Objective To explore the practical effects of multiple intelligence theory applied in Obstetrics and Gynecology clinical internship teaching for the medical students.Methods The Eight-year program medical students in the classes of 2009 and 2010 were collected,among which 45 students in theexperimental group were taught by multiple intelligence theory,and 40 students in the control group were taught by traditional teaching methods.The results determined by the questionnaire survey,written test scores,operation test scores,medical documents writing results,usual performance and teachers' job evaluation.The data were analyzed by SPSS 17.0 statistical software,chi-square test and t test.Results Compared with control group,the written test scores,operation test scores,medical documents writing results,usual performance,the student questionnaire and teachers' self work evaluation of the experimental group were significantly higher (89.720 ± 8.147) vs.(81.140 ± 9.142),(88.230 ± 4.328) vs.(80.360 ± 5.621),(86.530 ± 2.641) vs.(81.580 ± 2.036),(87.650 ± 3.957) vs.(82.360 ± 6.392),which showed statistically significant difference (P＜0.05).The experimental group students think the teaching methods with multiple intelligence theory are novel,producing following positive effects in fully inspiring learning initiative,fostering the ability of independent study,enlightening clinical thinking,strengthening collective cooperation and improving the ability of doctor-patient communication and problem-solving etc.Conclusions It shows that the application of multiple intelligences theory in Obstetrics and Gynecology clinical internship for the medical students could motivate the students' self-confidence and enthusiasm,and contribute to train high quality medical talent,Meanwhile,the higher requirements are needed for teachers.It is worth promoting the application.

In automatic skin damage analysis,segmentation is a challenging and critical operation due to factors such as the shape and contrast of hair and skin lesions on the skin.Compared with traditional segmentation methods,deep learning seamlessly integrates feature extraction and task-specific decision-making,achieving segmentation tasks more accurately and efficiently,and effectively reducing the burden and cost of skin cancer screening.This article first introduces the background of dermoscopic segmentation and deep learning models,and introduces the application of deep learning in dermoscopic segmentation.Secondly,this article introduces the algorithm models of convolutional neural networks and attention mechanisms,reviews the application of fused attention convolutional neural networks in dermoscopic segmentation since Jan 2022,and summarizes the improvement strategies,the advantages and disadvantages of the model.The model is further analyzed based on commonly used datasets of dermoscopy and evaluation indicators of image segmentation.Finally,the application of fused attention convolutional neural network in dermoscopic segmentation is summarized and prospected.

Objective:To explore the effect of the feedback method education model in patients with recurrent aphthous ulcer (RAU) , so as to provide a new education model for clinical health education.Methods:From May 2019 to May 2020, convenience sampling was used to select 76 RAU patients in the Stomatology Hospital of Southern Medical University. According to the method of random number table, the patients were divided into the experimental group and the control group, with 38 cases in each group. The experimental group implemented feedback method education model, and the control group carried out routine health education. The scores of Morisky Medication Adherence Scale (MMAS-8) , number of ulcers, healing time, pain degree, ulcer diameter and the Oral Health Impact Profile (OHIP-14) scores of patients were compared between the two groups before and after the intervention.Results:The score of MMAS-8 in the experimental group was higher than that in the control group after the intervention, and the difference was statistically significant ( P<0.05) . After the intervention, the number of ulcers in the experimental group was less than that in the control group, and the ulcer diameter was smaller than that in the control group, and the healing time was shorter than that in the control group, and the pain degree was lower than that in the control group, and the differences were statistically significant ( P<0.05) . After the intervention, the total score and dimension scores of OHIP-14 in the experimental group were lower than those in the control group, and the differences were also statistically significant ( P<0.05) . Conclusions:The feedback method education model can improve the adherence of RAU patients, the clinical indicators and the quality of life related to oral health of patients, which is worthy of clinical promotion and application.

Objective: To study the segment of liver according to the large amount of three-dimensional(3D) reconstructive images of normal human livers and the vascular system, and to recognize the basic functional liver unit based on the anatomic features of the intrahepatic portal veins. Methods: The enhanced CT primitive DICOM files of 1 260 normal human livers from different age groups who treated from October 2013 to February 2017 provided by 16 hospitals were analyzed using the computer-aided surgery system.The 3D liver and liver vascular system were reconstructed, and the digital liver 3D model was established.The vascular morphology, anatomical features, and anatomical distributions of intrahepatic portal veins were statistically analyzed. Results: The digital liver model obtained from the 3D reconstruction of CAS displayed clear intrahepatic portal vein vessels of level four.Perform a digital liver segments study based on the analysis of level four vascular distribution areas.As the less anatomical variation of left hepatic portal vein, the liver was classified into four types of liver segmentation mainly based on right hepatic portal vein.Type A was similar to Couinaud or Cho′s segmentation, containing 8 segments(537 cases, 42.62%). Type B contained 9 segments as there are three ramifications of right-anterior portal vein(464 cases, 36.82%). The main difference for Type C was the variation of right-posterior portal vein which was sector shape(102 cases, 8.10%). Type D contained the cases with special portal vein variations, which needs three-dimensional simulation to design individualized liver resection plan(157 cases, 12.46%). These results showed that there was no significant difference in liver segmental typing between genders(χ²=2.179, P=0.536) and did not reveal any significant difference in liver segmental typing among the different age groups(χ²=0.357, P=0.949). Conclusions The 3D digital liver model can demonstrate the true 3D anatomical structures, and its spatial vascular variations.The observation of anatomic features, distribution areas of intrahepatic portal veins and individualized liver segmentation achieved via digital medical 3D visualization technology is of great value for understand the complexity of liver anatomy and to guide the precise hepatectomy.

OBJECTIVE：To systematically evaluate the effects of CYP1A2 gene polymorphisms on blood concentrations of antipsychotic drugs （haloperidol，clozapine，olanzapine），and to provide evidence-based reference for the clinical drug use . METHODS：Retrieved from Cochrane Library ，PubMed，Embase，CBM，CNKI and Wanfang data ，during the inception to Nov. 2019，cross-sectional study was conducted to investigate the effects of CYP1A2 gene polymorphisms on blood concentrations of antipsychotic drugs （haloperidol，clozapine，olanzapine）were collected. After screening the literature ，extracting the data and quality evaluation with Q-Genie tool ，Meta-analysis was performed by using Rev Man 5.3 software. RESULTS ：A total of 11 cross-sectional studies were included ，with a total of 914 patients. Of these ，haloperidol was used in 2 studies，clozapine was used in 5 studies，and olanzapine was used in 4 studies. Meta-analysis showed that there was no statistically significant difference in the blood concentration of haloperidol between CYP1A2（－2964G＞A）G/G type and G/A+A/A type [SMD ＝－0.22，95％CI（－0.66， 0.23），P＝0.35]. The blood concentration of clozapine in CYP1A2（－163C＞A）A/C type was significantly lower than C/C type [SMD ＝0.31，95％CI（0.01，0.62），P＝0.04]；there was no statistical significance in blood concentration of clozapine between A/A type and C/C type [SMD ＝0.09，95％CI（－0.21，0.40），P＝0.56]，between A/A type and A/C type [SMD ＝－0.22，95％CI（－0.55， 0.10），P＝0.18]，between CYP1A2（－2467delT）delT/delT type and T/T type [SMD ＝－0.11，95％CI（－0.75，0.52），P＝0.72]， between delT/T type and T/T type [SMD ＝0.01，95％CI（－0.33，0.34），P＝0.97]，between delT/delT type and delT/T type [SMD ＝ －0.15，95％CI（－0.80，0.05），P＝0.66]. The blood concentration of olanzapine in CYP1A2（－163C＞A）A/A type was signifi- cantly lower than A/C type [SMD ＝－0.31，95％CI（－0.55， － 0.08），P＝0.009]；there was no statistically significant difference in the blood concentration of olanzapine between A/A liukefeng-num.1@163.com type and C/C type [SMD ＝－0.20，95％CI（－0.61，0.21），P＝ 0.34]，between A/C type and C/C type [SMD ＝0.06，95％CI E-mail：hnmuzj@163.com （－0.35，0.47），P＝0.77]，between CYP1A2（－2467delT）delT/T type and T/T type [SMD ＝0.28，95％CI（－0.15，0.71），P＝0.20]. CONCLUSIONS：CYP1A2（－163C＞A）A/C type is related to the reduction of clozapine blood concentration ，and A/A type is related to the reduction of olanzapine blood concentration. CYP1A2 （－163C＞A）gene polymorphism is significance for guiding individualized medication of schizophrenia patients.