腹腔镜腹膜内补片植入式疝修补术应用解剖研究

目的腹股沟疝是临床常见的外科疾病,主要以手术治疗为主,而腹股沟疝气的手术治疗是以对腹股沟区的解剖逐步认识而发展的,外科医生对腹股沟的解剖贡献巨大,我们通过临床手术实践发现腹股沟的另一种能很好、安全的运用于IPOM手术的解剖。     

195株铜绿假单胞菌的临床分布及耐药性分析

目的 了解该院铜绿假单胞菌临床来源及耐药情况,以指导临床合理用药.方法 收集该院2010年1~12月临床分离的铜绿假单胞菌,采用WHONET5.4软件分析.结果 共分离铜绿假单胞菌195株,其中从痰标本中分离121株(62.05%),分泌物中分离50株(25.64%);呼吸内科分离55株(28.21%),脑外科分离45株(23.08%).其对美罗培南耐药率最低(6.27%),对左氧氟沙星、环丙沙星、头孢吡肟耐药率也较低,分别为11.28%、13.85%、19.49%.结论 铜绿假单胞菌易产生多重耐药性,必须加强耐药监测,为临床用药提供指导.     

现实主义综述在护理领域的应用进展

介绍现实主义综述的定义、哲学基础和实施步骤，以及该方法学在护理领域的研究范围、应用现状及优势和不足，旨在提高护理研究者对现实主义综述的认识，为开展现实主义的护理相关研究提供思路。     

S-1 monotherapy as second line chemotherapy in advanced gastric cancer patients previously treated with cisplatin/infusional fluorouracil

The treatment choice of advanced gastric carcinoma after failure from first-line therapy is quite limited. To evaluate the efficacy and toxicity of S-1 monotherapy in patients with advanced gastric cancer after failure of first line cisplatin and fluorouracil combination (CF). S-1 monotherapy as a second line treatment was given to the patients who had failed to CF combination in SC-101 study. The efficacy and toxicity of S-1 monotherapy were evaluated exploratory. The results indicated that forty-one patients received S-1 as a second line therapy after disease progression. The overall response rate and disease control rate were 14.6% and 41.5%, respectively. The median progression free survival (PFS) was 5.1 months (ange: 2.9~6.2 month). The median overall survival time was 6.4 months. The survival rates at 6 month and 1 year were 56% and 7.3%, respectively. Grade 3/4 adverse events were uncommonly occurred, including anemia (2.4%), neutropenia (2.4%), thrombocytopenia (4.9%) and rash (2.4%). There were no unexpected or life-threatening toxicities. Only one patient experienced dose reduction due to grade 3 rash. In conclusion, S-1 monotherapy provided a mild response rate and overall survival, and a favorable toxicity profile in the second line setting after the first line failure to cisplatin and fluorouracil combination.     

Deep learning for intelligent diagnosis in thyroid scintigraphy

ObjectiveTo construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy.MethodsWe constructed DL models with AlexNet, VGGNet, and ResNet. The models were trained separately with transfer learning. We measured each model’s performance with six indicators: recall, precision, negative predictive value (NPV), specificity, accuracy, and F1-score. We also compared the diagnostic performances of first- and third-year nuclear medicine (NM) residents with assistance from the best-performing DL-based model. The Kappa coefficient and average classification time of each model were compared with those of two NM residents.ResultsThe recall, precision, NPV, specificity, accuracy, and F1-score of the three models ranged from 73.33% to 97.00%. The Kappa coefficient of all three models was >0.710. All models performed better than the first-year NM resident but not as well as the third-year NM resident in terms of diagnostic ability. However, the ResNet model provided “diagnostic assistance” to the NM residents. The models provided results at speeds 400 to 600 times faster than the NM residents.ConclusionDL-based models perform well in diagnostic assessment by thyroid scintigraphy. These models may serve as tools for NM residents in the diagnosis of Graves’ disease and subacute thyroiditis.     

Circulating CCL20: A potential biomarker for active vitiligo together with the number of Th1/17 cells

Background

Vitiligo is an autoimmune disease with varying pathological features. Activation of the CCL20-CCR6 axis plays an important role in chronic inflammatory diseases. However, whether CCL20-CCR6 and Th1/17 cells are indicative of active vitiligo is unclear.

A GWAS-supported variant interacting with diabetes predicts risk of atherothrombotic stroke in Han Chinese population

Background: A recent genome-wide association study has identified that rs4376531 variant conferred risk of atherothrombotic stroke (AS) in a Japanese population. This study was to explore the association in Han Chinese population.

Methods: A total of 1036 cases and 643 healthy controls were enrolled. We genotyped rs4376531 variant with SNPscan. Multivariate logistic regression analysis was used to determine the association of genetic variation with risk of AS. Interaction analysis was examined by SNPStats web tool.

Results: After adjusting for gender, age, body mass index (BMI), hypertension, diabetes and smoking, compared with CC genotype, we observed that GC and GG/GC genotypes were associated with a significantly decreased risk of AS (OR?=?0.76, 95% CI?=?0.58–0.99 and OR?=?0.76, 95% CI?=?0.58–0.98, respectively). The decreased risk was more obvious among subgroups with high BMI (OR?=?0.63, 95% CI?=?0.45–0.88), no hypertension (OR?=?0.66, 95% CI?=?0.46–0.94), diabetes (OR?=?0.33, 95% CI?=?0.17–0.64), and smoking (OR?=?0.65, 95% CI?=?0.44–0.95) in the dominant model (GG/GC vs CC). Interaction analysis also revealed that compared with non-diabetic patients with CC genotype, diabetic patients with CC genotype had a 4.48-fold (OR?=?4.48; 95% CI?=?2.98–6.72) increased risk of AS.

Conclusion: Our data suggested that GC and GG/GC of rs4376531 contributed to a decreased risk of AS while CC genotype, interacting with diabetes, increased the stroke risk in Han Chinese population.