This article aims to elucidate the classification of and optimal treatment for pancreatic pseudocysts.Various approaches, including endoscopic drainage, percutaneous drainage, and open surgery, have been employed for the management of pancreatic pseudocysts. However, no scientific classification of pancreatic pseudocysts has been devised, which could assist in the selection of optimal therapy.We evaluated the treatment modalities used in 893 patients diagnosed with pancreatic pseudocysts according to the revision of the Atlanta classification in our department between 2001 and 2010. All the pancreatic pseudocysts have course of disease >4 weeks and have mature cysts wall detected by computed tomography or transabdominal ultrasonography. Endoscopic drainage, percutaneous drainage, or open surgery was selected on the basis of the pseudocyst characteristics. Clinical data and patient outcomes were reviewed.Among the 893 patients, 13 (1.5%) had percutaneous drainage. Eighty-three (9%) had type I pancreatic pseudocysts and were treated with observation. Ten patients (1%) had type II pseudocysts and underwent the Whipple procedure or resection of the pancreatic body and tail. Forty-six patients (5.2%) had type III pseudocysts: 44 (4.9%) underwent surgical internal drainage and 2 (0.2%) underwent endoscopic drainage. Five hundred six patients (56.7%) had type IV pseudocysts: 297 (33.3%) underwent surgical internal drainage and 209 (23.4%) underwent endoscopic drainage. Finally, 235 patients (26.3%) had type V pseudocysts: 36 (4%) underwent distal pancreatectomy or splenectomy and 199 (22.3%) underwent endoscopic drainage.A new classification system was devised, based on the size, anatomical location, and clinical manifestations of the pancreatic pseudocyst along with the relationship between the pseudocyst and the pancreatic duct. Different therapeutic strategies could be considered based on this classification. When clinically feasible, endoscopic drainage should be considered the optimal management strategy for pancreatic pseudocysts.

This study screened microRNAs (miRNAs) that are abnormally expressed in papillary thyroid carcinoma (PTC) tissues to identify PTC and nodular goiter and the degree of PTC malignancy. A total of 51 thyroid tumor tissue specimens paired with adjacent normal thyroid tissues were obtained from the Department of Surgical Oncology of Hangzhou First People's Hospital from June-December 2011. miRNA expression profiles were examined by microarrays and validated by quantitative real-time PCR (qRT-PCR). Expression levels of the miRNAs were analyzed to assess if they were associated with selected clinicopathological features. Eleven miRNAs were significantly differentially expressed between nodular goiter and PTC and between highly invasive and low invasive PTC. miR-199b-5p and miR-30a-3p were significantly differentially expressed among the three groups. miR-30a-3p, miR-122-5p, miR-136-5p, miR-146b-5p and miR-199b-5p were selected for further study by were different between the PTC and nodular goiter groups. miR-199b-5p was over-expressed in PTC patients with extrathyroidal invasion and cervical lymph node metastasis. In OPEN ACCESSMolecules 2014, 19 11587 conclusion miR-146b-5p, miR-30a-3p, and miR-199b-5p may serve as biomarkers for the diagnosis of PTC and miR-199b-5p is associated with PTC invasiveness.

With the explosion of healthcare information, there has been a tremendous amount of heterogeneous textual medical knowledge (TMK), which plays an essential role in healthcare information systems. Existing works for integrating and utilizing the TMK mainly focus on straightforward connections establishment and pay less attention to make computers interpret and retrieve knowledge correctly and quickly. In this paper, we explore a novel model to organize and integrate the TMK into conceptual graphs. We then employ a framework to automatically retrieve knowledge in knowledge graphs with a high precision. In order to perform reasonable inference on knowledge graphs, we propose a contextual inference pruning algorithm to achieve efficient chain inference. Our algorithm achieves a better inference result with precision and recall of 92% and 96%, respectively, which can avoid most of the meaningless inferences. In addition, we implement two prototypes and provide services, and the results show our approach is practical and effective.