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.

Objective To evaluate the longitudinal imaging features of coronary artery plaques in elderly male patients with CHD and myocardial bridges and explore the longitudinal changing pat-terns.Methods A total of 117 elderly male CHD patients who underwent two examinations of coronary computed tomography angiography in our medical center from January 2018 to Septem-ber 2023 were enrolled in this study.Then 216 small plaques(0.1-50 mm3 in size)were subjec-ted,and classified into the proximal myocardial bridge group(98 plaques)and other heart part group(118 plaques)according to the site of the plaques.Plaque volume,plaque composition vol-ume,FAI,and CT-derived fraction flow reserve(CT-FFR)were calculated and recorded.Results In the 2 groups of plaques,there were no statistically differences in the plaque length,plaque nec-rotic core volume,and FAI derived from the second examination than the baseline one(P＞0.05).The plaque volume,intra-plaque fibers,and dense calcified volume of plaques in the second exami-nation were significantly greater than those at baseline,and CT-FFR was obviously smaller than the baseline level in both groups(P＜0.05,P＜0.01).In the proximal myocardial bridge group,the intra-plaque fibrofat volume in the second examination was significantly larger than that of baseline,while opposite phenomenon was observed in the plaques of the other heart part group(P＜0.05).The annual changing rates of intraplaque fibrofat volume and FAI were significantly higher in the proximal myocardial bridge group than the other heart part group[0.51％(-0.32％,0.51％)vs 0.02％(-0.46％,0.20％),P=0.046;0.55％(-2.44％,1.76％)vs 0.33％(-1.36％,2.63％),P=0.044].Conclusion In elderly male patients,the intraplaque fibrofat vol-ume,FAI and CT-FFR are more likely to change in the proximal plaques of the left anterior de-scending artery myocardial bridge than the plaques of other parts of heart,so the proximal plaques of the left anterior descending artery need more clinical attention and early intervention.

Objective:To analyze risk factors associated with false-positive results of quantitative fecal immunochemical testing (FIT), evaluate its performance for detecting advanced colorectal neoplasia across different subgroups, and explore the optimal positivity thresholds for each subgroup.Methods:Individuals who participated in the Zhejiang Colorectal Cancer Screening Program in 2020-2021, completed questionnaire-based risk assessment and quantitative FIT for initial screening, and undertook colonoscopy for confirmed diagnosis were included in this study. The information of individuals, including demographic characteristics, lifestyles, history of diseases, and family history of colorectal cancer (CRC), was collected by using questionnaires. The diagnostic outcomes of the individuals were obtained through colonoscopy and pathological examination. Multivariate logistic regression analyses were conducted to identify factors associated with false-positive FIT results. The optimal threshold of FIT was determined based on the receiver operating characteristic (ROC) curve and 10-fold cross-validation. The effectiveness of FIT screening in different subgroups was compared using the unified threshold of 100 ng/ml or optimal positivity thresholds.Results:There were 25 874 individuals included in the analysis, with 14 694 (56.79%) having fecal hemoglobin concentrations ≥100 ng/ml. A total of 3 830 advanced adenoma cases (14.80%) and 362 CRC cases (1.40%) were identified. Age below 60 years old, females, underweight, smoking, drinking, use of nonsteroidal anti-inflammatory drugs, no family history of CRC, no history of intestinal disease, no history of hypertension, and physical inactivity were associated with an elevated risk of false-positive results in FIT ( P<0.05). Compared to the predetermined threshold of 100 ng/ml, the false positive rate (FPR) of quantitative FIT decreased from 52.3% to 37.3% in all individuals, and decreased by more than 20% in females, individuals with normal weight, smokers, and those without a history of intestinal disease when adopting the optimal threshold (all P<0.001). Conclusion:The risk of false-positive results in quantitative FIT varies across different subgroups. Adopting the optimal thresholds could improve the specificity and reduce the FPR of quantitative FIT for CRC screening.

Objective:To explore the distribution of HIV-1 genetic subtypes and drug resistance profiles among HIV-1 infected patients with antiretroviral treatment (ART) failure in Henan Province and to provide evidence for optimizing ART regimens.Methods:HIV-1 infected patients who had received ART for at least 6 months with viral loads (VL) ≥200 copies/ml in 18 cities of Henan from January to December 2023. The plasma samples were collected, and partial pol gene sequences and full-length integrase ( int) gene sequences of HIV-1 were amplified using nested RT-PCR. HIV-1 subtypes were determined using the REGA HIV-1 subtyping tool, and drug resistance mutations were analyzed using the Stanford University HIV Drug Resistance Database ( http://hivdb.stanford.edu/). Chi-square tests and multivariate logistic regression were used to identify risk factors associated with drug resistance of HIV-1 infected patients. Results:Among 697 HIV-1 infected patients with ART failure, 14 HIV-1 genetic subtypes were identified. Subtype B was predominant (58.68%, 409/697), followed by CRF01_AE (21.95%, 153/697) and CRF07_BC (12.91%, 90/697). The overall drug resistance rate was 72.31% (504/697), with CRF55_01B exhibiting a resistance rate of 91.30% (21/23). Non-nucleoside reverse transcriptase inhibitors (NNRTIs) had the highest resistance mutation rate (67.29%, 469/697), followed by nucleoside reverse transcriptase inhibitors (NRTIs)(56.81%, 396/697), protease inhibitors (PIs)(5.74%, 40/697), and integrase strand transfer inhibitors (INSTIs)(2.75%, 19/691). The results of multivariate analysis showed that the positive correlation factor for drug resistance in HIV-1 infected individuals with failed ART was baseline CD4 +T lymphocyte counts <200 cells/μl (a OR=3.84, 95% CI: 1.69-8.72), and the negative correlation factor was ART duration of 3-5 years (a OR=0.32, 95% CI: 0.13-0.77), the initial treatment ART protocol used two types of NRTIs plus one type of PIs (a OR=0.14, 95% CI: 0.05-0.43) and two types of NRTIs plus one type of INSTIs protocol (a OR=0.12, 95% CI: 0.03-0.57). Conclusions:The drug resistance rate of HIV-1 infected patients with ART failure was relatively higher in Henan Province in 2023. Strengthening the monitoring of HIV-1 drug resistance is of great significance to improve the ART effect of HIV-1 infected patients.

OBJECTIVE To investigate a suspected outbreak of carbapenem-resistant Klebsiella pneumoniae(CRKP)infection in the intensive care unit of a traditional Chinese medicine hospital,identify the source of infec-tion and transmission routes,and provide a basis for prevention and control of CRKP infection.METHODS Epide-miological investigations were conducted on five patients with CRKP infections or colonization who were identi-fied in Jul.2024 at Suiyang County Hospital of Traditional Chinese Medicine.Samples were collected from pa-tients,the ward environments,and hand surfaces to detect CRKP.Fourteen CRKP isolates were selected for car-bapenemase gene testing,and homology analysis was performed by enterobacterial repetitive intergenic consensus polymerase chain reaction(ERIC-PCR)and multilocus sequence typing(MLST).RESULTS The median age of the five cases was 73 years,and all had undergone multiple invasive procedures.Environmental monitoring showed a CRKP positive rate of 26.35％,with CRKP isolates detected on the hands of healthcare workers,surfaces in the wards and medical equipment surfaces.Genetic analysis showed that all 14 CRKP strains carried the KPC resist-ance gene;except for case 1,other strains carried the VIM gene.MLST identified CRKP of all strains as sequence type 48(ST48);while ERIC-PCR revealed two distinct genotypes:genotype A for case 1 and genotype B for the other cases and environmental isolates.After strengthening patient isolation and group treatment,strictly cleaning and disinfecting the ward environments and medical equipment,and strictly implementing hand hygiene,the infec-tion was effectively controlled.CONCLUSIONS Inadequate disinfection of the ward environments and medical e-quipment and poor compliance with hand hygiene are the main contributors to the suspected CRKP outbreak.Ho-mology analysis suggests the existence of two independent transmission chains.Timely identification and manage-ment of the infection sources,interruption of transmission routes,protection of susceptible individuals and imple-mentation of comprehensive infection control measures are essential for effective outbreak control.

Objective:To analyze the drug resistance characteristics and influencing factors in human immunodeficiency virus (HIV)-1 treated patients in Henan Province.Methods:HIV-1 treated patients who had received anti-retroviral therapy (ART) for more than six months and had a viral load >200 copies/mL in the Zhengzhou Sixth People′s Hospital from January to December 2024 were enrolled. Plasma samples were collected. Partial pol region gene sequences and integrase gene sequences of HIV-1 were amplified by reverse transcription nested polymerase chain reaction. The REGA HIV-1 subtype analysis tool was used to determine the subtypes of HIV-1 isolates, and the HIV drug resistance database of Stanford University in the United States was used to analyze the genetic drug resistance mutations and antiviral drug susceptibility. The multivariate logistic regression analysis was used to analyze the factors related to drug resistance. Results:Among 933 HIV-1 treated patients with ART failure, 825 samples were successfully amplified, with the amplification success rate of 88.42%. The overall drug resistance rate was 70.06%(578/825), among which the drug resistance rates of nucleoside reverse transcriptase inhibitor (NRTI), non-nucleoside reverse transcriptase inhibitor (NNRTI), protease inhibitor (PI), and integrase inhibitor (INSTI) were 55.15%(455/825), 64.36%(531/825), 5.70%(47/825), and 2.31%(19/821), respectively. The most common drug resistance mutations included M184I/V (47.88%(395/825)), K103N/S (38.18%(315/825)), and K70E/G/N/Q/R/S/T/del (16.61%(137/825)). Multivariate analysis showed that the baseline CD4 + T cell count <200 cells/μL (adjusted odds ratio ( OR)=2.239, 95% confidence interval ( CI)1.011 to 4.960), an initial 2NRTI+ NNRTI-based treatment regimen (adjusted OR=44.332, 95% CI 5.191 to 378.593), initial 2NRTI+ PI/r (r means ritonavir)-based regimen (adjusted OR=14.391, 95% CI 1.304 to 158.805) and a change in the ART regimen (adjusted OR=5.941, 95% CI 2.373 to 14.878) were independent risk factors for drug resistance (all P<0.05). Conclusions:The drug resistance rate after virological failure in HIV-1 treated patients in Henan Province is relatively high, which is mainly characterized by NNRTI resistance. The baseline immune status and the choice of the initial treatment regimen are important factors affecting the occurrence of drug resistance. The treatment monitoring and drug resistance monitoring should be strengthened.

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.

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