High-throughput sequencing-based high-throughput screening （HTS²） technology， as a new advancement in the field of high-throughput biotechnology， is the world's first technology to integrate high-throughput sequencing into large-scale drug screening and target discovery. The artificially designed DNA probes were bound to the undetermined mRNAs of thousands of genes in cell lysates， and then the probes were ligated with ligases. The large-scale simultaneous detection of gene expression changes in thousands of drug-treated cell samples was performed using barcoding， automated operating platforms， and high-throughput sequencers. This technology enables high-throughput identification of drugs that significantly perturb the gene expression profiles characteristic of diseases. It can also take gene expression signature as the readout and exert great high-throughput advantages in the screening of multi-drug， multi-component， and multi-target drugs， as well as the research on complex mechanisms. Therefore， it is particularly suitable for elucidating the multi-target mechanisms of traditional Chinese medicine and identifying its multi-effective components. Its main technical advantages include high throughput， automation， and low cost. In recent years， HTS² technology has yielded important achievements in the elucidation of the mechanism of action of traditional Chinese medicine formulas， the scientific connotation analysis of the regional characteristics of traditional Chinese medicine， the targeted isolation of active compounds of traditional Chinese medicine， and the discovery of novel pharmacological functions of monomeric compounds of traditional Chinese medicine. In the era of artificial intelligence， HTS² technology will serve as a powerful tool for generating high-quality， original big data of traditional Chinese medicine， providing core data support and promoting AI-driven traditional Chinese medicine research. Ultimately， HTS² technology offers new strategies and critical data support for deeply analyzing the scientific connotation of traditional Chinese medicine and discovering novel traditional Chinese medicine-based drugs， thereby accelerating the modernization and internationalization of traditional Chinese medicine in China.

To summarize the clinical characteristics and genetic mutation spectrum of patients with SELENON-related myopathy(SELENON-RM), in order to improve awareness among physicians.

[Purpose]To evaluate the liver and kidney safety of traditional Chinese medicine(TCM)compounds in the treatment of gastric cancer.[Methods]The clinical data of gastric cancer patients who attended in Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from January 2012 to February 2022 were collected.The results of liver and renal func-tion tests were rated according to National Cancer Institute-Common Terminology Criteria for Ad-verse Events(NCI-CTCAE)V5.0.The patients were divided into 4 groups:TCM group,TCM+chemotherapy/targeted/antivascular therapy group,TCM+TCM preparation group and TCM+chemotherapy/targeted/antivascular therapy+TCM preparation group,and the effects of TCM on liver and renal functions were analyzed.[Results]A total of 7 943 patients were included in the analysis,of which 2 941 cases receiving TCM ≥12 months,1 468 months ≥36 months,and 687 months≥60 months.The highest incidence rate of liver function abnormality was 13.71％,the highest in-cidence rate of grade 3/4 abnormality was 2.58％;the highest incidence of creatinine abnormality was 2.32％,the highest incidence rate of grade 3/4 abnormality was 0.37％in patients with differ-ent duration of taking TCM.Most of liver and renal function abnormalities occurred in the early stage of drug taking.The incidence of liver and renal function abnormalities in the TCM group was lower than that of the other three groups.The incidence of grade 3/4 abnormality for direct biliru-bin(DBIL)in the TCM group was 0.14％,for aspartate transaminase(AST)was 0.11％,for alka-line phosphatase(ALP)was 0.16％,for alanine aminotransferase(ALT)was 0.06％and for total bilirubin(TBIL)was 0.07％,and there was no grade 3/4 creatinine abnormality observed.The ab-normal liver and renal function indexes were not increased with the increase of the length of herbal medicine taking.[Conclusion]The study shows that long term taking TCM drugs and stan-dardized prescriptions for gastric cancer patients are safe.

Objective To explore the diagnostic value of a combined model based on clinicopathological and MRI features in BRCA-mutated ovarian cancer.Methods The data of 132 patients with ovarian cancer who underwent pathology and BRCA gene tes-ting were analyzed retrospectively,including 52 cases of BRCA mutation group and 80 cases of BRCA wild group.The differences of MRI features and clinicopathological features between BRCA mutation group and BRCA wild group were compared.Binary logistic regression was used to construct a joint prediction model and analyze its diagnostic efficiency.Results There were significant differ-ences in cytokeratin 7(CK7),estrogen receptor(ER),Ki-67 and lymphovascular invasion(LVI)between the BRAC mutation group and the BRAC wild group(P＜0.05).Univariate analysis showed that CK7,ER,Ki-67,LVI and the apparent diffusion coefficient(ADC)value of the cystic part of tumor were risk factors for BRCA-mutated ovarian cancer.The combined model based on CK7,ER,Ki-67,LVI,and the ADC value of the cystic part of tumor for the diagnosis of BRCA-mutated ovarian cancer had an area under the curve(AUC)of 0.765.Conclusion CK7,ER,Ki-67,LVI and the ADC value of the cystic part of tumor are risk factors for BRCA-mutated ovarian cancer.The combined model based on the above characteristics demonstrates good diagnostic efficacy for BRCA-mutated ovarian cancer.

Objective To explore the influencing factors of immune-associated thyroid dysfunction caused by sintilimab treatment in solid tumors and construct a prediction model.Methods Medical records of patients diagnosed with solid tumors and treated with sintilimab at Peking University People's Hospital(Xizhimen Campus,Tongzhou Campus,Shijiazhuang Campus)from January 2023 to September 2024 were collected to explore the influencing factors that caused immune-related thyroid dysfunction using univariate and multifactorial binary logistic regression analyses and to establish a prediction model.The predictive effect of the model was assessed using the receiver operating characteristic(ROC)curve.Results A total of 120 patients were included,and 33 presented with immune-related thyroid dysfunction.Multifactorial logistic regression analysis revealed that thyroid-stimulating hormone(TSH)[OR=2.470,95%CI=(1.279,4.771)]and treatment cycles[OR=1.298,95%CI=(1.117,1.509)]were independent risk factors for the occurrence of immune-associated thyroid dysfunction,and the difference was statistically significant(P＜0.05).The area under the ROC curve was(0.897±0.043)[95%CI=(0.813,0.981)],the Yoden index was 0.703,and the model prediction accuracy was 86.5%.Conclusion The risk of immune-related thyroid dysfunction caused by sintilimab is high,and TSH and treatment cycle are the influencing factors,and the constructed model has certain predictive value and is of reference significance.

Objective To evaluate drug-related problems(DRPs)and to analyze the influencing factors of patients un-dergoing video-assisted thoracoscopic surgery(VATS)before operation in thoracic surgery.Methods Clinical pharmacists used the Pharmaceutical Care Network Europe(PCNE)classification system(version 9.1)to analyze DRPs and influencing fac-tors of patients who received VATS from March 1 to May 31,2023,and had at least one comorbidity.Results Out of 300 pa-tients,174 were involved in a total of 200 DRPs.The most common category of DRPs is treatment safety(47.50％),followed by treatment effectiveness(46.00％)and others(6.50％).The most common cause of the problem is drug selection(33.83％),fol-lowed by other(33.33％)and patient cause(19.90％).367 interventions were conducted for DRPs,with the most interventions being at the drug level(55.86％),followed by the doctor level(39.24％)and the patient level(3.54％).In the end,96.00％of the intervention plan was accepted,and 86.50％of the problems were resolved.There were significant differences(P＜0.05)in the number of underlying diseases,medication varieties,body mass index(BMI),and length of hospital stay between the group with and without DRPs.The results of multivariate analysis showed that comorbidities,number of medication types,and BMI were independent risk factors for preoperative occurrence(or potential)of DRPs in VATS patients in thoracic surgery(OR＞1,P＜0.05).Conclusions Clinical pharmacists can effectively evaluate preoperative DRPs in patients undergoing VATS in thoracic surgery through the PCNE classification system.Comorbidities,number of medications,and BMI are influential factors for the oc-currence of preoperative DRPs.Future clinical practice should focus on these risk factors to optimize treatment strategies and re-duce the occurrence of DRPs.

Objective To explore the efficacy of a model combining clinicopathological characteristics and multiparametric MRI features for predicting BRCA-mutated breast cancer(BC).Methods A total of 256 BC patients were retrospectively selected and divided into BRCA mutation group(116 cases)and BRCA wild group(140 cases)based on the BRCA results.Chi-square tests or independ-ent sample t-tests were used to compare the differences in clinicopathological characteristics and multiparametric MRI features between the BRCA mutation group and the wild group.Risk factors for BRCA-mutated BC were identified through univariate and multivariate logistic regression ananlyses,and a combined predictive model was constructed.Receiver operating characteristic(ROC)curve was used to ana-lyze the diagnostic efficacy of the model.Results There were statistically significant differences in T stage,human epidermal growth factor receptor 2(HER-2),Ki-67,non-mass enhancement,enhancement pattern,time-signal intensity curve(TIC)type,and apparent diffusion coefficient(ADC)values between the BRCA mutation group and the wild group.Univariate logistic regression analysis showed that T stage,HER-2,Ki-67,non-mass enhancement,enhancement pattern,TIC type,and ADC values were risk factors for BRCA-mutated BC(P<0.05).Multivariate logistic regression analysis revealed that T stage,HER-2,Ki-67,enhancement pattern,and TIC type were independent risk factors for BRCA-mutated BC(P<0.05).The combined model incorporating T stage,HER-2,Ki-67,enhancement pattern,and TIC type had the best diagnostic efficacy in predicting BRCA-mutated BC,with an area under the curve(AUC)of 0.751.Conclusion The combined model integrating T stage,HER-2,Ki-67,enhancement pattern,and TIC type has good efficacy in predicting BRCA-mutated BC.

Objective To explore the influencing factors of immune-associated thyroid dysfunction caused by sintilimab treatment in solid tumors and construct a prediction model.Methods Medical records of patients diagnosed with solid tumors and treated with sintilimab at Peking University People's Hospital(Xizhimen Campus,Tongzhou Campus,Shijiazhuang Campus)from January 2023 to September 2024 were collected to explore the influencing factors that caused immune-related thyroid dysfunction using univariate and multifactorial binary logistic regression analyses and to establish a prediction model.The predictive effect of the model was assessed using the receiver operating characteristic(ROC)curve.Results A total of 120 patients were included,and 33 presented with immune-related thyroid dysfunction.Multifactorial logistic regression analysis revealed that thyroid-stimulating hormone(TSH)[OR=2.470,95%CI=(1.279,4.771)]and treatment cycles[OR=1.298,95%CI=(1.117,1.509)]were independent risk factors for the occurrence of immune-associated thyroid dysfunction,and the difference was statistically significant(P＜0.05).The area under the ROC curve was(0.897±0.043)[95%CI=(0.813,0.981)],the Yoden index was 0.703,and the model prediction accuracy was 86.5%.Conclusion The risk of immune-related thyroid dysfunction caused by sintilimab is high,and TSH and treatment cycle are the influencing factors,and the constructed model has certain predictive value and is of reference significance.

ObjectiveTo investigate the pathogenic spectrum and epidemiological characteristics of diarrheal disease in Fengxian District of Shanghai, and to provide scientific basis for the prevention and control of diarrheal diseases. MethodsBasic information of the initial adult cases visited diarrheal disease surveillance sentinel hospital in Fengxian District, Shanghai, was collected from August 2013 to 2023, and fecal samples were collected at 1∶5 sampling intervals to isolate and identify 5 kinds of diarrheagenic Escherichia coli (DEC), Salmonella (SAL), Vibrio parahaemolyticus, Campylobacter, Vibrio cholerae, Shigella and Yersinia enterocolitica (YE). Simultaneously, nucleic acid detection was performed for 3 kinds of rotavirus, 2 kinds of norovirus, intestinal adenovirus, astrovirus and sapovirus. ResultsA total of 1 861 cases of newly diagnosed diarrheal disease were reported, with the peak in July to August. Additionally, 704 surveillance samples were detected, with a total positive detection rate of 50.57%. The detection rates of bacterial, viral and mixed infection were 25.14%, 21.02% and 4.40%, respectively. Among the pathogens detected, DEC accounted for the highest (17.61%, 124/704), followed by norovirus (16.48%, 116/704), rotavirus (6.39%, 45/704), SAL (5.97%, 42/704) and Campylobacter (3.84%, 27/704). DEC detected were mainly enteroaggregative Escherichia coli and enterotoxigenic Escherichia coli, with no detection of Vibrio cholerae, Shigella and YE. The highest total pathogen detection rate was observed from June to September, and the detection peaks of norovirus were from March to June and from October to December, whereas that of DEC was from June to October. The detection rate of rotavirus peaked from January to February, but which was not detected between 2020‒2023. The SAL positive rate peak was in September, whereas that of Campylobacter was from July to September. ConclusionThe main pathogens detected in Fengxian District from 2013‒2019 are DEC, norovirus, rotavirus, SAL and Campylobacter. Different pathogens have different detection peaks, with bacteria predominating in summer and viruses in winter and spring. Prevention and control measures should be carried out according to the epidemiological characteristics of different seasons.

Objective To explore the potential prognostic factors of patients with acute ischemic stroke(AIS)after undergoing endovascular mechanical thrombectomy and to construct an effective predictive model.Methods A retrospective analysis of clinical data was conducted on 202 patients with anterior circulation large vessel occlusion AIS from 2 stroke centers.All patients received endovascular mechanical thrombectomy treatment,with treatment and follow-up lasting at least 90 d.Basic demographic characteristics,medical records,and baseline blood biomarker data were collected,and the potential prognostic indicators for AIS after 90 d were screened using least absolute shrinkage and selection operator(LASSO)-logistic regression analysis.Results It was found that alcohol drinking(P=0.029),hypertension(P=0.001),diabetes mellitus(P=0.021),stroke or transient ischemic attack(P=0.049),systolic blood pressure on admission(P=0.009),diastolic blood pressure on admission(P=0.038),blood glucose(P=0.003),white blood cell count(P=0.001),neutrophil count(P=0.001),fibrinogen(P=0.010),systemic immune-inflammation index(P=0.008)and neutrophil-to-lymphocyte ratio(NLR)(P＜0.001)were associated with adverse clinical outcomes.Nine significant prognostic determinants were screened through LASSO-logistic regression analysis.Multivariate logistic regression analysis revealed that male sex(P=0.008),smoking history(P=0.013),hypertension(P=0.011),lymphocyte(P=0.028),fibrinogen(P=0.016),and NLR(P＜0.001)were significant predictive factors for poor prognosis in AIS patients after endovascular thrombectomy treatment.The constructed prognostic model had an accuracy of 76.2％,a sensitivity of 78.2％,a specificity of 71.7％,and a positive predictive value of 86.7％.Conclusion The predictive model established in this study can assist clinicians in identifying high-risk patients with AIS who have undergone endovascular thrombectomy,and it provide guidance for formulating individualized treatment strategies.