Feng Wang’s research while affiliated with Chinese Academy of Sciences and other places

In the context of rapid nanotechnology advancements, size effects have become key in determining material performance. In order to better investigate the impact of size effects on nanostructures, a new nonlocal modified couple stress (NL-MCS) model developed for magneto-electro-elastic (MEE) nanobeams is introduced in this research. This model comprehensively incorporates size-dependent effects, prominently reflecting the softening characteristics introduced by the nonlocal elasticity theory (NL), while also accounting for the influence of modified couple stress (MCS) on hardening. The model incorporates von Karman’s geometric nonlinearity theory, Reddy’s third-order shear deformation theory and Maxwell’s equations. The objective of this paper is to analyze the dynamic response behavior of MEE nanostructures, providing a theoretical foundation for the design and mechanical response of MEE nanostructures. The Galerkin method is employed to process the dynamic model of MEE nanobeams, followed by iterative solution of the processed model using the Newmark method. Additionally, quadratic extrapolation is utilized to enhance the convergence rate of the iterative process. A comprehensive analysis of the influences of material length scale parameter, nonlocal parameters, Winkler–Pasternak coefficients, aspect ratio, volume fraction of materials, applied magnetic potential and applied voltage on the nonlinear dynamic response of MEE nanobeams are conducted.

Background Severe hepatic steatosis can exacerbate Ischemia–reperfusion injury (IRI), potentially leading to early graft dysfunction and primary non-function. In this study, we investigated the heterogeneity of different subpopulations of Urine-derived stem cells (USCs) to explore the most suitable cell subtype for treating severe steatotic liver IRI. Methods This study utilized scRNA-seq and Bulk RNA-seq to investigate the transcriptional heterogeneity between Spindle-shaped USCs (SS-USCs) and Rice-shaped USCs (RS-USCs). Additionally, rat fatty Liver transplantation (LT) model, mouse fatty liver IRI model, and Steatotic Hepatocyte Hypoxia-Reoxygenation (SHP-HR) model were constructed. Extracellular vesicles derived from SS-USCs and RS-USCs were isolated and subjected to mass spectrometry analysis. The therapeutic effects of Spindle-shaped USCs Exosomes (SS-USCs-Exo) and Rice-shaped USCs Exosomes (RS-USCs-Exo) were explored, elucidating their potential mechanisms in inhibiting ferroptosis and alleviating IRI. Results Multiple omics analyses confirmed that SS-USCs possess strong tissue repair and antioxidant capabilities, while RS-USCs have the potential to differentiate towards specific directions such as the kidney, nervous system, and skeletal system, particularly showing great application potential in renal system reconstruction. Further experiments demonstrated in vivo and in vitro models confirming that SS-USCs and SS-USCs-Exo significantly inhibit ferroptosis and alleviate severe fatty liver IRI, whereas the effects of RS-USCs/RS-USCs-Exo are less pronounced. Analysis comparing the proteomic differences between SS-USCs-Exo and RS-USCs-Exo revealed that SS-USCs-Exo primarily inhibit ferroptosis and improve cellular viability by secreting exosomes containing Glutathione Peroxidase 4 (GPX4) protein. This highlights the most suitable cell subtype for treating severe fatty liver IRI. Conclusions SS-USCs possess strong tissue repair and antioxidant capabilities, primarily alleviating ferroptosis in the donor liver of fatty liver through the presence of GPX4 protein in their exosomes. This highlights SS-USCs as the most appropriate cell subtype for treating severe fatty liver IRI.

Background: Emerging evidence suggests that peripheral immunoinflammatory responses contribute to Alzheimer’s disease (AD) pathogenesis, and endothelial cells (ECs) are involved in these responses. Nevertheless, the potential molecular mechanisms and signaling pathways by which ECs modulate peripheral immunoinflammatory responses and thus contribute to AD pathogenesis are not fully understood. Methods: The single-cell RNA sequencing dataset GSE157827 was analyzed, and AD key genes were screened using LASSO regression and random forest algorithms. Functional enrichment analyses of these AD key genes were conducted using gene set enrichment analysis (GSEA) and gene set variation analysis. Immune cell infiltration analyses for AD key genes were performed using single-sample GSEA, and their correlations with immunoinflammatory factors were assessed using the TISIDB database. Peripheral blood RNA sequencing data from our cohort were utilized to validate the expression patterns of EC-related AD key genes in peripheral blood and to investigate their association with cognition. Results: ECs are the most significant contributors to AD among all brain cell subpopulations. For the first time, the EC-related genes EIF1 and HSPA1B were identified as key genes associated with AD progression. These two EC-related key genes may participate in AD pathogenesis by modulating peripheral immunoinflammatory responses. The levels of EIF1 and HSPA1B were significantly altered in the peripheral blood during AD progression, and EIF1 levels correlated with cognitive functions in AD clinical continuum patients. Conclusions: These findings underscore the critical roles of the EC-related genes EIF1 and HSPA1B in AD pathogenesis and their potential as biomarkers for this disease.

Oral microbiota is the second largest microbial colony in the body and forms a complex ecological community that influences oral and brain health. Impaired homeostasis of the oral microbiota can lead to pathological changes, resulting in central nervous system (CNS) diseases. However, the mechanisms and clinical value of how the oral microbiome influences the brain remain unclear. This review summarizes recent clinical findings on the role of the oral microbiota in CNS diseases and proposes potential approaches to understand the way the oral microbiota and brain communicate. We propose three underlying patterns involving neuroinflammation, neuroendocrine regulation, and CNS signaling between oral microbiota and CNS diseases. We also summarize the clinical characteristics and potential utilization of the oral microbiota in ischemic stroke, Alzheimer's and Parkinson's disease, intracranial aneurysms, and mental disorders. Although the current findings are preliminary and clinical evidence is incomplete, oral microbiota is a potential biomarker for the clinical diagnosis and treatment of CNS diseases.

Background Epilepsy is one of the most prevalent neurological disorders, but no updated analysis of its burden in China. Aims This study provides the most up-to-date, comprehensive analysis of temporal trends and predicts future trends of idiopathic epilepsy in China. Design Secondary analysis based on the Global Burden of Disease (GBD). Methods GBD 2021 data were analyzed to estimate the incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALYs) of epilepsy in China across different genders, age groups, and years. Joinpoint regression and decomposition analysis assessed temporal changes and the contributions of aging, population growth, and epidemiological changes to disease trends. The Bayesian Age-Period-Cohort (BAPC) model was used to predict age-standardized rates (ASRs) per 100,000 individuals until 2044. Results In 2021, the ASRs of incidence, prevalence, deaths, and DALYs for epilepsy in China were 28.2 (95% uncertainty interval [UI]: 19.0–37.9), 214.7 (150.1–278.6), 0.8 (0.7–1.0), and 101.4 (72.5–139.4) per 100,000 population, respectively. The incidence and prevalence rates were 26.1% and 13.4% higher than those in 1990, while deaths and DALYs decreased by 56.6% and 43.2%, respectively, compared to 1990. The highest burden was seen in the youngest and older adults, with men more affected than women. Predictions indicate rising incidence and prevalence rates by 2044, alongside declining mortality and disability rates. Conclusion Epilepsy poses a significant health burden in China, with increasing incidence and prevalence from 1990 to 2021, and projections indicating a continued rise through 2044. The disease burden also varies across genders, age groups, and time periods.

Purpose To explore the structural basis of functional network connectivity (FNC) changes and early cortical degenerative patterns in subcortical vascular cognitive impairment (SVCI). Methods We prospectively included SVCI cases and healthy controls (HCs). FNC alterations were evaluated using group-independent component analysis of resting-state functional MRI data. Cortical microstructural and macrostructural alterations were assessed using gray matter-based spatial statistics analysis with neurite orientation dispersion and density imaging and cortical thickness analysis with FreeSurfer software on T1-weighted images, respectively. Spearman correlation analyses were performed to assess relationships between FNC alterations and cortical microstructural/macrostructural alterations and between FNC, cortical thickness, or neurite density index (NDI)/orientation dispersion index (ODI) alterations and cognitive performance. Results Forty-six SVCI patients and 73 HCs were recruited. FNC analysis showed lower network connectivity between the visual network (VN) and sensorimotor network (SMN) in SVCI, positively correlated with information processing speed (p=0.008) and negatively with summary SVD score (p = 0.037). Cortical microstructural analyses exhibited a lower NDI, mainly in the VN and default mode network (DMN) areas (PFWE < 0.05, cluster > 100 voxels), and lower ODI, mainly in the SMN and DMN areas (PFWE < 0.05, cluster > 100 voxels) in SVCI, both of which were related to cognitive function (p < 0.05). However, cortical thickness did not differ between groups. Lower NDI in the lateral occipital cortex was linked to lower VN-SMN connectivity in SVCI (p = 0.002). Conclusion Cortical microstructural alterations may serve as the basis for FNC changes in SVCI Graphical abstract

Solar-driven photothermal catalytic CO2 conversion into fuels offers a promising approach to reducing fossil fuel dependence. To enhance the efficiency of photothermal CO2 reduction, photothermal catalyst design must not only sustain the high temperatures required for the reaction but also effectively utilize the entire solar spectrum. In this study, we present a novel photothermal catalyst architecture BiVO4/Bi/BiOCl that surpasses traditional designs by integrating plasmonic metal Bi as the “hot spot” and BiOCl as the thermal insulation layer on the outermost part. This structure realizes thermal management, contributing to maintaining the high temperatures required for the reaction. The BiVO4/Bi/BiOCl multi-component system synergistically absorbs the full solar light spectrum and achieves band-division utilization: short- and mid-wavelengths drive reduction and oxidation reactions, respectively, while long-wavelengths induce the photothermal effect. The BiVO4/Bi/BiOCl catalyst demonstrates high-efficiency CO2 conversion performance in an outdoor concentrating system, achieving a CO production rate of 9.5 μmol/h. This work presents a design strategy for functional photothermal catalysts, making them viable candidates for industrial-scale CO2 conversion processes.