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.

ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

A combination of the "disease-syndrome-symptom" approach was used to study the syndrome characterization and features of dampness-heat obstruction syndrome in papain-induced knee osteoarthritis(KOA) model rats during the disease process. Forty-eight male SD rats were randomly divided into sham and model groups. The KOA model was established by injecting a mixture of papain and L-cysteine into the joint cavity on days 1, 3, and 5. During the 8 weeks following model establishment, the rats were assessed weekly for the plantar mechanical pain threshold, knee joint diameter, local skin temperature of the knee joint, weight-bearing difference between the two hind feet, and the modified Lequesne MG score of the knee joint. Samples were collected at 1, 2, 4, 6, and 8 weeks after model establishment to observe the gross lesions in cartilage and synovium. Histopathological changes in joint tissues were examined using hematoxylin-eosin, Masson's trichrome, and Senna red O-solid green staining. ELISA and immunohistochemical analysis were performed to detect the levels of interleukin(IL)-1β, IL-6, tumor necrosis factor(TNF)-α, prostaglandin E2(PGE2), and the expression of aquaporins(AQP) 1 and 3 in serum and synovium. The results showed that the ink score of articular cartilage in the model group significantly increased from 4 to 8 weeks, the cartilage Mankin's score and the percentage of Masson-positive area in cartilage increased significantly from 1 to 8 weeks. The percentage of red-stained area for cartilage proteoglycans decreased significantly from 1 to 8 weeks. The synovitis score from 1 to 6 weeks and the percentage of blue-stained collagen fibers in the synovium from 1 to 8 weeks increased significantly, with statistically significant differences compared to the sham group. The mechanical pain threshold in the model group significantly decreased from 1 to 8 weeks, the knee joint diameter significantly increased from 1 to 6 weeks, and the local skin temperature of the knee joint, the weight-bearing difference between the two hind feet, and the modified Lequesne MG score from 1 to 5 weeks significantly increased, all with statistically significant differences compared to the sham group. The levels of IL-1β, IL-6, TNF-α, and PGE2 in serum and synovium of the model group significantly increased from 1 to 6 weeks. Serum TNF-α and PGE2, and synovial IL-1β, also significantly increased at 8 weeks. The levels of cartilage AQP1 and AQP3 significantly increased from 1 to 4 weeks, while synovial AQP1 and AQP3 increased significantly from 1 to 6 weeks, with all differences statistically significant compared to the sham group. In conclusion, papain-induced KOA rats exhibited pathological changes, including articular cartilage degeneration and synovial inflammation, within 1 week of induction. The KOA rats showed characteristics of dampness-heat obstruction syndrome, such as joint pain, swelling, elevated skin temperature, and decreased function, as well as increased inflammatory factors and AQP1、AQP3 in serum and joint tissues within 5 to 6 weeks of disease onset. These results provide an experimental model for studying the syndromes of KOA with dampness-heat obstruction syndrome.
Animals ; Male ; Rats, Sprague-Dawley ; Rats ; Osteoarthritis, Knee/physiopathology* ; Disease Models, Animal ; Humans ; Interleukin-1beta/metabolism* ; Interleukin-6/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Knee Joint/pathology*

The aim of this study was to investigate the improvement effect of Wenpi Pills(WPP) on non-alcoholic fatty liver disease(NAFLD). The experiment was divided into two parts, using C57BL/6 mouse models induced by a high-fat diet(HFD) and a methionine and choline deficiency diet(MCD). The HFD-induced experiment lasted for 16 weeks, while the MCD-induced experiment lasted for 6 weeks. Mice in both parts were divided into four groups: control group, model group, low-dose WPP group(3.875 g·kg~(-1), WPP＿L), and high-dose WPP group(15.5 g·kg~(-1), WPP＿H). After sample collection from the HFD-induced mice, lipid content in the serum and liver, liver function indexes in the serum, and hepatic pathology were examined. Real-time fluorescent quantitative reverse transcription PCR(qRT-PCR) was used to detect the expression of lipid-related genes. After sample collection from the MCD-induced mice, serum liver function indexes and inflammatory factors were measured, and hepatic pathology and lipid changes were analyzed by hematoxylin-eosin(HE) staining and widely targeted lipidomic profiling, respectively. The results from the HFD-induced experiment showed that, compared with the HFD group, WPP administration significantly reduced the levels of aspartate aminotransferase(AST), alanine aminotransferase(ALT), triglyceride(TG), and total cholesterol(TC) in the serum, with the WPP＿H group showing the most significant improvement. HE staining results indicated that, compared with the HFD group, WPP treatment improved the morphology of white adipocytes, reducing their size, and alleviated hepatic steatosis and lipid droplet accumulation. The qRT-PCR results suggested that WPP might increase the mRNA expression of liver cholesterol-converting genes, such as liver X receptor α(LXRα) and cytochrome P450 family 27 subfamily A member 1(CYP27A1), as well as lipid consumption genes like peroxisome proliferator-activated receptor α(PPARα) and adenosine mono-phosphate-activated protein kinase(AMPK). Meanwhile, WPP decreased the mRNA expression of lipid synthesis genes, including fatty acid synthetase(FAS), stearoyl-CoA desaturase 1(SCD1), and sterol regulatory element-binding protein 1c(SREBP-1c), thereby reducing liver lipid accumulation. The results from the MCD-induced experiment showed that, compared with the MCD group, WPP administration reduced the levels of ALT, AST, and inflammatory factors in the serum, thereby alleviating liver injury and the inflammatory response. HE staining of liver tissue indicated that WPP effectively improved hepatic steatosis. Non-targeted lipidomics analysis showed that WPP improved lipid metabolism disorders in the liver, mainly by affecting the metabolism of TG and cholesterol esters. In conclusion, WPP can improve hepatic lipid accumulation in NAFLD mice induced by both HFD and MCD. This beneficial effect is primarily achieved by alleviating liver injury and inflammation, as well as regulating lipid metabolism.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Lipid Metabolism/drug effects* ; Mice ; Mice, Inbred C57BL ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Diet, High-Fat/adverse effects* ; Liver/drug effects* ; Humans ; Disease Models, Animal ; Methionine