Search Results (50,325)

N6-methyladenosine (m⁶A) is a reversible RNA modification that dynamically regulates gene expression by modulating RNA stability, splicing, nuclear export, translation, and maturation—thereby orchestrating organismal development. In birds, including geese, the liver is a multi-functional organ central to metabolic regulation. Studies on the dynamic patterns of RNA m⁶A modifications during healthy liver growth and development remain limited. Here, we performed integrative methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA sequencing (RNA-seq) on liver tissues from geese at three biologically defined stages: post-hatch day 0 (0 week, P), fast growth (10 weeks, F), and sexual maturation (30 weeks, S). The level of m⁶A modification in total RNA extracted from liver tissues was higher in P than in F samples. Compared with other groups, the S group recorded the lowest m⁶A modification. In addition, 1641, 668, and 558 m⁶A peaks were differentially modified in the P, F, and S groups, respectively. The m⁶A peaks in the liver of the three groups were mainly enriched in the coding sequence and 3′ untranslated region. Moreover, integrated multi-omics analysis (MeRIP-seq and RNA-seq), combined with protein–protein interaction networks analysis, identified CDK1 as a core cell cycle regulator and IGF2BP3—a well-established m⁶A reader—as a consistently differentially expressed gene across all developmental stages. The m⁶A-regulated cell cycle, p53 signaling pathway, and pyrimidine metabolism pathway were identified in liver tissue as novel potential targets for controlling geese growth and metabolism. Together, these findings shed light on the dynamic regulation of RNA methylation during distinct growth phases in geese and advance our understanding of epigenetic mechanisms underlying poultry liver development. Full article

Objectives: Plant organs often allocate phenolic metabolites unevenly, resulting in organ-specific bioactivities. This study aimed to characterize the organ-specific phenolic profile of Acanthus dioscoridis var. perringii and determine how this chemical segregation is associated with antioxidant capacity and enzyme inhibitory activities. Materials and Methods: Organ-specific extracts (roots, stems, leaves, bracts, and flowers) were evaluated for total phenolic and flavonoid contents, targeted LC-MS analysis of individual phenolics, antioxidant activity by multiple assays, enzyme inhibition [acetylcholinesterase (AChE), butyrylcholinesterase (BChE), α-amylase, and α-glucosidase], and the relationships between phenolic composition and biological activities. Antioxidant performance was also assessed using the Relative Antioxidant Capacity Index (RACI). Results and Discussion: Roots showed the highest total phenolic content, whereas bracts had the highest total flavonoid level. Verbascoside was the dominant compound in all organs, with the highest levels in leaves, roots, and bracts. Roots exhibited the strongest reducing and radical-scavenging activities, while flowers showed the best metal-chelating capacity. Enzyme inhibition was organ-dependent and generally moderate, with stems showing the strongest cholinesterase inhibition, leaves the strongest α-amylase inhibition, and bracts together with roots the strongest α-glucosidase inhibition. Statistical analysis revealed close associations between phenolic richness, antioxidant responses, and cholinesterase inhibition. Conclusions: These findings demonstrate a clear organ-dependent distribution of phenolic compounds in A. dioscoridis var. perringii, reflected in distinct antioxidant and enzyme inhibitory profiles. Overall, the study provides a biochemical and bioactivity-based characterization of the species at the organ level. Full article

In this article, we investigate the existence and approximate controllability of a class of Sobolev-type fractional stochastic differential equations of order $1<\delta <2$ with infinite delay. The analysis is carried out in an abstract Hilbert space framework, incorporating fractional dynamics together with stochastic perturbations. By employing techniques from fractional calculus, semigroup theory, and fixed point theory, particularly the Banach contraction principle along with compactness arguments, we establish the existence of mild solutions for the proposed system. Subsequently, sufficient conditions for approximate controllability are derived by combining operator-theoretic methods with stochastic analysis. The novelty of this work lies in extending controllability results to Sobolev-type fractional stochastic systems of order $1<\delta <2$, where both the higher-order fractional structure and stochastic effects are treated simultaneously within a unified framework. This generalizes and complements several existing results in the literature that mainly address deterministic systems or fractional differential equations of order $0<\delta \le 1$. Finally, an illustrative example is presented to demonstrate the applicability and effectiveness of the theoretical findings. Full article

Aging is closely associated with oxidative stress, which contributes to functional decline and increased vulnerability to neurodegenerative diseases. Natural antioxidants, such as Chlorella Growth Factor (CGF) and γ-polyglutamic acid (γ-PGA), possess antioxidant and anti-aging properties; however, their combined effects remain unknown. This study investigated the potential synergistic effects of CGF and γ-PGA supplementation in senescence-accelerated mouse-prone 8 (SAMP8) mice, a model characterized by early cognitive decline, locomotor deficits, and elevated oxidative DNA damage. Three-month-old male SAMP8 mice (n = 40) were divided into four groups: control, CGF (49.2 mg/kg BW/day), γ-PGA (20.5 mg/kg BW/day), and combined CGF + γ-PGA (69.7 mg/kg BW/day), and were treated for 13 weeks. Behavioral and physiological assessments included locomotor activity, aging index, and cognitive function (passive and active avoidance tests). Biochemical analysis focused on brain 8-hydroxy-2′-deoxyguanosine (8-OHDG) as a biomarker of oxidative DNA damage. Supplementation with CGF and γ-PGA, particularly in combination, significantly improved locomotor activity, aging scores, and cognitive functions. Notably, the combined treatment yielded the greatest reduction in brain 8-OHDG levels. These findings indicate that CGF and γ-PGA, when administered together, exert enhanced protective effects against functional and molecular aging. In conclusion, long-term supplementation with CGF and γ-PGA protects against aging-related decline in SAMP8 mice. This study highlights the potential of CGF and γ-PGA as safe, natural candidates for the development of functional foods or nutraceuticals aimed at promoting healthy aging and reducing oxidative stress-associated disorders. Full article

Skin aging is characterized by fibroblast senescence, extracellular matrix (ECM) degradation, and impaired wound healing, driven by oxidative stress and telomere dysfunction. Here, we investigated the anti-aging effects of a standardized microwave-assisted propolis extract (MAPE) in both H₂O₂-induced and replicative senescence models of human dermal fibroblasts (HDFs). MAPE significantly reduced reactive oxygen species (ROS) accumulation and enhanced antioxidant gene expression (NQO1, GCLM), indicating activation of NRF2-dependent defense pathways. It suppressed senescence markers (CDKN2A, CDKN1A, IL6), decreased SA-β-gal activity, and attenuated inflammaging. Moreover, MAPE inhibited MMP1 expression, restored COL1A1, and improved fibroblast wound closure, thereby maintaining ECM homeostasis. Importantly, MAPE modulated Wnt/β-catenin signaling by upregulating WNT3A and LEF1 while suppressing DKK1, and increased TERT expression, suggesting involvement of telomerase-related regulatory pathways. These effects resembled those of CHIR99021, a canonical Wnt activator, while providing additional antioxidant protection. Together, our findings suggest that MAPE is a propolis-derived bioactive ingredient that counteracts fibroblast senescence through coordinated modulation of NRF2 and Wnt/β-catenin–TERT signaling pathways, supporting its potential as a cosmeceutical ingredient for mitigating skin aging. Full article

This work contributes to advancing sustainable energy and waste management strategies by investigating the thermochemical conversion of food-based biomass through pyrolysis, highlighting the role of artificial intelligence (AI) in enhancing process modelling accuracy and optimization efficiency. The main objective is to explore the potential of underutilized biomass resources like spent coffee grounds (SCGs) and DSs (date seeds) for sustainable hydrogen production. Specifically, it aims to optimize the pyrolysis process while evaluating the performance of these resources both individually and as blends. Proximate, ultimate, fibre, TGA/DTG, kinetic, thermodynamic, and Py-Micro-GC analyses were conducted for pure DS, SCG, and blends (75% DS-25% SCG, 50%DS-50%SCG, 25%DS–75%SCG). Blend 3 offered superior hydrogen yield potential but had the highest activation energy (Ea: 313.24 kJ/mol), while Blend 1 exhibited the best activation energy value (Ea: 161.75 kJ/mol). The kinetic modelling based on isoconversional methods (KAS, FWO, and Friedman) identified KAS as the most accurate. These approaches work together to provide a detailed understanding of the pyrolysis process with a particular emphasis on the integration of artificial intelligence (AI). An LSTM model trained with lignocellulosic data predicted TGA curves with exceptional accuracy (R²: 0.9996–0.9998). Full article

Generative artificial intelligence and foundation models have changed machine learning by allowing systems to produce readable text, realistic images, and other multimodal content with little direct input from a user. Foundation models are large neural networks trained on very large and varied datasets, and they form the core of many current generative AI (GenAI) systems. Their rapid development has led to major advances in areas like natural language processing, computer vision, multimodal learning, and robotics. Examples include GPT, LLaMA, and diffusion-based architectures, such as models often used for image generation. Systems such as Stable Diffusion show this shift by illustrating how AI can interpret information, draw basic inferences, and produce new outputs using more than one type of data. This review surveys common foundation model architectures and examines what they can do in generative tasks. It reviews Transformer, diffusion, and multimodal architectures, focusing on methods that support scaling and transfer across domains. The paper also reviews key approaches to pretraining and fine-tuning, including self-supervised learning, instruction tuning, and parameter-efficient adaptation, which support these systems’ ability to generalize across tasks. In addition to the technical details, this review discusses how GenAI is being used for text generation, image synthesis, robotics, and biomedical research. The study also notes continuing challenges, such as the high computing and energy demands of large models, ethical concerns about data bias and misinformation, and worries about privacy, reliability, and responsible use of AI in real settings. This review brings together ideas about model design, training methods, and social implications to point future research toward GenAI systems that are efficient, easy to interpret, and reliable, while supporting scientific progress and ethical responsibility. Full article

Diabetes mellitus is a rapidly escalating worldwide health issue that involves intricate molecular, metabolic, and systemic dysregulation. In addition to hyperglycemia, disease pathogenesis involves β-cell dysfunction, insulin resistance, mitochondrial dysfunction, endoplasmic reticulum stress (ER stress), redox imbalance, lipotoxicity, chronic inflammation, and inappropriate epigenetic modifications. New evidence also emphasizes the participation of mechanotransduction, ion channel signaling, circadian regulation, and organ cross-talk among the pancreas, liver, adipose tissue, skeletal muscle, heart, brain, and gut in modulating disease heterogeneity and progression. This review highlights updates of molecular mechanisms in diabetes, focusing on the β-cell response to stress, the AMPK–Sirtuin 1 (or PGC-1α) signaling pathway, mitochondrial quality control, mechanosensitive ion channels, immunometabolic crosstalk, and epigenetic regulation. We consider the increasing importance of multi-omics methods for early identification of pathogenic signatures and integration of artificial intelligence to enable precision stratification and therapeutic tailoring. Finally, we highlight novel experimental and translational tools, such as iPSC-derived β-cells or organoids, CRISPR-based gene editing, sophisticated metabolic imaging, and electrophysiology. Taken together, this review shifts the paradigm of diabetes as a system-level network disease and emphasizes the importance of data-driven multi-target strategies for prevention and reduction in long-term complications. Full article

The rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscores the need for antivirals that are resilient to resistance. Current Food and Drug Administration (FDA)-approved therapies primarily target single viral mechanisms, leaving gaps in efficacy. Here, we developed a Deep Learning-based Activity Screening Model (DLASM), which integrates graph convolutional network with machine learning to identify SARS-CoV-2 inhibitors, using experimental 3-chymotrypsin-like (3CL) main protease assay data. The optimized DLASMs virtually screened ~170,000 compounds from diverse in-house collections and yielded novel hits, several of which not only inhibited the 3CL protease but also blocked viral entry by interfering with heparan sulfate-mediated host interactions. These activities were validated through multiple assays, including 3CL enzymatic inhibition, SARS-CoV-2 pseudotyped particle entry, α-synuclein fibril uptake as a proxy for endocytosis, live virus cytopathic effect, heparan sulfate-dependent entry assay, and a 3D human lung mucociliary tissue model. Molecular docking studies elucidated binding modes at the 3CL protease active site, while molecular dynamics simulations provided insights into compound–heparan sulfate interactions. The identified compounds represent early-stage hits with moderate potency that demonstrate dual-mechanism antiviral activity. Together, these findings establish dual-target inhibition as a promising antiviral strategy, offering not only enhanced potency but also reduced risk of resistance. Moreover, our DLASM framework provides a generalizable pipeline for identifying chemically diverse scaffolds and for broader applications beyond SARS-CoV-2. Full article

While Western theology typically locates omniscience in a personal Creator-God, Indian philosophy presents a notable spectrum. This article traces the dialectical arc of omniscience (sarvajñāna) across major Indian philosophical traditions, arguing that what appears as an epistemological question—“who knows everything?”—is ultimately an ontological puzzle about the nature of consciousness itself. Moving from the Vedic oscillation between cosmic personhood (Puruṣa Sūkta) and primordial uncertainty (Nāsadīya Sūkta), through the Upaniṣadic internalization of omniscience as Self-knowledge (ātmajñatā), the article examines how Nyāya-Yoga affirms divine omniscience as a logical and soteriological necessity, how Mīmāṃsā displaces it onto an impersonal authorless text, and how Jainism and Buddhism reappropriate it as a perfected human achievement. The final section demonstrates that both Sāṃkhya’s isolation (kaivalya) and Advaita Vedānta’s non-dual realization ultimately transcend encyclopedic omniscience, revealing that authentic liberation requires not the possession of maximal information but a transformation from representational object-knowledge to non-objectifying awareness. Together, these trajectories constitute Indian philosophy’s most enduring contribution to the global philosophy of religion: the recognition that the “All” cannot be an object of knowledge, because it is the very condition for any knowledge whatever. Full article

Tetrahymena pyriformis is biologically similar to Ichthyophthirius multifiliis, the parasite that causes “white spot disease” in fish. Because it has immune evasion genes and grows quickly, T. pyriformis serves as an ideal model for developing treatments against I. multifiliis and related parasites. This study tested water extracts from 10 traditional Chinese herbs against T. pyriformis and identified 5 with strong antiparasitic effects: Morus alba, Psoralea corylifolia, Sophora flavescens, Polygonum cuspidatum, and Pomegranate Peel. Combination tests showed that certain pairs, especially P. corylifolia with M. alba, worked together synergistically. When infected guppies were treated with this herbal combination at a concentration of 1.39 g/L (1:144 dilution), their 10-day survival rate reached 66.7%. Gill tissue analysis identified 577 genes with changed activity after treatment—228 increased and 349 decreased. These genes were linked to immune responses, metabolism, and cell processes. The key differentially expressed genes include those involved in the IL-17 signaling pathway, amino sugar metabolism, and the cytosolic DNA-sensing pathway. These results show that the herbal combination works by both directly killing parasites and boosting the fish’s immune system. This study provides a scientific basis for using natural herbal treatments as an eco-friendly way to control parasitic diseases in aquaculture. Full article

Addressing principal challenges in common bean (Phaseolus vulgaris L.) breeding requires a holistic approach. A combined strategy was implemented to assess seven genotypes (landraces and commercial varieties) for yield potential, stability and resistance to bean common mosaic virus (BCMV) under Mediterranean low-input conditions. Pure-line selection and prognostic breeding together with SSR and CAPS-SCAR marker-assisted selection (MAS) formed the core methodology. Significant variation was detected across 24 morpho-agronomic descriptors, while SSR revealed 48.57% polymorphic loci and private alleles in specific landraces. High genetic coefficients of variation and high heritability were recorded for yield-related traits. Phenotypical evaluation showed diverse responses to BCMV, with mild symptoms predominating (52.14%). Entries G1 (45%) and G5 (35%) exhibited the highest frequency of the symptomless resistant phenotype. Molecular screening at I and bc-3/eIF4E loci confirmed G5’s robust dominant I gene profile, while G1 included individuals carrying both the dominant I gene and recessive bc-3, offering a valuable source for pyramiding resistance. Additionally, G1 (LI = 2.35; 100%) performed strongly in productivity, whereas G2 (SI = 3.1; 100%) and G7 (SI = 2.8; 89.7%) exhibited exceptional stability. Overall, the mixed-model approach highlighted the complementary characteristics of the tested genotypes and identified G1, G2, G5 and G7 as promising candidates for future breeding programs targeting high yield, low-input adaptability and resistance to BCMV. Full article

Motivated by altitude-induced fluctuations in oxygen partial pressure (pO₂) and their impacts on PCS off-line arc motion and erosion response, this study proposes a comparative experimental approach featuring single-variable control under constant total pressure and coordinated multi-source electrical-signal observation. A reciprocating current-carrying arc-generation rig was established, in which pO₂ was equivalently regulated via a constant-pressure gas substitution and mixing approach. High-speed imaging–based quantitative vision analysis was integrated with synchronized voltage–current measurements to evaluate the net effects of five O₂ volumetric fraction levels (6, 11, 14, 17, and 21 vol%) under a DC supply of 120 V/25 A on arc dynamics, electrochemical processes, and contact pair erosion. Based on repeated-test results, the 14 vol% case exhibited the poorest stability (maximum fluctuation coefficient 20.306%), whereas the 17 vol% case showed the lowest current-carrying efficiency (minimum 56.070%) together with the most severe erosion damage. Moreover, with increasing pO₂, the erosion morphology evolved in a staged manner, transitioning from localized central ablation accompanied by melt-related traces to adhesive wear-induced delamination, and ultimately to electrochemical oxidative wear. Overall, pO₂ imposes a pronounced non-monotonic “window effect” on arc stability and erosion, providing key evidence for PCS structural optimization and risk assessment in open operating environments. Full article

Background: The combination of conventional drugs and inhibitors of signaling molecules is an effective strategy to increase cancer treatment efficacy and reduce drug doses to protect against their cytotoxic effects. Our research has shown the cisplatin concentration-dependent shift in the role of MAP kinase JNK from antiapoptotic to proapoptotic in non-small cell lung cancer A549 cells. Cell death/survival signaling molecules, tumor suppressor p53 and pro-survival protein kinase AKT were detected to be differently regulated by JNK inhibition at low vs. high cisplatin concentrations. Here, we further investigated the phenomenon and potential mechanisms of combined JNK inhibition and cisplatin treatment. Methods: Cell death in vitro was evaluated by MTT and Western blot assays after combined cisplatin and specific inhibitor treatment; two-way ANOVA was used for analysis. Results: JNK is differently involved in determining cellular sensitivity to different DNA-damaging drugs. There is no universal cell death induction mechanism originating from DNA damage through the involvement of JNK. The outcome of JNK inhibition also depends on the cell type. We found that there is an unusual reciprocal interaction between p53 and AKT in cisplatin-treated A549 cells, where p53 inhibits AKT, while AKT activates p53. In the case of cisplatin + JNK inhibitor SP600125, DNA damage and reactive oxygen species (ROS) contribute to cell death regulation in different ways. ROS exert opposite roles on cell fate-determining molecules p53 and AKT, and ROS act on p53 and AKT in opposite directions at low vs. high concentrations of cisplatin, combined or not with JNK inhibition. The differentially activated p53 in response to ROS (at low versus high concentrations of cisplatin, combined with JNK inhibitor) may be a molecular switch in the role of JNK from antiapoptotic to neutral/proapoptotic, and an executor of cell death. ROS is a possible threshold regulator that, together with an as-yet-unidentified factor, can differentially regulate p53. As a result, AKT phosphorylation and function are altered. The findings emphasize the importance of assessing the role of drug concentration when combining them with JNK inhibition when monitoring therapeutic efficacy and toxicity issues in personalized cancer treatment. Full article

L-glutamate (L-Glu) is the primary excitatory neurotransmitter in the mammalian central nervous system. Developing a real-time monitoring system is essential to understanding the onset and progression of related conditions. However, the absence of an L-Glu dehydrogenase that is insensitive to oxygen limits the development of oxygen-independent electrochemical enzymatic sensors. Additionally, the most commonly used L-Glu-specific oxidase requires site-specific proteolytic post-translational modifications in specific host microorganisms, which makes protein engineering difficult. To address these issues, L-Glu oxidase derived from Streptomyces mobaraensis (SmEOx), which does not require post-translational modifications, was engineered to function as a dehydrogenase. Residues crucial for the oxidative half reaction with oxygen in SmEOx were identified, and mutagenesis studies were conducted. Mutant SmEOx variants with suppressed oxidase activity and improved dye-mediated dehydrogenase activity compared to the wild-type enzyme were successfully obtained. The ratio of dehydrogenase activity to oxidase activity (Dh/Ox) increased ~2900-fold in mutant M117I and ~6700-fold in mutant M117F/K400N compared to wild-type recombinant SmEOx. The resulting virtually L-Glu dehydrogenases (vEDHs) were modified with a redox mediator and evaluated using transient open-circuit potential (OCP)-based L-Glu measurements. As a result, the vEDH (M117F/K400N mutant)-immobilized electrode enabled electrochemical L-Glu detection under ambient oxygen without the need for an external electron mediator, unlike the wild-type enzyme. The created vEDH, together with the OCP sensor developed using it, paves the way for future development of miniaturized, real-time L-Glu monitoring systems with high temporal and spatial resolution. Full article