ObjectiveAbnormal lipids in neurons can cause the accumulation of α-synuclein（α-syn）. This study aimed to explore the mechanism of Acanthopanacis Senticosi Radix et Rhizoma seu Caulis extract （ASH） in treating Parkinson's disease （PD） mice using lipidomics combined with network pharmacology. MethodsMice were divided into the blank group， model group and ASH （45.5 mg·kg^-1） group. Motor ability was evaluated by pole climbing time and autonomous activity count； The oxidative stress indicators were detected by enzyme-linked immunosorbent assay （ELISA）. Lipid biomarkers in brain tissues were screened and identified by ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）， and metabolic pathway analysis was conducted. The key targets of ASH for PD treatment were explored using network pharmacology. The Kyoto Encyclopedia of Genes and Genomes （KEGG） database was used for pathway enrichment analysis， and the "compound-reaction-enzyme-gene" network was constructed using the MetScape plugin. The protein expression levels of glutathione S-transferase P1 （GSTP1）， glutathione S-transferase Mu 2 （GSTM2）， prostaglandin peroxide synthase 1 （PTGS1）， prostaglandin peroxide synthase 2 （PTGS2）， and prostaglandin E synthase （PTGES） were validated by Western blot. ResultsCompared with the blank group， the model group showed significantly prolonged pole climbing time and reduced autonomous activity count （P<0.01）. Compared with the model group， the ASH group demonstrated significantly faster pole climbing and increased autonomous activity count （P<0.01）. The model group exhibited significantly decreased superoxide dismutase （SOD） and glutathione peroxidase （GSH-Px） levels， and increased malondialdehyde （MDA） level in brain tissues compared with the blank group （P<0.01）. The ASH group showed increased SOD and GSH-Px levels and decreased MDA level compared with the model group （P<0.05， P<0.01）. Lipidomics analysis identified 10 differential metabolites and 8 differential metabolic pathways. Network pharmacological analysis revealed 213 intersection targets between ASH components and PD， with KEGG enrichment involving the sphingolipid signaling pathway， lipid arteriosclerosis， phosphoinositide 3-kinase/protein kinase B（PI3K/Akt） signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway， and hypoxia inducible factor-1（HIF-1） signaling pathway. Integrated lipidomics and network pharmacology analysis highlighted the central role of the arachidonic acid metabolic pathway. The Western blot results showed that ASH effectively up-regulated GSTP1， GSTM2， and PTGS1 protein expression， and down-regulated PTGS2 and PTGES protein expression. ConclusionASH can ameliorate behavioral deficits， exert antioxidant effects， regulate lipid differential metabolites and the arachidonic acid metabolic pathway， thereby exerting therapeutic effects in PD model mice.

Objective To investigate the perioperative safety of patients with myasthenia gravis who take high doses of oral glucocorticoids. Methods A retrospective analysis was conducted on the clinical data of patients with myasthenia gravis who received oral glucocorticoids and underwent thoracoscopic thymectomy at the Department of Thoracic Surgery, the University of Hong Kong-Shenzhen Hospital from April 2013 to October 2019. Patients were divided into a high-dose steroid group and a medium-to-low dose steroid group based on the dosage of oral steroids, and the clinical data of the two groups were compared. Results A total of 102 patients were included, including 19 (18.62%) males and 83 (81.37%) females, with an average age of (32.25±9.83) years. There were 75 patients in the medium-to-low dose steroid group and 27 patients in the high-dose steroid group. All patients in both groups successfully completed the surgery without major intraoperative bleeding, conversion to open chest surgery, delayed extubation, severe infection, or perioperative death. The daily oral steroid dose for the high-dose steroid group was (35.81±4.29) mg, and for the medium-to-low dose steroid group it was (15.29±2.17) mg. There was no statistical difference in the operation time [(124.69±23.51) min vs. (117.89±21.46) min, P=0.172] and intraoperative blood loss [(21.19±3.48) mL vs. (20.56±3.41) mL, P=0.419] between the two groups. Postoperatively, 12 (11.76%) patients developed complications: one patient of myasthenic crisis (the medium-to-low dose steroid group), which was improved after short-term respiratory support and intravenous immunoglobulin treatment; 11 patients of respiratory/swallowing difficulties (9 in the medium-to-low dose steroid group and 2 in the high-dose steroid group), which were improved after anticholinergic treatment to reduce oral secretions and sputum suction, and the patients were discharged smoothly. There was no statistical difference in the incidence of postoperative complications between the two groups (P=0.637). Conclusion On the basis of good perioperative management, it is safe and feasible for patients with myasthenia gravis who take high dose of oral steroids to undergo thymectomy, and they have the same perioperative safety as patients with medium-to-low dose steroids.

Metabolic dysfunction-associated fatty liver disease （MAFLD）， as one of the most common chronic liver diseases in the world， poses a severe challenge to precision diagnosis and treatment due to its complex pathogenesis and highly heterogeneous disease progression. Existing clinical classification systems cannot meet the needs for comprehensively analyzing the complexity of the disease and the heterogeneity of its adverse outcomes. In recent years， data-driven prognostic risk classification methods have gradually emerged， optimizing the ability for predicting adverse outcomes and enhancing the accuracy of identifying different endpoint outcomes. However， such paradigm of “classify first， associate outcomes later” suffers from a “black-box” nature， and there are various indicators for classification， leading to limited stability and generalizability in clinical application. Future research needs to integrate or establish large-scale population cohorts， develop outcome-oriented prognostic risk classification models， incorporate dynamic data， refine classification algorithms， and validate their generalizability across multiple populations， thereby providing reliable support for the precision diagnosis and treatment of MAFLD.

Metastatic dissemination is the major cause of death from breast-cancer (BC). Fusobacterium nucleatum (F.n) is widely enriched in BC and has recently been identified as one of the high-risk factors for promoting BC metastasis. Here, with an experimental model, we demonstrated that intratumoral F.n induced BC aggressiveness by transcriptionally activating Epithelial-mesenchymal transition-associated genes. Therefore, the F.n may be a potential target to prevent metastasis. Given the fact that cancer-associated fibroblasts (CAFs) are abundant in BC and located near blood vessels, we report an optogenetic system that drives CAF to in situ produce human antibacterial peptide LL37, with the characteristics of biosafety and freely intercellular trafficking, for depleting intratumoral F.n, leading to a 72.1% reduction in lung metastatic nodules number without affecting the balance of the systemic flora. Notably, mild photothermal treatment was found that could normalize CAF, contributing to synergistically inhibiting BC metastasis. In addition, the system can also simultaneously encode a gene of TNF-related apoptosis-inducing ligand to suppress the primary tumor. Together, our study highlights the potential of local elimination of tumor pathogenic bacteria to prevent BC metastasis.

Approximately 20% to 30% of the global workforce is engaged in shift work. As a significant cause of circadian disruption, shift work is closely associated with an increased risk for periodontitis. Nevertheless, how shift work-related circadian disruption functions in periodontitis remains unknown. Herein, we employed a simulated shift work model constructed by controlling the environmental light-dark cycles and revealed that shift work-related circadian disruption exacerbated the progression of experimental periodontitis. RNA sequencing and in vitro experiments indicated that downregulation of the core circadian protein brain and muscle ARNT-like protein 1 (BMAL1) and activation of the Gasdermin D (GSDMD)-mediated pyroptosis were involved in the pathogenesis of that. Mechanically, BMAL1 regulated GSDMD-mediated pyroptosis by suppressing NOD-like receptor protein 3 (NLRP3) inflammasome signaling through modulating nuclear receptor subfamily 1 group D member 1 (NR1D1), and inhibiting Gsdmd transcription via directly binding to the E-box elements in its promoter. GSDMD-mediated pyroptosis accelerated periodontitis progression, whereas downregulated BMAL1 under circadian disruption further aggravated periodontal destruction by increasing GSDMD activity. And restoring the level of BMAL1 by circadian recovery and SR8278 injection alleviated simulated shift work-exacerbated periodontitis via lessening GSDMD-mediated pyroptosis. These findings provide new evidence and potential interventional targets for circadian disruption-accelerated periodontitis.
Pyroptosis/physiology* ; ARNTL Transcription Factors/metabolism* ; Animals ; Periodontitis/etiology* ; Mice ; Phosphate-Binding Proteins/metabolism* ; Shift Work Schedule/adverse effects* ; Intracellular Signaling Peptides and Proteins/metabolism* ; Mice, Inbred C57BL ; Male ; Disease Models, Animal ; Gasdermins

Chimeric antigen receptor-modified T(CAR-T)cell therapy,as a new type of cellular immunotherapy,has shown good clinical efficacy in the treatment of malignant hematological tumors,especially B-cell acute lympho-blastic leukemia.However,there are problems such as antigen loss and immune evasion in single-target selection,so multi-target therapy strategies are gradually gaining attention.Multi-target CAR-T can effectively avoid antigen escape caused by a single target by targeting multiple tumor-associated antigens at the same time,reduce the risk of recurrence,and is expected to improve the therapeutic effect.This paper primarily discusses the structural types of multi-target CAR-T cell therapy and its clinical trial applications in the treatment of B-cell acute lymphoblastic leu-kemia(B-ALL),aiming to provide future references for the treatment of B-ALL.

Objective To establish an effective model for distinguishing glandular prodromal lesions(PGL)mixed with ground-glass nodules(mGGN)from minimally invasive adenocarcinoma(MIA)on CT based on artificial intelligence.Methods A retrospective analysis was conducted on the clinical and CT image data of 180 patients with lung adenocarcinoma confirmed by surgical pathology and with CT manifestations of mGGN in the First Affiliated Hospital of Wenzhou Medical University from January 2017 to June 2023,inclu-ding 66 patients with PGL and 114 patients with MIA.Patients were divided into the training set(n=144)and the test set(n=36)in an 8∶2 ratio using a completely random method.The quantitative parameters and radiomics features of the lesions in CT images were automatically extracted using artificial intelligence soft-ware(United Imaging Research Platform uRP).By incorporating the most obvious correlation features of omics through dimensionality reduction,five machine learning classifiers were established,including logistic regression(LR),support vector machine(SVM),Random forest(RF),Gaussian process(GP),and Decision Tree(DT).The classifier with the training set highest area under the curve(AUC)was selected as the best radiomics model,and output the result as radiomics score(Rad-score).The clinical information,CT morpho-logical characteristics and quantitative data of the two groups were included in the multivariate logistic regres-sion analysis to screen the independent influencing factors for effectively differentiating PGL and MIA,and a clinical model was established.Finally,a comprehensive prediction model was constructed based on Rad-score and clinical risk factors.The diagnostic performance of the three models was evaluated by using the AUC,sen-sitivity,specificity and accuracy of receiver operating characteristic(ROC)curve.Results Eleven radiomics features for distinguishing PGL from MIA were obtained through LASSO dimensionality reduction.Among the five machine learning classifiers,GP has the best diagnostic performance,with AUC of 0.865 in the train-ing set and 0.762 in the test set,respectively.Univariate and multivariate logistic regression analyses were used for clinical feature screening.The clinical model was constructed by using the average CT value,average long and short diameter,and solid partial long diameter of mGGN,and the AUCs of the training set and the test set were 0.870 and 0.794,respectively.The comprehensive prediction model demonstrated superior diag-nostic performance,with AUC,sensitivity,specificity,and accuracy in the training set being 0.948,81.1%,91.2%and 87.5%respectively,while 0.883,76.9%,91.3%and 86.1%respectively in the test set.Conclu-sion The comprehensive prediction model established based on the quantitative and omics feature analysis of pulmonary nodules by artificial intelligence can well distinguish mGGN mixed with PGL from MIA on CT,and can be used to guide clinical treatment decisions.

Small for gestational age (SGA) infants are more likely to experience neurocognitive impairments compared to appropriate for gestational age (AGA) infants. This paper reviews recent research on the neurocognitive development of SGA children. SGA can lead to a "brain-sparing effect" due to growth restriction, which may affect cerebral blood flow and brain structure. However, this does not guarantee normal brain development. Restrictive blood flow can result in changes in brain structure, such as reduced total white matter and gray matter volume in various brain regions, including the cerebral cortex, hippocampus and cerebellum, ultimately leading to decreased head circumference. SGA children also exhibit lower scores in all neurocognitive domains, including intelligence, attention, memory, and executive function. This may result in poor academic performance and an increased risk of social, behavioral, and neurological problems, such as cerebral palsy, epilepsy, visual and hearing impairments, as well as comorbidities like attention deficit hyperactivity disorder(ADHD), autism spectrum disorder(ASD), anxiety, depression, and schizophrenia. Several risk factors for SGA-related neurocognitive impairments have been identified, including gestational hypertension, abnormal gestational weight, smoking, and catch-up growth. Studies have shown that the best interventions to improve cognitive dysplasia include nutrient supplementation, continued breastfeeding, high-quality education, and appropriate early intervention (responsive parenting) are effective in improving cognitive outcomes for SGA children.

Objective:To explore the changes of dynamic cerebral autoregulation ability in pilots exposed to acute positive acceleration(+ Gz) by transcranial Doppler combined with beat-to-beat blood pressure.Methods:A total of 26 pilots enrolled in the + 8Gz manned centrifuge trial at the Air Force Medical Center, Air Force Medical University from June to October 2022 were prospectively included. Blood pressure and heart rate were monitored in the resting state before the trial and within 5 min after centrifugation. Transcranial Doppler combined with noninvasive continuous beat-to-beat blood pressure monitor were used to detect bilateral middle cerebral artery blood flow velocity and beat-to-beat pulse pressure respectively. The transfer function analysis was applied to derive the parameters of cerebral blood flow autoregulation in each frequency band from 0.02 to 0.50 Hz, and the phase, gain and coherence were calculated. The above parameters were compared between resting state and after acute + 8Gz positive acceleration exposure.Results:Compared with the resting state, in all of the 26 pilots after acute + 8Gz positive acceleration exposure, the systolic and diastolic blood pressure and heart rate increased significantly ( P<0.001), the phase significantly increased and the gain significantly decreased in the ultra-low frequency band (0.02-0.07 Hz) ( P<0.05); whereas there were no statistical differences of gain and phase in the low frequency band (0.07-0.20 Hz) and the high frequency band (0.20-0.50 Hz) (all P>0.05). Conclusions:Transcranial Doppler combined with beat-to-beat pulse pressure can be used for the assessment of changes in immediate dynamic cerebral autoregulation after acute + Gz exposure, and transfer function analysis of ultra-low frequency band parameters is suitable for this type of evaluation.

Objective This study aims to explore effective ways to enhance patient experience by analyzing relevant indi-cators before and after the implementation of a new admission model at a large public tertiary hospital.Methods A retrospective analysis and a questionnaire survey were conducted to assess changes in hospital admission convenience,timeliness,and patient satisfaction before and after the implementation of the new admission model.Results After the new admission model was imple-mented,the bed occupancy rate for waiting patients significantly increased,while the waiting time decreased.The time required for completing admission procedures was notably shortened,bed utilization rates improved,and the average pre-operative hospital stay decreased.Additionally,the volume of admitted critically ill patients increased,and indicators such as the proportion of level IV surgeries and inpatient satisfaction improved.Conclusion The implementation of the new admission model has enhanced serv-ice efficiency and quality,improved patient experience,and increased patient satisfaction,making it a model worth promoting.