Background: Atherosclerosis (AS), a chronic inflammatory condition of the vasculature, is a major contributor to cardiovascular morbidity. Yaoshi Tongyuan Tablet (YTT) is a food-medicine homology (FMH) formulation containing Panax Ginseng , Radix Puerariae , Sophora Japonica , Ginkgo Semen , Persicae Semen , Ziziphi Spinosae Semen , and Crataegus Pinnatifida , which shows promise for AS management; however, its mechanistic basis remains poorly defined. This study aims to explore the protective roles and mechanistic foundations of YTT in preventing and treating AS. Methods: A combination of network pharmacology, ultra-performance liquid chromatography coupled with Q Exactive Orbitrap mass spectrometry (UPLC-QE-MS), and molecular docking was employed to predict potential bioactive compounds and their molecular targets. ApoE ^−/− mice on a high-fat diet were used to model AS and were treated with low (250 mg/kg), medium (500 mg/kg), and high (1,000 mg/kg) doses of YTT for 4 weeks. Therapeutic efficacy and underlying molecular mechanisms were evaluated through biochemical assays, histopathological analysis, and Western blotting. Results: Integrated analyses revealed kaempferol, isorhamnetin, and quercetin as central bioactive molecules acting on AKT1, a key node within the PI3K/Akt signaling cascade. In vivo , YTT treatment markedly curbed weight gain, ameliorated dyslipidemia, reduced systemic inflammation, and diminished atherosclerotic plaque load, alongside promoting plaque stabilization. At the molecular level, YTT substantially inhibited activation of the PI3K/Akt axis and phosphorylation of NF-κB, leading to lowered secretion of pro-inflammatory cytokines. Conclusion: YTT ameliorates atherosclerosis by counteracting dyslipidemia and inflammation, primarily through modulation of the PI3K/Akt/NF-κB pathway. This study offers novel integrative insights into the anti-atherogenic properties of YTT and pinpoint crucial bioactive constituents worthy of further pharmacological investigation.

Allergic asthma is characterized by immune dysregulation, and deficiencies in regulatory T-cell (Treg) function are a hallmark of the disease. However, mechanisms of Treg impairment for their therapeutic correction remain poorly defined. The results showed that patient Tregs exhibited a senescent phenotype, including shortened telomeres, increased SA-β-gal activity, and heightened apoptosis. Functionally, they were compromised, showing reduced suppressive capacity and a pro-inflammatory cytokine shift. KQS-1 treatment robustly reversed these defects, restoring FOXP3- and IL-10–dependent Treg suppressive capacity and the production of anti-inflammatory cytokines. This functional rescue centered on these two core Treg signature genes was dependent on Dectin-1 binding and a downstream Raf-1/ROS signaling axis, which drove a sustained epigenetic program characterized by increased H3K4me3 and H3K27ac at the FOXP3 and IL10 loci, focal hypomethylation, and chromatin remodeling at these specific loci. CRISPR-mediated deletion of Dectin-1 abrogated all beneficial effects of KQS-1. As proof of principle that KQS1 is protective, we demonstrate attenuation of airway hyperresponsiveness, inflammation, and remodeling in dust mite–sensitized mice and in recipient mice upon adoptive transfer of KQS-1–trained human Tregs.

Obesity has been linked to an increased risk of cognitive impairment and dementia in later life. Although aging and obesity are both associated with cognitive decline, it remains unclear how they interact to affect cognitive function across the lifespan and how brain function might mediate their relationship with cognition. Our previous findings and other studies have shown that membrane type 1-matrix metalloproteinase (MT1-MMP/MMP14), which increases with age, regulates energy homeostasis. Inhibiting MT1-MMP improves insulin sensitivity, reduces body fat, and lowers serum cholesterol. Here, we demonstrate that MT1-MMP links neuroinflammation to cognitive decline in aging and obesity. Inflammatory responses in the brain increase MT1-MMP activation in the hippocampus of both mice and humans. Activation of hippocampal MT1-MMP alone can trigger cognitive decline and synaptic impairment independently of neuroinflammation. Conversely, ablation of MT1-MMP in the hippocampus reverses cognitive decline and improves synaptic plasticity in aging and obesity. Pharmacological inhibition of MT1-MMP, through an orally administered brain-penetrant inhibitor or targeted delivery of a neutralizing antibody to the hippocampus, improves memory and learning in aged and obese mice without toxicity. Mechanistically, MT1-MMP proteolytically inactivates G-protein-coupled receptor 158 (GPR158), a hippocampal receptor for osteocalcin (OCN) that is important for the maintenance of cognitive integrity, thus suppressing the ability of the OCN-GPR158 axis to promote cognition in aging and obesity. These findings suggest a new mechanism underlying hippocampal dysfunction and reveal the potential for treating multiple age-related diseases, including neurodegenerative disorders, obesity, diabetes, and atherosclerosis, with a single MT1-MMP-blocking agent.

Objectives: The burden of osteoarthritis (OA) among elderly adults in China is increasing, yet trends for site-specific OA in this population remain inadequately studied. To explore the disease burden of OA at different anatomical sites among elderly adults in China, as well as its gender and age disparities, and to forecast future trends. Methods: Using the Global Burden of Disease (GBD) 2023 database, we analyzed the trends of hand, knee, hip, and other-site OA among Chinese elderly adults (aged ≥60 years), stratified by gender and age groups, based on the absolute number of Years Lived with Disability (YLDs) and Age-Standardized YLDs Rate (ASYR) from 1990 to 2023. Joinpoint regression and age-period-cohort models were adopted for statistical analyses. Results: From 1990 to 2023, the YLD burden of site-specific OA exhibited an upward trend among Chinese elderly adults. Hand OA presented the largest increases in total YLD count and ASYR, with growth rates of 404.45 % and 60.17 %, respectively. Knee OA imposed the heaviest disease burden (ASYR ₂₀₂₃ =685.02/100,000), and females bore a higher burden than males. Age-period-cohort analyses revealed distinct site- and gender-specific disparities in age, period, and cohort effects across all OA subtypes. Projections for 2024 to 2035 indicated consistent rises in total YLD numbers for OA at all anatomical sites, while the magnitude of changes in ASYR remained modest and varied by lesion location. Conclusions: Between 1990 and 2023, the overall YLD burden of site-specific OA increased among Chinese elderly adults. Hand OA saw the most substantial growth, while knee OA carried the heaviest burden, with gender and age disparities observed for OA at all anatomical sites. Future research should conduct individual-level studies based on Chinese domestic cohorts, disease registries or hospital databases. OA screening, weight control, joint protection, and health education should be strengthened in primary care and community chronic disease management programs.

Epilepsy is a complex neurological disorder characterized by nonlinear dynamic interactions among multiple brain regions. The unscented Kalman Filter (UKF), a high-precision algorithm for nonlinear state and parameter estimation, has recently gained prominence in epilepsy research as it infers latent physiological parameters from electrophysiological signals to reveal the underlying seizure mechanisms. This review provides a comprehensive overview of recent progress in applying UKF to epileptic dynamics modeling and signal analysis, focusing on three major aspects: parameter estimation and model optimization based on neural computational models, seizure detection and prediction, and closed-loop control for seizure intervention. Studies have demonstrated that UKF can robustly reconstruct neuronal dynamics under noise and nonstationary conditions, providing real-time tracking of seizure evolution and contributing to a unified framework that integrates modeling, signal interpretation, and intervention. Despite these advances, important challenges remain, including noise covariance selection, high-dimensional parameter estimation, large-scale network modeling, and limited clinical validation. Future research should focus on adaptive mechanisms, improved multi-parameter estimation, and broader validation using multimodal data and real-patient cohorts. Overall, UKF has shown considerable promise as a model-based framework for epilepsy research and, more broadly, as an interpretable engineering approach for latent neural-state estimation from noisy physiological signals, although broader clinical evidence and further methodological refinement are still required before it can be considered a clinically mature framework.