Objective To study the relationship between blood microRNA-133b(miR-133b)and solu-ble fms-like tyrosine kinase 1(sFLT1)levels with the prognosis in the patients with endometrial cancer.Methods A total of 122 patients with endometrial cancer visited in the gynecology department of this hospital from January 2015 to January 2016 were prospectively selected as the study subjects,and divided into the sur-vival group(n=58)and death group(n=64)according to the 5-year prognosis of the patients with endome-trial cancer.The miR-133b and sFLT1 levels were compared between the two groups.The COX regression was used to analyze the relationship between miR-133b and sFLT1 with the prognosis of the patients with en-dometrial cancer.Results The levels of miR-133b and sFLT1 in the survival group were higher than those in the death group,and the differences were statistically significant(P＜0.05).The median survival time in the miR-133b low-level group was shorter than that in the miR-133b high level group,and the difference was sta-tistically significant(P＜0.05).The median survival time of the sFLT1 low level group was shoeter than that in the sFLT1 high level group,and the difference was statistically significant(P＜0.05).The FIGO stageⅢ-Ⅳ and lymph node metastasis were the independent risk factors for the prognosis of endometrial cancer(P＜0.05),and the pathological G1-G2,high level of miR-133b and sFLT1 were the independent protective factors for the prognosis of endometrial cancer(P＜0.05).Conclusion The miR-133b and sFLTl low levels in the patients with endometrial cancer are associated with the disease progression,and both are the independ-ent risk factors of prognosis.

AIM:To investigate the effect of hypericin(Hyp)on the heart of rats with myocardial ischemia-re-perfusion injury(MIRI),and to explore its mechanism.METHODS:Thirty SPF male SD rats were divided into 5 groups:sham group,MIRI group,low-dose Hyp(L-Hyp)group(MIRI+L-Hyp group),high-dose Hyp(H-Hyp)group(MIRI+H-Hyp group),and positive control trimetazidine(TMZ)group(MIRI+TMZ group),with 6 rats in each group.Apart from the sham group,the MIRI model was established by ligating the anterior descending branch of the left coronary artery and then recanalizing it in the remaining four groups of rats.The success of the modeling was determined by monitor-ing the electrocardiogram.We assessed the cardiac function in rats using echocardiography.TTC staining was employed to measure the area of myocardial infarction in rats,and HE staining was utilized to observe the morphological traits of rat myocardium.We assayed the activities of lactate dehydrogenase(LDH)and superoxide dismutase(SOD)and the levels of malondialdehyde(MDA)in rat serum using biochemical kits.ELISA kits were applied to assess the contents of cardiac troponin I(cTnI)and reactive oxygen species(ROS)in rat serum.Western blot analysis was perfomed to measure the pro-tein expression levels of AMPK,p-AMPK,Nrf2,and HO-1 in rat myocardial tissues.RESULTS:The rats in MIRI group exhibited increased myocardial tissue injury,larger myocardial infarction areas,decreased left ventricular ejection fraction(LVEF),and reduced left ventricular fractional shortening(LVFS)compared with sham group,as shown by echo-cardiography.Additionally,there were increases in LDH activity,cTnI,MDA and ROS levels,along with significant de-creases in SOD activity,and p-AMPK,Nrf2 and HO-1 protein levels(P<0.05).Compared with MIRI group,the rats in MIRI+L-Hyp,MIRI+H-Hyp and MIRI+TMZ groups showed decreased myocardial histopathological damage and reduced myocardial tissue infarction area,increased LVEF and LVFS,and lowered serum levels of LDH activity,cTnI,MDA and ROS,while SOD activity,p-AMPK,Nrf2 and HO-1 protein levels were elevated(P<0.05).CONCLUSION:Hypericin attenuates myocardial ischemia-reperfusion injury in rats,possibly by modulating the AMPK/Nrf2/HO-1 signaling path-way.

Objective To investigate the effect of computer-aided diagnosis(CAD)as a"second reader"integrated in prostate cancer(PCa)multiparametric magnetic resonance imaging(mpMRI)on the diagnostic performance.Methods Sixty-four patients were recruited retrospectively.Six readers were divided into 3 groups according to the experience.Unknown the pathologic diagnosis,readers graded according to prostate imaging reporting and data system(PI-RADS)v2.1 and accepted or rejected the revision of PI-RADS v2.1 scores by CAD.Using pathology as the gold standard,the diagnostic efficiency,diagnostic confidence and reading time of PI-RADS v2.1 were compared before and after CAD assistant.Results On the level of lesions,without CAD,the area under the curve(AUC)of reader A1 was higher than B1,C1 and C2,and the AUC of reader A2 was higher than C1 and C2,the difference was statistically significant(P＜0.05).While the difference of AUC among other readers were not significant(P＞0.05).With CAD,the difference of AUC among all readers were not significant(P＞0.05).On the level of patients,the mean AUC of all readers with CAD[0.903,95％confidence interval(CI)0.848-0.958]was higher than that without CAD(0.863,95％CI 0.800-0.929),the differ-ence was statistically significant(F=6.52,P=0.040).The difference of AUC between without and with CAD assistance was-0.040(95％CI-0.078--0.003),standard deviation was 0.016,the difference was statistically significant(t=-2.55,P=0.040).The diag-nostic confidence of readers was improved significantly with CAD(P＜0.05).Besides,the average reading time of each case required an additional 0.8 min.Conclusion After integrating CAD into PCa mpMRI diagnosis as a"second reader",the performance of less experienced readers can be improved and show similar diagnostic efficiency with experienced readers.

Objective:To establish a predictive model for post-induction hypotension (PIH) in the patients undergoing colorectal cancer resection using machine learning algorithms based on muscle CT parameters.Methods:This was a single-center, retrospective study. Electronic medical records from 318 patients who underwent colorectal cancer resection from September 1, 2018 to September 30, 2021 at our hospital were collected. Predictive variables included age, gender, body mass index, hemoglobin, American Society of Anesthesiologists Physical Status classification, TNM staging, age-adjusted Charlson comorbidity index, prognostic nutritional index, L 3 level skeletal muscle index, and muscle quality assessed by Hounsfield unit average calculation. The outcome variable was PIH. The training and testing sets were divided based on the timeline (patients before September 1, 2020 were included in the training set, and those after that date were included in the testing set). The filtering method was used to screen the feature variables. Eight models, including logistic regression, Bayesian models, K-nearest neighbors, support vector machines, neural networks, decision trees, extreme gradient boosting trees, and random forests, were established in the training set using over-sampling technique, repeated cross-validation and hyperparameter optimization. After selecting the best model, a sorting chart of the feature variables, a univariate partial dependency profile, and a breakdown profile were drawn. In the testing set, the confusion matrix and parameters were calculated, and the receiver operating characteristic curve, precision recall curve, calibration curve, and decision curve were drawn to evaluate the performance of the predictive model. Results:The screened feature variables were Hounsfield unit average calculation value, age, L 3 level skeletal muscle index, prognostic nutritional index, hemoglobin and body mass index. The random forest was the optimal model, with an accuracy of 0.985 9, a MCC of 0.970 8, the area under the receiver operating characteristic curve was 1.0, and the area under the precision recall curve was 1.0. The Brier score of the calibration curve was 0.076 6; the decision curve showed the highest clinical net benefit of 0.6. Conclusions:In this study, machine learning algorithm is used to identify the important characteristic variables and establish a high-performance PIH prediction model based on muscle CT parameters.

To explore the differentially expressed genes (DEGs) related to biosynthesis of active ingredients in wolfberry fruits of different varieties of Lycium barbarum L. and reveal the molecular mechanism of the differences of active ingredients, we utilized Illumina NovaSeq 6000 high-throughput sequencing technology to conduct transcriptome sequencing on the fruits of 'Ningqi No.1' and 'Ningqi No.7' during the green fruit stage, color turning stage and maturity stage. Subsequently, we compared the profiles of related gene expression in the fruits of the two varieties at different development stages. The results showed that a total of 811 818 178 clean reads were obtained, resulting in 121.76 Gb of valid data. There were 2 827, 2 552 and 2 311 DEGs obtained during the green fruit stage, color turning stage and maturity stage of 'Ningqi No. 1' and 'Ningqi No. 7', respectively, among which 2 153, 2 050 and 1 825 genes were annotated in six databases, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and clusters of orthologous groups of proteins (KOG). In GO database, 1 307, 865 and 624 DEGs of green fruit stage, color turning stage and maturity stage were found to be enriched in biological processes, cell components and molecular functions, respectively. In the KEGG database, the DEGs at three developmental stages were mainly concentrated in metabolic pathways, biosynthesis of secondary metabolites and plant-pathogen interaction. In KOG database, 1 775, 1 751 and 1 541 DEGs were annotated at three developmental stages, respectively. Searching the annotated genes against the PubMed database revealed 18, 26 and 24 DEGs related to the synthesis of active ingredients were mined at the green fruit stage, color turning stage and maturity stage, respectively. These genes are involved in carotenoid, flavonoid, terpenoid, alkaloid, vitamin metabolic pathways, etc. Seven DEGs were verified by RT-qPCR, which showed consistent results with transcriptome sequencing. This study provides preliminary evidences for the differences in the content of active ingredients in different Lycium barbarum L. varieties from the transcriptional level. These evidences may facilitate further exploring the key genes for active ingredients biosynthesis in Lycium barbarum L. and analyzing their expression regulation mechanism.
Flavonoids/metabolism* ; Fruit/genetics* ; Gene Expression Profiling/methods* ; Gene Expression Regulation, Plant ; Lycium/metabolism* ; Metabolic Networks and Pathways ; Transcriptome

【Objective】 To investigate whether the current retention methods in blood stations can fully meet the traceability requirements of blood test results by analyzing the traceability of retained samples for syphilis antibody testing. 【Methods】 Thirty-four one-assay-positive deep-well plate retention samples, 68 double-assay-positive deep-well plate retention samples and 263 negative retention blood braids and corresponding deep-well plate retention samples that expired retention period for syphilis antibody testing from 2014 to 2020 in our center were collected. The TP-ELISA assays of two manufacturers were used for retesting, and the results were recorded and compared with the original results statistically. 【Results】 The concordance rate of the double-assay-positive and single-assay-positive samples with their corresponding deep-well plate samples was 98.53%(67/68) and 67.65%(23/34), respectively(P<0.05). Specific results for single-assay-positive syphilis antibody samples and their corresponding deep-well plate retention samples were as follows: 1) Single positive (reagent A): 13 out of 14 original samples were 0.65