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.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To explore the factors associated with complete resolution of sentinel lymph node metastasis(pCR)after neoadjuvant chemotherapy in breast cancer and to establish a predictive model.Methods The medical records of 136 female patients with breast cancer who received neoadjuvant chemotherapy in the First Hospital of Lanzhou University from January 2022 to February 2024 were retrospectively analyzed.According to the 80/20 rule,the patients were randomly divided into a training set(108 cases)and a validation set(28 cases).Based on the pathological examination results of axillary lymph node dissection(ALND)after neoadjuvant chemotherapy in breast cancer patients,they were classified into the sentinel lymph node pCR group and non-pCR group.Multivariate logistic regression analysis was used to screen the independent risk factors of sentinel lymph nodes failing to reach pCR.Build a nomogram prediction model based on the screened risk factors.By drawing the receiver operating characteristic(ROC)curve calculation curve,the area under ROC curve,sensitivity and specificity are used to evaluate the discrimination of the model.Results Among the 108 breast cancer patients,46 cases achieved pCR in the sentinel lymph nodes,accounting for 42.59％(46 cases/108 cases).In addition,33 cases(30.56％)achieved pCR in the primary tumor lesion.The non-pCR group showed a higher proportion of stage Ⅲ clinical staging,lymph node short-axis reduction of less than 50％before and after treatment,tumor maximum diameter reduction of less than 50％before and after treatment,lymph node type Ⅲ classification,and blood flow grade Ⅲ compared to the pCR group(P＜0.05).Multivariate logistic regression analysis showed that Clinical staging(OR=3.593,95％CI:1.276-10.121),lymph node short-axis reduction of less than 50％before and after treatment(OR=4.272,95％CI:1.517-12.032),tumor maximum diameter reduction of less than 50％before and after treatment(OR=3.710,95％CI:1.317-10.449),lymph node type(OR=3.827,95％CI:1.359-10.779),and blood flow grade(OR=4.764,95％CI:1.691-13.418)were identified as risk factors for not achieving pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in breast cancer patients(P＜0.05).The sensitivity of the risk model for predicting non-achievement of pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in the training set of breast cancer patients was 0.826(95％CI:0.705-0.943),with a specificity of 0.826(95％CI:0.712-0.919)and an area under the ROC curve of 0.847(95％CI:0.738-0.952).In the validation set,the sensitivity for predicting non-achievement of pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in breast cancer patients was 0.731(95％CI:0.608-0.904),with a specificity of 0.827(95％CI:0.713-0.941)and an area under the ROC curve of 0.834(95％CI:0.729-0.951).Conclusion Clinical staging,changes in lymph node short-axis before and after treatment,changes in tumor maximum diameter before and after treatment,lymph node type,and blood flow grade are associated with pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in breast cancer patients.Constructing a predictive model can help evaluate the pCR status of sentinel lymph nodes after neoadjuvant chemotherapy.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To explore the factors associated with complete resolution of sentinel lymph node metastasis(pCR)after neoadjuvant chemotherapy in breast cancer and to establish a predictive model.Methods The medical records of 136 female patients with breast cancer who received neoadjuvant chemotherapy in the First Hospital of Lanzhou University from January 2022 to February 2024 were retrospectively analyzed.According to the 80/20 rule,the patients were randomly divided into a training set(108 cases)and a validation set(28 cases).Based on the pathological examination results of axillary lymph node dissection(ALND)after neoadjuvant chemotherapy in breast cancer patients,they were classified into the sentinel lymph node pCR group and non-pCR group.Multivariate logistic regression analysis was used to screen the independent risk factors of sentinel lymph nodes failing to reach pCR.Build a nomogram prediction model based on the screened risk factors.By drawing the receiver operating characteristic(ROC)curve calculation curve,the area under ROC curve,sensitivity and specificity are used to evaluate the discrimination of the model.Results Among the 108 breast cancer patients,46 cases achieved pCR in the sentinel lymph nodes,accounting for 42.59％(46 cases/108 cases).In addition,33 cases(30.56％)achieved pCR in the primary tumor lesion.The non-pCR group showed a higher proportion of stage Ⅲ clinical staging,lymph node short-axis reduction of less than 50％before and after treatment,tumor maximum diameter reduction of less than 50％before and after treatment,lymph node type Ⅲ classification,and blood flow grade Ⅲ compared to the pCR group(P＜0.05).Multivariate logistic regression analysis showed that Clinical staging(OR=3.593,95％CI:1.276-10.121),lymph node short-axis reduction of less than 50％before and after treatment(OR=4.272,95％CI:1.517-12.032),tumor maximum diameter reduction of less than 50％before and after treatment(OR=3.710,95％CI:1.317-10.449),lymph node type(OR=3.827,95％CI:1.359-10.779),and blood flow grade(OR=4.764,95％CI:1.691-13.418)were identified as risk factors for not achieving pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in breast cancer patients(P＜0.05).The sensitivity of the risk model for predicting non-achievement of pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in the training set of breast cancer patients was 0.826(95％CI:0.705-0.943),with a specificity of 0.826(95％CI:0.712-0.919)and an area under the ROC curve of 0.847(95％CI:0.738-0.952).In the validation set,the sensitivity for predicting non-achievement of pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in breast cancer patients was 0.731(95％CI:0.608-0.904),with a specificity of 0.827(95％CI:0.713-0.941)and an area under the ROC curve of 0.834(95％CI:0.729-0.951).Conclusion Clinical staging,changes in lymph node short-axis before and after treatment,changes in tumor maximum diameter before and after treatment,lymph node type,and blood flow grade are associated with pCR in the sentinel lymph nodes after neoadjuvant chemotherapy in breast cancer patients.Constructing a predictive model can help evaluate the pCR status of sentinel lymph nodes after neoadjuvant chemotherapy.

Objective:To investigate the protective effect of achyranthes bidentata(AB)on sperm quality in mice with sper-matogenic disorder through the glycolytic metabolic pathway and its action mechanism.Methods:We equally randomized 40 Kun-ming mice into a normal control,a model control,a low-dose AB(3.5 g/kg)and a high-dose AB group(7.0 g/kg),and established the model of spermatogenic disorder in the latter three groups of mice by intraperitoneal injection of doxorubicin(30 mg/kg).Two days after modeling,we collected the testis and kidney tissues and blood samples from the mice for observation of the pathological changes in the testis tissue by HE staining,detection of perm motility with the sperm quality analyzer,examination of the apoptosis of testis cells by flow cytometry,measurement of the levels of testosterone(T),malondialdehyde(MDA),superoxide dismutase(SOD)and cata-lase(CAT)in the serum and testis tissue by ELISA,and determination of expressions of the key enzymes of glycolysis hexokinase Ⅱ(HK2),pyruvate kinase M2(PKM2),platelet phosphofructokinase(PFKP),lactate dehydrogenase A(LDHA)and the meiosis pro-teins REC8 and SCP3 by Western blot,and the mRNA expressions of glycolytic phosphofructokinase 1(PFK1),phosphoglycerate ki-nase 1(PGK1),tumor necrosis factor-α(TNF-α)and interleukin-1 β(IL-1β)by fluorescence quantitative PCR(FQ-PCR).Results:Compared with the model controls,the mice in the AB groups showed significant increases in the testis coefficient,kidney in-dex,sperm concentration,sperm motility,spermatogonia,primary spermatocytes,spermatids,sperm count and the serum T level(P＜0.05 orP＜0.01),but dramatic decreases in the apoptosis of testis cells and percentage of morphologically abnormal sperm(P＜0.01).Achyranthes bidentata also significantly elevated the levels of SOD and CAT,and down-regulated the mRNA expressions of MDA,TNF-α and IL-1β(P＜0.05 or P＜0.01),and up-regulated the protein expressions of HK2,PKM2,PFKP,LDHA,REC8 and SCP3,and expressions of the glycolysis key genes Pfk1 and Pgk1(P＜0.05 orP＜0.01).Conclusion:Achyranthes bidentata ameliorates doxorubicin-induced spermatogenic disorder in mice by regulating the glycolytic pathway and reducing oxidative stress and the expressions of inflammatory factors.

Objective:To investigate the efficacy and safety of transurethral water vapor thermal therapy(WVTT)using the Rezūm system for benign prostatic hyperplasia(BPH)in the real world.Methods:A total of 181 patients with BPH were recruited from the Second Affiliated Hospital of Nanjing Medical University from August 2022 to December 2023,of whom 173 patients were treated with WVTT using the Rezūm system,while 8 patients were treated with WVTT combined with TURP.They were followed up at 1,3,and 6 months postoperatively to assess changes in the IPSS,QoL,Qmax,IIEF-5,and the occurrence of any complications.Results:All 181 surgeries in this group were successfully completed.The operation time of the Rezūm system was(4.6±1.4)mi-nutes.The postoperative indwelling catheterization time was(8.0±2.1)days.With a follow-up of at least 6 months,there was a significant decrease in PV,IPSS and QoL,and a remarkable increase had been found in Qmax as well(P＜0.05).There was no sig-nificant difference in IIEF-5 before and after the operation(P＞0.05).In this groups of patients,postoperative complications mainly included 95 cases(52.5％)of gross hematuria,6 cases(3.3％)of retrograde ejaculation,5 cases(2.8％)of urethral stricture,4 cases(2.2％)of prostatitis,and 10 cases(5.5％)of urinary tract infection.Four cases(2.2％)underwent surgical retreatment for BPH after surgery.Conclusion:In the real world,the use of Rezūm thermal steam ablation system for the treatment of BPH has sat-isfactory short-term effect,short surgical time,and significant improvement in IPSS,QoL,Qmax,which does not adversely affect sexu-al function.

Objective:Previous studies have shown that insomnia is closely related to erectile dysfunction(ED).However,the causal relationship between them is still unclear.Mendelian randomization(MR)provides a new method for studying the relationship between the two,and the theory of heart-kidney interaction in TCM provides a new idea for exploring the causal relationship between them.Methods:Based on the statistical data collected by genome-wide association studies(GWAS),the causal relationship be-tween insomnia and ED was discussed by MR.Inverse variance weighted(IVW)is the main analysis method,and weighted median(WME),simple mode(SM),weighted mode(WM)and MR Egger method were the supplementary analysis to evaluate the causal effect.MR-Egger intercept test,Cochran Q test and leave-one-out method were used in sensitivity analysis to verify the reliability of MR results.Results:Thirty-nine SNPs significantly related to insomnia were finally included for MR analysis.The results of IVW method in MR analysis showed that insomnia had a significant causal relationship with the increased risk of ED(OR=3.111,95％CI=1.566-6.181,P=1.193 × 10-3).The results obtained by MR-Egger method,WME method,WM method and SM method were consistent with IVW method in the direction of effect.The sensitivity results suggested that the results of this study were robust.Conclusion:Our study reveals the causal relationship between insomnia and ED,which provides a new basis for future clinical practice and prevention and treatment of ED.

Numerous c-mesenchymal-epithelial transition (c-MET) inhibitors have been reported as potential anticancer agents. However, most fail to enter clinical trials owing to poor efficacy or drug resistance. To date, the scaffold-based chemical space of small-molecule c-MET inhibitors has not been analyzed. In this study, we constructed the largest c-MET dataset, which included 2,278 molecules with different structures, by inhibiting the half maximal inhibitory concentration (IC₅₀) of kinase activity. No significant differences in drug-like properties were observed between active molecules (1,228) and inactive molecules (1,050), including chemical space coverage, physicochemical properties, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles. The higher chemical diversity of the active molecules was downscaled using t-distributed stochastic neighbor embedding (t-SNE) high-dimensional data. Further clustering and chemical space networks (CSNs) analyses revealed commonly used scaffolds for c-MET inhibitors, such as M5, M7, and M8. Activity cliffs and structural alerts were used to reveal "dead ends" and "safe bets" for c-MET, as well as dominant structural fragments consisting of pyridazinones, triazoles, and pyrazines. Finally, the decision tree model precisely indicated the key structural features required to constitute active c-MET inhibitor molecules, including at least three aromatic heterocycles, five aromatic nitrogen atoms, and eight nitrogen-oxygen atoms. Overall, our analyses revealed potential structure-activity relationship (SAR) patterns for c-MET inhibitors, which can inform the screening of new compounds and guide future optimization efforts.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome