ABSTRACT Spinal cord injury (SCI) induces neuroinflammation predominantly mediated by microglia, thereby establishing a detrimental milieu that impedes neurological recovery. Extracellular vesicles (EVs) derived from umbilical cord mesenchymal stem cells (UCMSCs) possess considerable therapeutic potential; however, their clinical translation is constrained by insufficient bioactivity, poor targeting specificity, and uncontrolled release kinetics. Here, we present a multidimensional engineering strategy that overcomes these barriers synergistically. Tetramethylpyrazine (TMP)‐pretreated extracellular vesicles (TEVs) are enriched with anti‐inflammatory and pro‐regenerative factors in their cargo, while Angiopep‐2 (Ang2) peptide‐modified TEVs (Ang‐TEVs) confer significantly enhanced microglial targeting. A reactive oxygen species (ROS)‐responsive hyaluronic acid (HA)‐phenylboronic acid (PBA)/polyvinyl alcohol (PVA) hydrogel serves as an intelligent depot for sustained, on‐demand Ang‐TEVs release at the lesion site. This construct, Ang‐TEVs@Gel, demonstrated robust lesion accumulation and selective microglial uptake. It delivered miR‐664a‐3p, which suppressed PIK3CA to attenuate PI3K‐AKT‐mTOR signaling and unleash autophagic flux, reprogramming microglia toward a reparative state that enhanced myelin debris clearance and quelled inflammation. Consequently, axonal regeneration and remyelination were markedly improved, driving significant motor recovery in SCI mice. By integrating preconditioning, active targeting, and stimuli‐responsive biomaterials, this strategy provides an elegant blueprint for engineering EV‐based therapies to repair the injured central nervous system.
Wu Xiong, Min-Hao Liu, Mingming Zheng et al.· Advancement of science· 0 citations
Introduction The cardiometabolic index (CMI), a comprehensive indicator for assessing body fat distribution and serum lipid level, has been found to be associated with biological aging. But the potential relationship between CMI and incident frailty remains unclear. Herein, we designed this study to delve into the relationship between CMI and frailty incidence in adults aged 45 years or older. Methods Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). Participants were categorized into quartiles (Q1–Q4) according to CMI levels. Multivariable logistic regression model and restricted cubic spline (RCS) analyses were performed to evaluate the connection between CMI and incident frailty risk. In addition, we conducted subgroup and interaction analyses to investigate heterogeneity across distinct subgroups. Results A total of 6200 participants were enrolled in our study, with an average age of 57.92 ± 8.57 years, 48.64% males. During a 7-year follow-up, 1166 (18.81%) participants developed frailty, and the incidence showed an increasing trend from Q1 to Q4. The fully adjusted odds of developing frailty increased by 1% for per 1-SD increment in CMI (OR = 1.02, 95% CI:1.00-1.03, P = 0.005). The participants with the highest CMI quartile (Q4) had a significantly elevated risk of developing frailty compared to those in the lowest CMI group (Q1) (OR = 1.06, 95% CI:1.02-1.09, P < 0.001). Subgroup analyses demonstrated consistent results across various subgroups (P for interaction > 0.05). The RCS analysis confirmed a positive association of CMI with incident frailty, and nonlinear relationship was observed (P for overall < 0.001, P for nonlinear = 0.012). Conclusion Higher CMI levels were associated with an increased likelihood of developing frailty. Given its accessibility, CMI may have potential value as a population-level marker for frailty risk assessment.
Zhen-You Liu, Qing-Yuan Wang, Jin Zhang et al.· Inquiry : a journal of medic...· 0 citations
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