Search Results (2,527)

Advances in geroscience suggest that aging is modulated by molecular pathways that are amenable to dietary and pharmacological intervention. We conducted an integrative critical review of caloric restriction (CR), intermittent fasting (IF), and caloric restriction mimetics (CR-mimetics) to compare shared mechanisms, clinical evidence, limitations, and translational potential. Across modalities, CR and IF consistently activate AMP-activated protein kinase and sirtuins, inhibit mTOR (mechanistic target of rapamycin) signaling, and enhance autophagy, aligning with improvements in insulin sensitivity, lipid profile, low-grade inflammation, and selected epigenetic aging measures in humans. CR-mimetics, such as metformin, resveratrol, rapamycin, and spermidine, partially reproduce these effects; however, long-term safety and efficacy in healthy populations remain incompletely defined. Methodological constraints—short trial duration, selective samples, intermediate (nonclinical) endpoints, and limited adherence monitoring—impede definitive conclusions on hard outcomes (frailty, disability, hospitalization, mortality). We propose the Active Management of Aging and Longevity (AMAL) model, a three-level biomarker-guided framework that integrates personalized diet, chrono-nutrition, exercise, and the selective use of CR-mimetics, along with digital monitoring and decision support. AMAL emphasizes epigenetic clocks, multi-omics profiling, inflammatory and microbiome metrics, and adaptive protocols to enhance adherence and clinical relevance. Overall, CR, IF, and CR mimetics constitute promising, complementary strategies to modulate biological aging; rigorous long-term trials with standardized biomarkers and clinically meaningful endpoints are needed to enable their scalable implementation. Full article

As water pollution from dyes, pharmaceuticals, heavy metals, and other emerging contaminants continues to rise at an alarming rate, ensuring access to clean and safe water has become a pressing global challenge. Conventional water treatment methods, though widely used, often fall short in effectively addressing these complex pollutants. In response, researchers have turned to Advanced Functional Membranes (AFMs) as promising alternatives, owing to their customizable structures and enhanced performance. Among the most explored AFMs are those based on metal–organic frameworks (MOFs), carbon nanotubes (CNTs), and electro–catalytic systems, each offering unique advantages such as high permeability, selective pollutant removal, and compatibility with advanced oxidation processes (AOPs). Notably, hybrid systems combining AFMs with electrochemical or photocatalytic technologies have demonstrated remarkable efficiency in laboratory settings. However, translating these successes to real-world applications remains a challenge due to issues related to cost, scalability, and long-term stability. This review explores the recent progress in AFM development, particularly MOF-based, CNT-based, and electro-Fenton (EF)-based membranes, highlighting their material aspects, pollutant filtration mechanisms, benefits, and limitations. It also offers insights into how these next-generation materials can contribute to more sustainable, practical, and economically viable water purification solutions in the near future. Full article

Cannabidiol (CBD) and other phytocannabinoids are gaining attention for their therapeutic potential in cardiovascular disease (CVD), the world’s leading cause of death. This review highlights advances in understanding the endocannabinoid system, including CB1 and CB2 receptors, and the mechanisms by which CBD exerts anti-inflammatory, antioxidative, vasoprotective, and immunomodulatory effects. Preclinical and translational studies indicate that selective activation of CB2 receptors may attenuate atherogenesis, limit infarct size in ischemia–reperfusion injury, decrease oxidative stress, and lessen chronic inflammation, while avoiding the psychotropic effects linked to CB1. CBD also acts on multiple molecular targets beyond the CB receptors, affecting redox-sensitive transcription factors, vascular tone, immune function, and endothelial integrity. Early clinical trials and observational studies suggest that CBD may lower blood pressure, improve endothelial function, and reduce sympatho-excitatory peptides such as catestatin, with a favorable safety profile. However, limited bioavailability, small sample sizes, short study durations, and uncertainty about long-term safety present challenges to its clinical use. Further research is needed to standardize dosing, refine receptor targeting, and clarify the role of the endocannabinoid system in cardiovascular health. Overall, current evidence supports CBD’s promise as an adjunct in CVD treatment, but broader clinical use requires more rigorous, large-scale studies. Full article

Air pollution is a leading environmental risk that causes respiratory morbidity and mortality. The increasing availability of high-resolution environmental data and air pollution-related health cases have accelerated the use of machine learning models (ML) to estimate environmental exposure–response relationships, forecast health risks and call for the needed policy and practical interventions. Unfortunately, ML models are opaque, in a sense that, it is unclear how these models combine various data inputs to make a concise decision. Thus, limiting its trust and use in clinical matters. Explainable artificial intelligence (xAI) models offer the necessary techniques to ensure transparent and interpretable models. This systematic review explores online data repositories through the lens of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline to synthesize articles from 2020 to 2025. Various inclusion and exclusion criteria were established to narrow the search to a final selection of 92 articles, which were thoroughly reviewed by independent researchers to reduce bias in article assessment. Equally, the ROBINS-I (Risk Of Bias In Non-randomized Studies of Interventions) domain strategy was helpful in further reducing any possible risk in the article assessment and its reproducibility. The findings reveal a growing adoption of ML techniques such as random forests, XGBoost, parallel lightweight diagnosis models and deep neural networks for health risk prediction, with SHAP (SHapley Additive exPlanations) emerging as the dominant technique for these models’ interpretability. The extremely randomized tree (ERT) technique demonstrated optimal performance but lacks explainability. Moreover, the limitations of these models include generalizability, data limitations and policy translation. Conclusion: This review’s outcome suggests limited research on the integration of LIME (Local Interpretable Model-Agnostic Explanations) in the current ML model; it recommends that future research could focus on causal-xAI-ML models. Again, the use of such models in respiratory health issues may be complemented with a medical professional’s opinion. Full article

Synthetic aperture radar (SAR) exhibits all-day and all-weather capabilities, granting it significant application in remote sensing. However, interpreting SAR images requires extensive expertise, making SAR-to-optical remote sensing image translation a crucial research direction. While conditional generative adversarial networks (CGANs) have demonstrated exceptional performance in image translation tasks, their massive number of parameters pose substantial challenges. Therefore, this paper proposes ILF-BDSNet, a compressed network for SAR-to-optical image translation. Specifically, first, standard convolutions in the feature-transformation module of the teacher network are replaced with depthwise separable convolutions to construct the student network, and a dual-resolution collaborative discriminator based on PatchGAN is proposed. Next, knowledge distillation based on intermediate-layer features and channel pruning via weight sharing are designed to train the student network. Then, the bio-inspired dynamic search of channel configuration (BDSCC) algorithm is proposed to efficiently select the optimal subnet. Meanwhile, the pixel-semantic dual-domain alignment loss function is designed. The feature-matching loss within this function establishes an alignment mechanism based on intermediate-layer features from the discriminator. Extensive experiments demonstrate the superiority of ILF-BDSNet, which significantly reduces number of parameters and computational complexity while still generating high-quality optical images, providing an efficient solution for SAR image translation in resource-constrained environments. Full article

In recent years, microneedles (MNs), an innovative transdermal drug delivery system, have demonstrated significant advantages in treating diverse skin diseases. The stratum corneum (SC), with its ‘brick-mortar’ structure, is the main barrier to drug penetration into the skin. MNs—including solid, coated, hollow, dissolving, and hydrogel-forming types—penetrate it minimally to form temporary micro-channels, enabling efficient delivery of a wide range of therapeutic agents. These include small molecules, biologics, nanoparticles, and photosensitizers, among others. This technology has been effectively applied in the treatment of androgenetic alopecia, acne, scars, melanoma, psoriasis, atopic dermatitis, and vitiligo. By avoiding stimulation of dermal blood vessels and nerves, MNs offer low pain and high patient compliance. These advantages underscore their broad clinical potential for dermatologic therapy. Future studies must optimize material selection, drug-carrying efficiency, and scale-up production to facilitate clinical translation. Full article

Ovarian cancer (OCa) remains the most lethal gynecologic malignancy in the United States, with low-grade serous and mucinous subtypes frequently driven by KRAS mutations. These mutations activate downstream MAPK and PI3K/AKT signaling pathways, contributing to tumor progression and resistance to therapy. Although the MEK inhibitor trametinib is used to target these pathways, its efficacy is limited in KRAS-mutant OCa due to compensatory activation of the leukemia inhibitory factor (LIF)/LIF receptor (LIFR) axis. In this study, we evaluated the therapeutic potential of combining trametinib with EC359, a selective LIFR inhibitor, in Ras/Raf-driven OCa models. EC359 significantly reduced cell viability, clonogenic survival, and induced cell death via ferroptosis in vitro. Mechanistic studies revealed that EC359 suppressed trametinib-induced activation of LIFR downstream signaling. RNA-seq analysis showed that combination therapy downregulated mitochondrial translation and MYC target genes while upregulating apoptosis-related genes. In vivo, EC359 and trametinib co-treatment significantly reduced tumor growth in xenograft and PDX models without inducing toxicity. Our studies identify LIFR signaling as a critical vulnerability in Ras/Raf-mutant and low grade serous OCa. Further, it provides strong preclinical rationale for EC359 and trametinib combination therapy as a new therapeutic strategy for treating Ras/Raf-driven OCa and low-grade serous OCa. Full article

Recent literature reports have shown that individual HEAs, especially those of the AlCoCrFeNi composition system alloyed with appropriately selected elements, exhibit excellent mechanical properties and corrosion resistance, making them promising candidates for replacing conventional materials such as austenitic steels in corrosive environments. Therefore, in the present study, the high-entropy alloy AlCoCrFeNiMo_0.25 was examined and compared with AISI 304L steel and the reference alloy AlCoCrFeNi. The HEA was produced by arc melting in vacuum. The effect of molybdenum addition (5% at.) on the structure, mechanical properties, and corrosion resistance was evaluated. Potentiodynamic polarization and electrochemical impedance spectroscopy tests were carried out in a 3.5% NaCl solution in a three-electrode electrochemical system. The addition of molybdenum to AlCoCrFeNiMo_x alloy additionally caused, along with the BCC phase, the formation of σ phase and FCC phase (less than 1%), as well as changes in the microstructure, leading to the fragmentation of grains and the formation of a mosaic structure. On the basis of nanoindentation tests, it was established that the addition of Mo increases hardness and elastic modulus and improves nanoindentation coefficients H/E and H³/E², as well as an increase in the elastic recovery index while decreasing plasticity index (vs. the reference equiatomic HEA). This indicates the improvement of anti-wear properties with impact loading resistance. In turn, electrochemical tests have shown that the addition of Mo improves corrosion resistance. Corrosion pitting develops in Al- and Ni-rich areas of HEA alloys, as a result of galvanic microcorrosion related to Cr chemical segregation. In general, the addition of 5% Mo results in a fine-grained mosaic structure, which primarily translates into favorable nanoindentation and corrosion properties of the AlCoCrFeNiMo_0.25 alloy. Full article

Hydroethanolic Cucurbita pepo seed extracts are traditionally used for alleviating lower urinary tract symptoms (LUTS), yet their mechanisms remain unclear. Adenosine, a purine nucleoside involved in neuromodulation and smooth muscle relaxation, was recently identified in C. pepo seeds. Since A₁ adenosine receptors (A₁AR) suppress parasympathetic bladder overactivity by inhibiting acetylcholine (ACh) release, we investigated to which extent purines from pumpkin seed extracts contribute to A₁AR activation. Complementary antioxidant capacity was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. Three hydrophilic seed extracts containing different adenosine levels (0.60–1.18 mg/g dw) were evaluated for agonist activity using a cAMP inhibition assay. The most active extract showed an EC₅₀ of 40.22 µg/mL. Selective removal of adenosine shifted the dose–response curve rightward, while further elimination of an adenosine derivative increased the EC₅₀ to 212.10 µg/mL, confirming adenosine as the principal active compound. Guanosine and inosine did not exhibit A₁AR agonist or allosteric effects. All samples exhibited measurable but weak antioxidant activity (IC₅₀ = 1.02–4.19 mg/mL), consistent with their low total phenolic content. These findings underscore the importance of accounting for naturally occurring agonists in plant extracts to avoid overestimating receptor-mediated effects in vitro which are not translatable in vivo. Full article

Background: B7-H3, an immunoregulatory protein of the B7 family, has been associated with both anti-cancer immunity and tumor promotion, with its expression commonly correlated with poor prognosis. Although it is frequently expressed across cancers, its heterogeneity may limit the effectiveness of B7-H3-targeted therapies. Consequently, a sensitive and non-invasive method is needed to assess B7-H3 expression for patient selection and stratification. Single-domain antibody fragments (sdAbs) offer a promising platform for developing such a diagnostic tool. Methods: To generate B7-H3 sdAbs, two Ilamas were immunized with the recombinant human B7-H3 protein. Positive clones were selected through Phage biopanning and characterized for thermal stability, binding specificity, and affinity to human and murine B7-H3 proteins. Selected sdAbs were radiolabeled with Technetium-99m (^99mTc) and evaluated for B7-H3 detection in two xenograft tumor models using micro-SPECT/CT imaging and dissection studies. Results: Sixteen purified sdAbs bound specifically to recombinant B7-H3 proteins and cells expressing native B7-H3 antigens, with nanomolar affinities. The four best-performing sdAbs bound promiscuously to tested mouse and human B7-H3 isoforms. Lead sdAb C51 labeled with ^99mTc displayed specific accumulation across two human B7-H3⁺ tumor models, achieving high contrast with a tumor-to-blood ratio of up to 10 ± 3.16, and a tumor uptake of up to 4.96 ± 1.4%IA/g at 1.5 h post injection. Conclusions: The lead sdAb enabled rapid, specific, and non-invasive imaging of human B7-H3⁺ tumors. Its isoform promiscuity supports broad applicability across cancers expressing different human B7-H3 isoforms. These results support further development for clinical translation to enable patient selection and improved B7-H3-targeted therapies. Full article

For this article, we reviewed and synthesized narratological theories on reliability and unreliability and used them as the basis for an exploratory study, examining how real readers respond to a literary short story that contains several unreliable or conflicting narrative accounts. The story we selected is “In a Grove” by Ryūnosuke Akutagawa (orig. 藪の中/Yabu no naka) from 1922 in the English translation by Jay Rubin from 2007. To investigate how readers evaluate trustworthiness in narrative contexts, we combined quantitative and qualitative methods. We analyzed correlations between reading habits (i.e., Author Recognition Test), cognitive traits (e.g., Need for Cognition; Epistemic Trust), and trust attributions to characters while also examining how narrative sequencing and character-specific reasons for (dis)trust shaped participants’ judgments. This mixed-methods approach allows us to situate narrative trust as a context-sensitive, interpretive process rather than a stable individual disposition. Full article

The research presented in this article aimed to analyze the impact of circular economy initiatives on the European Union environmental goods and services sector. Data from the Eurostat databases were used to conduct the research. Validation of the five research hypotheses involved the formulation of two regression equations: the first one focused on innovation and recycling performance indicators, and the second equation focused on circular-economy indicators. Both models were estimated using country fixed-effects regression with Driscoll–Kraay standard errors to ensure robust inference. The regression model was selected based on the Hausman test and F-test, but tests for autocorrelation, heteroscedasticity, and multicollinearity were also performed. The main findings, as the results suggest, refer to the central role of private investment in circular sectors and resource productivity, both exerting positive and significant effects on the environmental goods and services sector (EGSS). The material footprint also shows a positive effect, but in contrast, the circular material use rate does not display a significant impact, indicating that increases in the share of recycled materials do not automatically translate into greater economic value. Full article

Objectives: Emerging evidence suggests that propolis possesses significant anti-obesity properties. While gut hormones and microbiota are known to play crucial roles in obesity development, the specific mechanisms through which propolis exerts its effects via the gut hormone axis remain poorly characterized. Methods: A high-fat diet (HFD) rat model was established to investigate the regulatory effects of propolis. After 10 weeks of intervention, blood serum, liver, colon tissues, and luminal contents were analyzed for metabolic parameters, gene expression of gut hormones and AMPK pathway markers, microbial community structure, and short-chain fatty acid production. Results: Propolis effectively mitigated HFD-induced metabolic disturbances, including excessive weight gain, adipose tissue accumulation, hyperlipidemia, and hepatic dysfunction. These improvements were associated with significant upregulation of the AMPK pathway. Importantly, propolis enhanced intestinal barrier integrity and differentially modulated gut hormone expression by increasing the mRNA levels of Cck, Gip, and Ghrl, and decreasing Lep and Gcg levels. 16S rRNA sequencing analysis revealed that propolis administration selectively enriched butyrate- and propionate-producing bacterial species. Correlation analysis further identified the Eubacterium brachy group as a pivotal microbial mediator in the propolis-modulated gut microbiota–gut hormone–liver AMPK axis. Conclusions: Our findings establish that propolis ameliorates obesity-related metabolic disorders by orchestrating crosstalk among gut microbiota, enteroendocrine hormones, and hepatic AMPK signaling. These results elucidate a novel mechanistic pathway in rodents; however, their direct translatability to humans requires further clinical investigation. This tripartite axis offers a mechanistic foundation for developing microbiota-targeted anti-obesity therapies. Full article

Overcoming immune resistance remains the critical barrier to durable immunotherapy responses. Tumors with non-inflamed, “cold” microenvironments exclude cytotoxic lymphocytes and evade checkpoint blockade. Innate nucleic acid-sensing pathways—including TLRs, RIG-I-like RNA sensors, and the cGAS–STING DNA-sensing axis—can recondition this hostile landscape by licensing dendritic cells, restoring antigen presentation, and recruiting effector T and NK cells. In this review, we synthesize mechanistic insights into how these receptors function across tumor and immune compartments and evaluate recent translational advances spanning small-molecule and nucleic acid agonists, engineered delivery systems, and clinical trials. We highlight challenges that have limited clinical impact, including pathway silencing, systemic toxicity, and lack of predictive biomarkers, while emphasizing emerging solutions such as tumor-intrinsic targeting, CAR-T/NK engineering, and biomarker-guided patient selection. By integrating innate activation into rational combination regimens, innate immune reprogramming offers a blueprint to convert resistant disease into one susceptible to durable immune control. Full article

The site selection of catalyst elements plays a crucial role in urban micro-renewal. Existing site selection models are incapable of configuring multiple types of elements in parallel and exhibit limited capacity in translating urban spatial structures and balancing conflicting stakeholder interests, failing to meet the comprehensive and complex requirements inherent in catalyst element site selection problems. Drawing on the perspectives of urban planning, operations research, and computer science, this study proposes a Multi-objective Ccrossover Parallel Combinatorial Optimization (MCPCO) model for the site selection of catalyst elements, along with a corresponding optimization method. This model uses concise and universal model architecture to map complex and specific real-world problems, optimizing the simultaneous configuration of multiple types of catalyst elements under multiple and conflicting objectives. An empirical study, using the renewal of the Liuhe Confucian Temple historical area in Nanjing as a case study, demonstrates that the model effectively maps and solves the site selection problem of catalyst elements in urban micro-renewal, providing a useful reference for similar problems especially characterized by parallel site selection of multiple types of elements. Full article