Objective: To construct a scientific and perfect evaluation index system of infectious disease prevention and control ability in colleges and universities, so as to provide reference tools for colleges and universities to effectively respond to infectious disease. Methods: The initial framework of the evaluation index system of infectious disease prevention and control ability in colleges and universities was constructed by using literature analysis method. Experts familiar with infectious disease prevention and control or school health work were selected to conduct two rounds( n =16，18) of Delphi expert consultation for determining the evaluation index system. Analytical hierarchy process was used to calculate the index weights and combined weights. About 198 prevention and control personnel were conveniently selected from 3 universities in Inner Mongolia Autonomous Region to comprehensively evaluate the evaluation indicators by using fuzzy comprehensive evaluation method. Results: After two rounds of Delphi consultation questionnaire, the effective recovery rates were 80.0% and 90.0%, the expert authority levels were 0.89 and 0.86, the expert harmony coefficients for Kendall W were 0.166 and 0.310, and the variation coefficient of each index was <0.25. Finally, the evaluation index system of infectious disease prevention and control ability of colleges and universities included 4 first level indicators, 14 second level indicators and 75 third level indicators. The weights of prevention and monitoring and early warning, organizational system guarantee, emergency management, rehabilitation and summary were 0.176, 0.476, 0.268 and 0.080, respectively. The top 3 weights of the secondary indexes were 0.623 for infectious disease surveillance and early warning, 0.595 for loss assessment and 0.370 for emergency response. The score of fuzzy comprehensive evaluation of the index system of infectious disease prevention and control ability in colleges and universities was 79.148, suggesting a high level. Conclusion The established evaluation index system of infectious disease prevention and control ability in colleges and universities is scientific and reasonable, which is conducive to provide tool reference for the evaluation of infectious disease prevention and control ability in colleges and universities.

The classic formula Fangji Fulingtang is from ZHANG Zhongjing's Synopsis of the Golden Chamber in the Eastern Han dynasty. It is composed of Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma， with the effects of reinforcing Qi and invigorating spleen， warming Yang and promoting urination. By a review of ancient medical books， this paper summarizes the composition， original plants， processing， dosage， decocting methods， indications and other key information of Fangji Fulingtang， aiming to provide a literature basis for the research， development， and clinical application of preparations based on this formula. Synonyms of Fangji Fulingtang exist in ancient medical books， while the formula composition in the Synopsis of the Golden Chamber is more widespread and far-reaching. In this formula， Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma are the dried root of Stephania tetrandra， the dried root of Astragalus embranaceus var. mongholicus， the dried shoot of Cinnamomum cassia， the dried sclerotium of Poria cocos， and the dried root and rhizome of Glycyrrhiza uralensis， respectively. Fangji Fulingtang is mainly produced into powder， with the dosage and decocting method used in the past dynasties basically following the original formula. Each bag is composed of Stephaniae Tetrandrae Radix 13.80 g， Astragali Radix 13.80 g， Cinnamomi Ramulus 13.80 g， Poria 27.60 g， and Glycyrrhizae Radix et Rhizoma 9.20 g. The raw materials are purified， decocted in water from 1 200 mL to 400 mL， and the decoction should be taken warm， 3 times a day. Fangji Fulingtang was originally designed for treating skin edema， and then it was used to treat impediment in the Qing dynasty. In modern times， it is mostly used to treat musculoskeletal and connective tissue diseases and circulatory system diseases， demonstrating definite effects on various types of edema and heart failure. This paper clarifies the inheritance of Fangji Fulingtang and reveals its key information （attached to the end of this paper）， aiming to provide a theoretical basis for the development of preparations based on this formula.

The classic formula Fangji Fulingtang is from ZHANG Zhongjing's Synopsis of the Golden Chamber in the Eastern Han dynasty. It is composed of Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma， with the effects of reinforcing Qi and invigorating spleen， warming Yang and promoting urination. By a review of ancient medical books， this paper summarizes the composition， original plants， processing， dosage， decocting methods， indications and other key information of Fangji Fulingtang， aiming to provide a literature basis for the research， development， and clinical application of preparations based on this formula. Synonyms of Fangji Fulingtang exist in ancient medical books， while the formula composition in the Synopsis of the Golden Chamber is more widespread and far-reaching. In this formula， Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma are the dried root of Stephania tetrandra， the dried root of Astragalus embranaceus var. mongholicus， the dried shoot of Cinnamomum cassia， the dried sclerotium of Poria cocos， and the dried root and rhizome of Glycyrrhiza uralensis， respectively. Fangji Fulingtang is mainly produced into powder， with the dosage and decocting method used in the past dynasties basically following the original formula. Each bag is composed of Stephaniae Tetrandrae Radix 13.80 g， Astragali Radix 13.80 g， Cinnamomi Ramulus 13.80 g， Poria 27.60 g， and Glycyrrhizae Radix et Rhizoma 9.20 g. The raw materials are purified， decocted in water from 1 200 mL to 400 mL， and the decoction should be taken warm， 3 times a day. Fangji Fulingtang was originally designed for treating skin edema， and then it was used to treat impediment in the Qing dynasty. In modern times， it is mostly used to treat musculoskeletal and connective tissue diseases and circulatory system diseases， demonstrating definite effects on various types of edema and heart failure. This paper clarifies the inheritance of Fangji Fulingtang and reveals its key information （attached to the end of this paper）， aiming to provide a theoretical basis for the development of preparations based on this formula.

Objective To explore the feasibility of long non-coding RNAs (lncRNAs) as biomarkers for radiation-induced intestinal injury. Methods Mice were exposed to 15 Gy of ⁶⁰Co γ-rays to the abdominal area. The pathological changes in intestinal tissues were analyzed at 72 h post-irradiation to confirm the successful establishment of the radiation-induced intestinal injury model. Real-time quantitative PCR was conducted to detect the expression of candidate radiation-responsive lncRNAs in the jejunum, jejunal crypts, colon tissues, and plasma of irradiated mice. Human intestinal epithelial cell line HIEC-6 and human colon epithelial cell line NCM460 were exposed to 0, 5, 10, and 15 Gy of ⁶⁰Co γ-rays. The expression levels of candidate lncRNAs were measured at 4, 24, 48, and 72 h post-irradiation to observe their changes with the irradiation dose. Results Pathological analysis showed that abdominal irradiation with 15 Gy successfully established an acute radiation-induced intestinal injury mouse model. Real-time quantitative PCR showed that Dino, Lncpint, Meg3, Dnm3os, Trp53cor1, Pvt1, and Neat1 were significantly upregulated following the occurrence of radiation-induced intestinal injury (P < 0.05). Among them, Meg3 and Dnm3os in mouse plasma were significantly upregulated (P < 0.05), while Gas5 was significantly downregulated (P < 0.05). In HIEC-6 and NCM460 cells, the expression levels of DINO, MEG3, DNM3OS, and GAS5 showed dose-dependent patterns at certain time points (P < 0.05). Conclusion The lncRNAs encoded by MEG3, DNM3OS, and GAS5 in intestinal epithelial cells are responsive to ionizing radiation. Consistent differential expression changes were detected in mouse plasma and intestinal tissues, indicating their potential as biomarkers for radiation-induced intestinal injury.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

BACKGROUND:Steroid-induced femoral head necrosis is mostly caused by long-term and extensive use of hormones,but its specific pathogenesis is not yet clear and needs further study. OBJECTIVE:To screen out the differential miRNAs in osteoclast exosomes after the intervention of Panax notoginseng saponins,and on this basis,to further construct an osteogenic-related ferroptosis regulatory network to explore the potential mechanism and research direction of steroid-induced osteonecrosis of the femoral head. METHODS:MTT assay was used to detect the toxic effects of different concentrations of dexamethasone and different mass concentrations of Panax notoginseng saponins on Raw264.7 cell line.Tartrate resistant acid phosphatase staining and TUNEL assay were used to detect the effects of Panax notoginseng saponins on osteoclast inhibition and apoptosis.Exosomes were extracted from cultured osteoclasts with Panax notoginseng saponins intervention.Exosomes from different groups were sequenced to identify differentially expressed miRNAs.CytoScape 3.9.1 was used to construct and visualize the regulatory network between differentially expressed miRNAs and mRNAs.Candidate mRNAs were screened by GO analysis and KEGG analysis.Finally,the differential genes related to ferroptosis were screened out,and the regulatory network of ferroptosis-related genes was constructed. RESULTS AND CONCLUSION:(1)The concentration of dexamethasone(0.1 μmol/L)and Panax notoginseng saponins(1 736.85 μg/mL)suitable for intervention of Raw264.7 cells was determined by MTT assay.(2)Panax notoginseng saponins had an inhibitory effect on osteoclasts and could promote their apoptosis.(3)Totally 20 differentially expressed miRNAs were identified from osteoclast-derived exosome samples,and 11 differentially expressed miRNAs related to osteogenesis were predicted by target mRNAs.The regulatory networks of 4 up-regulated differentially expressed miRNAs corresponding to 155 down-regulated candidate mRNAs and 7 down-regulated differentially expressed miRNAs corresponding to 238 up-regulated candidate mRNAs were constructed.(4)Twenty-four genes related to ferroptosis were screened out from the differential genes.Finally,12 networks were constructed(miR-98-5p/PTGS2,miR-23b-3p/PTGS2,miR-425-5p/TFRC,miR-133a-3p/TFRC,miR-185-5p/TFRC,miR-23b-3p/NFE2L2,miR-23b-3p/LAMP2,miR-98-5p/LAMP2,miR-182-5p/LAMP2,miR-182-5p/TLR4,miR-23b-3p/ZFP36,and miR-182-5p/ZFP36).These results indicate that Panax notoginseng saponins may regulate osteoblast ferroptosis by regulating the expression of miRNAs derived from osteoclast exosomes,thus providing a new idea for the study of the mechanism of steroid-induced femoral head necrosis.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

OBJECTIVE To analyze the occurrence characteristics and risk factors of adverse drug reactions （ADR） of gemcitabine for injection in national centralized volume-based procurement （hereinafter referred to as “centralized procurement”）， and provide reference for clinical safe drug use. METHODS A retrospective study was conducted to collect the relevant case reports of gemcitabine for injection reported to the National Adverse Drug Reaction Monitoring System by Inner Mongolia Autonomous Region from January 2022 to December 2023； basic information of patients， drug use status， patient outcomes， rational drug use and other information were collected， and the occurrence characteristics of ADRs with leukopenia， myelosuppression， neutropenia， thrombocytopenia and liver dysfunction were analyzed. Univariate analysis and multivariate Logistic regression were used to analyze the correlation of gender， age， combination of antitumor drugs， original malignant tumor and drug dose with ADR. RESULTS A total of 315 cases reports （315 patients） of gemcitabine-induced ADR were included in this study， with a male-to-female ratio of 1.42∶1 and age of （61.17±9.13） years. The primary malignant tumor was pancreatic cancer （73 cases， 23.17%）. Leukopenia， myelosuppression and nausea were the most common ADR， followed by neutropenia， thrombocytopenia， liver dysfunction and so on. The severity grade of ADR was mainly 1-2， and the outcome of most ADR was good. Multivariate Logistic regression analysis showed that combination of antitumor drugs was a risk factor for myelosuppression and neutropenia （RR＝2.154， 95%CI： 1.218- 3.807， P＝0.008； RR＝3.099， 95%CI： 1.240-7.744， P＝0.016）； gender （female） was a risk factor for leukopenia and liver dysfunction （RR＝0.508， 95%CI： 0.302-0.853， P＝0.010； RR＝0.301， 95%CI： 0.102-0.887， P＝0.029）. In terms of drug use rationality， there were 143 cases （45.40%） of drug 126.com use in accordance with the indications of the label， and 172 cases （54.60%） of off-label drug use. Among them， the primary malignant tumors were bladder cancer， bile duct cancer and ovarian cancer， which ranked the top three off-label drug use. CONCLUSIONS The ADR caused by gemcitabine in Inner Mongolia is mainly in the blood and digestive systems. The severity of ADRs is mainly classified as 1-2 levels， and most ADRs have good outcomes. Gender （female） and combination medication are risk factors for gemcitabine-induced ADR. Appropriate chemotherapy regimen should be selected according to the patient’s condition and physical condition， and ADR monitoring in blood and digestive systems should be strengthened during medication of gemcitabine.