reductions in preadult survival, developmental time, fecundity, and oviposition period, as well as the population growth parameter net reproductive rate (R₀). The exposure to the NEEO increased catalase (CAT), glutathione S-transferase (GST), and superoxide dismutase (SOD) actions and inhibited α-esterase (α-NE), β-esterase (β-NE), and cytochrome P450 (CYP450) actions. Both the NEEO and EO inhibited acetylcholinesterase (AChE) and Na⁺/K⁺-ATPase, with higher inhibition in the NEEO group. Generally, S. hortensis NEEO enhanced toxicity, intensified physiological perturbations, and caused greater negative impacts on population growth parameters. Consequently, nanoemulsification of S. hortensis EO can be considered an effective method to strengthen the insecticidal potential of this natural agent. Full article

Protein molecularly imprinted polymers (MIPs), as artificial antibodies, are promising for protein separation due to their low cost, easy preparation, and high stability, but their performance is limited by poor mass transfer, imprecise imprinting, and single interaction modes. Herein, dendritic mesoporous silica nanoparticles (DMSNs) were used as the support, and a self-designed multifunctional poly(ionic liquid) macromonomer (p(VIMCD-co-VAIM-co-VSIM-co-VVIM)) served as the functional monomer to achieve directional anchoring of cytochrome C (Cyt-C). Surface-imprinted microspheres (DMSNs@MPS@PILs-MIPs) were prepared via free-radical copolymerization for Cyt-C recognition. The DMSNs possessed interconnected mesoporous channels, good dispersibility, an average particle size of ~80 nm, and a specific surface area of 267.97 m²/g. Ionic liquid monomers were synthesized via alkylation, and the macromonomer was constructed through a two-step method. Molecular dynamics simulations and spectroscopic characterization revealed the macromonomer-stabilized Cyt-C conformation, with interactions dominated by van der Waals forces. The DMSNs@MPS@PILs-MIPs featured a thin imprinted layer (~5 nm) to reduce mass-transfer resistance. Adsorption studies showed Cyt-C adsorption followed Langmuir and pseudo-second-order models, with a maximum capacity of 383.14 mg/g and an imprinting factor of 2.17. Only 12% capacity loss occurred after repeated cycles, indicating robust regeneration stability. This study provides a feasible strategy for constructing protein surface-imprinted polymers based on multifunctional synergistic interactions and conformational stabilization. Full article

The Colorado potato beetle, Leptinotarsa decemlineata, is a major insect pest of potatoes. Our previous studies have demonstrated that two cytochrome P450 monooxygenase (P450s) genes, CYP9Z140 and CYP9AY1, and a uridine diphosphate–glycosyltransferase (UGT) gene, UGT321AP1, play important roles in thiamethoxam resistance to L. decemlineata. However, the related upstream regulatory mechanism remains unclear. In this study, we first monitored the resistance of L. decemlineata field populations to thiamethoxam in Xinjiang to determine the resistance ratios. The predicted results demonstrated that four transcription factors (TFs), CncC/Maf, Abd-B, FoxO, and Ptx1, may bind to the core regions of three gene promoters. The qRT-PCR results revealed that the TFs were significantly upregulated by thiamethoxam and exhibited specific spatiotemporal expression patterns. Dual-luciferase reporter assays indicated that the CncC pathway could regulate the expression of three detoxification genes, whereas Abd-B and FoxO only regulate CYP9Z140 and UGT321AP1 expressions, respectively. Ptx1 could regulate the expression of both CYP9AY1 and UGT321AP1. Furthermore, knockdown of several TFs through RNA interference significantly reduced expression of the corresponding detoxification genes, consistent with the dual-luciferase reporter assay results, and increased the thiamethoxam susceptibility of test adults. These findings aid in gaining a deeper understanding of the transcriptional regulation mechanisms of insecticide resistance in insects. Full article

This study investigated the application of six machine learning regression algorithms such as Random Forest, CatBoost, K-Nearest Neighbours, XGBoost, LightGBM, and Gradient Boosting, paired with Molecular ACCess System (MACCS) key fingerprints for the quantitative prediction of aromatase (CYP19A1) inhibitory potency, expressed as pIC₅₀. A dataset of 187 compounds was assembled from the ChEMBL database (version 33, Target ID: CHEMBL1978) following by systematic data curation workflow encompassing duplicate removal, pIC₅₀ transformation, and activity-based filtering. Model performance was rigorously evaluated using an 80/20 stratified train/test split, 5-fold cross-validation, and Y-randomisation testing to ensure unbiased assessment of predictive generalisation. Feature selection via CatBoost permutation importance on the held-out test set identified the top 20 predictive MACCS keys from an initial 166-bit space, substantially reducing dimensionality and improving generalisation across all models. Among the algorithms evaluated, CatBoost trained on the top 20 features achieved the strongest test-set performance (R² = 0.693, RMSE = 0.794, MAE = 0.659) with the most stable cross-validation R² (0.062 ± 0.304), outperforming all other algorithms. Y-randomisation testing returned an empirical p-value of <0.01, confirming that model performance reflects genuine structure–activity relationships rather than statistical chance. Permutation importance and SHAP analysis identified nitrogen-containing heterocyclic fragments (MACCS_41, MACCS_145) and halide-bearing substructures (MACCS_109) as the primary structural determinants of aromatase inhibitory potency, consistent with established CYP19A1 pharmacophoric requirements. Application of the model to ten representative plasticizers demonstrated that the refined applicability domain (h* = 0.423) accommodated eight of the ten compounds, enabling reliable potency predictions across phthalate esters and bisphenol analogues. These findings establish a transparent and reproducible QSAR framework for first-tier endocrine disruption risk screening of plasticizers and highlight the importance of permutation-based feature selection and applicability domain assessment in QSAR model development. Full article

Meningiomas are the most common intracranial tumours, yet the molecular programs underlying WHO grade 1 subtypes—particularly transitional diploid tumours—remain insufficiently defined, partly due to the scarcity of biologically faithful in vitro models. Here, we report the establishment of a long-term, genetically unmanipulated grade 1 meningioma cell line (H8T-MG) maintained under normoxic conditions in serum-containing, growth-factor-supplemented medium, together with a complementary long-term primary culture (H16T-MG), and provide an integrated descriptive and functional characterization of these models, combined with a subtype-restricted transcriptomic analysis of diploid transitional grade 1 tumours versus normal meninges. Both cultures preserved the dual meso-neuroectodermal identity characteristic of meningothelial cells, exhibiting stable adherent growth, preserved contact inhibition and a coherent immunocytochemical profile, expressing vimentin, α-SMA, nestin, connexin-43 and cannabinoid receptors—reported here for the first time in grade 1 meningioma cultures—highlighting cannabinoid-related pathways as potential targets for exploration. Transcriptomic analysis identified 51 differentially expressed genes, revealing a coherent inflammatory–metabolic programme characterised by downregulation of IL-17 and TNF signalling, cytokines and chemokines (IL6, CCL2, SELE, S100A8), together with reduced extracellular-matrix and cytoskeletal activity. In parallel, the enrichment of arachidonic acid metabolism, cytochrome-P450/xenobiotic pathways, retinol metabolism and oxidative/epoxygenase activity indicated a lipid/xenobiotic-oriented metabolic shift distinctive of this subtype. Protein–protein interaction analysis identified four hub genes—ASPN, SELE, ACKR1 and ABCB1—integrating ECM remodelling, endothelial–immune modulation and xenobiotic transport, reinforcing an immune-attenuated, metabolically adapted tumour landscape. Collectively, these findings provide the first integrated in vitro and transcriptomic characterisation of diploid transitional meningiomas, underscore the value of biologically stable models for early-stage meningioma research, and support the value of histological and ploidy stratification in grade 1 meningioma biology. Full article

To identify candidate genes associated with skin tissue responses in Hu sheep raised under different regional rearing environments and to preliminarily explore their potential relevance to low-temperature-related environmental responses, this study used 1-year-old female Hu sheep raised in Anhui and Xinjiang as the experimental animals. Skin tissues were collected from the left scapular region, and their transcriptomic profiles were characterized by integrating histological analysis, RNA sequencing (RNA-seq), differential expression analysis, functional enrichment analysis, protein–protein interaction (PPI) network construction, and RT-qPCR validation. The results showed significant differences between the two groups in body weight, body length, body height, cannon circumference, rectal temperature, and ear temperature. Hematoxylin and eosin (H&E) staining indicated that the Xinjiang group exhibited a denser distribution of hair follicles, a relatively thicker dermis, and a more compact arrangement of collagen fibers, suggesting enhanced insulation-related skin characteristics. Transcriptome sequencing identified 295 differentially expressed genes (DEGs), including 193 upregulated and 102 downregulated genes. GO and KEGG enrichment analyses showed that these DEGs were mainly involved in immune and inflammatory responses, redox processes, extracellular matrix remodeling, and lipid and energy metabolism-related pathways, with significant enrichment in cytokine–cytokine receptor interaction, the chemokine signaling pathway, the NF-κB signaling pathway, glutathione metabolism, and drug metabolism–cytochrome P450. By further integrating PPI network analysis and functional annotation, CXCL13, CCL2, FGF21, GPX3, CYP1A1, HSD11B1, CDO1, and STEAP4 were identified as candidate genes. RT-qPCR results showed that the expression trends of the selected genes were generally consistent with the RNA-seq results. Overall, this study revealed differences in phenotypic traits, skin histological structure, and transcriptomic characteristics between Hu sheep raised in different regions, providing preliminary molecular clues potentially associated with low-temperature-related environmental responses. Given the differences in geographic origin and rearing environments between the two groups, the findings should be interpreted as associative evidence of skin transcriptomic responses in Hu sheep under different environmental conditions—rather than as direct causal evidence that low temperature alone drove these transcriptomic differences. Full article

Heme metabolism in the liver has traditionally been described as a linear pathway that supports oxygen utilization, redox balance, and detoxification. Here, we synthesize recent evidence and propose a framework in which heme functions as a system-level regulator, the “queen” of metabolism, whereas its upstream intermediate protoporphyrin IX (PPIX) represents a chemically reactive “dark twin” that emerges when metabolic flux fails to resolve. In this view, metabolic state is defined not only by end products but also by the behavior of pathway intermediates. This system is spatially organized. Hepatocytes dominate heme synthesis and utilization. In contrast, liver stromal compartments, particularly Kupffer cells, play a central role in heme degradation through heme oxygenase-1 (HMOX1), linking heme turnover to iron recycling and stress adaptation. The metabolic state of the liver therefore reflects not only pathway flux but also the degree of coupling between these cellular compartments. We propose a state model of hepatic heme metabolism. In the resolution state, most evident during inflammation, coordinated hepatocyte–macrophage activity maintains flux and limits intermediate accumulation. In contrast, the expansion state, exemplified in cancer, is defined by impaired flux completion, leading to PPIX accumulation, metabolic heterogeneity, and oxidative stress. This framework reframes liver disease through intermediate behavior rather than pathway presence: porphyrias reflect direct overload, metabolic liver diseases partial expansion, and hepatocellular carcinoma a fully developed expansion state. By focusing on the “intermediate space,” this model links biochemistry, spatial organization, and disease pathogenesis, while suggesting new opportunities for diagnosis and therapy based on metabolic state. Full article

Interpretation of pharmacometabolomics results, aiming particularly at biomarker (sets) discovery for drug exposure, remains a major challenge. The metabotyping of drug exposure depends on resolution of specific metabolomics techniques and comprises individual metabolic phenotypes (“metabotypes”), disease-, drug- and microbiome-specific patterns, as well as conditional metabolic states (e. g. fasting). In this clinical trial with 16 healthy participants, an exploratory objective was to evaluate the untargeted urinary metabolomics of voriconazole, administered in four single doses, using proton nuclear magnetic resonance (¹H-NMR) spectroscopy. Voriconazole is a second-generation triazole and a potent inhibitor of drug-metabolizing enzymes such as cytochrome P450 (CYP) isozymes CYP3A4 and CYP2C19. Therefore, identification of metabolites reflecting acute CYP3A4 inhibition was of particular interest. On two treatment days without and with voriconazole (with background microdosed midazolam and omeprazole administration for CYP3A4 and CYP2C19 phenotyping, respectively), spot urine was collected after overnight fasting (predose) and 4 h later (postdose fasting). In the postdose versus predose fingerprints, most changes at the annotated metabolite level were attributable to fasting metabolomics or potential confounders. ¹H-NMR spectroscopy identified neither a short-term voriconazole-specific signature nor patterns or metabolites potentially reflecting acute CYP3A4 inhibition. Our study emphasizes crucial significance of strict standardization of fasting time and minimization of confounder influences by clinical trial design as well as selection of adequate baselines and high-resolution analytical techniques in pharmacometabolomics research, especially for biomarker discovery. Full article

Antiretroviral drugs (ARVDs) remain the cornerstone of HIV/AIDS management, but their therapeutic efficacy and safety are highly influenced by bioconversion processes such as hepatic metabolism and enzymatic transformation. Variability in metabolic pathways, mediated by cytochrome P450 enzymes and other liver-based systems, contributes to interindividual differences in drug response, toxicity, and resistance. Recent advances in artificial intelligence, particularly artificial neural networks (ANNs), offer promising tools for modeling and optimizing these complex bioconversion processes. ANNs are capable of learning nonlinear relationships from high-dimensional datasets, making them ideal for predicting the pharmacokinetic parameters, enzyme–substrate interactions, and metabolic stability of ARVDs. This review explores the emerging role of ANNs in understanding and optimizing the metabolic transformation of antiretroviral agents. Key applications are discussed, including prediction of drug–enzyme interactions, in silico modeling of hepatic clearance, and simulation of enzyme kinetics. The integration of molecular descriptors, omics data, and clinical parameters into ANN models allows for improved prediction accuracy and personalized therapy. Furthermore, ANN-based tools can aid in early-stage drug development by identifying metabolic liabilities and guiding structural modifications to enhance metabolic stability. Despite their potential, challenges such as data scarcity, model interpretability, and standardization remain. Future research should focus on hybrid models combining ANN with mechanistic pharmacokinetics, the incorporation of real-world patient data, and validation against experimental outcomes. Overall, ANNs represent a powerful approach to optimizing ARVDs bioconversion, with the potential to improve efficacy, reduce toxicity, and support the development of next-generation antiretroviral therapies Full article

The recent rise in whole blood usage for traumatic hemorrhagic shock has renewed interest in the impact of leukocytes on hemostatic function during cold storage. This study investigated whether tissue factor (TF)-bearing extracellular vesicles (EVs) are released from human monocytic cells during cold storage or upon rewarming and whether this process is mechanistically linked to apoptosis. We further examined the contribution of superoxide anion generated by NADPH oxidase (NOX). Methods: THP-1 cells were incubated at 4 °C for up to 24 h with/without test reagents and subsequently rewarmed at 37 °C. Cells were washed by centrifugation before rewarming as required. TF activity in the cell supernatant was quantified, EVs were analyzed by flow cytometry with size-defined gating, and NOX activity normalized to p22^phox was measured by cytochrome c reduction. Results: TF levels and apoptotic cells increased during cold storage. TF release was enhanced 1–2 h after cell lavage following cold exposure, indicating active shedding of TF-bearing EVs rather than passive leakage from damaged membranes. Flow cytometry demonstrated that TF-bearing EVs were distinct from apoptotic vesicles, with a substantial proportion falling within the microvesicle size range. Cold exposure enhanced NOX activity. Both superoxide dismutase (SOD) and catalase inhibited TF release during cold storage; however, only SOD suppressed TF release after cell lavage. Conclusions: TF-bearing EVs are actively shed from human monocytic cells during and after cold storage via a NOX-dependent, superoxide-mediated mechanism. Extracellular SOD suppressed this procoagulant EV release, suggesting a potential strategy to modulate hemostatic alterations associated with cold-stored blood. Full article