This study applied the grading of recommendations assessment, development and evaluation(GRADE) system and the integrated evidence chain-based effectiveness evaluation of traditional Chinese medicine(Eff-iEC) to evaluate the evidence for 12 commonly used Chinese patent medicines for the treatment of osteoporosis, which are frequently recommended in guidelines or expert consensuses. The results showed that Xianling Gubao Capsules/Tablets were rated as C(low-level evidence) according to the GRADE system, and as BA~+B~+(intermediate evidence) according to the Eff-iEC system. Jintiange Capsules were rated as C(low-level evidence) by the GRADE system, and as AA~+B(high-level evidence) by the Eff-iEC system. Gushukang Granules/Capsules were rated as C(low-level evidence) by GRADE system, and as BA~+B~+(intermediate evidence) by Eff-iEC system. Zuogui Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Qianggu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B~+(high-level evidence) by Eff-iEC system. Zhuanggu Zhitong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BA~+B(intermediate evidence) by Eff-iEC system. Jingui Shenqi Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B(high-level evidence) by Eff-iEC system. Quanduzhong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AD~+B~+(low-level evidence) by Eff-iEC system. Epimedium Total Flavones Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AAB~+(high-level evidence) by Eff-iEC system. Yougui Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~(++)B~(+ )(high-level evidence) by Eff-iEC system. Qigu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BB~+B(intermediate evidence) by Eff-iEC system. Liuwei Dihuang Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Overall, the Eff-iEC system provides a more comprehensive assessment of the effectiveness evidence for traditional Chinese medicine(TCM) than the GRADE system. However, it still has certain limitations that hinder its wider promotion and application. In terms of clinical evidence evaluation, both the Eff-iEC and GRADE systems reflect that the current clinical research quality on Chinese patent medicines for the treatment of osteoporosis is generally low. High-quality clinical trials are still needed in the future to further validate clinical efficacy.
Drugs, Chinese Herbal/therapeutic use* ; Osteoporosis/drug therapy* ; Humans ; Nonprescription Drugs/therapeutic use* ; Evidence-Based Medicine ; Medicine, Chinese Traditional

OBJECTIVE: To investigate the common mechanisms among collagen-induced arthritis (CIA), bleomycin (BLM)-induced pulmonary fibrosis, and CIA+BLM to evaluate the therapeutic effect of triptolide (TP) on CIA+BLM. METHODS: Thirty-six male Sprague-Dawley rats were randomly assigned to 6 groups according to a random number table (n=6 per group): normal control (NC), CIA, BLM, combined CIA+BLM model, TP low-dose (TP-L, 0.0931 mg/kg), and TP high-dose (TP-H, 0.1862 mg/kg) groups. The CIA model was induced by intradermal injection at the base of the tail with emulsion of bovine type II collagen and incomplete Freund's adjuvant (1:1), with 200 µL administered on day 0 and a booster of 100 µL on day 7. Pulmonary fibrosis was induced via a single intratracheal injection of BLM (5 mg/kg). The CIA+BLM model combined both protocols, and TP was administered orally from day 14 to 35. After successful modeling, arthritis scores were recorded every 3 days, and pulmonary function was assessed once at the end of the treatment period. Lung tissues were collected for histological analysis (hematoxylin eosin and Masson staining), immunohistochemistry, measurement of hydroxyproline (HYP) content, and calculation of lung coefficient. In addition, HE staining was performed on the ankle joint. Total RNA was extracted from lung tissues for transcriptomic analysis. Differentially expressed genes (DEGs) were compared with those from the RA-associated interstitial lung diseases patient dataset GSE199152 to identify overlapping genes, which were then used to construct a protein-protein interaction network. Hub genes were identified using multiple topological algorithms. RESULTS: The successfully established CIA+BLM rat model exhibited significantly increased arthritis scores and severe pulmonary fibrosis (P<0.01). By intersecting the DEGs obtained from transcriptomic analysis of lung tissues in CIA, BLM, and CIA+BLM rats with DEGs from rheumatoid arthritis-interstitial lung disease patients (GSE199152 dataset), 50 upregulated and 44 downregulated genes were identified. Through integrated PPI network analysis using multiple topological algorithms, IGF1 was identified as a central hub gene. TP intervention significantly improved pulmonary function by increasing peak inspiratory flow (P<0.01), and reduced lung index and HYP content (P<0.01). Histopathological analysis showed that TP alleviated alveolar collapse, interstitial thickening, and collagen deposition in the lung tissues (P<0.01). Moreover, TP treatment reduced the expression of collagen type I and α-SMA and increased E-cadherin levels (P<0.01). TP also significantly reduced arthritis scores and ameliorated synovial inflammation (P<0.05). Both transcriptomic and immunohistochemical analyses confirmed that IGF1 expression was elevated in the CIA+BLM group and downregulated following TP treatment (P<0.05). CONCLUSION TP exerts protective effects in the CIA+BLM model by alleviating arthritis and pulmonary fibrosis through the inhibition of IGF1-mediated EMT.
Animals ; Pulmonary Fibrosis/complications* ; Bleomycin/adverse effects* ; Phenanthrenes/pharmacology* ; Male ; Rats, Sprague-Dawley ; Diterpenes/pharmacology* ; Epoxy Compounds/therapeutic use* ; Arthritis, Experimental/complications* ; Insulin-Like Growth Factor I/metabolism* ; Rats ; Lung/physiopathology*

Taxifolin (TAX) is a natural compound known for its liver protection effect, but the mechanism remains unknown. Phosphorylated proteomics analyses discovered that the phosphorylation level of NDRG1 at T328 was a key event of TAX-improved liver fibrosis. We established models with NDRG1 knockout (KO) in vivo and in vitro, demonstrating that NDRG1 KO attenuated the development of hepatocyte injury, and combining NDRG1 KO and TAX administration did not result in a reduction in protection against liver injury. Cellular thermal shift assay and surface plasma resonance analysis showed that TAX directly binds to NDRG1 rather than its upstream kinase, subsequently demonstrating that TAX regulated phosphorylation of NDRG1 at T328 through binding to its C289 site. NDRG1 T328A (phosphorylated mutation) and T328E (mimic phosphorylation) in vivo and in vitro confirmed that pNDRG1_T328 exacerbates hepatocyte injury along with DNA damage, inflammatory response, and apoptosis, thereby contributing to hepatic stellate cells (HSCs) activation. In contrast, TAX can inhibit the above pathological abnormalities and block hepatocyte injury-triggered HSCs activation and fibrosis. Overall, TAX is a potent liver protection drug primarily targeting NDRG1 and inhibiting pNDRG1_T328 in hepatocytes.

By summarizing the mass spectrometric fragmentation patterns of oxyphenisatin substances,an analytical method was established for screening of illegally added oxyphenisatin compounds in weight-loss health foods using high performance liquid chromatography-in-source-fragmentation-quadrupole time-of-flight mass spectrometry(HPLC-ISF-QTOF-MS),along with a quantitative method for 11 kinds of oxyphenisatin compounds.Based on the developed screening method,an oxyphenisatin derivative was discovered in the reference standards,which was tentatively identified as 4-(3-(4-hydroxyphenyl)-2-oxoindolin-3-yl)phenyl acetate and confirmed by MS/MS analysis.The results showed that all 11 kinds of oxyphenisatin compounds had correlation coefficients greater than 0.9971,with limits of detection(LODs)ranging from 0.12 to 0.68 μg/L and limits of quantification(LOQ)from 0.21 to 2.29 μg/L.The LODs for 11 kinds of characteristic ions ranged from 0.45 to 9.11 μg/kg.At spiking levels of 25,50 and 100 μg/kg,the recoveries ranged from 78.9%to 117.3%.The instrumental precision,intra-day method precision and inter-day method precision were 0.23%?1.70%,0.7%?2.4%,and 1.1%?3.3%,respectively.The developed targeted and non-targeted detection method demonstrated high sensitivity,strong stability,rapid analysis,and an expanded screening range for oxyphenisatin substances,and provided robust technical support for regulatory authorities in combating illegal adulteration.

Objective:To investigate the clinical characteristics of omphalocele, and to assess the risk factors associated with adverse outcomes.Methods:A retrospective cohort study was conducted. Clinical data of 224 patients diagnosed with omphalocele, who were hospitalized at Children′s Hospital, Zhejiang University School of Medicine from January 2013 to December 2022, were collected. Based on their discharge outcomes, the patients were classified into 2 groups: favorable outcomes and unfavorable outcomes. Chi-square test or continuity correction χ2 test or Fisher exact probability method, and Mann-Whitney U test were used for intergroup comparisons. Logistic regression analysis was performed to identify risk factors associated with adverse outcomes in omphalocele. Results:Among the 224 patients with omphalocele, 126 were male. A total of 208 patients (92.9%) had favorable outcomes, while 16 patients (7.1%) had unfavorable outcomes. In the unfavorable outcomes group, 14 patients had giant omphaloceles, while 100 patients had giant omphaloceles in the favorable outcomes group. The rates of herniation of more than two intra-abdominal organs in the hernial sac, congenital heart defects, patent ductus arteriosus, pulmonary hypertension, sepsis and infection of the hernial sac, were all higher in the unfavorable outcomes group compared to the favorable outcomes group (all P<0.05). Patients with unfavorable outcomes had longer mechanical ventilation time, duration of oxygen use, duration of parenteral nutrition, hospital stays, and higher rates of parenteral nutrition-associated cholestasis compared to those with favorable outcomes (all P<0.01). Multivariate Logistic regression analysis indicated that pulmonary hypertension ( OR=9.39, 95% CI 1.20-73.32), sepsis ( OR=8.59, 95% CI 1.32-55.86), and congenital heart defects ( OR=6.55, 95% CI 1.11-38.73) were all independent risk factors for adverse outcomes in omphalocele (all P<0.05). Conclusions:Infants with omphalocele are prone to complications such as cardiovascular malformations, infections, and pulmonary hypertension. Adverse outcomes in omphalocele are associated with pulmonary hypertension, sepsis, and congenital heart defects.

Cancer is one of the major diseases of high morbidity and mortality worldwide,and its therapeutic approaches are facing great challenges.Immunotherapy,especially the activation of innate immunity represented by the cGAS-STING signaling pathway,is the current research hotspot in tumor immunotherapy.Activation of innate immune response by gas therapy is the latest development in tumor therapeutic approaches,especially the use of gas signaling molecules(NOx CO,H2S and SO2)to activate the cGAS-STING signaling pathway to induce intrinsic immunity of the organism,which leads to anti-tumor immunotherapy.Although intrinsic immunity activated by gas signaling molecules plays an important role in tumor immunotherapy,few reviews have been reported on its association with the cGAS-STING signaling mechanism.In this paper,we will comprehensively describe how gas signaling molecules damage the mitochondrial matrix and DNA damage through oxidative/nitrosative stress,thereby activating the cGAS-STING signaling pathway and triggering the innate immune cascade,aiming to summarize the process of activation of anti-tumor immune effects by gas signaling molecules,and to provide more references for the gas therapies in the future anti-tumor immunity research.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective:To investigate the correlation between pathological features at the positive margins and biochemical re-currence after radical prostatectomy for prostate cancer.Methods:From June 2014 to December 2019,a total of 200 patients with organ-confined prostate cancer who underwent radical prostatectomy were included in this study by the method of case matching(1:1).One hundred patients with positive surgical margin and 100 with negative surgical margin were enrolled in this study.All patients did not receive any adjuvant treatment after surgery with a clinical stage of T2/N0.BCR-free survival was estimated using the Kaplan-Meier method.An optimal cutoff for the PSM length which differentiated risk for BCR was identified by Classification and Regression Tree analysis(CART).Cox proportional hazards regression model was used to assess the association between variables and BCR-free surviv-al.Results:A total of 200 patients were included in this study,and 177 patients with pT2 stage were pathological after operation.The median follow-up time of this group of patients was 32.8 months ranged from 5.6 to 80.5 months.A total of 28 cases of biochemi-cal recurrence were found through PSA follow-up after surgery,including 6 cases(6.0％)in the negative margin group and 22 cases(22.0％)in the positive margin group.The result of Kaplan Meier survival curve analysis showed that the non biochemical recurrence survival time of the negative margin group was longer than that of the positive margin group(log rank x2=9.336,P=0.003).It was found that the length of positive margin≥1 mm in the positive margin group was positively correlated with postoperative biochemical re-currence.Multivariate Cox proportional hazards regression was used to identify that the highest Gleason score ≥8 and the length of pos-itive ≥ 1 mm were independent factors of postoperative biochemical recurrence in both the overall patients and the patients with positive margin.Conclusion:The patients with highest Gleason score ≥8 and the length of positive ≥1mm are at elevated risk for BCR.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.