OBJECTIVES: To explore the mechanism by which Pulsatilla saponin D (PSD) inhibits invasion and metastasis of triple-negative breast cancer (TNBC). METHODS: The public databases were used to identify the potential targets of PSD and the invasion and metastasis targets of TNBC to obtain the intersection targets between PSD and TNBC. The "PSD-target-disease" interaction network was constructed and protein-protein interaction (PPI) analysis was performed to obtain the core targets, which were analyzed for KEGG pathway and GO functional enrichment. Molecular docking study of the core targets and PSD was performed, and the therapeutic effect and mechanism of PSD were verified using Transwell assay and Western blotting in cultured TNBC cells. RESULTS: Network pharmacology analysis identified a total of 285 potential PSD targets and 26 drug-disease intersection core targets. GO analysis yielded 175 entries related to the binding of biomolecules (protein, DNA and RNA), enzyme activities, and regulation of gene transcription. KEGG analysis yielded 46 entries involving pathways in cancer, chemical carcinogenesis-receptor activation, microRNAs in cancer, chemical carcinogenesis-reactive oxygen species, PD-L1 expression and PD-1 checkpoint pathway in cancer. Molecular docking showed high binding affinities of PSD to MTOR, HDAC2, ABL1, CDK1, TLR4, TERT, PIK3R1, NFE2L2 and PTPN1. In cultured TNBC cells, treatment with PSD significantly inhibited cell invasion and migration and lowered the expressions of MMP2, MMP9, N-cadherin and the core proteins p-mTOR, ABL1, TERT, PTPN1, HDAC2, PIK3R1, CDK1, TLR4 as well as NFE2L2 expressionin the cell nuclei. CONCLUSIONS The inhibitory effects of PSD on TNBC invasion and metastasis are mediated by multiple targets and pathways.
Humans ; Triple Negative Breast Neoplasms/metabolism* ; Saponins/pharmacology* ; Pulsatilla/chemistry* ; Female ; Molecular Docking Simulation ; Cell Line, Tumor ; Neoplasm Invasiveness ; Protein Interaction Maps ; Neoplasm Metastasis ; Signal Transduction/drug effects* ; Cell Movement/drug effects*

Objective To investigate the recovery of plasma metabolism in asymptomatic and mild patients of coronavirus disease 2019(COVID-19)one year after recovery.Methods A total of 174 participants were recruited from the communities in Wuhan,including 80 healthy volunteers and the COVID-19 patients who had recovered for one year.According to the disease severity,the recovered COVID-19 patients were grouped as asymptomatic patients(n=80)and mild patients(n=14).The liquid chromatography mass spectrometry platform was employed to study the metabolomic characteristics of the plasma from all the participants.Results The plasma metabolites in asymptomatic patients and mild patients remained abnormal compared with those in healthy volunteers.Among the differential metabolites in asymptomatic patients and mild patients,some metabolites showed a downward trend only in mild patients,such as phosphatidylethanolamine[20∶3(5Z,8Z,11Z)/P-18∶0],sphingomyelin(d18∶1/24∶0),and cholesteryl(15∶0).The metabolic pathway involving the differential metabolites in mild patients was mainly glycerophospholipid metabolism.Conclusions Even one year after recovery,the mild COVID-19 patients still exhibit metabolic abnormalities.Hence,these patients may experience an extended period of time for recovery.
Humans ; COVID-19/metabolism* ; Metabolomics ; SARS-CoV-2 ; Metabolome ; Female ; Male ; Adult ; Middle Aged

ObjectiveTo analyze the evolutionary characteristics and genetic variations of the HA (hemagglutinin) and NA (neuraminidase) genes of influenza A(H1N1) viruses in Shanghai during 2024, to investigate their transmission patterns, and to evaluate their potential impact on vaccine effectiveness. MethodsFrom January to October 2024, throat swab specimens were collected from influenza like illness (ILI) patients at 4 hospitals in Shanghai. Real-time fluorescence ploymerase chain reaction (RT-PCR) was used for virus detection and isolation of H1N1 influenza viruses. Forty influenza A(H1N1) virus strains were sequenced using Illumina NovaSeq 6000 platform, followed by phylogenetic analyses, genetic distance analysis, and amino acid variation analyses of HA and NA genes. ResultsPhylogenetic tree of the HA and NA genes revealed that the 40 influenza A(H1N1) virus strains circulating in Shanghai in 2024 exhibited no significant geographic clustering, with a broad origin of strains and complex transmission chains. Genetic distance analyses demonstrated that the average intra-group genetic distances of HA and NA genes among the Shanghai strains were 0.005 1±0.000 6 and 0.004 6±0.000 6, respectively, which were comparable to or higher than those observed in global surveillance strains. Both HA and NA genes displayed frequent mutations. Compared to the 2023‒2024 and 2024‒2025 Northern Hemisphere A(H1N1) vaccine strains (WHO-recommended), the HA proteins of 40 Shanghai strains exhibited amino acid substitutions at positions 120, 137, 142, 169, 216, 223, 260, 277, 356 and 451, with critical mutations at positions 137 and 142 located within the Ca2 antigenic determinant. Furthermore, mutations in the NA protein were observed at positions 13, 50, 200, 257, 264, 339 and 382. ConclusionThe genetic background of the 2024 Shanghai influenza A(H1N1) virus strains is complex and diverse, and antigenic variation may affect vaccine effectiveness. Therefore, it is recommended to enhance genomic surveillance of influenza viruses, evaluate vaccine suitability, and implement more targeted prevention and control strategies against imported influenza viruses.

Objective:To explore the mechanism of zoledronic acid (ZOL) affects osteogenic differentiation and bone formation through the regulation of sirtuin 3 (SIRT3) / P53 expression.Methods:Bone marrow mesenchymal stem cells (BMSCs) were induced to differentiate into osteogenic cells, the expression of SIRT3 in the cells was detected, and the targeting regulation relationship between SIRT3 and P53 was analyzed. The intracellular expressions of SIRT3 and P53 were intervened and ZOL was used to treat the cells. MTT method, Western blot method and kit were used to detect cell viability, osteogenesis-related genes Osteoprotegerin (OPG), runt-related transcription factor 2 (Runx2) expression, alkaline phosphatase (ALP) activity and alizarin red S (ARS) staining, respectively. Ovariectomy (OVX) was used to construct a rat model and explore the effect of ZOL on the progression of osteoporosis (OP) in vivo.Results:ZOL promoted osteogenic differentiation of BMSCs. The expression of SIRT3 was down-regulated in the serum of OP patients (0.78±0.23) compared with that of healthy subjects (1.00±0.26 vs. 0.78±0.23. t=3.85, P<0.001). During the osteogenic differentiation of BMSCs, the expression level of SIRT3 gradually increased with the prolonged induction of osteogenesis. Compared with the p53 protein expression and BMSCs activity in the control group, SIRT3 knockout could increase the expression level of p53 protein (0.59±0.05 vs. 1.01±0.11. t=6.02, P=0.004) but inhibited the activity of BMSCs (100.00±8.41 vs. 51.26±5.59. t=8.36, P=0.001). After ZOL treatment, the inhibitory effect of SIRT3 on cell viability (49.61±5.11 vs. 87.61±7.31. t=7.38, P=0.002) and osteogenesis was relieved, and the level of P53 was inhibited (1.10±0.10 vs. 0.69±0.04. t=6.59, P=0.003). P53 overexpression partially offseted the effects of ZOL on cell viability (84.61±6.52 vs. 66.54±5.47. t=3.68, P=0.021) and osteogenesis. Compared with the sham surgery group, the OVX group showed inhibition of osteogenesis in rats, and ZOL treatment significantly improved osteogenic inhibition. ZOL treatment increased the expression level of SIRT3 protein in bone tissue of OVX rats, but inhibited the expression level of P53. Conclusion:ZOL promoted osteogenic differentiation and bone formation of BMSCs by promoting the ubiquitination and degradation of P53 by SIRT3.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Sarcopenia is a syndrome associated with decreased muscle mass,decreased muscle strength,and reduced physical performance. Due to multiple factors such as tumor metabolism,systemic inflammatory response,disease progression,and reduced physical activity associated with treatment itself,the risk of sarcopenia in patients with lung cancer is higher than that of the general population. Sarcopenia is closely related to the clinical outcomes,including increased risk for mortality,and significantly impacts patients' long-term quality of life and mental health. This study systematic reviewed the risk factors for sarcopenia in patients with lung cancer,its negative effects on clinical outcomes,long-term quality of life and mental health,and the interventions for sarcopenia. Given the significant impact of sarcopenia on patients with lung cancer,it is urgent to explore a multidisciplinary intervention model to improve their survival and quality of life.

Objective To evaluate the effectiveness and safety of Yiyang Pill in preventing and treating cardiovascular adverse reactions in patients with traditional Chinese medicine(TCM)syndrome with qi and yin deficiency and thyroid stimulating hormone(TSH)inhibition after differentiated thyroid cancer(DTC)resection.Methods A randomized,double-blind,placebo-controlled clinical trial was conducted,and 120 patients with TSH inhibition after DTC surgery were enrolled and randomized into two groups in a 1∶1 ratio using SAS 9.4 software generated random tables.The control group received a placebo and TSH suppression therapy,whereas the treatment group received the Yiyang Pill and TSH suppression therapy.The treatment period was 3 months.The incidence of cardiovascular adverse reactions,blood pressure,blood lipids,thyroid function,the dosage of levothyroxine,the efficacy of TCM syndrome,and safety indicators were compared between the two groups.Multivariate Logistic regression was used to analyze the influencing factors of cardiovascular adverse reactions.Results The incidence of cardiovascular adverse reactions in the treatment group was lower than that in the control group(P<0.05),and the efficacy of TCM syndrome treatment was significantly higher than in the control group(P<0.05).The free tetraiodothyronine level in the treatment group was higher than that before treatment(P<0.05),and the systolic and diastolic blood pressure in the control group increased compared to those before treatment(P<0.05).No severe adverse events were observed in either group.Compared with the control group,the cardiovascular incidence in the treatment group was lower,and the cardiovascular incidence in the<100 μg/d group was lower than that in the group with≥100 μg/d before treatment.Conclusion The Yiyang Pill can reduce the incidence of cardiovascular adverse reactions in patients after DTC surgery,effectively improve TCM syndromes,and be safe to use.Yiyang Pill treatment is a protective factor for cardiovascular adverse reactions,and the dosage of levothyroxine≥100 μg/d was a risk factor.

Objective To investigate the influencing factors of falls and serious falls among individuals aged 45 years and above in China,as well as explore the association between falls and multimorbidity,thereby pro-viding empirical evidence for the formulation of effective strategies to prevent falls.Methods The study utilized data from the CHARLS 2020 dataset and employed various statistical methods,including descriptive statistics,χ2 test,quadratic regression,and logistic regression.Additionally,subgroup analyses were conducted on key vari-ables.Results The prevalence of falls and serious falls among individuals aged 45 and above in China was found to be 17.42%and 6.86%,respectively.Multimorbidity emerged as a significant determinant influencing both falls and serious falls,with a higher number of diseases being associated with an increased prevalence of these events.Conclusion In order to effectively address the issue of falls in middle-aged and elderly individuals,particularly those with multimorbidity,it is imperative to integrate multimorbidity considerations into the comprehensive fall intervention process.

Objective: To explore the feasibility of remotely obtaining complex information on traditional Chinese medicine (TCM) pulse conditions through voice signals. Methods: We used multi-label pulse conditions as the entry point and modeled and analyzed TCM pulse diagnosis by combining voice analysis and machine learning. Audio features were extracted from voice recordings in the TCM pulse condition dataset. The obtained features were combined with information from tongue and facial diagnoses. A multi-label pulse condition voice classification DNN model was built using 10-fold cross-validation, and the modeling methods were validated using publicly available datasets. Results: The analysis showed that the proposed method achieved an accuracy of 92.59% on the public dataset. The accuracies of the three single-label pulse manifestation models in the test set were 94.27%, 96.35%, and 95.39%. The absolute accuracy of the multi-label model was 92.74%. Conclusion Voice data analysis may serve as a remote adjunct to the TCM diagnostic method for pulse condition assessment.

Objective:To investigate the changes of exam scores of retrained peritoneal dialysis (PD) operators (patients, family members, or nannies) with an internal of one year during COVID-19 epidemic and provide basis for targeted training.Methods:It was a cross-sectional survey study. The maintenance PD patients who participated in two trainings with an interval of one year during COVID-19 epidemic from November 1, 2019 to February 28, 2021 in Department of Nephrology in Peking University People's Hospital were enrolled. During COVID-19 epidemic, retraining was extended from once every six months to once a year. The clinical data were collected, the self-designed training exam score table including theoretical knowledge and operational skills assessment was used to investigate the exam scores of two trainings, and the total exam scores and sub-item scores of PD operators before and after one year were compared. Logistic regression analysis was used to analyze the associated factors of the reduction of exam scores.Results:A total of 59 patients were enrolled, with 35 males (59.32%), age of (58.41±14.52) years, and dialysis duration of 42 (12, 84) months. There were 54 patients (91.53%) operating by themselves, 22 operators (37.29%) having college degree or above, and 35 operators (59.32%) having decreased exam scores. The total exam scores were 83.17±7.90 and 80.61±8.20 before and after one year, respectively ( t=2.732, P=0.008). In the six contents of itemized scoring, compared with one year ago, the exam scores of complication treatment ( t=4.928, P<0.001) and self-monitoring ( t=3.222, P=0.002) were significantly decreased. There was no statistically significant difference in the exam scores of environment and hygiene, dialysate replacement operation, exit nursing and diet before and after one year (all P>0.05). The total exam scores in patients with dialysis duration <12 months and 36-60 months after one year were significantly lower than before one year ( t=2.309, P=0.041; t=3.086, P=0.009). There was no statistically significant difference in the exam scores of PD operators with dialysis duration of 12-<36 months and >60 months before and after one year (both P>0.05). Logistic regression analysis showed that dialysis duration was an independent associated factor of exam scores reduction (dialysis duration 36-60 months/>60 months, OR=6.233, 95% CI 1.035-37.529, P=0.046). Conclusions:During COVID-19 epidemic, the reduced frequency of retraining reduces the training exam scores of PD operators, especially in patients with dialysis duration of 36-60 months. The weak points are focused on complication management and self-monitoring. Training should be strengthened for key patients and key contents if regular retraining is not possible due to special circumstances.