Search Results (34,660)

Statins are the drugs most commonly used for lowering plasma low-density lipoprotein (LDL) cholesterol levels and reducing cardiovascular disease risk. Although generally well-tolerated, statins can induce myopathy, a major cause of non-adherence to treatment. Impaired mitochondrial function has been implicated in the development of statin-induced myopathy, but the underlying mechanism remains unclear. We have shown that simvastatin downregulates the transcription of TOMM40 and TOMM22, genes that encode major subunits of the translocase of the outer mitochondrial membrane (TOM) complex. Mitochondrial effects of knockdown of TOMM40 and TOMM22 in mouse C2C12 and primary human skeletal cell myotubes include impaired oxidative function, increased superoxide production, reduced cholesterol and CoQ levels, and disrupted markers of mitochondrial dynamics and morphology as well as increased mitophagy, with similar effects resulting from simvastatin exposure. Overexpression of TOMM40 and TOMM22 in simvastatin-treated mouse and human skeletal muscle cells rescued effects on markers of mitochondrial dynamics and morphology, but not oxidative function or cholesterol and CoQ levels. These results show that TOMM40 and TOMM22 have key roles in maintaining both mitochondrial dynamics and function and indicate that their downregulation by statin treatment results in mitochondrial effects that may contribute to statin-induced myopathy. Full article

We investigate an extended Gauss iterative map by incorporating the q-exponential function, a key component of the Tsallis framework. This extension enables us to investigate the non-linear dynamics of the Gauss iterative map across a broader range of scenarios, encompassing periodic, chaotic, and bistable behaviors. Regular and chaotic phenomena have been observed in coupled systems. In this context, we propose a network of coupled extended Gauss iterative maps. In our network, we found the emergence of chimera states, characterized by the coexistence of coherent and incoherent behaviors. These states are identified within specific parameter regimes using Gopal’s metric. In this work, we show the interplay between chaos and emergent collective dynamics in coupled extended Gauss iterative maps. Full article

Caffeoylquinic acids (CQAs), a class of phenolic acid metabolites widely distributed in plants, encompass 15 positional isomers from mono- to tetra-esters, with 5-O-caffeoylquinic acid (5-CQA) as the predominant form. The biosynthesis of 5-CQA from phenylalanine proceeds through five primary pathways, which are finely regulated by environmental, hormonal, and transcription factors from families such as MYB, WRKY, and bHLH. These regulators control 5-CQA synthesis by binding specifically to the promoter regions of key structural genes, including PAL, 4CL and HCT/HQT. Subsequently, 5-CQA serves as a central precursor for the biosynthesis of other CQAs. In terms of bioactivity, CQAs possess remarkable pharmacological activities, encompassing antioxidant, antimicrobial, anti-diabetic, anti-inflammatory and anti-tumor properties. For instance, anti-inflammatory effects are demonstrated by the ability of 5-CQA to reduce key pro-inflammatory cytokines (e.g., TNF-α and IL-1β) and downregulate the TLR4/NF-κB pathway. The synergistic action of 5-CQA with ultraviolet-A reduced succinate-coenzyme Q reductase activity by approximately 72%, highlighting its potential to disrupt bacterial metabolism and combat antibiotic resistance. Furthermore, 3,4,5-triCQA exhibits potent anti-influenza virus activity, potentially through a mechanism distinct from existing neuraminidase inhibitors. Beyond medicine, CQAs show promise in light industry. They serve as antibiotic alternatives in livestock feed to enhance gut health, extend food shelf life through their antioxidant activity, and function as active ingredients in UV-protective skincare formulations. CQAs also enhance plant stress tolerance to cold, arsenic, and pests by mechanisms such as scavenging reactive oxygen species and inhibiting pest mobility. While this review consolidates progress in the biosynthesis and bioactivity of CQAs specifically with caffeoyl substituents, future efforts should leverage modern biotechnological tools and interdisciplinary approaches to bridge critical knowledge gaps in their biosynthesis, transport, and clinical translation. Full article

Vascular Plant One-Zinc finger (VOZ) transcription factors are pivotal regulators of plant growth and stress adaptation, yet their functional roles in Gossypium hirsutum, a key fiber crop, remain poorly characterized. In this study, we systematically identified six VOZ genes in G. hirsutum and conducted a comprehensive analysis of their phylogenetic relationships, genomic distribution, promoter architecture, and expression profiles. Phylogenetic classification placed the GhVOZ proteins into three distinct clades, and chromosomal localization revealed that family expansion was likely driven by segmental duplication events. Promoter analysis uncovered an abundance of stress-related cis-regulatory elements, suggesting a potential role in abiotic stress signaling. Consistent with this, expression profiling demonstrated that GhVOZ1/3, GhVOZ2/4/5, and GhVOZ6 were specifically induced under drought, salt, and cold stress, respectively, with qRT-PCR further confirming their tissue-specific dynamic regulation under salt treatment. Furthermore, the GhVOZ family exhibited stage-specific expression patterns during somatic embryogenesis. GhVOZ1, GhVOZ3, and GhVOZ4 were upregulated at the early induction phase, implicating them in the initiation of cell reprogramming. In contrast, GhVOZ2 and GhVOZ4 showed sustained expression in embryogenic callus at later stages, suggesting a role in maintaining embryogenic competence, whereas GhVOZ5—preferentially expressed in non-embryogenic callus—may act as a repressor of embryogenesis. Synteny analysis further highlighted evolutionary conservation and subgenomic divergence of VOZ genes in G. hirsutum. Collectively, these findings establish GhVOZs as key regulators integrating abiotic stress response and somatic embryogenesis, providing a genetic framework for future functional studies and crop improvement. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a sexually dimorphic condition, with higher prevalence in men than in women. Sex differences in hepatic lipid metabolism and the modulatory role of sex hormones have been described but are still insufficiently understood. The aim of this study was to introduce the variables sex and sex hormones into a human in vitro model of hepatic steatosis. Methods: Primary human hepatocytes (PHHs) were isolated from male and female donors, treated with free fatty acids (FFA) to induce steatosis, and further exposed to physiological concentrations of estrogen, progesterone, or testosterone. Intracellular triacylglyceride (TAG) content, lipid droplet (LD) formation, FFA uptake, and very-low-density lipoprotein (VLDL) excretion were assessed. In parallel, the expression of lipid metabolism-related genes was quantified by qPCR. Results: FFA treatment induced comparable uptake and intracellular TAG storage in both sexes. However, female PHHs secreted approximately twice as many VLDL particles as male cells. Steatosis significantly increased expression of LDLR, CPT2, and PLA1A only in male PHHs. Sex hormones exerted distinct, sex-specific effects: estrogen reduced TAG accumulation in female PHHs; whereas testosterone reduced TAG in male but increased it in female PHHs after prolonged treatment. LD characterization confirmed sex- and hormone-dependent differences in lipid storage patterns. In male PHHs, progesterone promoted lipid storage and increased apoB-100 secretion, accompanied by reduced LDLR and APOA5 expression, and testosterone increased the FFA-mediated CPT2 even further. Conclusions: Sex and sex hormones distinctly shape hepatocellular lipid handling under steatotic conditions. While female PHHs demonstrated greater lipid excretion capacity, male PHHs exhibited stronger transcriptional responses. Sex-specific responses to estrogen and testosterone resembled clinical observations on sex hormone effects. These findings highlight the need to account for sex-specific differences in MASLD pathophysiology and therapeutic strategies. Full article

Statistical inference in spatiotemporal trend analysis often involves testing separate hypotheses for each pixel in datasets containing thousands of observations. A pixel is considered significant if its p-value falls below a rejection threshold (α). However, this uncorrected approach ignores the large number of simultaneous tests and greatly increases the risk of false positives. This issue, known as multiple testing or multiplicity, can be addressed by controlling the false discovery rate (FDR), defined as the expected proportion of false positives (i.e., false discoveries) among all rejected hypotheses, at a pre-specified control level q. This study implements the linear adaptive two-stage Benjamini–Krieger–Yekutieli (BKY) procedure for FDR control in spatiotemporal trend testing and compares it with two alternatives: the uncorrected significance approach and the original non-adaptive Benjamini–Hochberg (BH) procedure. The BKY method empirically estimates the number of true null hypotheses (m₀) and adaptively relaxes the rejection threshold when many true alternatives are present, thereby increasing statistical power without compromising FDR control. Results indicate that the BKY procedure is a recommended approach for large-scale trend testing using spatiotemporal environmental data, particularly in gridded-data-intensive fields such as environmental remote sensing, climatology, and hydrology. To foster reproducibility, R code is provided as supplementary material to apply the BKY procedure and compare it with the uncorrected raw p-values and the BH approach on any gridded dataset. Full article

This study used Q methodology to explore and categorise caregivers’ subjective perceptions of artificial intelligence (AI)-powered ‘virtual human’ (AVH) devices in caring for older adults. We derived 123 initial statements from literature and focus groups and narrowed them to 34 statements as the final Q sample. Seventeen caregivers, nurses, and social workers completed the Q-sorting procedure. Using principal component analysis and Varimax rotation in Ken-Q, we identified three perception types: Active Acceptors, who emphasise the devices’ practical utility in patient communication; Improvement Seekers, who conditionally accept the technology while seeking greater accuracy and effectiveness; and Emotional Support Seekers, who view the device as a tool for emotional relief and psychological support. These findings suggest that technology acceptance in caregiving extends beyond functional utility. It also involves trust, affective experience, and interpersonal interaction. This study integrates multiple frameworks, including the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), Science and Technology Studies (STS), and Human–Machine Communication (HMC) theory, to provide a multifaceted understanding of caregivers’ acceptance of AI technology. The results offer valuable implications for designing user-centred AI care devices and enhanced emotional and communicative functions. Full article

Intelligent connected vehicles (ICVs) face challenges in handling intensive onboard computational tasks due to limited computing capacity. Vehicular edge computing networks (VECNs) offer a promising solution by enabling ICVs to offload tasks to mobile edge computing (MEC), alleviating computational load. As transportation systems are dynamic, vehicular tasks and MEC capacities vary over time, making efficient task offloading and resource allocation crucial. We explored a vehicle–road collaborative edge computing network and formulated the task offloading scheduling and resource allocation problem to minimize the sum of time and energy costs. To address the mixed nature of discrete and continuous decision variables and reduce computational complexity, we propose a hybrid hierarchical deep reinforcement learning (HHDRL) algorithm, structured in two layers. The upper layer of HHDRL enhances the double deep Q-network (DDQN) with a self-attention mechanism to improve feature correlation learning and generates discrete actions (communication decisions), while the lower layer employs deep deterministic policy gradient (DDPG) to produce continuous actions (power control, task offloading, and resource allocation decision). This hybrid design enables efficient decomposition of complex action spaces and improves adaptability in dynamic environments. Results from numerical simulations reveal that HHDRL achieves a significant reduction in total computational cost relative to current benchmark algorithms. Furthermore, the robustness of HHDRL to varying environmental conditions was confirmed by uniformly designing random numbers within a specified range for certain simulation parameters. Full article

In this study, a PRISMA-guided scoping review of research papers on teachers’ epistemic meta didactic–mathematical knowledge with regard to functions is carried out. The objective is to identify the factors that characterize the epistemic meta didactic–mathematical knowledge of teachers who lead epistemically suitable instructional processes for functions. The Web of Science and Scopus databases were used to select 15 papers published between 2019 and 2024 that examine mathematics teachers’ epistemic meta didactic–mathematical knowledge when teaching functions. Two qualitative analyses of the chosen texts were performed. With the support of the R interface for multidimensional analysis of texts and questionnaires, five categories were obtained from the first analysis. Those categories guided the second analysis, which consists of a manual study of the documents. The result is the following characterization of the meta didactic–mathematical knowledge a teacher should have when teaching functions: (1) complexity of functions in the history of mathematics and in the curriculum, (2) personal practice of multiple processes using functions in different contexts, and (3) analysis of the tasks designed in instructional processes and reflection on teaching practice. The main conclusion of this research is that the presence of these contents in teacher preparation programs can contribute to improving the teaching of functions. Full article

Background/Objective: Dendritic cells (DCs) act as sentinels bridging innate and adaptive immunity, and their functions are strongly influenced by dietary and environmental factors. Phytochemicals such as α-Mangostin (A phytochemical, a xanthone derivative from Garcinia mangostina, known for its anti-inflammatory and antioxidant properties) are widely recognized for their antioxidant and anti-inflammatory effects, but their potential to modulate antiviral pattern recognition pathways remains unclear. This study investigated whether phytochemicals activate retinoic acid–inducible gene I (RIG-I: DDX58, a cytosolic receptor recognizing viral RNA and inducing antiviral responses)–dependent signaling in human monocyte-derived dendritic cells (MoDCs) and affect downstream T cell responses. Methods: MoDCs were generated from peripheral blood and stimulated with selected phytochemicals. RIG-I pathway–related transcripts were quantified by qPCR, and protein expression was assessed by Western blotting, intracellular flow cytometry, and immunofluorescence staining. Functional outcomes were evaluated by co-culturing MoDCs with T cells, followed by phenotypic analysis via flow cytometry and measurement of IFN-γ production by ELISA. Results: α-Mangostin stimulation increased RIG-I (DDX58) mRNA levels in MoDCs and induced time-dependent changes in intracellular protein expression. In co-culture, α-Mangostin–treated MoDCs tended to increase the proportion of OX40⁺ 4-1BB⁺ CD4⁺ T cells, accompanied by a significant elevation of IFN-γ levels in supernatants. Experiments with CpG-ODN (synthetic oligodeoxynucleotides mimicking bacterial DNA that activate TLR9) suggested context-dependent crosstalk between the TLR9 and RIG-I signaling axes. Conclusions: Phytochemicals, exemplified by α-Mangostin, prime antiviral responses in human DCs through upregulation of RIG-I and promote Th1-dependent immune responses. These findings suggest that phytochemicals may represent promising nutritional strategies to enhance antiviral immunity while mitigating excessive inflammation under infectious conditions. Full article

Artificial Intelligence (AI) has brought a revolution in many areas, including the education sector. It has the potential to improve learning practices, innovate teaching, and accelerate the path towards personalized learning. This work introduces Reinforcement Learning (RL) methods to develop a personalized examination scheduling system at a university level. We use two widely established RL algorithms, Q-Learning and Proximal Policy Optimization (PPO), for the task of personalized exam scheduling. We consider several key points, including learning efficiency, the quality of the personalized educational path, adaptability to changes in student performance, scalability with increasing numbers of students and courses, and implementation complexity. Experimental results, based on case studies conducted within a single degree program at a university, demonstrate that, while Q-Learning offers simplicity and greater interpretability, PPO offers superior performance in handling the complex and stochastic nature of students’ learning trajectories. Experimental results, conducted on a dataset of 391 students and 5700 exam records from a single degree program, demonstrate that PPO achieved a 42.0% success rate in improving student scheduling compared to Q-Learning’s 26.3%, with particularly strong performance on problematic students (41.3% vs 18.0% improvement rate). The average delay reduction was 5.5 months per student with PPO versus 3.0 months with Q-Learning, highlighting the critical role of algorithmic design in shaping educational outcomes. This work contributes to the growing field of AI-based instructional support systems and offers practical guidance for the implementation of intelligent tutoring systems. Full article

The Tibetan Plateau is a globally critical climate-sensitive and ecologically fragile region. Vegetation phenology serves as a key indicator of ecosystem responses to climate change and simultaneously influences regional carbon cycling, water regulation, and ecological security. However, systematic quantitative assessments of phenological responses under the combined effects of multiple climate factors remain limited. This study integrates multi-source remote sensing data (MODIS MCD12Q2) and ERA5-Land meteorological data from 2001 to 2023, leveraging the Google Earth Engine (GEE) cloud platform to extract key phenological metrics, including the start (SOS) and end (EOS) of the growing season, and growing season length (GSL). Sen’s slope estimation, Mann–Kendall trend tests, and partial correlation analyses were applied to quantify the independent effects and spatial heterogeneity of temperature, precipitation, solar radiation, and evapotranspiration (ET) on GSL. Results indicate that: (1) GSL on the Tibetan Plateau has significantly increased, averaging 0.24 days per year (Sen’s slope +0.183 days/yr, Z = 3.21, p < 0.001; linear regression +0.253 days/yr, decadal trend 2.53 days, p = 0.0007), primarily driven by earlier spring onset (SOS: Sen’s slope −0.183 days/yr, Z = −3.85, p < 0.001), while autumn dormancy (EOS) showed limited delay (Sen’s slope +0.051 days/yr, Z = 0.78, p = 0.435). (2) GSL changes exhibit pronounced spatial heterogeneity and ecosystem-specific responses: southeastern warm–wet regions display the strongest responses, with temperature as the dominant driver (mean partial correlation coefficient 0.62); in high–cold arid regions, warming substantially extends GSL (Z = 3.8, p < 0.001), whereas in warm–wet regions, growth may be constrained by water stress (Z = −2.3, p < 0.05). Grasslands (Z = 3.6, p < 0.001) and urban areas (Z = 3.2, p < 0.01) show the largest GSL extension, while evergreen forests and wetlands remain relatively stable, reflecting both the “climate sentinel” role of sensitive ecosystems and the carbon sequestration value of stable ecosystems. (3) Multi-factor interactions are complex and nonlinear; temperature, precipitation, radiation, and ET interact significantly, and extreme climate events may induce lagged effects, with clear thresholds and spatial dependence. (4) The use of GEE enables large-scale, multi-year, pixel-level GSL analysis, providing high-precision evidence for phenological quantification and critical parameters for carbon cycle modeling, ecosystem service assessment, and adaptive management. Overall, this study systematically reveals the lengthening and asymmetric patterns of GSL on the Tibetan Plateau, elucidates diverse land cover and climate responses, advances understanding of high-altitude ecosystem adaptability and climate resilience, and provides scientific guidance for regional ecological protection, sustainable management, and future phenology prediction. Full article

Grid-connected inverters play an indispensable and crucial role between new energy power generation devices and the power grid. As an important method for stability analysis of grid-connected inverters, impedance criteria have been widely applied. However, traditional impedance criteria have the problem of inaccurately representing system stability margins. Moreover, under weak grid conditions where grid impedance cannot be ignored, voltage disturbances at the point of common coupling will cause phase angle deviations in the output of the phase-locked loop, thereby affecting the stability of the control system. To address these issues, this paper establishes a stability analysis model based on the reshaping of impedance criteria and proposes a q-axis improved control compensation method, which expands the adaptability range of grid impedance for inverters and enhances the stability of grid-connected inverters. Finally, the correctness of the proposed algorithm is verified through experiments. Full article

This study characterized leaf extracts of Cymbopogon flexuosus (Ryukyu Lemongrass Corporation, Okinawa, Japan) and evaluated the bioaccessibility and bioactivities of phenolic compounds following a simulated in vitro gastrointestinal model of digestion (in vitro GID) of plant material. Undigested (controls, AqC, EtC) and digested aqueous (AqD) and ethanolic (EtD) extracts were analyzed. Control extracts contained higher total phenolics and flavonoids than digested ones, with EtC showing the highest values. UHPLC-QToF-MS (ultra-high-performance liquid chromatography system coupled to a quadrupole time-of-flight mass spectrometer) identified 32 compounds, including phenolic acids, flavone aglycones, C-glycosides, and derivatives. Hydroxybenzoic acids, coumaric acid, caffeic esters, flavones, tricin derivatives, vitexin, and isoorientin exhibited reduced recovery, while coumaric acid hexoside, ferulic acid hexoside, and isoschaftoside/schaftoside exceeded 100% recovery, suggesting release from the matrix. Some compounds were absent from AqD, and many were found in the pellet, indicating potential colonic metabolism. Antioxidant activity (DPPH, reducing power, β-carotene/linoleic acid) was stronger in controls but always weaker than BHT/ascorbic acid. Extracts mildly inhibited α-amylase but more strongly inhibited α-glucosidase as shown with applied enzyme inhibition assays, especially EtD (76.93% at a concentration of 10 mg/mL), which showed stronger activity than controls but remained below acarbose (87.74% at 1 mg/mL). All extracts promoted HaCaT keratinocyte growth and reduced HCT-116 colon cancer cell viability at 250 µg/mL, with the strongest effects in AqC and AqD. Overall, GID decreased antioxidant activity but enhanced antidiabetic potential, confirming the safety and selective anticancer effects of C. flexuosus extracts. Full article

Reproductive efficiency is a key determinant of sheep productivity, yet Hetian sheep remain limited by relatively low fecundity despite their adaptability to harsh environments. The inhibitor of DNA binding 2 (ID2) gene is known to regulate cell proliferation and differentiation, but its specific role in sheep reproduction is not well understood. This study aimed to characterize the ID2 gene in Hetian sheep and to assess its functional association with ovarian granulosa cells and litter size. The coding sequence of ovine ID2 was cloned and analyzed using bioinformatics tools. Tissue-specific expression patterns were measured by quantitative PCR at different pubertal stages. A total of 157 ewes were genotyped to identify single-nucleotide polymorphisms (SNPs) and their association with litter size. Functional studies were performed by lentiviral overexpression of ID2 in granulosa cells, with effects evaluated using CCK-8 proliferation assays, ELISA for hormone secretion, and RT-qPCR for related gene expression. ID2 was highly expressed in the ovary, particularly during puberty. Four SNPs (g.18202368 A>T, g.18202372 G>A, g.18202431 G>C, g.18202472 G>C) were significantly associated with increased litter size. Overexpression of ID2 promoted granulosa cell proliferation, increased progesterone, decreased estradiol, and altered expression of key genes in the TGF-β/BMP-SMAD signaling pathway. The ID2 gene plays a crucial role in ovarian function and reproductive regulation in Hetian sheep. Its polymorphisms and functional impact on granulosa cells suggest that ID2 is a promising candidate gene for marker-assisted selection to improve reproductive efficiency in sheep. Full article