OBJECTIVE To explore a model for constructing a platform for medical institution formulation and provide insights for promoting their development. METHODS By systematically reviewing the development status and challenges of medical institution preparations in China， and based on the theory of industry-university-research collaborative innovation， the organizational structure， collaborative processes， and safeguard mechanisms of the platform were designed. RESULTS & CONCLUSIONS Medical institution formulations in China mainly faced challenges such as weak research and development （R&D） capacity， uneven quality standards， and blocked transformation pathways. This study established a full-chain， whole- industry collaborative innovation network covering the government， medical institutions， universities/research institutes， pharmaceutical enterprises， and the market， forming a new “government-industry-university-research-application” five-in-one platform model for medical institution formulations. By establishing mechanisms such as multi-entity collaborative cooperation， full- chain intellectual property management， contribution-based benefit distribution， staged risk-sharing， and third-party evaluation， the model clarified the responsibilities and collaborative pathways of all parties. The new model highlights the whole-process transformation of clinical experience-based prescriptions， enabling precise alignment between clinical needs and technological R&D， as well as between preparation achievements and industrial transformation. While breaking down the barriers of traditional platform construction， it effectively achieves optimal resource allocation and complementary advantages， addresses problems emerging in the development of medical institution preparations， and provides reference value for the formulation of relevant systems.

Objective:The prediction model of postoperative recurrence of ovarian endometriosis cyst(OEM)was constructed to provide a reference for evaluating postoperative recurrence of OEM patients.Methods:The clinical,pathological and follow-up data of 342 patients who underwent the initial laparoscopic ovarian cystectomy for OEM at The Second Hospital of Hebei Medical University from January 1,2017 to October 31,2021 were retro-spectively analyzed.Based on univariate and multivariate Cox regression analysis,the relevant factors affecting OEM recurrence were identified.According to the results of multivariate analysis,a nomogram was drawn.The C index and receiver operating characteristic(ROC)curve were used to test the efficiency of the prediction model.Results:The 2-year recurrence rate of OEM patients was 20.4%and the 5-year recurrence rate was 35.2%.Uni-variate and multivariate Cox regression analysis showed that menstrual cycle(HR 0.916,95%CI 0.860-0.976,P=0.006),delivery≥1(HR 0.376,95%CI 0.171-0.827,P=0.015),CA125≥100 U/ml(HR 1.790,95%CI 1.167-2.746,P=0.008),total cyst diameter≥10 cm(HR 2.254,95%CI 1.318-3.854,P=0.003),and postoperative medications(HR 0.434,95%CI 0.292-0.644,P=0.000)were associated with OEM recurrence and were included in the no-mogram prediction model.The C-index of the nomogram prediction model was 0.710(95%CI 0.665-0.754),and the area under the curve(AUC)of the ROC for OEM patients with recurrence at 2 years after surgery was 0.786 and 0.708 at 5 years.Conclusions:In this study,we developed a nomogram to predict the probability of recur-rence at 2 years and 5 years for OEM patients under 45 years who underwent conservative surgery,which has i-deal predictive performance and helps clinicians to screen high-risk patients,and thus give high-risk OEM patients additional attention and intervention.

AIM: To identify the primary active components and underlying mechanisms of Yijing Decoction(YJD)in treating early diabetic retinopathy(DR)based on liquid chromatography-mass spectrometry and network pharmacology.METHODS: Active components of YJD were characterized through LC-MS. Components with optimal ADME(absorption, distribution, metabolism, excretion)properties were selected as key bioactive candidates. Network pharmacology approaches were employed to predict YJD-DR therapeutic targets. Protein-protein interaction(PPI)networks, gene ontology(GO)enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were subsequently conducted to predict core targets and networks. Critical targets and pathways were experimentally validated through Western blot.RESULTS: Ten core therapeutic targets were identified, including TNF, Alb, EGFR, STAT3, PTGS2, ESR1, PPAR, MMP9, TLR4, and MAPK. YJD was related to cancer-related signaling, fluid shear stress and atherosclerosis, and neurodegenerative diseases, encompassing key biological processes such as inflammatory response regulation, programmed cell death activation, and enhanced cell migration. Furthermore, Western blot analysis confirmed that YJD significantly inhibited high glucose-induced phosphorylation of STAT3(P-STAT3/STAT3)and ERK(P-ERK/ERK)in rat retinal microvascular endothelial cells.CONCLUSION: This study revealed YJD's pharmacodynamical basis and its multi-component, multi-target, and multi-paths pharmacology. YJD exerts therapeutic effects on DR by coordinately regulating critical signaling pathways and alleviating intraocular inflammation, thus preserving retinal vascular endothelial cells, maintaining blood-retinal barrier integrity, and facilitating retinal neurovascular repair.

Objective:The prediction model of postoperative recurrence of ovarian endometriosis cyst(OEM)was constructed to provide a reference for evaluating postoperative recurrence of OEM patients.Methods:The clinical,pathological and follow-up data of 342 patients who underwent the initial laparoscopic ovarian cystectomy for OEM at The Second Hospital of Hebei Medical University from January 1,2017 to October 31,2021 were retro-spectively analyzed.Based on univariate and multivariate Cox regression analysis,the relevant factors affecting OEM recurrence were identified.According to the results of multivariate analysis,a nomogram was drawn.The C index and receiver operating characteristic(ROC)curve were used to test the efficiency of the prediction model.Results:The 2-year recurrence rate of OEM patients was 20.4%and the 5-year recurrence rate was 35.2%.Uni-variate and multivariate Cox regression analysis showed that menstrual cycle(HR 0.916,95%CI 0.860-0.976,P=0.006),delivery≥1(HR 0.376,95%CI 0.171-0.827,P=0.015),CA125≥100 U/ml(HR 1.790,95%CI 1.167-2.746,P=0.008),total cyst diameter≥10 cm(HR 2.254,95%CI 1.318-3.854,P=0.003),and postoperative medications(HR 0.434,95%CI 0.292-0.644,P=0.000)were associated with OEM recurrence and were included in the no-mogram prediction model.The C-index of the nomogram prediction model was 0.710(95%CI 0.665-0.754),and the area under the curve(AUC)of the ROC for OEM patients with recurrence at 2 years after surgery was 0.786 and 0.708 at 5 years.Conclusions:In this study,we developed a nomogram to predict the probability of recur-rence at 2 years and 5 years for OEM patients under 45 years who underwent conservative surgery,which has i-deal predictive performance and helps clinicians to screen high-risk patients,and thus give high-risk OEM patients additional attention and intervention.

Objective : To explore the association between serum γ-aminobutyric acid ( GABA) levels and the risk of developing type 2 diabetes( T2DM) ． Methods : 187 cases of T2DM patients attending the hospital were selected as the T2DM group，and 187 cases of non-T2DM population attending the same period of time were selected as the control group according to age ( ± 3 years) and gender 1 ∶ 1．On-site questionnaires and physical examination were conducted for the study subjects，and serum levels of GABA，Malondialdehyde ( MDA) and activities of superoxide dismutase ( SOD) and Glutathione peroxidase ( GSH-Px) were detected by using ELISA kits．The differences in the levels of GABA and oxidative stress indicators ( SOD，GSH-Px，MDA) between the two groups were compared， and the correlation between GABA and oxidative stress indicators was analyzed by Spearman's method; GABA and oxidative stress indicators were divided into three groups according to their control quartiles，respectively ［low level group ( Q1: ＜P25) ，medium level group ( Q2: P25 －P75) ，high level group ( Q3: ＞P75) ］，and conditional logistic regression was applied to analyze the relationship between GABA，oxidative stress indicators and the risk of develo- ping T2DM; the dose-response relationship between GABA，oxidative stress indicators and the risk of developing T2DM was analyzed by using restricted cubic spline ( RCS) ． Results : T2DM group ( P＜0. 05) ．Spearman's correlation analysis showed that GABA level was positively correlated with SOD and GSH-Px activities and negatively correlated with MDA level ( P＜0. 001) ．Conditional logistic regression analysis showed that medium levels of SOD and GSH-Px as well as medium and high levels of GABA were protective factors for T2DM compared with low levels in each group ( P＜0. 05) ．RCS results showed that a negative dose-response relationship between GABA，GSH-Px and the risk of developing T2DM，and SOD showed a trend of decreasing and then increasing the risk of developing T2DM ( P＜0. 05) ． Conclusion Serum GABA levels have been associated with the risk of developing T2DM．As serum GABA levels increase，the risk of developing T2DM may decrease．