OBJECTIVE To build a new workflow of pharmacy intravenous admixture services （PIVAS）， effectively connect intelligent equipment， and promote the intelligent development of PIVAS. METHODS Based on intelligent auxiliary equipment， PIVAS workflow was optimized， and a process-oriented model was established. This model integrated intelligent prescription review （automatic prescription review+manual intervention mode）， intelligent labeling， intelligent allocation， intelligent sorting， and finished infusion quality inspection system. Furthermore， an assessment was conducted to examine unreasonable medical order rate of intelligent prescription review， the working efficiency and error rate of intelligent labeling machine and intelligent sorting machine， and the dispensing efficiency and accuracy of intelligent dispensing robot. RESULTS Under the intelligent prescription review mode， the rate of unreasonable medical orders decreased from 0.157% to 0.050% （P＜0.05）； automatic labeling efficiency reached 21.7 sheets/min， surpassing the manual labeling efficiency of 13.8 sheets/min （P＜0.05）， and the daily labeling error rate decreased from 6.1‰ to 2.5‰ （P＜0.05）. Simultaneously operating two dispensing robots significantly improved the efficiency of batch dispensing and reduced the residual amount of liquid medicine （P＜0.05）； additionally， a quality testing system for finished infusion was established， involving appearance， Tyndall effect， insoluble particles， turbidity， absorbance， pH and osmotic pressure， to ensure the quality of finished infusion and reduce the risk of infusion. CONCLUSIONS The new process of PIVAS connected with intelligent devices in our hospital can improve work efficiency， reduce dispensing errors， ensure the quality of finished infusion， and improve the level of pharmaceutical care.

Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

S-methyl-L-cysteine sulfoxide (SMCO) is a non-protein sulfur-containing amino acid with a variety of functions. There are few reports on the enzymes catalyzing the biosynthesis of SMCO from S-methyl-L-cysteine (SMC). In this study, the flavin-containing monooxygenase gene derived from Schizosaccharomyces pombe (spfmo) was heterologously expressed in Escherichia coli BL21(DE3) and the enzymatic properties of the expressed protein were analyzed. The optimum catalytic conditions of the recombinant SpFMO were 30 ℃ and pH 8.0, under which the enzyme activity reached 72.77 U/g. An appropriate amount of Mg²⁺ improved the enzyme activity. The enzyme kinetic analysis showed that the K_m and k_cat/K_m of SpFMO on the substrate SMC were 23.89 μmol/L and 61.71 L/(min·mmol), respectively. Under the optimal reaction conditions, the yield of SMCO synthesized from SMC catalyzed by SpFMO was 12.31% within 9 h. This study provides reference for the enzymatic synthesis of SMCO.
Schizosaccharomyces/genetics* ; Escherichia coli/metabolism* ; Recombinant Proteins/metabolism* ; Cysteine/biosynthesis* ; Mixed Function Oxygenases/metabolism* ; Schizosaccharomyces pombe Proteins/metabolism* ; Oxygenases/metabolism* ; Kinetics

AIM:To explore the mechanism of berberine on breast cancer cells based on network pharmacology and in vitro cell experiments.METH-ODS:Firstly,berberine and breast cancer were tak-en as the research objects,the intersection targets of the two were screened by VEEN diagram,GO function and KEGG enrichment analysis were per-formed by R language,and molecular docking and visualization were carried out by Autodock Vina and Pymol software.Then,berberine treated breast cancer MCF-7 cells for 24 h,and then in vi-tro cell experiments were performed.CCK-8 was used to detect cell viability,Edu and plate cloning were used to detect cell proliferation and cloning,and apoptosis was detected by An-nexin V-FITC/PI double staining and Western blot.Laser confocal and CETSA were used to verify the binding effect of berberine and AKT1 protein.RESULTS:The results of network pharmacology showed that berberine had a good binding to the core targets AKT1,AKT2 and MAPK3.Berberine(20,40,80 μmol/L)signifi-cantly inhibited the proliferation and cloning ability of MCF-7 cells in a concentration-dependent man-ner(P＜0.05,P＜0.01).The results of laser confocal and CETSA experiments showed that berberine and AKT1 had a binding effect,and the stability of the two was enhanced after the combination.CONCLU-SION:Berberine inhibits MCF-7 cell proliferation and induces apoptosis in human breast cancer cells by targeting binding to AKT1 protein.

Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

AIM:To explore the mechanism of berberine on breast cancer cells based on network pharmacology and in vitro cell experiments.METH-ODS:Firstly,berberine and breast cancer were tak-en as the research objects,the intersection targets of the two were screened by VEEN diagram,GO function and KEGG enrichment analysis were per-formed by R language,and molecular docking and visualization were carried out by Autodock Vina and Pymol software.Then,berberine treated breast cancer MCF-7 cells for 24 h,and then in vi-tro cell experiments were performed.CCK-8 was used to detect cell viability,Edu and plate cloning were used to detect cell proliferation and cloning,and apoptosis was detected by An-nexin V-FITC/PI double staining and Western blot.Laser confocal and CETSA were used to verify the binding effect of berberine and AKT1 protein.RESULTS:The results of network pharmacology showed that berberine had a good binding to the core targets AKT1,AKT2 and MAPK3.Berberine(20,40,80 μmol/L)signifi-cantly inhibited the proliferation and cloning ability of MCF-7 cells in a concentration-dependent man-ner(P＜0.05,P＜0.01).The results of laser confocal and CETSA experiments showed that berberine and AKT1 had a binding effect,and the stability of the two was enhanced after the combination.CONCLU-SION:Berberine inhibits MCF-7 cell proliferation and induces apoptosis in human breast cancer cells by targeting binding to AKT1 protein.

The prevalence of diabetes mellitus is increasing globally,which has contributed to a surge in diabetic reti-nopathy(DR)patients.DR has become the leading cause of visual impairment and blindness in the working-age popula-tion.The progressive development of DR involves many molecular and biochemical mechanisms,which interact with each other to affect the homeostasis of retinal blood vessels and cells.With the further study of the pathogenesis of DR,more and more molecular targets have been discovered.Studying the pathogenesis of DR and seeking potential therapeutic targets are of great clinical significance for the early prevention and treatment of DR and the prevention of its progression.In this paper,the latest developments in pathogenesis and potential therapeutic targets of DR are briefly reviewed.

As a novel neuromodulation technology,the application of deep brain stimulation(DBS)in treatment-resistant psychiatric disorders has received widespread attention in recent years.Based on the current research frontiers,this review puts forward several unique and insightful issues of DBS in psychiatric disorders,including therapeutic targets,stimulation modes,closed-loop modulation,and long-term efficacy in order to provide suggestions and perspectives for future research directions.

Objective To explore the mechanism of Prunella vulgaris and Scutellaria barbata herb pair against breast cancer based on network pharmacology and in vitro cell experiments.Methods The effective components and targets of Prunella vulgaris and Scutellaria barbata herb pair were screened.GeneCards and OMIM databases were used to find breast cancer targets,and then drug-active ingredient-key target network and protein-protein inter-action(PPI)were constructed.R language was used to perform GO function and KEGG pathway enrichment analy-sis and survival analysis.Then the screened active components and core targets were verified by molecular docking.Cell viability was detected by CCK-8 assay.EdU and flow cytometry were used to detect cell proliferation and apop-tosis.The protein expression levels of p-AKT1,AKT1,β-catenin and c-MYC were detected by Western blot.Results Through databases analysis,a total of 36 active components and 105 intersection targets were screened out,the core components were quercetin,luteolin,kaempferol,wogonin and baicalein.Through PPI and survival analysis,the key targets were AKT1,ESR1,CASP3 and MYC.GO analysis contained 4 303 enrichment results,KEGG analysis contained 232 pathways.Molecular docking showed that the core components had strong binding ability with the key targets.Cell experiments showed that the core active ingredient quercetin could inhibit the proliferation of breast cancer cells and promote their apoptosis(P＜0.05),and down-regulate the expression levels of p-AKT1,β-catenin and c-MYC proteins(P＜0.05).Conclusion The active components quercetin in Prunella vulgaris and Scutel-laria barbata herb pair may play a role through AKT1/β-catenin signaling pathway,which provides a scientific refer-ence for the study of its mechanism of action in the treatment of breast cancer.

Objective:To explore the clinical application and triage management value of using blood circulating cell-free DNA (cfDNA) (cysteine dioxygenase type 1 gene, CDO1, and Homeobox protein A9 gene, HOXA9) hypermethylation level to detect and diagnose ovarian cancer.Methods:A case-control study was conducted on patients who went for surgery at Chengdu Womens and Childrens Central Hospital from November 2022 to October 2023. Blood samples were collected before surgery for evaluation of cancer antigen 125 (CA125), human epididymis protein 4 (HE4), risk of ovarian malignancy algorithm (ROMA) score, and DNA methylation testing. The basic clinical information, biomarkers, and transvaginal ultrasound (TVS) information were collected simultaneously. Information from a total of 151 patients was collected, including 122 cases with benign pathology and 29 ovarian cancer cases. The pathologic diagnosis of ovarian tissue was defined as the gold standard. The multivariate logistic regression analysis was used to identify high-risk factors for ovarian cancer. The clinical efficacy of DNA methylation detection for ovarian cancer was analyzed using the area under curve (AUC).Results:The results showed that the age, menopausal status, CA125 and HE4 detection, ROMA score, positivity rate of CDO1 gene and HOXA9 gene single or combined testing in ovarian cancer patients were higher than those in the benign group and showed significant differences ( P<0.05). Among these detection protocols, the AUC of CDO1 and HOXA9 dual gene methylation testing for ovarian cancer was the highest at 0.936 (95% CI, 0.878-0.994), with 89.7% (95% CI 73.6%-96.4%) sensitivity and 97.5% (95% CI 93.0%-99.2%) specificity, respectively. The positive detection rate of CDO1 and HOXA9 dual gene methylation in early ovarian cancer FOGO I-II stage is 12/14 higher than other tests. Conclusion:Blood cfDNA methylation detection, a simple, non-invasive, and highly sensitive detection method, is superior to the current ovarian cancer testing in the risk assessment and early detection.