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.

Objectives: . The prognostic value of the pretreatment albumin-to-alkaline phosphatase ratio (AAPR) in head and neck cancer (HNC) remains uncertain. This meta-analysis aimed to evaluate the predictive role of AAPR for survival outcomes in patients with HNC. Methods: . A comprehensive search of the Cochrane Library, PubMed, and Embase databases was conducted to identify relevant studies published up to July 30, 2024. We included studies on AAPR and survival outcomes in HNC patients. Results: . Eight studies comprising 1,737 HNC patients were analyzed using random-effects models. Lower AAPR values were significantly correlated with worse overall survival (hazard ratio [HR], 2.08), progression-free survival (HR, 2.00), and disease-free survival (HR, 2.18). Sensitivity analyses confirmed the robustness of these results, with no significant publication bias detected. Conclusion . Our findings suggest that pretreatment AAPR could serve as a valuable and cost-effective prognostic indicator in HNC, potentially aiding clinicians in risk stratification and treatment decision-making. However, additional validation studies are warranted to confirm its clinical applicability.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

Background/Aims: Endoscopic radiofrequency ablation (ERFA) is a treatment option for superficial esophageal squamous cell neoplasia (ESCN), with a relatively low risk of stenosis; however, the long-term outcomes remain unclear. We aimed to compare the long-term outcomes of patients with widespread superficial ESCN who underwent endoscopic submucosal dissection (ESD) or ERFA. Methods: We retrospectively analyzed the clinical data of patients with superficial ESCN who underwent ESD or ERFA between January 2015 and December 2021. The primary outcome measure was recurrence-free survival. Results: Ninety-two and 33 patients with superficial ESCN underwent ESD and ERFA, respectively. The en bloc, R0, and curative resection rates for ESD were 100.0%, 90.2%, and 76.1%, respectively. At 12 months, the complete response rate was comparable between the two groups (94.6% vs 90.9%, p=0.748). During a median follow-up of 66 months, recurrence-free survival was significantly longer in the ESD group than in the ERFA group (p=0.004), while no significant differences in overall survival (p=0.845) and disease-specific survival (p=0.494) were observed.Preoperative diagnosis of intramucosal cancer (adjusted hazard ratio, 5.55; vs high-grade intraepithelial neoplasia) was an independent predictor of recurrence. Significantly fewer patients in the ERFA group experienced stenosis compare to ESD group (15.2% vs 38.0%, p=0.016). Conclusions The risk of recurrence was higher for ERFA than ESD for ESCN but overall survival was not affected. The risk of esophageal stenosis was significantly lower for patients who underwent ERFA.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

This comprehensive review systematically explores the multifaceted applications, inherent challenges, and promising future directions of artificial intelligence (AI) within the medical domain. It meticulously examines AI's specific contributions to basic medical research, disease prevention, intelligent diagnosis, treatment, rehabilitation, nursing, and health management. Furthermore, the review delves into AI's innovative practices and pivotal roles in clinical trials, hospital administration, medical education, as well as the realms of medical ethics and policy formulation. Notably, the review identifies several key challenges confronting AI in healthcare, encompassing issues such as inadequate algorithm transparency, data privacy concerns, absent regulatory standards, and incomplete risk assessment frameworks. Looking ahead, the future trajectory of AI in healthcare encompasses enhancing algorithm interpretability, propelling generative AI applications, establishing robust data-sharing mechanisms, refining regulatory policies and standards, nurturing interdisciplinary talent, fostering collaboration among industry, academia, and medical institutions, and advancing inclusive, personalized precision medicine. Emphasizing the synergy between AI and emerging technologies like 5G, big data, and cloud computing, this review anticipates a new era of intelligent collaboration and inclusive sharing in healthcare. Through a multidimensional analysis, it presents a holistic overview of AI's medical applications and development prospects, catering to researchers, practitioners, and policymakers in the healthcare sector. Ultimately, this review aims to catalyze the deep integration and innovative deployment of AI technology in healthcare, thereby driving the sustainable advancement of smart healthcare.

During orthodontic treatment, clinical monitoring of patients is a crucial factor in determining treatment success. It aids in timely problem detection and resolution, ensuring adherence to the intended treatment plan. In recent years, digital technology has increasingly permeated orthodontic clinical diagnosis and treatment, facilitating clinical decision-making, treatment planning, and follow-up monitoring. This review summarizes recent advancements in digital technology for monitoring orthodontic tooth movement, related complications, and appliance-wearing compliance. It aims to provide insights for researchers and clinicians to enhance the application of digital technology in orthodontics, improve treatment outcomes, and optimize patient experience. The digitization of diagnostic data and the visualization of dental models make chair-side follow-up monitoring more convenient, accurate, and efficient. At the same time, the emergence of remote monitoring technology allows orthodontists to promptly identify oral health issues in patients and take corresponding measures. Furthermore, the multimodal data fusion method offers valuable insights into the monitoring of the root-alveolar relationship. Artificial intelligence technology has made initial strides in automating the identification of orthodontic tooth movement, associated complications, and patient compliance evaluation. Sensors are effective tools for monitoring patient adherence and providing data-driven support for clinical decision-making. The application of digital technology in orthodontic monitoring holds great promise. However, challenges like technical bottlenecks, ethical considerations, and patient acceptance remain.

Objective To analyze the characteristics of adverse drug reactions （ADR） reported in Sixth People’s Hospital South Campus, Shanghai Jiaotong University from 2021 to 2023, to provide reference for promoting rational clinical drug use. Methods ADR data reported in our hospital were collected retrospectively, including patients’ basic information, drugs causing adverse reactions, types of adverse reactions and outcomes. Descriptive analysis methods were used to summarize and analyze the data. Results A total of 979 cases of ADR were reported in our hospital from 2021 to 2023. The highest proportion of patients with ADR occurred in the age range of 31 to 50, and more male patients （63.5%）. The top five drugs involved with adverse reactions were antibiotics （48.8%）, Chinese medicine injections（19.2%）, vitamins（7.5%）, Chinese traditional medicine（7.2%）, equine tetanus immunoglobulin（6.3%）. Among antibiotics, cefuroxime, ceftazidime and cefotiam were the majority. The organs/systems involved in all ADR were mainly skin and accessories damage （55.4%）. The clinical manifestations were rash, itching, and maculopapular rash. Conclusion From 2021 to 2023, the most common drugs causing adverse drug reactions in our hospital were mainly antibacterial drugs, and the rational clinical use of antibacterial drugs still needs to be concerned.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.