Background: Frailty is common and not limited to older age group. Serum α-Klotho works as a biomarker of anti-aging effect. However, there is limited research about the relationship between them in middle-aged and older people and controversy still exists. Methods: Based on data from National Health and Nutrition Examination Survey (NHANES) 2007–2016, we constructed weighted logistic regression models and conducted sensitivity tests to investigate the correlation between frailty and α-Klotho among people aged 40 to 79. And then their relationship was visualized by Restricted Cubic Spline (RCS). Finally, the stratified analyses and interaction tests of covariables was presented in the forest plot. Results: A total of 7052 individuals were involved in this study, with mean age of 62.76 ± 0.18 years and females accounting for 51.05%. 2554 of them were in “frailty”. After adjustment for relevant covariables, weighted logistic regression models showed that the odds ratio and 95% confidence interval [ORs (95%CI)] of correlation between frailty and Natural Logarithm(ln)-transformed α- Klotho[ln(α-Klotho)] was 0.63 (0.50, 0.79); we then performed a sensitivity analysis and found that the results remained stable. In model 3, individuals in quartiles 2, 3, and 4 showed statistical differences compared with the lowest ln(α-Klotho) quartiles, ORs (95% CI) were 0.74 (0.59, 0.93), 0.72 (0.57, 0.91), 0.71 (0.57, 0.87), respectively. Subsequently, non-linear associations were exhibited by RCS (p<0.001). The turning point for α-Klotho and ln(α-Klotho) were 785.7(pg/ml) and 6.67, respectively. Finally, analysis of the relationship between different levels of ln(α-Klotho) and frailty in different populations revealed differences between groups. The results of the interaction test showed that no other covariables had significant interaction with serum α-Klotho in our study. Conclusion: The L-shaped and negative correlation was found between α-Klotho and frailty among people aged 40 to 79 in the NHANES from 2007 to 2016.

JOURNAL/nrgr/04.03/01300535-202507000-00025/figure1/v/2026-04-26T112544Z/r/image-tiff To investigate the mechanisms underlying the onset and progression of ischemic stroke, some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex. However, these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied, although ischemic stroke is strongly age-related. In this study, we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser. We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation. Moreover, we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke. Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages, thereby highlighting the technique’s potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

Objective: This study innovatively investigates the cumulative associations between behavioral determinants of health (BDoH), metabolic determinants of health (MDoH), and systemic inflammation biomarkers in U.S. adults, using a novel cross-sectional framework to quantify their synergistic effects.Methods: Utilizing cross-sectional data from 18,500 participants in the National Health and Nutrition Examination Survey (NHANES 2005–2018 cycle), we developed a composite exposure model integrating BDoH (smoking status, physical activity, dietary quality) and MDoH (obesity metrics, hypertension, diabetes) through standardized questionnaires and clinical measurements. Systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI) were calculated from peripheral blood cell counts. Multivariable-adjusted logistic regression models examined dose–response relationships, with trend analysis explicitly testing cumulative BDoH-MDoH interactions.Results: The cohort (mean age 44.3 ± 0.3 years; 52.4% male) demonstrated significant positive associations between adverse health determinants and inflammatory indices. Current tobacco use (OR = 1.32, 95%CI = 1.18–1.47), suboptimal diet (HEI < 52: OR = 1.24, 95%CI = 1.11–1.38), obesity (BMI ≥ 30 kg/m²: OR = 1.41, 95%CI = 1.27–1.56), and central adipometry (OR = 1.39, 95%CI = 1.25–1.54) showed strongest correlations with elevated SII/SIRI. Metabolic disorders exhibited distinct patterns: hypertension and diabetes associated specifically with SIRI elevation (OR = 1.19, 95%CI = 1.06–1.33 and OR = 1.17, 95%CI = 1.03–1.32, respectively), while physical inactivity (<600 MET-min/week) uniquely correlated with SII increase (OR = 1.26, 95%CI = 1.13–1.40). Notably, our cumulative model revealed synergistic effects: exposure to ≥3 adverse behavioral determinants amplified inflammation risks (SII: OR = 1.57, 95%CI = 1.42–1.73; SIRI: OR = 1.49, 95%CI = 1.35–1.64), with significant dose-dependent trends (P-trend<0.001). Co-occurring metabolic abnormalities demonstrated additive inflammatory effects (P-trend<0.001), exceeding individual risk factor impacts.Conclusion: This cross-sectional study provides the first evidence that integrated BDoH-MDoH cumulative exposure models uncover distinct and synergistic inflammatory pathways. Both individual and combined behavioral-metabolic risk factors significantly associate with systemic inflammation biomarker elevation, highlighting the necessity of dual-target intervention strategies.