ObjectiveThis paper aims to clarify the material basis of Gualou Niubangtang and establish a quantitative analysis method for its main constituents， providing a reference for the overall quality control of this preparation. MethodsThe constituents in the formula were systematically characterized based on ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry （UPLC-Q-TOF-MS/MS）. Identification was performed by matching with the UNIFI 9.6 software and utilizing database platforms such as PubChem， ChemicalBook， and ChemSpider， combined with relevant literature reports. A quantitative analysis method for the seven main constituents in Gualou Niubangtang was established by using high performance liquid chromatography （HPLC）. ResultsUPLC-Q-TOF-MS/MS analysis identified 155 constituents， including 69 flavonoids， 36 terpenoids， 23 phenylpropanoids， 8 phenylethanoid glycosides， and 19 other types of constituents. In the established quantitative analysis method， the seven main constituents showed good linearity within their respective linear ranges. The precision， repeatability， stability， and spike recovery all met the required standards. The results showed that the content ranges of geniposide， liquiritin， hesperidin， arctiin， baicalin， oroxylin A-7-O-β-D-glucuronide， and wogonoside in 15 batches of Gualou Niubangtang were 13.67-21.25， 1.20-7.64， 5.45-7.45， 22.97-33.51， 29.95-39.07， 2.58-4.80， and 6.56-9.31 mg·g^-1， respectively. ConclusionThis study successfully characterizes and attributes multi-category constituents in Gualou Niubangtang， clarifying that its material basis is primarily composed of flavonoids， terpenoids， phenylethanoid glycosides， and phenylpropanoids. Furthermore， it enables the quantification of seven constituents within the formula. This work lays a foundation for research on the quality control， action mechanism， and clinical application of this formula.

Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

Objective:To analyze the preferences of medical staff in TCM hospitals in Beijing regarding the achievements transformation of hospital traditional Chinese medicine preparations,and to provide a reference for formulating incentive policies.Methods:233 medical staff from five TCM hospitals in Beijing were taken as the research objects,and surveyed with a questionnaire designed based on the discrete choice experiment(DCE).Mixed logit models and latent class models were then used to analyze their transformation preferences.Results:The mixed Logit model revealed that seven key attributes significantly influenced medical staff's preferences for the achievements transformation of traditional Chinese medicine preparations(P<0.05).Latent class analysis identified three distinct preference groups among respondents:an organization-dependent group(27.0%),a pro-transformation group(61.4%),and a conservative group(11.6%).Conclusions:Medical Staff preferred transformation conditions that increased monthly income;utilized"human use+re-experimentation";involved the hospital's achievements transformation department as the entity;were funded by the hospital;offered a 70%profit share;enabled promotion three years earlier,and assigned patents to the hospital.The study recommends implementing diverse incentive measures and developing differentiated strategies tailored to the distinct Medical Staff categories to facilitate the transformation of hospital traditional Chinese medicine preparations into new drugs.

Objective To explore the characteristics and influencing factors of drug-induced liver injury(DILI)associated with the postoperative use of propacetamol,and to provide guidance for rational clinical medication.Methods A retrospective analysis was conducted on hospitalized patients who underwent surgical treatment and were administered propacetamol from January 2022 to June 2024.Cases were screened based on established inclusion and exclusion criteria.Statistical analyses were performed on patients'demographic data,medication information,liver function indicators before and after medication,comorbid conditions,and concomitant medications to assess the incidence and influencing factors of propacetamol-related DILI.A multivariate Logistic regression analysis was conducted to identify related risk factors.Results A total of 7,579 patients were sampled,of which 2,114 met the inclusion criteria.Among them,531 patients(25.1%)experienced DILI,primarily presenting with abnormal liver function indicators.This included elevated alanine aminotransferase in 379 cases(71.4%),elevated aspartate aminotransferase in 197 cases(37.1%),elevated alkaline phosphatase in 209 cases(39.4%),and elevated total bilirubin in 92 cases(17.3%).Univariate analysis revealed that there were significant differences in gender,height,age,weight,body mass index(BMI),duration of propacetamol use,total medication dosage,concomitant use of hepatic-metabolized antibiotics,and history of liver disease between the DILI group and non-DILI group(P<0.05).Multivariate Logistic regression analysis showed that patient gender,BMI,total propacetamol dosage,liver-related diseases,and concomitant use of hepatic-metabolized antibiotics as independent risk factors for DILI(P<0.05).Conclusion The use of propacetamol for postoperative analgesia presents a risk for liver injury,and the risk is particularly pronounced in males,obesity,high-dose dosing,patients with underlying hepatic disease,and comorbid hepatic metabolism of antimicrobial drug use.It is recommended to strengthen the monitoring of liver function in clinical application,strictly control the dosage and duration of treatment,and avoid co-administration with hepatotoxic drugs to ensure the safety of drug use.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Objective:To study the role of cadherin 1 (CDH1) gene DNA methylation in autoimmune thyroiditis (AIT) in population from different water-iodine regions.Methods:From May to June 2019, the information of AIT cases and healthy individuals in Shandong Province were collected in three types of water-iodine regions: iodine-fortification (IF) region, iodine-adequate (IA) region and iodine-excess (IE) region. A case-control study design was applied to match 176 AIT cases (case group) with age, gender, body mass index, and place of residence in a 1 ∶ 1 ratio to 176 healthy individuals (control group). Fasting urine and whole blood samples were collected to test the contents of urinary iodine, thyroid function indicators [serum free triiodothyronine (FT 3), free thyroxine (FT 4), thyroid stimulating hormone (TSH)], and serum iodine. The DNA methylation levels of the target region of the CDH1 gene and its four CpG sites in whole blood were determined using methylation sequencing technology for target regions (MethylTarget TM). Results:The DNA methylation level of the target region of CDH1 gene in the case group was 0.832 ± 0.044, and that in the control group was 0.828 ± 0.049, there was no statistically significant difference between the two groups ( t = 0.76, P = 0.448). There was no statistically significant difference in DNA methylation levels of the four CpG sites in the target region of CDH1 gene between the case group and the control group ( P > 0.05). There was no statistically significant difference in the DNA methylation level of the CDH1 gene target region between the case group and the control group in IF, IA and IE regions ( P > 0.05). The detection results of DNA methylation levels at CpG sites in the target region of CDH1 gene in different water iodine regions showed that the DNA methylation level at site 83 in case group in IF region was higher than that in the control group ( t = 2.30, P = 0.023). However, there was no statistically significant difference in the DNA methylation levels of the four CpG sites between the case group and the control group in IA and IE regions ( P > 0.05). The DNA methylation level of CDH1 gene target region in AIT patients was not significantly correlated with urinary iodine, serum iodine, and serum FT 3, FT 4, and TSH contents ( P > 0.05), but was significantly negatively correlated with age ( r =-0.19, P = 0.014). Conclusions:The DNA methylation level at CpG site 83 of CDH1 gene in AIT patients in IF region is significantly higher than that in control population, indicating that DNA methylation at this locus may be involved in the occurrence and development of AIT after iodine fortification. The DNA methylation level of CDH1 gene is negatively correlated with age.

Objective:To investigate the distribution of iodine and other chemical elements in soil, grain and vegetables in different water iodine areas of Xi'an City, and to provide theoretical basis for prevention and treatment of iodine related diseases and water improvement measures.Methods:From September to November 2021, a stratified cluster sampling method was used to select three survey villages in Xi'an, namely Yehu Village, Xingbei Village, and Quanzhong Village, where the iodine level of residents' drinking water < 10, 10 - 100, and > 100 μg/L. Drinking water samples were collected from seven survey sites based on the source of domestic drinking water to determine the iodine level of the water. At the same time, soil samples of cultivated land, residents' grains (wheat, corn), and vegetables were collected from survey villages to determine the content of 14 elements including calcium, iron, magnesium, chromium, nickel, copper, zinc, cadmium, lead, arsenic, mercury, selenium, iodine, and fluoride.Results:The iodine level in the water of 7 survey sites in three survey villages was 5.80, 6.40, 25.51, 42.20, 53.90, 111.65, and 177.63 μg/L, respectively. A total of 70 samples of soil, 65 samples of wheat, 76 samples of corn, and 141 samples of vegetables were collected. Among them, the levels of various elements in vegetables and grains were lower than those in the soil. Only calcium and fluoride were higher in vegetables than in grains, while iron, chromium, copper, zinc, selenium, and iodine were lower in vegetables than in grains. According to the range of water iodine level, there were statistically significant differences in the content of calcium, iron, chromium, nickel, copper, zinc, mercury, iodine, and fluoride in soils from different water iodine regions ( Fcalcium, iron, chromium, nickel = 42.04, 13.55, 12.22, 11.20, Hcopper, zinc, mercury, iodine, fluoride = 14.27, 9.19, 14.72, 25.14, 16.50, P < 0.05). The comparison of magnesium, zinc, cadmium, arsenic, and selenium content in wheat showed statistically significant differences ( Fadmium, selenium = 6.34, 3.31, Hmagnesium, zinc, arsenic = 6.12, 11.55, 6.23, P < 0.05). The comparison of calcium, iron, magnesium, chromium, nickel, copper, zinc, cadmium, lead, arsenic, mercury, iodine, and fluoride content in corn showed statistically significant differences ( Fmagnesium, chromium, nickel, copper, zinc, iodine = 18.89, 13.76, 17.86, 24.17, 28.46, 15.96, Hcalcium, iron, cadmium, lead, arsenic, mercury, fluoride = 11.57, 40.53, 26.50, 33.05, 33.73, 36.01, 29.21, P < 0.05). The comparison of calcium, iron, magnesium, chromium, zinc, cadmium, lead, arsenic, mercury, and selenium content in vegetables showed statistically significant differences ( H = 23.93, 8.12, 10.03, 7.01, 16.09, 18.36, 23.07, 6.51, 27.67, 7.86, P < 0.05). Conclusions:There are significant differences in the distribution of 14 elements in soil, grain, and vegetables in different water iodine regions. In addition to drinking water, precise guidance should also be provided based on the iodine content in soil, grain, and vegetables in different water iodine areas.

Objective:To investigate the dynamic changes of serum long non-coding ribonucleic acid antisense non-coding RNA in the INK4 locus (LncRNA ANRIL), long non-coding ribonucleic acid maternally expressed gene 3 (LncRNA MEG3) and inflammatory factors [interferon-γ (IFN-γ), interleukin-6 (IL-6), interleukin-18 (IL-18) and interleukin-1β (IL-1β)] in patients with acute ischemic stroke and their correlation with neurological impairment.Methods:This prospective study included fifty-two patients with acute ischemic stroke admitted to the Central Hospital of Dalian University of Technology were included, and the neurological impairments of the patients were scored using the National Institutes of Health stroke scale (NIHSS) on the first day of the onset of the disease, and serum LncRNA ANRIL, LncRNA MEG3 and inflammatory factors (IFN-γ, IL-6, IL-18 and IL-1β) were detected using enzyme-linked immunosorbent assay (ELISA) at the first, second and seventh day of the onset of the disease. The correlation between serum LncRNA ANRIL, LncRNA MEG3 and inflammatory factor levels and neurological impairment at each time point was analyzed by Spearman correlation analysis.Results:Among 52 patients, mild group had 22 cases (NIHSS score <5 scores), and moderate-to-severe group had 30 cases (NIHSS score ≥5 scores). In acute ischemic stroke patients with moderate-to-severe group, the expression level of LncRNA MEG3 was higher than in the mild group, but the intergroup difference did not reach statistical significance ( P>0.05). LncRNA ANRIL, LncRNA MEG3, IFN-γ, IL-18 and IL-1β peaked at the same time point in acute ischemic stroke patients, all within second day of the onset of the disease. Spearman correlation analysis showed that the serum LncRNA MEG3 level on the first day of the onset of the disease was significantly positively correlated with NIHSS score ( P = 0.006), and serum LncRNA ANRIL level on seventh day was significantly positively correlated with NIHSS score ( P = 0.049). Conclusions:Serum LncRNA ANRIL, LncRNA MEG3 and inflammatory factors (IL-18, IL-1β and IFN-γ) are highly expressed in patients with acute ischemic stroke, peaking on the second day of onset. LncRNA MEG3 levels on the first day of onset and LncRNA ANRIL levels on the seventh day of onset are helpful in determining the degree of neurological impairment in patients with acute ischemic stroke.

Aim To investigate the effect of triptolide(TP)on corticosterone(CORT)-induced depression-like behaviors in mice and explore the antidepressant mechanism of TP based on the CREB/BDNF/TrkB sig-naling pathway.Methods Sixty 8-week-old male C57BL/6J mice were randomly divided into five groups:control group,CORT group,TP groups of low and high doses(10,30 μg·kg-1),and fluoxetine(FLU)group(10 mg·kg-1).Except for the control group,the other groups received subcutaneous injec-tions of CORT for three consecutive weeks to establish the model of depression.During the last two weeks of modeling,normal saline,TP and FLU were adminis-tered via intraperitoneal injection respectively.After the administration,depression-like behaviors in mice were assessed using forced swimming test,tail suspen-sion test,and sucrose preference test.Biochemical methods were used to measure the levels of SOD and MDA in the hippocampus and prefrontal cortex(PFC).Cell apoptosis was detected by TUNEL meth-od.Immunohistochemistry,immunofluorescence,and Western blotting were employed to detect the expres-sion of apoptosis/autophagy-related proteins,synaptic structure markers,and proteins related to the CREB/BDNF/TrkB signaling pathway.Results TP signifi-cantly ameliorated CORT-induced depression-like be-haviors in mice,mainly manifested by reduced immo-bility time in the tail suspension test and forced swim-ming test,and increased sucrose preference rate.TP alleviated CORT-induced oxidative stress by increasing SOD levels and reducing MDA production in brain tis-sue.Additionally,TP also inhibited apoptosis and ex-cessive autophagy of neurons in the hippocampus and prefrontal cortex,maintained synaptic plasticity,and significantly upregulated the expression of p-CREB,BDNF,and TrkB.Conclusions TP exhibits potential antidepressant effect in mice by upregulating the CREB/BDNF/TrkB signaling pathway,reducing oxida-tive stress,inhibiting excessive neuronal apoptosis and autophagy,and improving synaptic plasticity.