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Exercise and time-restricted and/or dietary feeding jointly improve hepatic lipid homeostasis in diet-induced obese mice
Abstract Obesity and metabolic syndrome are associated with dysregulated hepatic lipid metabolism, contributing to metabolic dysfunction-associated steatotic liver disease (MASLD). Though lifestyle interventions such as a low-fat diet (LFD), treadmill (TM) exercise, and time-restricted feeding (TRF) reduce hepatic lipid accumulation, their combined effects on hepatic lipid composition and lipid metabolism-related gene regulation remain poorly understood. Here, we examined the individual and combined effects of LFD, TM, and/or TRF on liver function, comprehensive hepatic lipidomics, and lipid metabolism-related gene expression in diet-induced obese mice, thereby extending our previous work through detailed lipid class-specific analyses and assessment of interactive intervention effects. Among all interventions, LFD led to the greatest weight loss and normalized plasma aspartate aminotransferase (AST) as well as alanine aminotransferase (ALT) levels. Combined interventions, including TM and TRF, reduced markers of liver damage even under continued HFD conditions compared to HFD alone. LFD with TRF and/or TM decreased the expression of lipogenic genes ( Srebf1 , Lxrα , Apoe ), while expression of genes further involved in lipid synthesis ( Fasn and Hmgcr ) tended to be increased when TM was combined with either LFD or HFD. β-oxidation-related genes ( Ppara, Acox1, Cpt1a ) were most downregulated in the LFD groups vs. the HFD + TM group, likely representing a metabolic adaptation to increased lipid mobilization. For the first time, lipidomics analysis demonstrated that in particular LFD alone or in combination with TM most effectively increased sphingomyelin (SM) and dihydrosphingomyelin (DHSM) as well as lysophosphatidylcholine (LPC) and phosphatidylcholine (PC), potentially reflecting compensatory lipid remodeling. Taken together, these findings highlight distinct and additive effects of combined lifestyle interventions on hepatic lipid composition and gene regulation, clearly delineating the novel contributions of the present study and supporting combined dietary and physical strategies as potential approaches to improve hepatic lipid homeostasis and mitigate MASLD development.
Silver nanoparticles as antimicrobials: A comparative analysis of green and traditional chemistry synthesis methods
Silver nanoparticles (AgNPs) have garnered attention due to their antimicrobial properties and applications in nanomaterials. The objective of this study is to compare the antimicrobial activities of AgNPs synthesized using green and traditional methods with silver ions (Ag + ). The characterization of AgNPs was conducted through the utilization of UV-Vis spectroscopy, energy-dispersive X-ray spectrometry, transmission electron microscopy, X-ray diffraction, and differential pulse voltammetry (DPV). AgNPs presented quasi-spherical nature and well-dispersed characteristics, with a mean diameter around 10nm and 25nm for the traditional and green methods respectively. DPV measurements showed a decline of the area under the curve from 1.79 μA mm -2 to 0.7679 μA mm -2 , indicating limited colloidal stability of green AgNPs. In contrast, traditional AgNPs demonstrated stability over time, maintaining an area under the curve of around 31 μA mm -2 over a 30-day period. The antimicrobial efficacy against Staphylococcus aureus and Escherichia coli was assessed via the broth dilution method. The results indicated that there were similar minimum inhibitory concentrations and minimal bactericidal concentrations (MIC and MBC) for both nanoparticle types and Ag + against S. aureus (≈ 1 mM). While differences were detected against E. coli : traditional AgNPs evidenced lower MIC and MBC values on day 30 (≈ 0.5 mM) and Ag + evidenced MIC and MBC values of 0.5 and 0.75 mM on both days 1 and 30. Green AgNPs exhibited heightened antimicrobial activity over time, as evidenced by the planktonic growth of S. aureus and E. coli in days 1 and 30. This observation is concomitant with an increase in Ag⁺ release evidenced by DPV, underscoring the key role of silver ions in mediating antibacterial effects. This research contributes to a more comprehensive understanding of how synthesis method, nanoparticle stability, silver ion release, and testing methodology influence the antimicrobial performance of AgNPs, offering insights critical for their practical application.
Environmental impacts of metro rail construction in chennai on air quality noise pollution and urban sustainability
Brain morphological changes in acquired hearing loss: A surface-based morphometry study
Prolonged auditory deprivation induces neuroplastic changes throughout the brain, including the auditory system. Understanding these structural alterations is crucial for optimizing auditory rehabilitation strategies. This study investigated brain morphological alterations associated with bilateral severe-to-profound sensorineural hearing loss (bilateral deafness; BD), focusing on cortical thickness (CT) and cortical volume (CV), and examined whether alterations in auditory-related cortical regions were associated with the duration of deafness (DoD) or hearing aid use (DoHA). High-resolution three-dimensional T1-weighted MRI data from 47 BD patients (≥10 years of hearing loss) and 73 normal hearing (NH) controls were retrospectively analyzed using surface-based morphometry (SBM) in FreeSurfer. Vertex-wise group comparisons of CT and CV were performed using a general linear model controlling for age. Partial correlation analyses were then conducted between CT/CV of eight auditory-related regions of interest and DoD/DoHA. Compared with the NH group, the BD group showed reduced CT in the bilateral superior temporal gyri and lateral occipital cortices, along with significant CV reductions in the bilateral superior temporal gyri, superior parietal cortices, and lateral occipital cortices. Notably, longer DoHA was positively correlated only with CT in the right superior temporal gyrus (r = 0.409, p = 0.005, FDR-adjusted p = 0.040). These findings demonstrate that long-term BD is associated with widespread cortical atrophy, affecting regions involved in auditory processing and the integration of somatosensory and visual information. Sustained hearing aid use may help preserve cortical structure, suggesting that timely auditory rehabilitation could slow neurodegeneration and potentially mitigate cognitive risks associated with hearing loss.
Unveiling of phytochemicals, antioxidants, cytotoxic effects and anthelmintic potency of green tea (Camellia sinensis) beverage against albendazole resistant Hamonchus contortus
Abstract Haemonchus contortus remains the main multidrug resistant strongyle threatened livestock productivity. The phytochemical components of green tea beverage (GT) might provide an alternative and sustainable anthelmintic effect. Therefore, this study aimed to evaluate the anthelmintic effect of GT beverage against albendazole resistant H. contortus from naturally infected sheep. Albendazole resistance was detected through egg hatch inhibition assay. Assessment of GT phytochemicals, antioxidant ability, anthelmintic effect and cytotoxicity MTT (dimethylthiazol-diphenyltetrazolium bromide) colorimetric assay were achieved. The GT was of high Total Phenolic Content; 555.32 mg gallic acid equivalents /g. Remarkable GT antioxidant qualities were noted where, 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity (85.14%), DPPH antioxidant activity as 907.57 mg vitamin C/g equivalents, and Ferric Reducing Antioxidant Power (8991.04 µg Trolox/g). High Performance Liquid Chromatography showed rich profile of phenolics mainly catechine (70,190.8 µg/g). A potent anthelmintic activity of the GT was noted at 50 mg/mL; complete inhibition of egg hatchability (LC 50 ; 0.144 mg/mL), significant larval motility inhibition (LC 50 ; 0.127 mg/mL) and severe structural deformity on H. contortus eggs and larvae. Additionally, 100% worm motility inhibition and mortality index 1 were recorded at 400 mg/mL in 2 h incubation (LC 50 ; 13.387 mg/mL). The light and electron scanning microscopy of the treated adult proved distortion in the muscular layer of the cuticle wall with severe degenerative changes. The GT maintained viability of the BJ1 cell lines without cytotoxic effect at (0.78 to 200 µg/mL) concentrations. Overall, green tea beverage could be offered as safe and potent alternative anthelmintic to combat the albendazole-resistance isolates of H. contortus .
Evaluation of Ascophyllum nodosum extract supplementation on feed degradability, ruminal fermentation and methane production using the rumen simulation technique (RUSITEC)
This study investigated the effects of liquid Ascophyllum nodosum (ASC) extracts on feed degradability, ruminal fermentation, total gas and methane (CH 4 ) production using the rumen simulation technique (RUSITEC). Two experiments were conducted: Experiment 1 assessed a grass-based diet with an ASC extract included at 0.1%, 0.2% and 0.3% of dry matter (DM), while Experiment 2 evaluated a grass silage-based diet with an ASC extract included at 0.3%, 0.4% and 0.5% of DM. Both diets included a control treatment (CTR; no seaweed extract). In Experiment 1, the 0.3% treatment reduced CH 4 production relative to CTR, primarily by decreasing nutrient degradation and total volatile fatty acid production, resulting in reductions of 20% for total gas, 34% for CH 4 (mmol/d) and 30% for CH 4 (mmol/g of digestible organic matter; DOM). Metabolic hydrogen produced and incorporated were also reduced. In Experiment 2, the 0.5% treatment decreased DM and organic matter degradation compared to CTR, with no effects on crude protein or neutral detergent fibre degradation, or rumen fermentation parameters. Despite this, all ASC extract treatments reduced total gas by 20–24%, CH 4 (mmol/d) by 23–26% and CH 4 (mmol/g DOM) by 21–29% relative to CTR. Metabolic hydrogen recovery decreased by 22% across all ASC extract treatments, suggesting other mechanisms were at play redirecting hydrogen away from methanogenesis. These findings highlight the potential of ASC extract as a natural CH 4 -mitigating feed additive under controlled fermentation conditions, supporting the development of more sustainable ruminant production systems.
Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator
Establishment of a rabbit uterine cancer model using VX2 tumor fragments
Background Preclinical uterine cancer models using the rabbit VX2 system have been described in previous studies; however, they often involve complex procedures such as cell culture, uterine suturing, or imaging validation. This study aimed to establish a technically simple and reproducible rabbit model of uterine cancer using VX2 tumor fragments. Methods We established a rabbit uterine cancer model by injecting minced VX2 tumor tissue into the endometrium of New Zealand White rabbits. We first generated VX2 tumors in donor rabbits via subcutaneous thigh injection and harvested them after three weeks. Recipient rabbits were assigned to two cohorts with scheduled assessments at 14 days or 4 weeks post-implantation. Tumor formation was assessed at each time point by intraoperative inspection and histopathological analysis. Results In the initial 14-day cohort (n = 8), all rabbits developed well-defined uterine tumors without perioperative complications. Histological analysis confirmed viable tumor growth. No lymph node metastasis or distant spread was observed at the 14-day endpoint. In a separate, extended 4-week cohort (n = 8), all rabbits also developed uterine tumors. This cohort demonstrated tumor progression, with 75% exhibiting retroperitoneal lymph node metastasis, and 37.5% showing peritoneal metastasis. Conclusion This study demonstrates the feasibility and reproducibility of a simplified VX2 uterine cancer model using tumor fragments. Furthermore, the model replicates metastatic progression, including retroperitoneal lymph node and peritoneal metastasis, by 4 weeks. The model may serve as a reliable platform for future preclinical studies involving uterine tumor biology and metastatic progression.
Multi-omics analysis of associations between host demographics and saliva metabolome, sugar profiles, and microbiome profiles
Abstract Omics profiling of saliva is an emerging research area with potential to uncover molecular signatures associated with oral and systemic health. We conducted a comprehensive multi-omics analysis of saliva to investigate associations between host demographics (age, sex, body mass index (BMI)) and molecular profiles. Saliva from 423 participants (16–79-years-old) were analyzed using LC-MS metabolomics (9,380 metabolite features for 416 participants), GC×GC-MS sugar profiling (69 sugars for 200 participants), and full-length 16S rDNA sequencing (500 microbial species for 420 participants). We used random forest modeling, multivariate OPLS analysis, and partial correlation networks for data integration. Age emerged as the strongest demographic factor, explaining up to 30% of variance in metabolite features, 17% in sugars, and 25% in microbial species, while sex showed moderate and BMI minimal associations. Age-associated metabolites included caffeine and trigonelline (higher in older participants) and urocanic acid (higher in younger participants). Younger participants had greater abundance of saccharolytic, facultative anaerobic bacteria while older participants had more anaerobic species. Species in the Streptococcus , Prevotella , and Veillonella genera correlated strongly with salivary sugars. These findings demonstrate that saliva provides a rich source of molecular information related to the individual, and that demographic factors must be considered in saliva-based biomarker-discovery studies.
Modeling the seasonal epidemic of human brucellosis in China: A comparative time series analysis
Background While time-series models have been applied to forecast brucellosis incidence in China, systematic comparisons of multiple models remain relatively limited. This study aimed to elucidate the epidemic characteristics of human brucellosis and to provide a comparative assessment of several time-series prediction models, in order to identify a suitable predictive framework for future incidence forecasting. Methods Monthly and annual incidence rates (per 100,000 population) of brucellosis in China from January 2011 to December 2020 were used as raw data. Seven time-series models were developed and compared using R software (version 4.3.1): Seasonal Autoregressive Integrated Moving Average (SARIMA), Holt-Winters additive model, Holt-Winters multiplicative model, Neural Network Autoregressive (NNAR) model, Exponential Smoothing State Space (ETS) model, TBATS model, and Prophet model. A rolling-window cross-validation was applied to assess model stability. Model performance was evaluated using root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean absolute scaled error (MASE). Results Among the seven models evaluated, the Holt-Winters multiplicative model demonstrated the most stable and superior predictive performance on the test set (MAE = 0.034, RMSE = 0.040, MAPE = 14.881%, MASE = 0.891), which serves as strong evidence for its best generalization capability among the compared models. Conclusions Given its stable and superior performance in the test set, the Holt-Winters multiplicative model is recommended for short-term brucellosis forecasting in China. It captures the characteristic spring-summer peak, and its integration into surveillance systems could enhance early warning and targeted interventions.
Adaptive fuzzy sliding mode control applied to inverted pendulum
Understanding policy alignment in addressing hydrological hazards in the Niger Delta region, Nigeria
Combating climate change, flood risk, managing land use, and developmental change need cohesive policy action. Analysing policies is essential to assess whether there is a coherent approach where various sectors support each other, or at least do not conflict. This study analyses policy documents addressing hydrological hazards in the Niger Delta region, Nigeria using Qualitative Document Analysis, content analysis, keyword analysis and frequency counts. These insights were used to examine: 1) the types of hydrological hazards and their drivers recognised in six national policy documents across environment, climate change, agriculture, water, forest, and petroleum policy sectors, 2) the measures outlined to reduce the risks from these hazards, and 3), how well aligned the measures are across sectors for management of the Niger Delta region. Results reveal that the policies across the Environment and Climate Change directly address hydrological hazards and their climatic drivers. In contrast, Agriculture, Water, and Forest policies demonstrate sector-specific approaches, while the Petroleum policy stands out for its very limited consideration of hydrological hazards and their drivers. Hydrological hazards were considered as high rainfall, river floods, sea level rise, storm surges, and warming trends as key hydrological hazards. Climate variability and human activity arising from urbanisation, deforestation, industrialisation, agriculture, and population are identified as drivers that can exacerbate the hazards and their impacts. Measures across the policies consider flood defence structures, preparing comprehensive hazard maps and vulnerability analysis to strengthen smart water management to reduce risk and build adaptive capacity across the region. Overall alignment of the six national policies is found to be low, indicating limited attention to the interactions between sectors and stakeholders. This pattern indicates horizontal misalignment. For Nigeria to better manage climate change impacts, all hydrological hazards and their drivers must be recognised. There is a need for the policy framework to be more joined-up so that a multi-sector approach can reduce risks from hydrological hazards.
COVID-19 pandemic and vaccine hesitancy in a Brazilian state capital
Abstract The COVID-19 pandemic was disclosed to have both positive and negative impacts on vaccine acceptance. To further comprehend its influences on the population’s perceptions about vaccination, we conducted a cross-sectional study that aimed to evaluate the trends and determinants of vaccine hesitancy before and after the onset of the COVID-19 pandemic, in Campo Grande, a state capital in Brazil. Data was collected through household interviews conducted between 2022 and 2023, using questions addressing both the pre- and post-pandemic periods. Information on socioeconomic and demographic characteristics, COVID-19 vaccine hesitancy, and the number of COVID-19 vaccine doses received was collected. Vaccine hesitancy over time was assessed using the World Health Organization 10-item Vaccine Hesitancy Scale (VHS), applied retrospectively to the periods before and after the beginning of the pandemic. Positive items were reverse-scored so that higher score indicated greater vaccine hesitancy. Some items of the VHS were aligned in two factors (lack of trust and risk perception) and two bivariable and two linear regression models were performed to describe the association between the variables and those factors. We observed an increase in both factors and in the overall VHS score after the onset of the pandemic. Lower trust was associated with older age, whereas lower COVID-19 vaccine hesitancy was associated with a higher number of COVID-19 vaccine doses received. Increased risk perception was associated with higher COVID-19 vaccine hesitancy. These findings suggest that the COVID-19 pandemic contributed to an overall rise in vaccine hesitancy in this population.
Temporal invariance of centrality correlations and hierarchical topology in evolving cross-shareholding networks in Japan (2001–2023)
In this study, we investigate the long-term evolution of the hierarchical structure and the stability of centrality correlations within Japan’s cross-shareholding networks. Using a 23-year dataset (2001–2023) of all listed Japanese companies, we conducted network analysis of semi-annually constructed networks of industrial sectors based on strongly connected components. To examine hierarchical structures, centrality distributions, and their intercorrelations, we applied bow-tie decomposition, PageRank, and the Hypertext-Induced Topic Selection (HITS) algorithm. The largest strongly connected component (the core group) decreased over time, whereas the number of companies that held shares in core members without being held in return (IN) or that remained entirely disconnected increased. Correlations among network measures exhibited temporal stability. The in-strength was positively correlated with both PageRank ( p a ), computed from the original directed network, and an authority score, whereas the out-strength was positively correlated with the Reversed PageRank ( p h ) computed from the reversed network and the hub score. A negative correlation was observed between p a and p h . The correlation between in-strength and out-strength shifted from negative to positive around 2010, suggesting stronger cross-shareholding ties among companies. Most industries exhibited network-measure correlations similar to those observed in the overall network. In contrast, transportation equipment showed no significant correlation between in-strength and the corresponding p a , which suggests that firms were less influenced despite holding significant inbound voting rights. The relative ranking of network measures across industries remained stable over time. Banks consistently ranked low for in-strength and high for out-strength. Although their p h ranks remained high, their hub score ranks decreased. These findings, such as the declining influence of banks and the rising centrality of the information & communication and real estate sectors, suggest that traditional firm-level or short-term monitoring may overlook systemic ownership structures. Periodic network-based monitoring can help to identify resilient and structurally influential firms or clusters.
Oral mucosal scrapes capture cancer associated microRNA expression consistent with histopathology
A dual-path framework for enhancing student engagement and learning outcomes in sports education: Integrating technology acceptance, self-regulation, and self-efficacy
The rapid adoption of mobile learning technologies in education has presented new opportunities and challenges for the innovative transformation of physical education. This study expands the Technology Acceptance Model (TAM) to systematically analyze how mobile applications influence learning behaviors in higher education physical education. Specifically, it explores the role of mobile technology in hybrid physical education environments by integrating the theoretical dimensions of self-regulated learning, learning self-efficacy, and technology acceptance. Findings reveal that students’ perceptions of usefulness and attitudes toward usage significantly and positively impact their behavioral intentions and self-regulated learning abilities, while also indirectly enhancing learning self-efficacy. This theoretical extension not only provides valuable insights into the mechanisms driving technology-based educational innovation but also introduces a new analytical framework for hybrid physical education. The findings have important practical implications for technology integration and learning behavior optimization in higher education.
A hybrid RL–GA–LSTM–AE framework for energy-aware and SLA-driven task scheduling in cloud computing environments
Assessment of long COVID symptom burden in patients testing positive for SARS-CoV-2 at a nationwide retail pharmacy
Background Numerous grouping and scoring methodologies have been proposed to assess long COVID symptomatology. One approach is to use symptom count as a simple, quantifiable measure of long COVID symptom burden. Methods This was a secondary analysis of a nationwide patient-reported outcomes (PRO) study that recruited symptomatic adults testing positive for SARS-CoV-2 at a Retail Pharmacy in the spring of 2023. EQ-5D-5L TM , work productivity and impairment (WPAI), the Patient-Reported Outcomes Measurement Information System (PROMIS ® ) fatigue, and a long COVID symptom questionnaire were administered at Week 4, Month 3, and Month 6 after testing. Pre-infection EQ-5D-5L, WPAI, PROMIS fatigue were collected via recall. Cronbach’s α assessed internal consistency of symptoms. Scree plots determined number of significant factors (symptoms) to retain for analysis. Spearman correlation coefficients were calculated between number of symptoms and EQ-5D-5L, WPAI, PROMIS fatigue scores and their changes from pre-COVID baseline. Categorization of long COVID burden using number of symptoms was proposed based on scores via equipercentile linking. Results Of 505 patients, mean age was 46.3 years, 70.7% were female. Cronbach’s α was 0.865, denoting good internal consistency of the symptom survey instrument. The scree plot supported use of one factor for the composite 30-symptom list. Number of symptoms correlated strongly with EuroQol Utility Index (r = −0.53), presenteeism (r = 0.51), activity impairment (r = 0.51) and fatigue (r = 0.56). Statistically significant differences in mean number of symptoms were found between patients with versus those without problems in any of the 5 domains of the EQ-5-dimensional descriptive system. Based on linked PRO scores, subjects could be classified into low (≤2), medium (3–9), and high (≥10) symptom burden. Conclusions Number of long COVID symptoms correlated with validated PRO measures and identified three symptom-based categories of long COVID burden. Number of symptoms is a valid and internally consistent measure to assess long COVID burden in outpatient settings.