This paper uses literature and network data to systematically sort out the theoretical and practical foundations of global public health cooperation,combines expert interviews to conduct empirical analyses,and further explores China's strategies for participating in global public health cooperation through quantitative statistics and text mining of interview data,and proposes a plan for China's participation in global public health cooperation under the current international situation.Under the countercurrents to globalization,China should take its own public health capacity building as the foundation,put global security and health equity at the core,with a philosophy of open cooperation and sustainable development,actively promote bilateral and multilateral cooperation,focus on cultivating global health talents,and enhance the effectiveness of disease prevention and control by making use of existing platforms,international mechanisms and digital health technologies,so as to help build a Global Community of Health for All.

Objective To construct machine learning models to predict the incidence of linezolid-induced thrombocytopenia(LIT).Methods A total of 198 patients treated with linezolid in a hospital between January 2020 and March 2024 were retrospectively included.Firstly,the patients were divided into LIT and non-LIT groups,and the basic characteristics of the two groups were compared.Then,the variables with significant differences between the two groups were selected as potential risk factors to construct models for predicting LIT,including Logistic regression,decision tree and random forest models,and the prediction performance of the models was evaluated and compared.Results There were 52(26.3％)patients developed LIT during the treatment.The univariate analysis showed significant differences in linezolid trough concentration(Cmin),baseline platelet counts and creatinine clearance,the incidence of cerebrovascular disease,acute respiratory distress syndrome,and abdominal infection in patients with and without LIT.Among the three models built based on these variables,the random forest model has the best predictive performance.The results of variable importance analysis based on random forest model showed that Cmin,baseline platelet count and combined with acute respiratory distress syndrome had higher importance scores.Conclusions The random forest model has high accuracy in predicting the occurrence of LIT,and the risk of LIT is higher in patients with higher levels of linezolid exposure and lower baseline platelets.

Objective To construct machine learning models to predict the incidence of linezolid-induced thrombocytopenia(LIT).Methods A total of 198 patients treated with linezolid in a hospital between January 2020 and March 2024 were retrospectively included.Firstly,the patients were divided into LIT and non-LIT groups,and the basic characteristics of the two groups were compared.Then,the variables with significant differences between the two groups were selected as potential risk factors to construct models for predicting LIT,including Logistic regression,decision tree and random forest models,and the prediction performance of the models was evaluated and compared.Results There were 52(26.3％)patients developed LIT during the treatment.The univariate analysis showed significant differences in linezolid trough concentration(Cmin),baseline platelet counts and creatinine clearance,the incidence of cerebrovascular disease,acute respiratory distress syndrome,and abdominal infection in patients with and without LIT.Among the three models built based on these variables,the random forest model has the best predictive performance.The results of variable importance analysis based on random forest model showed that Cmin,baseline platelet count and combined with acute respiratory distress syndrome had higher importance scores.Conclusions The random forest model has high accuracy in predicting the occurrence of LIT,and the risk of LIT is higher in patients with higher levels of linezolid exposure and lower baseline platelets.

OBJECTIVE: Although dietary preferences influence chronic diseases, few studies have linked dietary preferences to mortality risk, particularly in large cohorts. To investigate the relationship between dietary preferences and mortality risk (all-cause, cancer, and cardiovascular disease [CVD]) in a large adult cohort. METHODS: A cohort of 1,160,312 adults (mean age 62.48 ± 9.55) from the Shenzhen Healthcare Big Data Cohort (SHBDC) was analyzed. Hazard ratios ( HRs) for mortality were estimated using the Cox proportional hazards model. RESULTS: The study identified 12,308 all-cause deaths, of which 3,865 (31.4%) were cancer-related and 3,576 (29.1%) were attributed to CVD. Compared with a mixed diet of meat and vegetables, a mainly meat-based diet (hazard ratio [ HR] = 1.13; 95% confidence interval [ CI]: 1.02, 1.27) associated with a higher risk of all-cause mortality, while mainly vegetarian ( HR = 0.87; 95% CI: 0.78, 0.97) was linked to a reduced risk. Furthermore, there was a stronger correlation between mortality risk and dietary preference in the > 65 age range. CONCLUSION A meat-based diet was associated with an increased risk of all-cause mortality, whereas a mainly vegetarian diet was linked to a reduced risk.
Humans ; China/epidemiology* ; Middle Aged ; Male ; Female ; Prospective Studies ; Aged ; Cardiovascular Diseases/mortality* ; Diet/statistics & numerical data* ; Neoplasms/mortality* ; Adult ; Cause of Death ; Food Preferences ; Proportional Hazards Models ; Mortality ; Cohort Studies

Objective To explore the relationship between C-reactive protein/albumin ratio(CAR)and the disease severity in patients with severe pneumonia,and its predictive value for 28-day mortality risk.Methods A retrospective analysis was conducted on 152 patients with severe pneumonia admitted to Fuyang People's Hospital from January 2020 to January 2022.They were divided into non-critical illness group(n=51),critical illness group(n=63),and extremely critical illness group(n=38)based on the disease severity.The clinical data such as age and gender of patients was collected,and Pearson correlation analysis was used to explore the correlation between CAR and the severity of illness[determined by Acute Physiology and Chronic Health Evaluation Ⅱ(APACHE Ⅱ)score].Multivariate logistic regression was employed to identify independent influencing factors of the severity of illness.According to the survival status of patients after 28 days of treatment,they were divided into survival group(n=107)and death group(n=45).CAR was categorized into quintiles(Q1-Q5),and multivariate logistic regression analysis was conducted to explore the correlation between CAR and 28-day mortality risk in severe pneumonia patients.A restricted cubic spline(RCS)model was used to analyze the dose-response relationship between CAR and mortality risk.The predictive value of CAR and related indicators for patient mortality risk was evaluated using the receiver operating characteristic curve(ROC).Results CAR was significantly positively correlated with the severity of the disease(APACHE Ⅱ score)(r=0.716,P<0.05).Neutrophil/lymphocyte ratio(NLR),blood lactate(Lac),and high CAR were independent risk factors for the disease severity in patients with severe pneumonia(P<0.05).After adjusting for confounding factors,the mortality risk increased with the increase of CAR(P<0.05).Subgroup analysis of the screened confounding factors revealed that the correlation between CAR and 28-day mortality risk in severe pneumonia patients remained stable across different APACHE Ⅱ scores,GCS scores,SOFA scores,white blood cell counts(WBC),neutrophils(NEU),red cell volume distribution width(RDW),procalcitonin(PCT),and Lac,with interactions observed between NLR and Lac subgroups(P<0.05).The RCS model indicated that there was no non-linear dose-response relationship between CAR and 28-day mortality risk in patients with severe pneumonia of different genders.ROC curve analysis showed that CAR,Lac,and NLR had good predictive value for 28-day mortality in severe pneumonia patients,with the combined predictive efficacy being significantly higher than that of individual indicators.Conclusion There is a close relationship between CAR and the progression and prognosis of severe pneumonia,making it a new approach to assessing the severity of illness and predicting mortality risk in patients.

This paper uses literature and network data to systematically sort out the theoretical and practical foundations of global public health cooperation,combines expert interviews to conduct empirical analyses,and further explores China's strategies for participating in global public health cooperation through quantitative statistics and text mining of interview data,and proposes a plan for China's participation in global public health cooperation under the current international situation.Under the countercurrents to globalization,China should take its own public health capacity building as the foundation,put global security and health equity at the core,with a philosophy of open cooperation and sustainable development,actively promote bilateral and multilateral cooperation,focus on cultivating global health talents,and enhance the effectiveness of disease prevention and control by making use of existing platforms,international mechanisms and digital health technologies,so as to help build a Global Community of Health for All.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Outer membrane vesicles (OMVs) are nanoscale vesicles secreted by Gram-negative bacteria. As a unique bacterial secretion, OMV secretion can help bacteria maintain the outer membrane stability or remove harmful substances. Studies have shown that local separation of outer membrane and peptidoglycan layers led by abnormalities in outer membrane protein function, abnormal structure or excessive accumulation of LPS, and erroneous accumulation of phospholipids in the outer leaflet, which can all lead to bacterial outer membrane protrusion and eventually bud formation of OMVs. Since OMVs are mainly composed of bacterial outer membrane and periplasmic components, the pathogen associated molecular patterns (PAMPs) on their surface can trigger strong immune responses. For example, OMVs can recruit and activate neutrophils, polarize macrophages to secrete large amounts of inflammatory factors. More importantly, OMVs can act as adjuvants to induce dendritic cell (DC) maturation to enhance adaptive immune response in the body. At the same time, OMVs are derived from bacteria, which make it easy to modify. The methods by genetic engineering and others can improve their tumor targeting, give them new functions, or reduce their immunotoxicity, which is conducive to their application in tumor therapy. OMVs not only induce apoptosis or pyroptosis of tumor cells, but also regulate the host immune system, which makes OMVs themselves have a certain killing effect on tumors. In addition, the tendency of neutrophils to inflammatory tumor sites and the formation of neutrophil extracellular traps enable OMVs to target tumor sites, and the suitable size and the characteristic that they are easily taken up by DCs give OMVs a certain lymphatic targeting ability. Therefore, OMVs are often employed as excellent drug or vaccine carriers in tumor therapy. This review mainly discusses the biological mechanism of OMVs, the regulatory effects of OMVs on immune cells, the functional modification strategies of OMVs, and their research progress in tumor therapy.

Aim To explore the effect and mechanism of the artesunate(ART)on hepatocellular carcinoma(HCC).Methods The cell lines MHCC-97H and HCC-LM3 were used to be detected.MTT and clone formation were used to determine the cell proliferation;Wound healing was used to detect the cell migration;Transwell was used to test the cell invasion.Flow-cy-tometry was used to detect cell apoptosis and cell cy-cle.RNA-seq and qRT-PCR was used to detect the genes expression.Results The proliferation,migra-tion and invasion of treated cells were obviously inhibi-ted(P＜0.01).Moreover,the apoptosis rate in-creased significantly,so did the proportion of G2/M cells.Transcriptomic analysis identified GADD45A as a potential target of ART through RNA-sequencing da-ta,and suggested that ART might induce apoptosis and cell cycle arrest through regulating the expression of GADD45A.In addition,the results of mechanism studies and signaling analysis suggested that GADD45A had interaction with its upstream gene NACC1(nucle-us accumbens associated 1).Moreover,after ART treatment,the expressions of GADD45A and NACC1 were changed significantly.Conclusion ART may be a potential drug to resist HCC by affecting the expres-sion of GADD45A and its upstream gene NACC1,which provides a new drug,a new direction and a new method for the clinical treatment of HCC.

Chinese patent medicine (CPM) is an important part of traditional and Chinese medicine (TCM). Its quality has direct impact on the safety and effectiveness of clinical use. The quality standard is the pivotal approach to guarantee the quality of CPM. Due to the complex material basis, multitudinous quality influencing factors and unveiled active ingredients, dose-effect relationship and action mechanism, the investigation on quality standard faces many difficulties. This paper surveys the current quality status of CPM and the general situation of CPM standards. At present, the dosing problem has the crucial impact on the quality of CPM. The current quality standard system of CPM is confirmed and the limitations are indicated. Based on the above analysis, the principles and considerations on investigation of quality standard are proposed as follows: ① Adhere to safety as the bottom line, strengthen the risk-control ability of the standard of CPM; ② Adhere to theory of TCM and comprehensive quality, improve the integrative control level of the CPM standard; ③ Emphasize technological development and innovation, promote the quality control competence of CPM standard; ④ Facilitate planning and coordination, optimize the management of the CPM standard system; ⑤ Reinforce investigation on evaluation method, develop grade evaluation standard, accelerate high-quality development of CPM. Finally, the future perspective on investigation of CPM quality standard is prospected.