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find Author "WUKai" 3 results
  • Study on Abnormal Topological Properties of Structural Brain Networks of Patients with Depression Comorbid with Anxiety

    This paper is aimed to analyze the topological properties of structural brain networks in depressive patients with and without anxiety and to explore the neuropath logical mechanisms of depression comorbid with anxiety. Diffusion tensor imaging and deterministic tractography were applied to map the white matter structural networks. We collected 20 depressive patients with anxiety (DPA), 18 depressive patients without anxiety (DP), and 28 normal controls (NC) as comparative groups. The global and nodal properties of the structural brain networks in the three groups were analyzed with graph theoretical methods.The result showed that ① the structural brain networks in three groups showed small-world properties and highly connected global hubs predominately from association cortices; ② DP group showed lower local efficiency and global efficiency compared to NC group, whereas DPA group showed higher local efficiency and global efficiency compared to NC group; ③ significant differences of network properties (clustering coefficient, characteristic path lengths, local efficiency, global efficiency) were found between DPA and DP groups; ④ DP group showed significant changes of nodal efficiency in the brain areas primarily in the temporal lobe and bilateral frontal gyrus, compared to DPA and NC groups. The analysis indicated that the DP and DPA groups showed nodal properties of the structural brain networks, compared to NC group. Moreover, the two diseased groups indicated an opposite trend in the network properties. The results of this study may provide a new imaging index for clinical diagnosis for depression comorbid with anxiety.

    Release date:2017-01-17 06:17 Export PDF Favorites Scan
  • Application of Telescopic Embedding Anastomosis in Surgical Treatment of Esophageal and Cardiac Carcinoma: A Case Control Study

    ObjectiveTo explore the effects of modified telescopic embedding anastomosis in surgical treatment of esophageal and cardiac carcinoma. MethodsWe retrospectively analyzed the clinical data of 160 patients with esophageal or cardiac cancer undergoing surgery in our group from January 2014 through May 2015. There were 119 males and 41 females with a mean age of 61.6±7.1 years. Sixty-four patients received Sweet esophagectomy and 96 patients underwent minimally invasive Mckeown esophagectomy, and all the patients received end to side mechanical anastomosis. The patients were divided into a modified group and a traditional group according to the embedding types. There were 34 males and 12 females aged 61.7±6.4 years in the modified group undergoing modified telescopic embedding. There were 85 males and 29 females aged 62.2±7.5 years in the traditional group undergoing traditional interrupted horizontal mattress suture embedding. The anastomostic time and postoperative complications were compared between the two groups. ResultsCompared with the traditional group, obviously lower incidence of anastomotic fistula (0.0% vs. 12.3%, χ2=4.478, P=0.013), shorter anastomosis time (28.9±2.9 min vs. 30.0±3.1 min, t=-1.983, P=0.049), but a higher incidence of anastomotic stenosis (30.4% vs. 3.5%, χ2=23.799, P=0.000) in the modified group were found. There were no significant differences in the incidences of pulmonary complications, cardiovascular complications, laryngeal recurrent nerve injury, or perioperative mortality between the two groups (P>0.05). ConclusionModified telescopic embedding anastomosis is safe and feasible in surgical treatment of esophageal and cardiac carcinoma, and can effectively reduce the incidence of anastomotic fistula.

    Release date:2016-10-19 09:15 Export PDF Favorites Scan
  • A Maternal Health Care System Based on Mobile Health Care

    Wearable devices are used in the new design of the maternal health care system to detect electrocardiogram and oxygen saturation signal while smart terminals are used to achieve assessments and input maternal clinical information. All the results combined with biochemical analysis from hospital are uploaded to cloud server by mobile Internet. Machine learning algorithms are used for data mining of all information of subjects. This system can achieve the assessment and care of maternal physical health as well as mental health. Moreover, the system can send the results and health guidance to smart terminals.

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