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 explore the effects of different education and examination methods on the examination results during the screening/evaluation of patent foramen ovale by contrast-enhanced transcranial Doppler(cTCD).Methods Patients who underwent cTCD screening/evaluation for patent foramen ovale in our hospital from May 2023 to February 2024 were retrospectively selected as the research subjects.The patients were divided into the observation group and the control group according to different education and examination methods during the peri-examination period.Patients who received video education,modified Valsalva maneuver,and injection of contrast agent with 20 mL syringe were included into the observation group,and patients who received artificial education,Valsalva maneuver,and injection of contrast agent with 10 mL syringe were included into the control group.The positive detection rate of patent foramen ovale,right-to-left shunt microbubble grading during Valsalva/modified Valsalva maneuver,systolic blood flow velocity,pulsatility index(PI),resistive index(RI),examination duration,total physician-patient communication time,whether occlusion surgery was performed,and patient satisfaction were compared between the two groups.Results The positive detection rate of patent foramen ovale by cTCD(82.93%vs.95.92%),the detection rate of the maximum amout(grade Ⅲ)of microbubbles(39.02%vs.61.22%),the total physician-patient communication time during the peri-examination period[11.30(10.00,14.00)minutes vs.8.23(7.00,10.00)minutes],the rate of occlusion surgery(48.78%vs.73.47%),and the total patient satisfaction(80.49%vs.91.84%)showed statistically significant differences between the control group and the observation group(P<0.05).Additionally,the receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC)for diagnosing patent foramen ovale were 0.718 in the control group and 0.855 in the observation group.Conclusion Peri-examination interventions such as video education,modified Valsalva maneuver,and injection of contrast agent with 20 mL syringe can improve the positive detection rate of patent foramen ovale,reduce ineffective physician-patient communication,and improve patient satisfaction.

Objective To investigate the application of a 3-D printed femoral locator designed based on the modified quadrant method,combined with patient imaging data,then assist in femoral positioning for anterior cruciate ligament(ACL)reconstruction.Methods From January 2023 to January 2024,60 patients with primary ACL rupture who met the inclusion criteria were randomly assigned to either the 3-D printed guide group(using a 3-D printed femoral positioning guide to assist ACL reconstruction with nylon material)or the traditional surgery group(traditional surgery with direct visualization ACL reconstruction),with 30 patients in each group.Preoperative and postoperative knee CT scans and three-dimensional reconstructions were performed.The modified quadrant method was used to analyze and compare the percentage coordinates(Fx and Fy)of the femoral tunnel center point pre-and postoperatively within the same group and between different groups.Results The guides were made using nylon material.The surgery duration was significantly shorter in the 3D-printed guide group(53.8±6.0)min compared to the traditional surgery group(62.4±7.8)min,the difference was statistically significant(P＜0.05).Analysis using the modified quadrant method showed that the postoperative relative coordinate position percentages of the femoral tunnel center in the 3D-printed guide group(28.4±2.0)％and(35.5±2.3)％were not significantly different from the preoperative planned values(28.4±0.0)％and(35.7±0.0)％,the differences were not statistically significant(P＞0.05).Similarly,in the traditional surgery group,the postoperative coordinate percentages(28.1±2.9)％and(35.2±3.2)％showed no significant difference compared to the preoperative planned values(28.4±0.0)％and(35.7±0.0)％,the differences were not statistically significant(P＞0.05).There was no statistically significant difference in the postoperative femoral tunnel center position percentages between the two groups(P＞0.05).The Lysholm score and International Knee Documentation Committee(IKDC)score of the two groups showed an increasing trend after surgery,and the differences between Lysholm score and IKDC score at each time point were statistically significant(P＜0.05).However,no statistical differences were found between the two groups at each postoperative time point(P＞0.05).Conclusion Both intra-articular 3D-printed guide-assisted and traditional surgery-assisted femoral positioning for ACL reconstruction can achieve anatomical reconstruction,with no significant difference in bone tunnel positioning.However,the use of intra-articular 3D-printed guide technology has a more centralized distribution of the femoral tunnel center point and a shorter surgery duration.This study provides proof of concept for the creation of personalized femoral tunnel locators for patients undergoing ACL reconstruction.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Objective To analyze the serum metabolomic changes of preterm infants with bronchopulmonary dysplasia(BPD)at postmenstrual age(PMA)36 weeks,screen potential biomarkers and associated metabolic pathways,and assess their relationship with short-term respiratory outcomes.Methods A retrospective case-control study was conducted.Infants with gestational age 28-32 weeks admitted to the Children's Hospital Affiliated to Zhengzhou University from January to December 2024 were included.Twenty infants with BPD and 20 gestational age-,birth weight-,and sex-matched non-BPD preterm infants were included.Serum collected at PMA 36 weeks was subjected to untargeted metabolomics analysis,and associations with short-term respiratory outcomes were analyzed.Results Thirteen potential biomarkers distinguishing BPD were identified(area under the curve>0.75,P<0.05).Eight biomarkers—including terephthalic acid,phosphatidylinositol,fumarate,and lysophosphatidic acid—were significantly upregulated(FC≥1.5),while five biomarkers,such as 7α-hydroxy-3-oxo-4-cholestenoate ester and phosphatidylcholine,were significantly downregulated(FC≤1/1.5).Pathway analysis indicated five pathways associated with BPD,including glycerophospholipid metabolism and phenylalanine metabolism.Dysregulation of glycerophospholipid and bile acid metabolism may affect adverse short-term respiratory outcomes in infants with BPD.Conclusions The 13 significantly different metabolites may serve as biomarkers for the diagnosis of BPD.Glycerophospholipid metabolism is associated with the occurrence of BPD and with adverse short-term respiratory outcomes.

Objective This study aimed to explore the clinical and etiological characteristics of bloodstream infections in diabetic patients with different levels of glycosylated hemoglobin(HbA1c)for improving empirical diagnosis and treatment in clinical practice.Methods A retrospective study was conducted for diabetic patients with bloodstream infections who were admitted to Sichuan Mental Health Center from 2017 to 2023.Patients were assigned to one of the three groups based on HbA1c levels:low level(HbA1c＜7.0％),medium level(7.0％≤HbA1c＜9.0％),high level(HbA1c≥9.0％).The clinical data,pathogen distribution,and antimicrobial resistance were analyzed and compared between groups.Results A total of 426 diabetic patients with bloodstream infection were included.The proportion of community-acquired bloodstream infection,acidosis,and liver abscess in the high level HbA1c group were significantly higher than those in the medium and low level HbA1c groups.Overall,452 strains of nonduplicate pathogenic bacteria were isolated,the most common of which were Escherichia coli(47.1％),Klebsiella pneumoniae(23.0％),and Staphylococcus aureus(5.8％).The pathogens of bloodstream infections varied with different HbA1c levels.The proportion of K.pneumoniae in the high-level HbA1c group(30.7％)was significantly higher than that in the low-level HbA1c group(15.1％)and medium level HbA1c group(16.0％).More than 50％of E.coli isolates were resistant to piperacillin,cefazolin,and ampicillin,while lower than 10％of the isolates were resistant to cefoxitin and minocycline,and lower than 1％of the isolates were resistant to piperacillin-tazobactam,meropenem,imipenem,and amikacin.The E.coli strains isolated from hospital-acquired infections showed slightly higher resistance rates to penicillin,cephalosporins,aminoglycosides,and fluoroquinolones than the strains isolated from community-acquired infections.K.pneumoniae strains showed low resistance rates(＜30％)to the commonly used antibiotics.However,the strains isolated from hospital-acquired infections were significantly more resistant to cephalosporins,carbapenems,and aminoglycosides than the strains isolated from community-acquired infections.Conclusions E.coli,K.pneumoniae and S.aureus were the common pathogens of bloodstream infections in diabetic patients.Poor HbA1c control was associated with K.pneumoniae bloodstream infection,especially those originated from liver abscess.The antibiotic-resistant E.coli and K.pneumoniae strains were prevalent in hospital-acquired bloodstream infections in diabetic patients.Antimicrobial resistance surveillance should be strengthened for this patient population.

Objective To analyze the serum metabolomic changes of preterm infants with bronchopulmonary dysplasia(BPD)at postmenstrual age(PMA)36 weeks,screen potential biomarkers and associated metabolic pathways,and assess their relationship with short-term respiratory outcomes.Methods A retrospective case-control study was conducted.Infants with gestational age 28-32 weeks admitted to the Children's Hospital Affiliated to Zhengzhou University from January to December 2024 were included.Twenty infants with BPD and 20 gestational age-,birth weight-,and sex-matched non-BPD preterm infants were included.Serum collected at PMA 36 weeks was subjected to untargeted metabolomics analysis,and associations with short-term respiratory outcomes were analyzed.Results Thirteen potential biomarkers distinguishing BPD were identified(area under the curve>0.75,P<0.05).Eight biomarkers—including terephthalic acid,phosphatidylinositol,fumarate,and lysophosphatidic acid—were significantly upregulated(FC≥1.5),while five biomarkers,such as 7α-hydroxy-3-oxo-4-cholestenoate ester and phosphatidylcholine,were significantly downregulated(FC≤1/1.5).Pathway analysis indicated five pathways associated with BPD,including glycerophospholipid metabolism and phenylalanine metabolism.Dysregulation of glycerophospholipid and bile acid metabolism may affect adverse short-term respiratory outcomes in infants with BPD.Conclusions The 13 significantly different metabolites may serve as biomarkers for the diagnosis of BPD.Glycerophospholipid metabolism is associated with the occurrence of BPD and with adverse short-term respiratory outcomes.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

The analysis presented here is based on the blood components of Guanxin Qiwei tablets, the key anti-atherosclerosis pathway of Guanxin Qiwei tablets was screened by network pharmacology, and the anti-atherosclerosis mechanism of Guanxin Qiwei tablets was clarified and verified by cell experiments. HPLC-Q-Exactive-MS/MS technique was used to analyze the components of Guanxin Qiwei tablets into blood, to determine the precise mass charge ratio of the compounds, and to conduct a comprehensive analysis of the components by using secondary mass spectrometry fragments and literature comparison. Finally, a total of 42 components of Guanxin Qiwei tablets into blood were identified. To better understand the interactions, we employed the Swiss Target Prediction database to predict the associated targets. Atherosclerosis (AS) disease targets were searched in disease databases Genecard, OMIM and Disgent, and 181 intersection targets of disease targets and component targets were obtained by Venny 2.1.0 software. Protein interactions were analyzed by String database. The 32 core targets were selected by Cytscape software. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed in DAVID database. It was found that the anti-atherosclerosis pathways of Guanxin Qiwei tablets mainly include lipid metabolism and atherosclerosis and AGE-RAGE signaling pathway in diabetic complications and other signal pathways. The core targets and the core compounds were interlinked, and it was found that cryptotanshinone and tanshinone ⅡA in Guanxin Qiwei tablets were well bound to TNF, PPARγ, AKT1, PTG2 and other targets. The lipid metabolism and atherosclerotic pathway was verified using human hl-7702 hepatocytes. This study preliminarily identified the potential pharmacodynamic components of Guanxin Qiwei tablets in the treatment of AS diseases and predicted their pathways of action, and verified the relationship between regulating lipid metabolism and atherosclerosis of Guanxin Qiwei tablets in vitro, providing a reference for the further study of the pharmacodynamic material basis and mechanism of action of this prescription. This experiment was approved by the Medical Ethics Committee of Inner Mongolia Medical University (No. YKD202401262).

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.