Analyzing brain structural differences associated with categories of blood pressure in adults using empirical kernel mapping-based kernel ELM.

BACKGROUND: Hypertension increases the risk of angiocardiopathy and cognitive disorder. Blood pressure has four categories: normal, elevated, hypertension stage 1 and hypertension stage 2. The quantitative analysis of hypertension helps determine disease status, prognosis assessment, guidance and management, but is not well studied in the framework of machine learning. METHODS: We proposed empirical kernel mapping-based kernel extreme learning machine plus (EKM-KELM+) classifier to discriminate different blood pressure grades in adults from structural brain MR images. ELM+ is the extended version of ELM, which integrates the additional privileged information about training samples in ELM to help train a more effective classifier. In this work, we extracted gray matter volume (GMV), white matter volume, cerebrospinal fluid volume, cortical surface area, cortical thickness from structural brain MR images, and constructed brain network features based on thickness. After feature selection and EKM, the enhanced features are obtained. Then, we select one feature type as the main feature to feed into KELM+, and the rest of the feature types are PI to assist the main feature to train 5 KELM+ classifiers. Finally, the 5 KELM+ classifiers are ensemble to predict classification result in the test stage, while PI is not used during testing. RESULTS: We evaluated the performance of the proposed EKM-KELM+ method using four grades of hypertension data (73 samples for each grade). The experimental results show that the GMV performs observably better than any other feature types with a comparatively higher classification accuracy of 77.37% (Grade 1 vs. Grade 2), 93.19% (Grade 1 vs. Grade 3), and 95.15% (Grade 1 vs. Grade 4). The most discriminative brain regions found using our method are olfactory, orbitofrontal cortex (inferior), supplementary motor area, etc. CONCLUSIONS: Using region of interest features and brain network features, EKM-KELM+ is proposed to study the most discriminative regions that have obvious structural changes in different blood pressure grades. The discriminative features that are selected using our method are consistent with the existing neuroimaging studies. Moreover, our study provides a potential approach to take effective interventions in the early period, when the blood pressure makes minor impacts on the brain structure and function.

Inhibition of mTORC1 renders cardiac protection against lipopolysaccharide.

Sepsis-induced cardiac dysfunction is a severe clinical problem. It is evident that rapamycin can protect heart from pathological injuries. However, there are no data demonstrating rapamycin reverse cardiac dysfunction induced by sepsis. In this study, Lipopolysaccharide (LPS) was administrated to mice and H9c2 cells. After treatment, we further determined cardiac function by echocardiography, ANP, BNP and inflammatory markers by qPCR and apoptosis by TUNEL staining. Moreover, mTORC1 signaling pathway and Akt activity were measured by Western blots. We found that rapamycin attenuated cardiac dysfunction, increase in ANP and BNP as well as apoptosis induced by LPS both in mice and in H9c2 cells. Unexpectedly, LPS did not significantly affect the mRNA levels of TNF-α and IL-6. Furthermore, rapamycin further reduced the decrease in mTORC1 signaling and Akt activity induced by LPS. In conclusion, rapamycin can protect heart from LPS induced damages by inhibition mTORC1 signaling and elevation of Akt activity.

[Observation on analgesia effect of electroacupuncture during gynecologic outpatient operation].

OBJECTIVE: To verify the feasibility of electroacupuncture analgesia applied to gynecologic outpatient operation. METHODS: Two hundred patients were randomly divided into an electroacupuncture analgesia group and an intravenous anesthesia group, 100 cases in each group. Operation types included artificial abortion, diagnostic curettage and remove of intrauterine divice. The electroacupuncture analgesia group was treated with electroacupuncture at bilateral Hegu (LI 4) and Neiguan (PC 6), and the routine gynecologic outpatient operation was performed under patients' waking state. The intravenous anesthesia group was treated with routine gynecologic outpatient operation after intravenous injection of fentanyl and propofol. RESULTS: The excellent rate and the effective rate of analgesia were 88.0% (88/100) and 100.0% (100/100) in the electroacupuncture analgesia group, and 94.0% (94/100) and 100.0% (100/100) in the intravenous anesthesia group, with no statistically significant differences between the two groups (all P > 0.05). There was no adverse reaction in the electroacupuncture anesthesia group, but 11 cases of adverse reactions in the intravenous anesthesia group. CONCLUSION: Electroacupuncture analgesia can effectively alleviate the pain during gynecologic outpatient operation and it is simple and safe without adverse reactions.