BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

OBJECTIVE: To evaluate the protective effects of gentiopicroside (GPS) against reactive oxygen species (ROS)-induced NOD-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome activation in endothelial cells, aiming to reduce atherosclerosis. METHODS: Eight-week-old male ApoE-deficient mice were randomly divided into 2 groups (n=10 per group): the vehicle group and the GPS treatment group. Both groups were fed a high-fat diet for 16 weeks. GPS (40 mg/kg per day) was administered by oral gavage to the GPS group, while the vehicle group received an equivalent volume of the vehicle solution. At the end of the treatment, blood and aortic tissues were collected for assessments of atherosclerosis, lipid profiles, oxidative stress, and molecular expressions related to NLRP3 inflammasome activation, ROS production, and apoptosis. Additionally, in vitro experiments on human aortic endothelial cells treated with oxidized low-density lipoprotein (ox-LDL) were conducted to evaluate the effects of GPS on NLRP3 inflammasome activation, pyroptosis, apoptosis, and ROS production, specifically examining the role of the sirtuin 1 (SIRT1)/nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. SIRT1 and Nrf2 inhibitors were used to confirm the pathway's role. RESULTS: GPS treatment significantly reduced atherosclerotic lesions in the en face aorta (P<0.01), as well as in the thoracic and abdominal aortic regions, and markedly decreased sinus lesions within the aortic root (P<0.05 or P<0.01). Additionally, GPS reduced oxidative stress markers and proinflammatory cytokines, including interleukin (IL)-1 β and IL-18, in lesion areas (P<0.05, P<0.01). In vitro, GPS inhibited ox-LDL-induced NLRP3 activation, as evidenced by reduced NLRP3 (P<0.01), apoptosis-associated speck-like protein containing a CARD, cleaved-caspase-1, and cleaved-gasdermin D expressions (all P<0.01). GPS also decreased ROS production, apoptosis, and pyroptosis, with the beneficial effects being significantly reversed by SIRT1 or Nrf2 inhibitors. CONCLUSION GPS exerts an antiatherogenic effect by inhibiting ROS-dependent NLRP3 inflammasome activation via the SIRT1/Nrf2 pathway.
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Reactive Oxygen Species/metabolism* ; Iridoid Glucosides/therapeutic use* ; NF-E2-Related Factor 2/metabolism* ; Animals ; Atherosclerosis/metabolism* ; Inflammasomes/drug effects* ; Male ; Sirtuin 1/metabolism* ; Signal Transduction/drug effects* ; Humans ; Endothelial Cells/pathology* ; Mice ; Oxidative Stress/drug effects* ; Apoptosis/drug effects* ; Lipoproteins, LDL ; Mice, Inbred C57BL

Obesity is a significant risk factor for cancer and is associated with breast cancer metastasis. Nevertheless, the mechanism by which alterations in systemic metabolism affect tumor microenvironment (TME) and consequently influence tumor metastasis remains inadequately understood. Herein, we found that perturbations in circulating metabolites induced by obesity promote metastasis-like phenotypes in breast cancer. Oleoylcarnitine (OLCarn) concentrations were elevated in the serum of obese mice and humans. Administration of exogenous OLCarn induces metastasis-like characteristics in breast cancer cells. Mechanistically, OLCarn directly interacts with the Arg176 site of adenylate cyclase 10 (ADCY10), leading to the activation of ADCY10 and enhancement of cAMP production. Mutations at Arg176 prevent OLCarn from binding to ADCY10, disrupting the ADCY10-mediated activation of cyclic adenosine monophosphate (cAMP) signaling pathway. This activation promotes transcription factor 4 (TCF4)-dependent kinesin family member C1 (KIFC1) transcription, thereby driving breast cancer metastasis. Conversely, the neutralization of both ADCY10 and KIFC1 through knockdown or pharmacological inhibition abrogates the oncogenic effects mediated by OLCarn. Hence, obesity-induced systemic environmental changes lead to the aberrant accumulation of OLCarn within the TME, making it a potential therapeutic target and biomarker for breast cancer.

Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals ; Autophagy/physiology* ; Oligodendroglia/metabolism* ; Myelin Sheath/physiology* ; Aging/pathology* ; Myelin Basic Protein/metabolism* ; Cell Lineage/physiology* ; Mice ; Oligodendrocyte Precursor Cells ; Mice, Inbred C57BL ; Brain/cytology* ; Cells, Cultured ; Cell Count

Ovarian cancer poses a significant threat to women's health, necessitating effective therapeutic strategies. Emd-D, an emodin derivative, demonstrates enhanced pharmaceutical properties and bioavailability. In this study, Cell Counting Kit 8 (CCK8) assays and Ki-67 staining revealed dose-dependent inhibition of cell proliferation by Emd-D. Migration and invasion experiments confirmed its inhibitory effects on OVHM cells, while flow cytometry analysis demonstrated Emd-D-induced apoptosis. Mechanistic investigations elucidated that Emd-D functions as an inhibitor by directly binding to the glycolysis-related enzyme PFKFB4. This was corroborated by alterations in intracellular lactate and pyruvate levels, as well as glucose transporter 1 (GLUT1) and hexokinase 2 (HK2) expression. PFKFB4 overexpression experiments further supported the dependence of Emd-D on PFKFB4-mediated glycolysis and SRC3/mTORC1 pathway-associated apoptosis. In vivo experiments exhibited reduced xenograft tumor sizes upon Emd-D treatment, accompanied by suppressed glycolysis and increased expression of Bax/Bcl-2 apoptotic proteins within the tumors. In conclusion, our findings demonstrate Emd-D's potential as an anti-ovarian cancer agent through inhibition of the PFKFB4-dependent glycolysis pathway and induction of apoptosis. These results provide a foundation for further exploration of Emd-D as a promising drug candidate for ovarian cancer treatment.
Female ; Humans ; Ovarian Neoplasms/physiopathology* ; Phosphofructokinase-2/genetics* ; Apoptosis/drug effects* ; Glycolysis/drug effects* ; Animals ; Cell Line, Tumor ; Mice ; Cell Proliferation/drug effects* ; Emodin/administration & dosage* ; Mice, Nude ; Mice, Inbred BALB C ; Hexokinase/metabolism* ; Xenograft Model Antitumor Assays

Objective To observe the value of whole-brain CT perfusion(CTP)parameters at different time and clinical data for predicting delayed cerebral ischemia(DCI)and 3-month poor prognosis in patients with aneurysmal subarachnoid hemorrhage(aSAH).Methods Totally 127 aSAH patients were retrospectively enrolled.Clinical and CTP data within 24 h of symptom onset and during DCI time window(DCITW)were collected.The patients were divided into DCI group(n=34)and non-DCI group(n=93)based on DCI occurred or not during hospitalization,also into poor outcome group(modified Rankin scale[mRS]≥3,n=36)and good outcome group(mRS≤2)based on 3-month's follow-up.Multivariate logistic regression was performed to select independent predictive factors among variates being significantly different between groups.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the predictive performance of logistic regression model.Results Patients'age,modified Fisher score(mFS),subarachnoid hemorrhage early brain edema score(SEBES)and mean flow extraction product(mFEP)within 24 h of onset were all identified as independent predictive factors of DCI,and the AUC of their combination for predicting DCI during hospitalization was 0.817.Patients' age and mFS within 24 h of onset,alternatively,World Federation of Neurosurgical Societies(WFNS)grade and mFEP during DCITW were all independent predictive predictors of 3 months' prognosis,and the combination of the latter two showed better predictive performance(AUC=0.922)tahn the former two(AUC=0.822,P＜0.05).Conclusion Whole-brain CTP parameters combined with clinical data within 24 h of onset of aSAH could be used to predict the occurrence of DCI during hospitalization,whole-brain CTP parameters during DCITW could be used to predict 3 months'poor prognosis.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.