An acute myocardial infarction rat model was established by ligation of the left ventricular coronary artery.Plasma samples of rats were collected and analyzed by ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) to study the myocardial protection mechanism of compound Danshen dropping pill (CDDP).After principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), 22 metabolites were identified as potential biomarker of AMI.Furthermore, CDDP had remarkable effect on AMI rats.p-Tolyl sulfate, hippuric acid, equol 7-O-glucuronide, lysoPC(16∶0), cholic acid, oleamide, palmitic amide and SM(d18∶1/16∶0) were significantly changed in treatment group.The results showed that CDDP had a very good myocardial protection effect on AMI rats, and might influence the pathways of phenylalanine metabolism, glycerophospholipid metabolism, fatty acid metabolism, primary bile acid biosynthesis and Sphingolipid metabolism.

Ideal blood glucose control requires accurate insulin injections under the guidance of frequent glucose monitoring.Artificial pancreas (AP),the closed-loop control system can adjust the input amount of insulin automatically with the body's blood glucose levels.The AP allows diabetics to control blood glucose ideal,then get the benefit of prevention of complications and bring convenience and safety in clinical application.Accuracy is the key issue of the AP.To improve the accuracy of such a system need to improve the detection accuracy and reliability,increase speed and accuracy of the output control,and improve the accuracy of the system regulation model.

Objective To investigate the effect of methylprednisolone on T helper 17 cell (Th17 cells) related cytokines (interleukin (IL)-23,17A,21,22,6,and tansforming growth factor (TGF)-β) in serum and cerebrospinal fluid from patients with relapsing remitting multiple sclerosis and their effects on the pathogenesis.Methods We recruited relapsing remitting multiple sclerosis group (38 patients)and noninflammatory neurological disease group (20 controls),and detected the levels of IL-23,IL-17A,IL-21,IL-22,TGF-β and IL-6 in serum and cerebrospinal fluid (CSF) with ELISA kit in both controls and patients before and after treatment by methylprednisolone.Results After treatment in relapsing remitting multiple sclerosis patients,IL-17A,IL-23,IL-21,and IL-22 levels in cerebrospinal fluid and serum were significantly decreased,however,they were still higher than that in the non-inflammatory neurological disease patients.TGF-β levels was significantly increased (serum:(17.2 ± 5.9) pg/ml vs (34.1 ± 6.5) pg/ml,t =14.351,P =0.000 ; CSF:(26.4 ± 4.7) pg/ml vs (73.2 ± 19.7) pg/ml,t =16.352,P =0.000).The levels of TGF-β in serum and CSF in patients before treatment were lower than those of in non-inflammatory neurological disease patients (serum:(30.2 ± 8.9) pg/ml,t =6.769,P =0.012 ; CSF:(3 1.4 ± 7.5) pg/ml,t =9.368,P =0.017).However,the levels of TGF-β in CSF in patients after treatment were significantly higher than those in non-inflammatory neurological disease patients (t =9.138,P =0.000).Correlation analysis showed that IL-23 and IL-17A were positive correlation in the serum of relapsing remitting multiple sclerosis patients before treatment.Moreover,positive correlations among IL-23,IL-17A and IL-21 were detected in the CSF of relapsing remitting multiple sclerosis patients before treatment.Conclusions Decreased levels of IL-23,IL-17A,IL-21 and IL-22,and elevated levels of TGF-β were detected in serum and CSF of patients with relapsing remitting multiple sclerosis after methylprednisolone treatment.IL-23,IL-17A,IL-21,IL-22 and TGF-β might involve in the pathogenesis of relapsing remitting multiple sclerosis.

Background To explore the relationship between polymorphism of APOE gene in traumatic brain injury(TBI)patients suffering from traffic accident and the outcome of TBI.Methods TBI patients were randomly selected in this study with caxe-wntrol trial. The genotype of APOE allele was tested by a polymerase chain reaction-restriction fragment length polymorphism ( PCR-RFLP), and the association between different genotypes of APOE alleles and outcome of TBI patients, were analyed.Results In TBI group frequency of APOE ε2 allele was 0. 1010, and frequency of APOE ε2/ε3 was 0. 1596.Both of these results were significantly higher than that in normal people (APOE epsilon 2 was 0. 0050, APOE ε2/ε3 was 0. 0100) (P＜0.05). Frequency of APOE ε2 and APOE ε2/ε3 in TBI group who died was 0. 1970 and 0. 2727. These were significantly high compared to TBI patients who had good recovery.Conclusions APOE allele ε2 and APOE genotype ε2/ε3alleles indicate a poor prognosis of traumatic brain injury patients.

Objective To investigate the value of automatic segmentation of carotid vessel wall in multicontrast MR images using U?Net neural network. Methods Patients were retrospectively collected from 2012 to 2015 in Carotid Atherosclerosis Risk Assessment (CARE II) study. All patients who recently suffered ischemic stroke and/or transient ischemic attack underwent identical, state?of?the?art multicontrast MRI technique. A total of 17 568 carotid vessel wall MR images from 658 subjects were included in this study after inclusion criteria and exclusion criteria. All MR images were analyzed using customized analysis platform (CASCADE). Randomly, 10 592 images were assigned into training dataset, 3 488 images were assigned into validating dataset and 3 488 images were assigned into test dataset according to a ratio of 6∶2∶2. Data augmentation was performed to avoid over fitting and improve the ability of model generalization. The fine?tuned U?Net model was utilized in the segmentation of carotid vessel wall in multicontrast MR images. The U?Net model was trained in the training dataset and validated in the validating dataset. To evaluate the accuracy of carotid vessel wall segmentation, the sensitivity, specificity and Dice coefficient were used in the testing dataset. In addition, the interclass correlation and the Bland?Altman analysis of max wall thickness and wall area were obtained to demonstrate the agreement of the U?Net segmentation and the manual segmentation. Results The sensitivity, specificity and Dice coefficient of the fine?tuned U?Net model achieved 0.878,0.986 and 0.858 in the test dataset, respectively. The interclass correlation (95% confidence interval) was 0.921 (0.915-0.925) for max wall thickness and 0.929 (0.924-0.933) for wall area. In the Bland?Altman analysis, the difference of max wall thickness was (0.037±0.316) mm and the difference of wall area was (1.182±4.953) mm2. The substantial agreement was observed between U?Net segmentation method and manual segmentation method. Conclusion Automatic segmentation of carotid vessel wall in multicontrast MR images can be achieved using fine?tuned U?Net neural network, which is trained and tested in the large scale dataset labeled by professional radiologists.

【Objective】 To analyze the gene expression profile of central nervous system primitive neuroectodermal tumors （CNS-PNETs） by bioinformatics methods so as to explore the possible pathogenesis of CNS-PNETs at the molecular level. 【Methods】 The gene expression profile of CNS-PNETs was downloaded from the GEO database， GSE35493 and GSE74195. The differentially expressed genes （DEGs） were screened by the online analysis tool of GEO2R and Venn software， DEGs were analyzed by using the online analysis tools of David database， such as Gene Ontology （GO） and pathway enrichment （KEGG）. The protein interaction network analysis （PPI） of CNS-PNETs was made by using STRING online analysis tool， Cytoscape software and its plug-in cytohubba to find the key genes. 【Results】 We obtained 262 DEGs， including 49 upregulated genes and 213 downregulated genes. The analysis of GO function and KEGG signal pathway enrichment showed that DEG was involved in DNA transcription and mitosis， cell division， synaptic signal transmission and other biological processes， and associated with cell cycle， tumor-related pathway， p53 signal pathway， synapsis-related signal pathway， cAMP signal pathway and calcium ion signal pathway. Ten key genes， namely， CDK1， CDC20， MAD2L1， KIF11， ASPM， TOP2A， TTK， NDC80， NUSAP1 and DLGAP5 were screened out by STRING analysis. 【Conclusion】 Ten key genes including CDK1 may play an important role in the initiation and progression of CNS-PNETs， providing new clues for exploring the pathogenesis of CNS-PNETs.

Objective: To investigate the value of automatic segmentation of carotid vessel wall in multicontrast MR images using U-Net neural network. Methods: Patients were retrospectively collected from 2012 to 2015 in Carotid Atherosclerosis Risk Assessment (CARE II) study. All patients who recently suffered ischemic stroke and/or transient ischemic attack underwent identical, state-of-the-art multicontrast MRI technique. A total of 17 568 carotid vessel wall MR images from 658 subjects were included in this study after inclusion criteria and exclusion criteria. All MR images were analyzed using customized analysis platform (CASCADE). Randomly, 10 592 images were assigned into training dataset, 3 488 images were assigned into validating dataset and 3 488 images were assigned into test dataset according to a ratio of 6∶2∶2. Data augmentation was performed to avoid over fitting and improve the ability of model generalization. The fine-tuned U-Net model was utilized in the segmentation of carotid vessel wall in multicontrast MR images. The U-Net model was trained in the training dataset and validated in the validating dataset. To evaluate the accuracy of carotid vessel wall segmentation, the sensitivity, specificity and Dice coefficient were used in the testing dataset. In addition, the interclass correlation and the Bland-Altman analysis of max wall thickness and wall area were obtained to demonstrate the agreement of the U-Net segmentation and the manual segmentation. Results: The sensitivity, specificity and Dice coefficient of the fine-tuned U-Net model achieved 0.878,0.986 and 0.858 in the test dataset, respectively. The interclass correlation (95% confidence interval) was 0.921 (0.915-0.925) for max wall thickness and 0.929 (0.924-0.933) for wall area. In the Bland-Altman analysis, the difference of max wall thickness was (0.037±0.316) mm and the difference of wall area was (1.182±4.953) mm². The substantial agreement was observed between U-Net segmentation method and manual segmentation method. Conclusion Automatic segmentation of carotid vessel wall in multicontrast MR images can be achieved using fine-tuned U-Net neural network, which is trained and tested in the large scale dataset labeled by professional radiologists.

The passing of ethical review is a necessary conditions and prerequisite for the development of life science and medical research involving humans. At present, some medical and health institutions have no or insufficient ethical review capabilities. The lack of ethical review ability has become a bottleneck restricting the development of life science and medical research involving humans. According to documents such as Opinions on Deepening the Reform of the Review and Approval System and Encouraging the Innovation of Pharmaceutical and Medical Devices, Opinions on Strengthening the Ethical Governance of Science and Technology, institutions can entrust competent institutional ethics review committees or regional ethics review committees in writing to conduct ethical review. Entrustment ethical review provides a viable solution for institutions that need to carry out life science and medical research involving humans but do not have an ethics (review) committee or the ethics (review) committee is not competent to review. To conduct the entrustment ethical review, the entrustment between the principal and the trustee is required. According to The Measures for Ethical Review of Life Sciences and Medical Research Involving Humans, if medical and health institutions and their ethical review committees do not accept the formal entrustment to provide the ethical review opinions for other institutions, the local health authorities at or above the county level will impose administrative penalties and sanctions on the relevant institutions and personnel in accordance with the law. Signing the entrustment ethical review contract, implementing legal compliance entrusted ethical review to protect the rights and interests of the trustee and the principal, and protect the research participants.