ObjectiveTo investigate the current situation of mutual recognition for ethical review outcomes in multicenter clinical research across 10 contracting medical institutions in Guangdong Province， analyze existing issues and propose improvement recommendations， thereby promoting the standardized management of mutual recognition for ethical review outcomes in medical institutions. MethodsData from 381 multicenter clinical studies conducted in these 10 medical institutions from January 24 to October 31， 2024， were collected. Text visualization was performed using Python and the WordCloud library， and statistical analyses were conducted with SPSS 25.0. ResultsOf the 381 studies investigated， industry-sponsored clinical trials （ISTs） accounted for 51.71%， while investigator-initiated clinical trials （IITs） constituted 48.29%. The proportions of ethical committees serving as primary reviewers and collaborative reviewers were 33.33% and 66.67%， respectively. The confirmation methods of mutual recognition outcomes were primarily expedited reviews （50.66%） and meeting reviews （49.34%）， and no cases of “direct confirmation” were found. The Chi-square test revealed statistically significant differences in review confirmation methods based on project type （χ²=14.851， P<0.001） and ethics committee role （χ²= 69.435， P<0.001）. The frequency distribution trend of the contingency table showed that IST projects and primary ethics committees preferred to employ meeting review （58.88% and 79.53% respectively， both higher than the average level of 49.34%）， while IIT projects and the collaborative ethics committees more frequently utilized expedited review （60.87% and 65.75% respectively， both higher than the average level of 50.66%）. ConclusionThe confirmation methods of mutual recognition for ethical review outcomes in multicenter clinical research are significantly associated with the role of the ethics committee and the type of project. It is recommended to improve management systems， enhance information construction and personnel training， as well as clarify mutual recognition responsibilities and strengthen supervision. This aims to ensure review quality while improving mutual recognition efficiency， thereby safeguarding the rights and interests of research participants.

Objective: To explore the relationship between non suicidal self injury (NSSI) behavior and serum lipid levels as well as thyroid function among college students with depression. Methods: A total of 169 college students with depression in the psychiatry departments of tertiary hospitals (grade 3A and 3B) in Ningbo from December 2023 to April 2025 were selected. The Adolescent Self injury Scale (ASIS) was used to assess the presence of NSSI, and participants were accordingly divided into a NSSI group ( n =51) and a non NSSI group ( n =118). General demographic data (including gender, age, and family situation) were collected from both groups. Blood tests were performed to measure lipid profiles [triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C)] and thyroid hormones [triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH)]. Multivariate Logistic regression was employed to analyze risk factors for NSSI, and receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of serum lipid and thyroid hormone levels for NSSI occurrence in college students with depression. Results: The levels of TC, LDL-C, and TSH in the NSSI group were (4.02±0.73) mmol/L, (2.32±0.36) mmol/L, and (6.57±1.95) mU/L , which were significantly higher than those in the non NSSI group [(3.41±0.56) mmol/L, (2.00±0.27) mmol/L, and ( 4.48± 1.09) mU/L, respectively] ( t =5.32, 5.60, 7.20, all P <0.05). Logistic regression analysis revealed that college students from single parent/reconstituted families, those who had experienced school bullying, and those with higher levels of TC, LDL-C, and TSH had a significantly increased risk of engaging in NSSI ( OR =5.22, 6.12, 5.90, 83.64, 3.64, all P <0.05). ROC curve analysis demonstrated that the combined detection of TC, LDL-C, and TSH had high diagnostic efficacy for predicting NSSI in college students with depression, with a sensitivity of 86.3% and a specificity of 94.9%. Conclusions NSSI behavior in college students with depression is associated with serum lipid levels and thyroid function. These biomarkers may serve as useful reference indicators for assessing the conditions of these patients.

BackgroundPersistent cognitive impairment is prevalent among patients with stable schizophrenia. While serum total bile acid （TBA） level in acute-phase patients are known to be associated with cognitive dysfunction， the relationship between serum TBA and multi-dimensional cognitive functions in stable phase patients remains unclear. ObjectiveTo investigate the correlation between serum TBA level and cognitive function in patients with stable schizophrenia， and to evaluate its predictive value for cognitive impairment， thereby providing a serological biomarker for the timely identification and objective assessment of cognitive dysfunction. MethodsA cross-sectional study was conducted on 137 inpatients with stable schizophrenia at The Fourth People's Hospital of Yancheng from March to December 2024. All participants met the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）. Cognitive function was evaluated using the Chinese Brief Cognitive Test （C-BCT）， patients were categorized into four groups： normal cognition （n=28）， mild impairment （n=28）， moderate impairment （n=47）， and severe impairment （n=34）. Fasting venous blood samples were collected， and serum TBA level was quantified using an enzymatic cycle assay. Spearman correlation analysis was ultilized to determine the relationship between serum TBA level， overall cognitive function， and specific cognitive domains. Binary Logistic regression model was used （adjusting for covariates such as age， gender， and disease duration） to analyze the impact of serum TBA level on overall and individual cognitive functions. The predictive value of serum TBA level for overall cognitive impairment was evaluated using receiver operating characteristic （ROC） curve. ResultsSerum TBA levels differed significantly among the four groups （H=18.677， P<0.01）. Specifically， serum TBA levels in both the moderate and severe cognitive impairment groups were significantly higher than those in the normal cognitive group （adjusted P<0.01）. Serum TBA level was positively correlated with the severity grading of overall cognitive impairment （r_s=0.354， P<0.05）， and negatively correlated with T-scores on the trail making test （r_s=-0.328， P<0.05）， continuous performance test （r_s=-0.247， P<0.05）， digit span （r_s=-0.265， P<0.05）， and symbol coding （r_s=-0.221， P<0.05）. Binary Logistic regression analysis identified serum TBA level as an independent risk factor for overall cognitive impairment （OR=1.322， 95% CI： 1.021 - 1.713， P=0.034）， with a particularly robust predictive ability for impaired information processing speed （OR=1.325， 95% CI： 1.057 - 1.661， P=0.015）. The area under ROC curve （AUC） for serum TBA level in predicting overall cognitive impairment was 0.738， with a sensitivity of 60.61% and a specificity of 78.64%. ConclusionIn patients with stable schizophrenia， elevated serum TBA levels are associated with worse overall cognitive function， as well as deficits in information processing speed， attention， working memory， and executive function. Serum TBA serves as an independent risk factor and exhibits moderate predictive value for overall cognitive impairmen，particularly in the domain of information processing speed. ［Funded by Yancheng Municipal Health Commission Medical Research Project （number， YK2024141）］

Objective To explore the risk factors of painful diabetic neuropathy (PDN) in patients with type 2 diabetes mellitus (T2DM). Methods A total of 269 patients with type 2 diabetes mellitus (T2DM) who were treated in the Department of Endocrinology at Zhangjiagang Hospital Affiliated to Soochow University from January 2020 to December 2024 were selected. The patients were divided into two groups: T2DM without PDN (n=190) and T2DM with PDN (n=79). The general characteristics and biochemical indicators of the two groups of patients were compared. Multivariate logistic regression was used to analyze the associated factors with PDN in T2DM. The receiver operating characteristic (ROC) curve was used to evaluate fasting C-peptide (FC-P), body mass index (BMI), and disease duration to predict the risk of PDN. Results Compared with the T2DM group without concurrent PDN, the T2DM group with concurrent PDN had a longer disease course, lower BMI, higher HDL-C, lower FC-P, and a higher proportion of diabetic retinopathy. The differences between the two groups were statistically significant (P<0.05). The results of multivariate logistic regression analysis showed that BMI, duration, and FC-P were associated factors of PDN. Conclusion BMI, duration and FC-P are associated factors of painful neuropathy complicated with type 2 diabetes.

Objective: Scutellarin in Shuganning injection has potential allergenicity and is prone to causing anaphylactoid reactions. There is an urgent need to establish a simple and rapid chromatographic quantitative method to achieve the limit control of scutellarin in Shuganning injection.
Methods: For scutellarin, HPLC method was used in the quantitative analysis using a Shim-pack GIS C₁₈ (2.1 mm×150 mm, 5 μm) column. The mobile phase was a blend of 0.1% trifluoroacetic acid in water and acetonitrile, and gradient elution progress was applied for the whole process. The flow rate was 0.3 mL·min^-1 and the column temperature was maintained at 37 ℃. The detecting wavelength was 320 nm.
Results: The linear regression equation was y=51 456x-27 352, the correlation coefficient r=0.999 8, namely the calibration curve was linear in the range of 1.02-102.00 μg·mL^-1; the average recovery was 103.76%; the detection and quantification limit for determining scutellarin was 0.16 μg·mL^-1 and 0.57 μg·mL^-1, respectively; the injection sample was stable at room temperature for 48 h.
Conclusion: This method is easy to operate, reproducible and has high accuracy, thus can be used for quality control of Shuganning injection.

ObjectiveTo systematically review the association between non-alcoholic fatty liver disease （NAFLD） and depression， and to provide a basis for synergistic management in clinical practice. MethodsThis study was conducted according to the PRISMA guidelines， with the PROSPERO registration number of CRD42023482013. PubMed， Embase， the Cochrane Library， Web of Science， CNKI， Wanfang Data， VIP， and CBM were searched for articles on the association between NAFLD and depression published up to November 1， 2024. The articles were screened according to the inclusion and exclusion criteria， and related data were extracted. RevMan 5.3 was used to perform the Meta-analysis. ResultsA total of 18 studies were included， involving 396 793 participants. Among these studies， 12 discussed the influence of NAFLD on depression， involving 224 269 participants， among whom there were 75 574 patients with NAFLD. The Meta-analysis showed that NAFLD was significantly associated with the risk of depression （odds ratio ［OR］=1.21， 95% confidence interval ［CI］： 1.12 — 1.30， P0.001）. Six studies examined the influence of depression on NAFLD， involving 172 524 participants， among whom there were 29 368 patients with depression. The meta-analysis showed that depression caused a significant increase in the risk of NAFLD （OR=1.13， 95%CI： 1.05 — 1.22， P=0.001）. ConclusionThere is a significant bidirectional association between NAFLD and depression. It is recommended to perform the screening for depression and enhance mental health monitoring in patients with NAFLD， and metabolic function assessment and exercise intervention should be performed for patients with depression.

OBJECTIVE To compare the predictive accuracy and clinical applicability of four vancomycin individualized dosing tools （SmartDose， ClinCalc， Gulou， Pharmado） and provide a basis for rational clinical medication use. METHODS A retrospective cohort study was conducted， enrolling 479 adult patients who received vancomycin therapy and underwent steady-state trough concentration monitoring in Zhongshan Hospital， Fudan University （Xiamen Branch） from January 1， 2022， to June 30， 2024. The predictive accuracy of each tool was evaluated using indicators， such as mean error （ME）, mean absolute error （MAE）， mean percentage error （MPE）， mean absolute percentage error （MAPE）， the proportion of patients with an absolute percentage error （APE） of less than 30%， the 95% limits of agreement， and the overall relative percentage difference between predicted and measured values. Using indicators such as accessibility， patient management， and recommendation of multiple treatment options， the clinical panxso@163.com applicability of the tools for all patients was evaluated； using the discrepancy in accuracy between the predicted and actual measured blood drug concentrations as an indicator， the clinical applicability was assessed for patients in different renal function subgroups （hyperfunction， normal， mild impairment， moderate impairment， and severe impairment）. RESULTS In terms of accuracy， SmartDose demonstrated the best overall performance with an MAPE of 46.40% and a proportion of APE ＜30% （46.56%）. Bland-Altman analysis indicated that SmartDose had the smallest overall relative percentage difference （－7.25%）， although the 95% limits of agreement were broad for all tools， with differences between the upper and lower limits exceeding 200%. In terms of applicability， all four dosing tools were freely accessible and demonstrated good availability； SmartDose and Pharmado provided the most comprehensive solutions， offering features such as patient management， multiple regimen recommendations， and drug concentration-time curve plotting. Stratified analysis based on renal function revealed that Pharmado showed optimal prediction for hyperfiltration patients （mean difference： 0.11 mg/L）. SmartDose and ClinCalc showed relatively better performance in normal and mild renal impaiment （mean difference： 0.37， 0.51 mg/L and －1.13， －1.33 mg/L，respectively）. SmartDose performed best in moderate renal impairment （mean difference： －2.60 mg/L）. Pharmado and Gulou had smaller prediction biases in severe renal impairment （mean differences： 1.52 mg/L and －0.23 mg/L， respectively）. CONCLUSIONS The four individualized dosing tools demonstrated limited accuracy in the initial prediction of vancomycin concentrations. Among them， SmartDose demonstrates the highest overall prediction accuracy and possesses comprehensive clinical management features. It is recommended that Pharmado be preferred for patients with renal hyperfiltration； SmartDose or ClinCalc can be used for patients with normal or mildly impaired renal function； SmartDose is recommended for patients with moderately impaired renal function； Pharmado or Gulou may be considered for patients with severely impaired renal function.

Haematitum and Limonitum are two iron-containing mineral medicines included in the 2020 edition of the Chinese Pharmacopoeia. They have similar main components and major differences in their property, flavor, channel tropism, and clinical uses. In this study, we investigated the surface properties, mineral composition, mineral dissociation, elemental composition, and iron state of Haematitum and Limonitum to explore their mineralogical differences. Scanning electron microscopy(SEM), specific surface and porosity analyzer, X-ray diffractometer(XRD), X-ray photoelectron spectrometer(XPS), and advanced mineral identification and characterization system(AMICS) were used to analyze the mineralogy of Haematitum and Limonitum. The results showed that Haematitum had an angular surface with granular attachments and a specific surface area of 17.04 m~2·g~(-1). In comparison, Limonitum had a smooth and flat surface with a bundled acicular crystal structure and a specific surface area of 46.29 m~2·g~(-1). Haematitum consists of 31 detectable minerals containing 18 elements, with the major element, iron(44.5% Fe~(2+) and 55.5% Fe~(3+)) distributed in 17 minerals, including hematite, iron oxide, knebelite, siderite, and magnesioferrite. Limonitum consists of 32 detectable minerals containing 17 elements, with the major element, iron(14.5% Fe~(2+) and 85.5% Fe~(3+)) distributed in 19 minerals, including limonite, iron oxide, chlorite, and knebelite. In summary, the elemental composition of Haematitum and Limonitum does not differ greatly, but there are large differences in the mineral composition and iron state. The large specific surface area and strong adsorption capacity of Limonitum may be one of the mechanisms of its anti-diarrheal action. The Fe_2O_3 and illite contained in Haematitum and Limonitum may be the key substances for their hemostasis effects. The mineralogical differences are expected to provide a reference for explaining the scientific connotation of mineral medicine and laying a material foundation for studying its mechanism of action.
Iron/analysis* ; Minerals/chemistry* ; Drugs, Chinese Herbal/chemistry* ; X-Ray Diffraction ; Microscopy, Electron, Scanning ; Photoelectron Spectroscopy