ObjectiveTo investigate whether Shenmai injection （SMI） improves cisplatin resistance in non-small cell lung cancer （NSCLC） by modulating lipid metabolism and inducing ferroptosis. MethodsHuman lung adenocarcinoma cisplatin-resistant A549/DDP cells were divided into the following groups： Blank group， cisplatin group （23.3 μmol·L^-1 cisplatin）， SMI group （20 g·L^-1 SMI）， cisplatin combined with SMI group （23.3 μmol·L^-1 cisplatin + 20 g·L^-1 SMI）， cisplatin combined with ferroptosis inhibitor/inducer Ferrostatin-1/Erastin group （23.3 μmol·L^-1 cisplatin + 10 μmol·L^-1 Ferrostatin-1/5 μmol·L^-1 Erastin）， and cisplatin combined with SMI and Ferrostatin-1/Erastin group （23.3 μmol·L^-1 cisplatin + 20 g·L^-1 SMI + 10 μmol·L^-1 Ferrostatin-1/5 μmol·L^-1 Erastin）. Network pharmacology， transcriptomics and metabolomics， Cell Counting Kit-8 （CCK-8） assay， transmission electron microscopy （TEM）， colorimetric assays， and Western blot analysis were employed to evaluate the effects of these treatments on A549/DDP cell viability， lipid droplet formation， lipid metabolite levels， mitochondrial function， lipid peroxidation， glutathione （GSH） content， total and ferrous iron content， and effects on ferroptiosis and autophagy related protein expression levels. ResultsSMI improved cisplatin resistance in NSCLC mainly by targeting lipid metabolism-related pathways in A549/DDP cells， affecting tumor cell lipid metabolism via autophagy， ferroptosis， and glycerophospholipid metabolism pathways. Compared with the cisplatin group， the cisplatin combined with SMI group showed significantly decreased cell viability （P<0.01）， increased lipid droplet accumulation （P<0.01）， and reduced mitochondrial maximal respiration， basal respiration， mitochondrial membrane potential， GSH content， total iron， and ferrous iron （all P<0.01）. Mitochondrial reactive oxygen species （ROS） was significantly elevated（P<0.01）， and lipid peroxidation levels were significantly increased. Protein expression analysis showed significant downregulation of solute carrier family 7 member 11 （SLC7A11） and p62 （P<0.05，P<0.01） and upregulation of ferritin heavy chain （FTH） and microtubule-associated protein 1 light chain 3Ⅱ （LC3Ⅱ） （P<0.05，P<0.01）. Compared with the cisplatin combined with SMI group， addition of Ferrostatin-1 significantly increased cell viability （P<0.05）， decreased mitochondrial ROS levels （P<0.05）， alleviated mitochondrial shrinkage， and reduced lipid peroxidation. Conversely， addition of Erastin further decreased cell viability （P<0.01）. ConclusionSMI improves cisplatin resistance in NSCLC by inducing oxidative stress， which may trigger ferroptosis through upregulation of lipophagy.

This study aims to integrate data mining techniques of single cell transcriptomics and spatial transcriptomics, along with animal experiment validation, so as to systematically characterize the protective effects of Jianpi Tongluo Formula(JTF) on the cartilage in knee osteoarthritis(KOA) and elucidate the underlying molecular mechanisms. Single cell transcriptomics and spatial transcriptomics datasets(GSE254844 and GSE255460) of the cartilage tissue obtained from KOA patients were analyzed to map the single cell-spatial heterogeneity and identify key pathogenic factors. After that, a KOA rat model was established via knee joint injection of papain. The intervention effects of JTF on the expression features of these key factors were assessed through real-time quantitative polymerase chain reaction(PCR), Western blot, and immunohistochemical staining. As a result, the integrated single cell and spatial transcriptomics data identified distinct cell subsets with different pathological changes in different regions of the inflamed cartilage tissue in KOA, and their differentiation trajectories were closely related to the inflammatory fibrosis-like pathological changes of chondrocytes. Accordingly, the expression levels of the two key effect targets, namely nuclear receptor coactivator 4(NCOA4) and high mobility group box 1(HMGB1) were significantly reduced in the articular surface and superficial zone of the inflamed joints when JTF effectively alleviated various pathological changes in KOA rats, thus reversing the abnormal chondrocyte autophagy level, relieving the inflammatory responses and fibrosis-like pathological changes, and promoting the repair of chondrocyte function. Collectively, this study revealed the heterogeneous characteristics and dynamic changes of inflamed cartilage tissue in different regions and different cell subsets in KOA patients. It is worth noting that NCOA4 and HMGB1 were crucial in regulating chondrocyte autophagy and inflammatory reaction, while JTF could reverse the regulation of NCOA4 and HMGB1 and correct the abnormal molecular signal axis in the target cells of the inflamed joints. The research can provide a new research idea and scientific basis for developing a personalized therapeutic schedule targeting the spatiotemporal heterogeneity characteristics of KOA.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Osteoarthritis, Knee/pathology* ; Humans ; Male ; Cartilage, Articular/metabolism* ; Chondrocytes/metabolism* ; Rats, Sprague-Dawley ; Female ; Protective Agents/administration & dosage* ; Single-Cell Analysis ; Middle Aged ; HMGB1 Protein/metabolism*

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Obesity is a worldwide health problem. An imbalance in energy metabolism is an important cause of obesity and related metabolic diseases. Our previous studies showed that inhibition of miR-429 increased the protein level of uncoupling protein 1 (UCP1) in beige adipocytes; however, whether local inhibition of miR-429 in subcutaneous adipose tissue affects diet-induced obesity and related metabolic disorders remains unclear. The aim of this study was to investigate the effect of local overexpression of miR-429 sponge in subcutaneous adipose tissue on obesity and related metabolic disorders. The control adeno-associated virus (AAV) or AAV expressing the miR-429 sponge was injected into mouse inguinal white adipose tissue. Seven days later, the mice were fed a high-fat diet for 10 weeks to induce obesity. The effects of the miR-429 sponge on body weight, adipose tissue weight, plasma glucose and lipid levels, and hepatic lipid content were explored. The results showed that the overexpression of miR-429 sponge in subcutaneous white adipose tissue reduced body weight and fat mass, decreased fasting blood glucose and plasma cholesterol levels, improved glucose tolerance, and alleviated hepatic lipid deposition in mice. Mechanistic investigation showed that the inhibition of miR-429 significantly upregulated the expression of UCP1 in adipocytes and adipose tissue. These results suggest that local inhibition of miR-429 in subcutaneous white adipose tissue ameliorates obesity and related metabolic disorders potentially by upregulating UCP1, and miR-429 is a potential therapeutic target for the treatment of obesity and related metabolic disorders.
Animals ; MicroRNAs/physiology* ; Obesity/metabolism* ; Mice ; Adipose Tissue, White/metabolism* ; Metabolic Diseases ; Subcutaneous Fat/metabolism* ; Male ; Uncoupling Protein 1/metabolism* ; Diet, High-Fat ; Mice, Inbred C57BL

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

OBJECTIVE: Burning solid cooking fuel contributes to household air pollution and is associated with frailty. However, how solid cooking fuel use contributes to the development of frailty has not been well illustrated. METHODS: This study recruited 8,947 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study, 2011-2018. Group-based trajectory modeling was employed to identify frailty trajectories. Multinomial logistic regression was used to assess the association between solid cooking fuel use and frailty trajectories. Population-attributable fractions were used to estimate the frailty burden from solid fuel use. RESULTS: We identified three frailty trajectories: low-stable ( n = 5,789), moderate-increasing ( n = 2,603), and fast-increasing ( n = 555). Solid fuel use was associated with higher odds of being in the moderate-increasing ( OR: 1.24, 95% CI: 1.08-1.42) and fast-increasing ( OR: 1.48, 95% CI: 1.14-1.92) trajectories. These associations were strengthened by longer solid fuel use ( P for trend < 0.001). Switching to clean fuel significantly reduced the risk of being in these trajectories compared with persistent solid fuel users. Without solid fuel, 8% of moderate- and 19% of fast-increasing trajectories demonstrated frailty development like the low-stable group. CONCLUSION Solid cooking fuel use is associated with frailty trajectories in middle-aged and older Chinese populations.
Humans ; China/epidemiology* ; Cooking ; Male ; Female ; Middle Aged ; Aged ; Air Pollution, Indoor/adverse effects* ; Frailty/etiology* ; Longitudinal Studies ; Cohort Studies

AIM To investigate the effects of Qifu Yixin Granules on cardiac inflammation in a rat model of heart failure.METHODS The rats were induced into chronic heart failure(CHF)models by 6-week intraperitoneal injection of doxorubicin followed by the random assignment of the successful rat models into the model group,the captopril group(22.5 mg/kg),and the low-dose,medium-dose,and high-dose Qifu Yixin Granules groups(2.84,5.67,11.34 g/kg),in contrast to the normal rats of the blank group.The rats had their body weight monitored;their cardiac function assessed by echocardiography;their serum levels of NT-proBNP,TNF-α,IL-6,IL-1 and CRP measured by ELISA;their cardiac morphological alterations observed by HE and Masson staining;their cardiac protein expressions of TLR4,MyD88 and NF-κB detected by immunohistochemistry and Western blot;and their cardiac mRNA expressions of TLR4,MyD88 and NF-κB measured by RT-qPCR.RESULTS Compared to the blank group,the model group exhibited significantly reduced body weight,LVEF and LVFS(P＜0.01),alongside significantly elevated LVEDD,LVESD,and serum concentrations of NT-proBNP,TNF-α,IL-6,IL-1 and CRP(P＜0.01).Additionally,the model group displayed greater myocardial inflammatory cell aggregation,increased collagen deposition(P＜0.01);and upregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.01).Compared to the model group,the groups intervened with captopril or medium/high dose Qifu Yixin Granules demonstrated significantly increased body weight,LVEF and LVFS(P＜0.05,P＜0.01);significantly reduced LVEDD,LVESD,and serum levels of the aforementioned indicators(P＜0.05,P＜0.01);mitigated inflammation and collagen deposition(P＜0.05,P＜0.01);and downregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.05,P＜0.01).CONCLUSION Qifu Yixin Granules attenuate cardiac inflammation and improve cardiac function in doxorubicin-induced CHF rats;this therapeutic effect is mediated by inhibiting the activation of the TLR4/MyD88/NF-κB signaling pathway.

Objective:To investigate the association of systemic immune-inflammation index(SII)and serum cysta-tin C(CysC)with the severity of acute pulmonary embolism(APE),and their predictive value for prognosis.Meth-ods:A total of 181 patients who were first diagnosed with APE in Cangzhou People's Hospital between January 2018 and January 2023 were retrospectively selected.The severity of APE was determined according to risk stratification criteria for pulmonary embolism,and the patients were divided into low-risk group(n=67),middle-risk group(n=81)and high-risk group(n=33).General clinical data and venous blood neutrophils,platelet and lymphocyte counts,CysC and other indicators were collected,and SII was calculated according to the formula.The relevant in-dicators were compared among three groups,and their correlation with the severity of APE was analyzed by Spearman correlation analysis.According to the prognosis,all APE patients were divided into favorable outcome group(n=129)and unfavorable outcome group(n=52).The general clinical data were compared and multivariate Cox regression analysis was used to study the influencing factors of unfavorable outcome in APE patients.The re-ceiver operating characteristic curve(ROC)was drawn to evaluate the predictive value of SII,CysC and their com-bination for the prognosis of APE patients.Nomogram model for prognosis was constructed.Results:Compared with patients in low-risk group,those in the middle-risk group and the high-risk group had significantly higher levels of serum creatinine,CysC and uric acid(P＜0.05 or＜0.01).The SII in the high-risk group was significant-ly higher than those of middle-risk group and low-risk group(P＜0.001 all).Spearman correlation analysis showed that serum creatinine,CysC,uric acid and SII were significant positively correlated with the severity of APE(r=0.356,0.358,0.233,0.353,P＜0.01 all).Compared with patients in the favorable outcome group,those in the unfavorable outcome group had significantly higher levels of D-dimer,serum creatinine,CysC,uric acid and SII(P＜0.01 all).There was a statistically significant difference in the severity of APE between the two groups(P=0.001).Multivariate Cox regression analysis showed that CysC,SII,and middle or high risk of disease severity were independent risk factors for unfavorable outcome in APE patients(HR=1.001～14.453,P＜0.05 or＜0.01).ROC curve indicated that the AUC of SII,CysC and their combination in predicting unfavorable outcome of APE patients were 0.815(95％CI 0.749～0.881),0.747(95％CI 0.661～0.832)and 0.878(95％CI,0.821～0.936),respectively.The combined AUC of the two was significantly higher than those of SII and CysC alone(Z=-2.234,-3.500,P＜0.05 or＜0.01).Based on the above independent risk factors,the AUC values of the 1-year and 3-year unfavorable outcome nomogram models were 92.9 and 88.2,respectively.The calibration prediction curve and the ideal curve fitted well.The decision curve showed that the model had a good net benefit.Conclusion:SII and CysC are significant positively correlated with the severity of APE and they are independent risk factors for unfavor-able outcome of APE,and the combination of the two indicators has a good predictive value for the prognosis of APE.The nomogram constructed has good accuracy and practicability.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.