ObjectivePost-ischemic acute inflammation and the subsequent persistent dysregulation of the immune microenvironment represent major pathological drivers that aggravate neuronal injury and severely restrict functional recovery following ischemic stroke. Although current reperfusion therapies partially restore blood flow, they fail to effectively modulate the secondary inflammatory cascade and oxidative stress, which remain critical barriers to neurological restoration. To address this challenge, this study aimed to engineer and systematically evaluate a biomimetic nanosystem composed of transforming growth factor-β1 (TGF-β1)-loaded platelet membrane-camouflaged lipid nanoparticles (PLP). This nanosystem was designed to achieve dual lesion-targeted delivery and immune microenvironment remodeling. By verifying its spatiotemporal accumulation, anti-inflammatory activity, and neuroprotective efficacy, we sought to establish an integrated therapeutic strategy that simultaneously enables lesion targeting, immune regulation, and functional recovery after ischemic injury. MethodsThe physicochemical properties of PLP, including hydrodynamic particle size, zeta potential, structural stability, and morphology, were characterized using dynamic light scattering, zeta potential analysis, and transmission electron microscopy. The preservation of platelet membrane-derived adhesion and immunoregulatory proteins was confirmed by SDS-PAGE through comparative analysis of protein band profiles between PLP and native platelet membranes. The in vitro biological activities of PLP were evaluated using two complementary cellular models. LPS-induced M1-polarized RAW264.7 macrophages were employed to assess inflammatory modulation, while oxygen glucose deprivation/reperfusion (OGD/R)-induced BV2 microglial cells and SH-SY5Y neuronal cells were utilized to investigate neuroinflammatory regulation and neuronal protection. For in vivo validation, a transient middle cerebral artery occlusion (tMCAO) mouse model was established to mimic ischemia-reperfusion injury. The spatiotemporal biodistribution and lesion-targeting capability of the PLP were monitored through live fluorescence imaging. Therapeutic efficacy was comprehensively evaluated by triphenyltetrazolium chloride (TTC) staining, glial fibrillary acidic protein (GFAP) immunofluorescence analysis, body weight monitoring, and neurological severity score (NSS) assessment. ResultsPLP nanoparticles displayed a uniform spherical morphology, nanoscale particle size distribution, and stable negative surface charge, indicating favorable colloidal stability and circulation potential. SDS-PAGE results confirmed the effective retention of key platelet membrane proteins associated with endothelial adhesion, immune evasion, and inflammatory regulation, demonstrating the successful biomimetic construction. Optimal therapeutic concentrations were determined in OGD/R-induced BV2 cells, where PLP exhibited excellent cytocompatibility and anti-inflammatory activity.In vitro experiments demonstrated that PLP significantly inhibited the polarization of RAW264.7 macrophages toward the pro-inflammatory M1 phenotype and markedly reduced neuronal apoptosis under ischemia-reperfusion conditions. In vivo fluorescence imaging revealed that PLP rapidly accumulated in the ischemic brain hemisphere and maintained prolonged retention for up to 7 d, suggesting enhanced lesion-specific targeting and sustained drug release. Compared with control group, PLP treatment significantly reduced cerebral infarct volume, attenuated reactive astrogliosis, improved weight recovery, and accelerated neurological functional restoration, as reflected by significantly improved NSS scores. ConclusionThis study establishes a multifunctional biomimetic nanoplatform that integrates platelet membrane-mediated active targeting with the anti-inflammatory, antioxidative, and neuroprotective properties of TGF-β1. The PLP system enables rapid lesion homing and long-term retention while synergistically regulating the post-stroke inflammatory microenvironment by suppressing pro-inflammatory immune activation, reducing neuronal apoptosis, and limiting excessive astrocyte reactivity. Importantly, this study proposes a conceptually therapeutic paradigm that combines targeted delivery with immune microenvironment remodeling to achieve comprehensive neurovascular protection. These findings provide strong experimental evidence supporting the translational potential of biomimetic nanotherapeutics as next-generation precision interventions for ischemic stroke.

Abstract To clarify the service targets, service contents, and safeguard mechanisms of the basic public service program for student vision health management, the study grounded in the current status of child and adolescent myopia prevention and control in China and integrated with the practical experience and innovative practices of Wuhan National Demonstration Area for Student Vision Health Management, takes education as the main thread and schools as the base, consolidating resources from multiple stakeholders including education administrative departments, schools, families, and professional technical service institutions. Centering on four core components—vision health education, monitoring and record keeping, risk prevention and control, and dynamic management, the study constructs a multi tiered basic public service system for vision health management of primary and secondary school students. It further proposes the use of an intelligent management platform and a "three tier color coded early warning" mechanism (red, yellow, blue) to prevent and control student myopia at the source, providing schools with replicable and operable implementation pathways to enhance the level of student vision health management.

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Objective:To investigate the application value of multi-parameter ultrasound in the non-invasive assessment of renal fibrosis in patients with chronic kidney disease（CKD）.Methods:From December 2023 to April 2024，77 CKD patients（CKD group）and 30 healthy individuals（control group）from Renmin Hospital of Wuhan University were prospectively collected. The CKD group was further classified into mild（ n = 30），moderate（ n = 25）and severe（ n = 22）groups according to pathological assessment of renal fibrosis. Ultrasound parameters and clinical data of all patients were collected for group comparisons. Ultrasound parameters that showed statistically significant differences in univariate analysis were incorporated into a Logistic regression model to identify independent influencing factors. ROC curve was constructed，and the area under the curve（AUC）was calculated for statistical evaluation. Results:① The moderate and severe groups compared to control group，as well as the severe group compared to the mild and moderate groups，showed increased levels of SCr and BUN，and decreased level of eGFR，with statistically significant differences（all P < 0.05）. The kidney length and renal parenchymal thickness in the moderate group were smaller than those in the control group，while the kidney length，renal parenchymal thickness，and renal cortical thickness in the severe group were smaller than those in the control，mild，and moderate groups，with statistically significant differences among the groups（all P < 0.05）. The Vmax in the severe group was lower than those in the control，mild，and moderate groups，while the RI was higher than those in the control，mild，and moderate groups，with statistically significant differences（all P < 0.05）. ②In superb microvascular imaging，perfusion levels were predominantly grade 5 in the control and mild groups（83.3%，25/30；70.0%，21/30），grade 4 in the moderate group（48.0%，12/25），and grade 3 in the severe group（63.6%，14/22）. No significant differences were observed between the mild and control groups，or between the moderate and severe groups（all P>0.05），significant differences in blood flow perfusion were found between other groups（ P < 0.05）.③Shear wave elastography and super-resolution imaging revealed that mean of Young's modulus（Emean）in renal cortex increased progressively from the mild to the severe group，while microvascular density decreased. Except for Emean，which did not show significant differences between the moderate and severe groups（ P > 0.05），all other parameters showed significant differences between groups（ P < 0.05）. ④ROC curve analysis indicated that differentiating the control group from the mild group using Emean and microvascular density，the AUC was 0.769（95% CI = 0.631 - 0.872， P<0.001），with a sensitivity of 0.821 and specificity of 0.539. For the combined use of Emean，microvascular density，peak inter-arterial velocity，and resistance index for distinguishing mild from moderate-to-severe fibrosis resulted in an AUC of 0.902（95% CI = 0.843 - 0.972，P < 0.001），with a sensitivity of 0.967 and specificity of 0.755. These multi-parameter combined diagnostic approaches outperformed single ultrasound parameters. Conclusions:Multi-parameter ultrasound technology can display multidimensional renal changes in patients with CKD and effectively assess the degree of renal fibrosis. It is expected to become a non-invasive，highly sensitive tool for evaluating renal fibrosis in CKD.

To evaluate the efficacy and safety of dye-free submucosal injection solution for gastric endoscopic submucosal dissection (ESD), a retrospective cohort study was performed on data of inpatients with early gastric cancer and precancerous lesions who underwent ESD at the Digestive Endoscopy Center of Jiangsu Province Hospital of Traditional Chinese Medicine from January to December 2020. Cases were divided into dye-free submucosal injection solution group (the observation group) and dye-containing solution group (the control group). A total of 108 cases met the eligibility criteria for analysis (39 VS 69). Baseline characteristics were comparable between the two groups ( P>0.05). Compared with the control group, the observation group showed similar median procedure time (30.5 min VS 35.0 min), median dissection speed (0.3 cm2/min VS 0.4 cm2/min), mean volume of injection solution used (39.2 mL VS 38.8 mL), en bloc resection rate [100.0% (39/39) VS 98.6% (68/69)], and curative resection rate [97.4% (38/39) VS 97.1% (67/69)] (all P>0.05). Postoperative stay was 3.0±0.8 days in the observation group and 3.2±0.8 days in the control group ( t=-0.908, P=0.378). Delayed bleeding occurred in 3 (7.7%) patients VS 2 (2.9%) patients ( P=0.349), and postoperative infection occurred in 3 (7.7%) patients VS 8 (11.6%) patients ( P=0.743), respectively. In gastric ESD, dye-free submucosal injection solution demonstrates efficacy comparable with dye-containing solution and does not appreciably increase the incidence of intraoperative or postoperative complications.

Objective To observe the clinical effect of pressing needle in preventing and reducing nausea and vomiting in patients after gynecological laparoscopic surgery.Methods A total of 199 patients undergoing gynecological laparoscopic surgery from May to Nov 2023 at Obstetrics and Gynecology Hospital,Fudan University were randomly divided into research group(n=99)and control group(n=100).The observation group was given Tanzhong,zanzhu and Taichong pressing needles on the basis of the control group.The postoperative nausea and vomiting were observed in the two groups.Results There were significant differences in the incidence and duration of postoperative nausea,the incidence of postoperative vomiting between the two groups(P<0.05),but there was no significant difference in the duration of postoperative vomiting.The incidence of nausea and vomiting in the observation group was lower than that in the control group.Conclusion Pressing needle can effectively prevent the occurrence of nausea and vomiting after gynecological laparoscopic surgery,and reduce the degree of nausea and vomiting,and reduce the duration of nausea.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents