Search Results (184)

Teleost social behavior plays an important role in foraging, reproduction, and aquaculture management, yet its physiological basis remains poorly understood. This study investigated individual differences in sociability in the large yellow croaker (Larimichthys crocea) using behavioral assays and metabolomic profiling in the brain–intestine axis. Behavioral tests revealed that high-sociability (HS) fish spent significantly more time near conspecifics than low-sociability (LS) fish, indicating clear behavioral divergence between groups. Targeted metabolomics of brain tissue showed distinct neurotransmitter signatures between HS and LS individuals, including significant differences in acetylcholine, DOPAC, xanthurenic acid, and glutamine. Untargeted intestinal metabolomics identified 65 differential metabolites between groups. Intestinal metabolites such as LEA and CEA exhibited significant group-specific variation and were functionally associated with CB1 and CB2 cannabinoid receptors, suggesting a potential endocannabinoid-mediated contribution to sociability differences. Differential metabolites enriched in amino–sugar and nucleotide–sugar metabolic pathways. Integration of behavioral and metabolomic data suggests that neurotransmitter regulation and gut–brain metabolic signaling jointly contribute to sociability differences in large yellow croaker. These findings provide mechanistic insights into social behavior and offer potential biomarkers for welfare assessment and selective breeding in aquaculture. Full article

The central Bohai Sea (CBS) is the distribution center and wintering grounds for economically important species of fish, shrimp, and crabs migrating from the Yellow Sea and the BS. However, the frequency of hypoxia in the CBS has gradually increased, posing a threat to its ecology. Therefore, we analyzed data from an on-site investigation of the cold-water mass coverage area in the southern part of the BS in the spring, summer, and autumn of 2022. We investigated the characteristics of seasonal variation in water quality parameter, the main characteristics and leading factors affecting the distribution of bottom hypoxia using stratification data and the Nutritional Status Quality Index. The “boot-shaped” distribution of hypoxia in summer was primarily the result of the intrusion of cold and highly saline water from the northern part in the study area, as well as the intrusion of high-temperature and low-salinity water from the Yellow River estuary (YRE) and the high-salinity water in the northeast corner of the study area, which had altered the stratification effect of the region. This is also the main reason that affects the accuracy of the prediction for occurrence of hypoxia stations in summer. The results show that the cold-water mass in the northern part of the Bohai Sea invades the cold-water mass in the southern part in summer 2022. Thus, this study provides novel insights into the formation and distribution of hypoxia in the CBS. Full article

Cannabinoid receptor (CB1), a G protein coupled receptor (GPCR), is a known pharmacological target in several diseases and modulates key physiological processes through Gi protein-mediated signaling. However, recent evidence suggests that CB1 can also activate other G proteins, including the stimulatory Gs protein, a phenomenon with unclear structural determinants. Here, we use a computational approach to elucidate the structural basis of the CB1-Gs interaction. Protein–protein docking and extensive molecular dynamics simulations yield a model for the CB1-Gs complex that agrees well with both existing experimental data and available GPCR-Gs structures, supporting its validity. This work provides new insights into the structural basis of CB1’s ability to couple with different G-proteins. The model provides a basis for future studies dissecting the functional consequences of CB1-Gs signaling and the development of improved therapeutics targeting the CB1 receptor and the wider endocannabinoid system. Full article

The article’s main focus is on identifying the key enablers that are making Industry 4.0 adoption easier, utilizing structural equation modeling via SPSS version 26. A comprehensive examination of previous studies led to the identification of 10 main enablers and 35 associated sub-enablers. Data collected from 182 manufacturing companies in India, selected by simple random sampling, was used for quantitative research. The analysis basically depends on PLS-SEM and CB-SEM (Partial Least Squares and Covariance-Based Structural Equation Modeling) path modeling. The findings indicate that technological enablers such as data analytics and artificial intelligence, computational power and connectivity, technologies that integrate physical and digital systems, and other enabling technologies are crucial to Industry 4.0 adoption. Additionally, organizational enablers (including a supportive organization, government efforts and promotions, and human resources) are also found to be significant contributors to Industry 4.0 implementation. Additionally, the study identified a significant mediating effect between technological and organizational enablers, emphasizing the importance of collaborative visualization mechanisms, established through bootstrapping with bias-corrected confidence intervals. Strengthening technological, organizational, and collaborative capabilities through Industry 4.0 adoption allows firms to attain improved operational performance while advancing sustainability objectives. These results contribute to the present understanding of Industry 4.0 adoption by offering useful implications for policymakers and industry practitioners. These insights guide managers and policymakers in structuring digital transformation initiatives. Full article

Global warming has accelerated glacier retreat worldwide, intensifying the vulnerability of ecosystem services and posing challenges to the sustainability of glacier-based tourism. Understanding how environmental changes influence tourist behavior is essential for balancing ecological conservation with tourism development. This study examines the Gangshika Glacier in the Lenglongling region of the eastern Qilian Mountains, China. By integrating Revealed Preference (RP) and Stated Preference (SP) data within a Travel Cost–Contingent Behavior (TC-CB) model, we assess the recreational value of glacier tourism and simulate tourist responses under alternative environmental scenarios. The findings indicate that the total annual recreational value of the site is approximately 6.52 billion CNY, with a per-visit consumer surplus (CS) of 1.16 × 10⁴ CNY. Moreover, environmental degradation exerts a statistically significant negative effect on visitation frequency (p < 0.01). Beyond quantifying economic value, the study highlights the broader implications for ecotourism management, emphasizing the need for dynamic environmental monitoring, low-impact infrastructure, and local community engagement. These results provide actionable insights into how glacier destinations can enhance resilience and contribute to sustainable development under climate change. Full article

This study examines how Zero-Waste Management (ZWM) and Green Innovative Supply Chain Management (GISCM) influence environmental and operational performance through the mediating role of Green Dynamic Capabilities (GDCs). Building on the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), the study develops a model that explains how firms translate green practices into superior performance outcomes. Using survey data from 132 manufacturing firms in Oman and covariance-based structural equation modeling (CB-SEM), the results demonstrate that both ZWM and GISCM significantly enhance sustainable performance, with GISCM exerting the stronger overall effect. Moreover, GDC fully mediates the relationship between ZWM and operational performance and partially mediates the GISCM–performance links. These findings highlight that sustainability-driven outcomes depend on firms’ abilities to sense, seize, and reconfigure resources for continuous environmental innovation. The study advances theory by integrating RBV and DCT within the green operations context and provides practical insights for managers in emerging economies on developing dynamic and learning-based capabilities to achieve sustainable manufacturing competitiveness. Full article

This study assesses air quality and health impact in Hanoi, Vietnam, using the Community Multiscale Air Quality (CMAQ) model and health impact assessment to evaluate the effectiveness of traffic emission reduction strategies under two scenarios. An updated emission inventory was used as the input data for the CMAQ model. The Weather Research and Forecasting (WRF-CMAQ) model (version 5.4), incorporating the CB6 chemical mechanism, was applied alongside a calibrated meteorological model to simulate pollutant dispersion. The model achieved strong performance in PM_2.5 simulation, with a correlation coefficient (R) of 0.78, an index of agreement (IOA) of −0.5, a Normalized Mean Bias (NMB) of 7.11%, and a normalized mean error (NME) of 28.51%. Seasonal analysis revealed higher concentrations of CO, NO₂, O₃, and SO₂ in January compared to July, driven by traffic and industrial emissions. Improved air quality in July was attributed to favorable meteorological conditions, such as increased rainfall and clean airflows from the sea. Spatial distribution highlighted elevated pollutant levels in urban areas, while PM_2.5 was significantly influenced by long-range transport and atmospheric processes. However, fine dust concentrations remained high in suburban areas, driven by secondary emissions and nearby industrial zones. An emission reduction scenario based on the Hanoi city policy decree focusing on traffic sources demonstrated its potential to reduce NO₂, SO₂, and PM_2.5 concentrations, though the impacts varied across time and space. Health impact due to population exposure to PM_2.5 shows that the densely populated suburbs surrounding the urban core have the largest impact in terms of mortality and cardiovascular diseases hospitalization. As PM_2.5 has the largest impact on these two health endpoints, only PM_2.5 impact assessment is performed. Health impact due to air pollution is higher in January (dry season) with estimated 625 deaths and 124 cardiovascular diseases (cvd) hospitalization as compared with estimated 94 deaths and 18 cvd hospitalization in July (wet season). One of the research questions posed by the city authority is whether converting diesel buses to electric buses can yield environmental and health benefits. Our work shows that the scenario based on Hanoi city decree of replacing 50% of fossil fuel combustion buses with electric buses by 2035 does not yield perceptible change in mortality health effect. This is due to emission from buses being small as compared to those from the whole transport sector and other sectors. This study emphasizes the need for integrated, targeted emission control strategies to address spatial and temporal variability in pollution. The findings offer valuable insights for policymakers to develop effective measures in urban planning for improving air quality and protecting the health of people in Hanoi. Full article

Background/Objectives: The cannabinoid type 2 receptor (CB₂ receptor) has been extensively studied in recent years due to the benefits associated with its modulation, including the regulation of the inflammatory response, neuroimmunomodulatory properties, and antitumor effects, all with the advantage of lacking significant psychoactive effects. Herein, we report the design, synthesis, characterization, biological assays, and molecular modelling analyses of novel (5/6-chloro-2-aryl-1H-benzo [d]imidazol-1-yl)(4-methoxyphenyl)methanone and 5/6-chloro-1-(4-methoxybenzyl)-2-aryl-1H-benzo [d]imidazole regioisomers as potential cannabinoid type 2 receptor ligands. Methods: The compounds were evaluated for their presumed CB₂ agonist activity using an indirect receptor-dependent apoptotic cell death assay exerted by cannabinoids, using the cell lines HEK293 (low CB₁/CB₂ expression), U-87 MG (high CB₁ expression), and HL-60 (exclusive CB₂ expression), and including the known cannabinoid ligands WIN-55,212-2 and AM630 as reference ligands. Flow cytometry was performed to assess apoptosis. Molecular docking and molecular dynamics simulations were used to explore ligand-receptor interactions at the CB₂ active site. Results: Compounds 3a, 3b’, 3c, and 4b selectively reduced HL-60 cell viability, similar to WIN-55,212-2, while showing no toxicity toward HEK293 or U-87 MG cells. Flow cytometry indicated that compounds 3a and 3c induced apoptosis in HL-60 cells comparable to WIN-55,212-2. Computational studies suggested that both compounds bind within the CB₂ receptor active site predominantly through π–π and hydrophobic interactions involving their benzo [d]imidazole cores, 2-aryl moieties, and 4-methoxybenzoyl scaffolds, resembling the binding patterns of established CB₂ ligands. Conclusions: Compounds 3a and 3c exert selective cytotoxicity against HL-60 cells, likely via a CB₂ agonist-mediated apoptotic mechanism. The applied combined experimental and computational approach provides a rapid, informative strategy for preliminary evaluation of CB₂ ligands and guides subsequent detailed pharmacological studies. Full article

The antigenic relationship between Eurasian avian-like H1N1 swine influenza viruses (EA H1N1) and human pandemic 2009 H1N1 viruses (2009/H1N1) remains a critical question for influenza surveillance and vaccine efficacy. This study systematically investigated the antigenic differences between strains A/swine/Tianjin/312/2016 (TJ312, EA H1N1) and A/Guangdong-Maonan/SWL1536/2019 (GD1536, 2009/H1N1). Cross-hemagglutination inhibition (HI) assays revealed a significant antigenic disparity, with a 16-fold reduction in heterologous versus homologous HI titers. Comparative sequence analysis identified 22 amino acid differences across the five major antigenic sites (Sa, Sb, Ca1, Ca2, and Cb) of the HA1 subunit. Using reverse genetics, a panel of mutant viruses was generated. This study revealed that a single histidine (H)-to-asparagine (N) substitution at residue 128 (H3 numbering) in the Sa antigenic site acts as a primary determinant of antigenic variation, sufficient to cause a four-fold change in HI titers and a measurable drift in antigenic distance. Structural modeling via AlphaFold3 and PyMOL software suggests that the H128N mutation may alter the local conformation of the antigenic site. It is plausible that H at position 128 could exert electrostatic repulsion with adjacent amino acids, whereas N might facilitate hydrogen bond formation with neighboring residues. These interactions would potentially lead to structural changes in the antigenic site. Our findings confirm that residue 128 is a critical molecular marker for the antigenic differentiation of EA H1N1 and 2009/H1N1 viruses. The study underscores the necessity of monitoring specific HA mutations that could reduce cross-reactivity and provides valuable insights for refining vaccine strain selection and pandemic preparedness strategies. Full article

As the workforce adapts to evolving professional demands, working conditions simultaneously become increasingly stressful, competitive, and challenging, making it essential to examine the determinants of job performance among highly educated workers. This study investigates the influence of psychological capital, work–life balance, rewards, and incentives, and work commitment on job performance among higher education professionals, with particular attention to gender differences. A survey was administered to 661 university-educated workers, and the data was analyzed using covariance-based structural equation modeling (CB-SEM). Results demonstrate that psychological capital, work–life balance, and rewards and incentives positively influence job performance across both genders. However, the mediating effect of work commitment between rewards and incentives, work–life balance, and job performance was confirmed only among women. Work–life balance emerged as the primary factor influencing psychological capital, surpassing the impact of rewards and incentives. The findings reveal significant gender differences in professional commitment patterns, suggesting that women workers exhibit stronger emotional connections between organizational support mechanisms and performance outcomes. Practical implications emphasize the need for organizations to prioritize work–life balance strategies as foundational elements of human resource management, while implementing comprehensive reviews of gender equality policies to ensure equitable workplace experiences. This research contributes valuable insights for developing targeted interventions that optimize professional performance while addressing gender-specific workplace dynamics in emerging economies. Full article

Background/Objectives: Hypertension is a global health challenge. Zhengan Xifeng Decoction (ZXD), a classical traditional Chinese medicine, has shown clinical efficacy against hypertension. This study aimed to identify the bioactive constituents of ZXD and elucidate its antihypertensive mechanisms by integrating plasma UPLC–MS (ultra-performance liquid chromatography–mass spectrometry) analysis, network pharmacology, and molecular dynamics (MD) simulations. Methods: ZXD constituents and plasma-absorbed compounds were characterized by UPLC–MS. Putative targets (TCMSP, SwissTargetPrediction) were cross-referenced with hypertension targets (GeneCards, OMIM) and analyzed in a STRING protein–protein interaction network (Cytoscape) to define hub targets, followed by GO/KEGG enrichment. Selected protein–ligand complexes underwent docking, Prime MM-GBSA calculation, and MD validation. Results: A total of 72 absorbed components were identified, including 14 prototype compounds and 58 metabolites. Network pharmacology identified ten key bioactive compounds (e.g., liquiritigenin, isoliquiritigenin, and caffeic acid), 149 hypertension-related targets, and ten core targets such as SRC, PIK3CA, PIK3CB, EGFR, and IGF1R. Functional enrichment implicated cardiovascular, metabolic, and stress-response pathways in the antihypertensive effects of ZXD. Molecular docking demonstrated strong interactions between key compounds, including liquiritigenin, caffeic acid, and isoliquiritigenin, and core targets, supported by the MM-GBSA binding free energy estimation. Subsequent MD simulations confirmed the docking poses and validated the stability of the protein–ligand complexes over time. Conclusions: These findings provide mechanistic insights into the multi-component, multi-target, and multi-pathway therapeutic effects of ZXD, offering a scientific basis for its clinical use and potential guidance for future drug development in hypertension management. Full article

TGR5 has emerged as a promising therapeutic target for obesity and metabolic disorders due to its regulatory roles in energy expenditure, glucose homeostasis, thermogenesis, and gut hormone secretion. This review summarizes the structural mechanisms of TGR5 activation, focusing on orthosteric and allosteric ligand interactions, toggle switch dynamics, and G protein coupling based on cryo-EM and docking-based models. A wide range of bioactive natural compounds including oleanolic acid, curcumin, betulinic acid, ursolic acid, quinovic acid, obacunone, nomilin, and 5β-scymnol are examined for their ability to modulate TGR5 signaling and elicit favorable metabolic effects. Molecular docking simulations using CB-Dock2 and PDB ID 7BW0 revealed key interactions within the orthosteric pocket, supporting their mechanistic potential as TGR5 agonists. Emerging strategies in TGR5-directed drug development are also discussed, including gut-restricted agonism to minimize gallbladder-related side effects, biased and allosteric modulation to fine-tune signaling specificity, and AI-guided optimization of natural product scaffolds. These integrated insights provide a structural and pharmacological framework for the rational design of safe and effective TGR5-targeted therapeutics. Full article

Skeletal muscle, constituting 40–50% of total body mass, is vital for mobility, posture, and systemic homeostasis. Muscle contraction heavily relies on ATP, primarily generated by mitochondrial oxidative phosphorylation. Mitochondria play a key role in decoding intracellular calcium signals. The endocannabinoid system (ECS), including CB₁ receptors (CB₁Rs), broadly influences physiological processes and, in muscles, regulates functions like energy metabolism, development, and repair. While plasma membrane CB₁Rs (pCB₁Rs) are well-established, a distinct mitochondrial CB₁R (mtCB₁R) population also exists in muscles, influencing mitochondrial oxidative activity and quality control. We investigated the role of mtCB₁Rs in skeletal muscle physiology using a novel systemic mitochondrial CB₁ deletion murine model. Our in vivo studies showed no changes in motor function, coordination, or grip strength in mtCB₁ knockout mice. However, in vitro force measurements revealed significantly reduced specific force in both fast-twitch (EDL) and slow-twitch (SOL) muscles following mtCB₁R ablation. Interestingly, knockout EDL muscles exhibited hypertrophy, suggesting a compensatory response to reduced force quality. Electron microscopy revealed significant mitochondrial morphological abnormalities, including enlargement and irregular shapes, correlating with these functional deficits. High-resolution respirometry further demonstrated impaired mitochondrial respiration, with reduced oxidative phosphorylation and electron transport system capacities in knockout mitochondria. Crucially, mitochondrial membrane potential dissipated faster in mtCB₁ knockout muscle fibers, whilst mitochondrial calcium levels were higher at rest. These findings collectively establish that mtCB₁Rs are critical for maintaining mitochondrial health and function, directly impacting muscle energy production and contractile performance. Our results provide new insights into ECS-mediated regulation of skeletal muscle function and open therapeutic opportunities for muscle disorders and aging. Full article

This study aims to elucidate the neurodevelopmental toxicity and molecular mechanisms of endocrine-disrupting chemicals (EDCs) in neurodevelopmental disorders (NDDs) through a network toxicology approach, using triclosan exposure as a case example. Potential targets of triclosan were identified via comparative analysis of toxicogenomics databases such as the Comparative Toxicogenomics Database (CTD), Similarity Ensemble Approach (SEA), SwissTargetPrediction, and TargetNet. NDD-related targets were retrieved from GeneCards, Disease Gene Network (DisGeNET), and Online Mendelian Inheritance in Man (OMIM), resulting in 633 overlapping genes associated with disease pathology and triclosan effectors. Protein–protein interaction networks were constructed using STRING and Cytoscape, applying median-based algorithms to identify six core genes: AKT1, TP53, EGFR, FN1, SRC, and ESR1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses via Metascape revealed that triclosan-induced NDDs are primarily associated with endocrine signaling disruption and activation of the PI3K-Akt pathway. Molecular docking with CB-Dock2 demonstrated strong binding affinities between triclosan and the core targets, while YASARA molecular dynamics simulations confirmed stable interactions, notably with EGFR, exhibiting high binding stability. Collectively, these findings delineate the potential molecular mechanisms underlying triclosan-induced NDDs and underscore the utility of network toxicology, molecular docking, and molecular dynamics simulations in assessing neurotoxicity and related molecular pathways. This research provides novel insights for future investigations, enhances understanding of the potential impact of neurodevelopmental disorders on health, and lays a scientific foundation for the development of preventive and therapeutic strategies. Full article

Molecular profiling of testicular germ cell tumors (TGCTs) provides critical insights into personalized treatment approaches, particularly for patients with recurrent or treatment-resistant disease. In this study, we retrospectively analyzed clinicopathological and targeted genomic sequencing data from 27 TGCT patients, including 7 seminomas, 19 non-seminomas, and 1 prepubertal type teratoma, across stage I (48%), stage II (41%), and stage III (11%). Tumor samples were obtained from 27 orchiectomies, with additional pathological specimens collected from 16 of these patients during retroperitoneal lymph node dissections (RPLNDs); these included 8 chemotherapy-naïve and 8 post-chemotherapy cases. The median tumor mutational burden (TMB) was 0.5 mutations/Mb, consistent with the low mutation rate typically observed in TGCTs. Somatic mutations and copy number gain alterations were detected in 56% (15/27) of patients, primarily in KRAS (25.9%), KIT (11.1%), and PIK3CB (7.4%). PD-L1 positive immunoreactivity by immunohistochemistry was observed in 75% of tumors (60% in stage I, 100% in stage III) analyzed (n = 8), suggesting potential immune checkpoint inhibitor applicability in advanced disease. Microsatellite instability (MSI) status was identified in 23 tumors; all were classified as MSI-low, supporting the rarity of MSI-driven tumorigenesis in TGCTs. Actionable gene alterations linked to FDA-approved therapies, interventional therapies, and clinical trials in TGCTs and other cancers (lung, skin, colon, liver, stomach, and breast) were present in 59.3% (16/27) of patients, indicating potential therapeutic repurposing. Additionally, germline variants of uncertain clinical significance in known cancer actionable genes, including MSH2, MSH6, RB1, and BRCA2, were found in 9 patients, warranting further investigation regarding their clinical relevance and susceptibility risk. Our findings highlight that a substantial proportion of TGCT patients harbor potentially actionable molecular alterations across all disease stages. Full article