[A Case of Intestinal Lymphoma with Two Perforation in a Short Period Time].

An 86 years old man was diagnosed with jejunum tumor by detail examination of anemia. Eight days after endoscopy he developed abdominal pain, an emergency surgery was performed by a diagnosis of gastrointestinal perforation. They detected perforation in jejunum and performed jejunum resection, small intestinal lymphoma was diagnosed by histopathological examination. We were talked about chemotherapy against lymphoma, he was transferred at our hospital. The first chemotherapy was provided, abdominal pain appeared at 2 days after chemotherapy. Computed tomography revealed air bubbles out of intestinal tract, we performed emergency operation. A perforation of jejunum in the part where is different from the last time was existed, we performed jejunum resection. Chemotherapy was performed postoperatively, resulted in successful progress. Lymphoma of gastrointestinal tract often causes intestinal perforations, but reports that perforations heterochrony in separate parts multiple tumors of intestine is rare. We report a case of intestinal lymphoma with 2 perforations in a short period time.

[Suggesting the Significance of Pericardial Fat Pad in Bronchial Stump Fistula].

Bronchial stump fistula is a post-operative complication with poor outcome after pulmonary lobectomy. In order to prevent this complication, the bronchial stump is covered with pericardial fat tissue in our hospital. The case was 58 year old male who received adjuvant chemotherapy after sigmoidectomy for sigmoid colon cancer. As he developed multiple pulmonary metastases, 48 courses of chemotherapy were performed. The lesions had been localized at the right lower lobe, and neither increase in the size of these lesions nor development of other lesions were observed. Hence, an operation was performed. After right lower lobectomy, the bronchial stump was covered with the pericardial fat tissue. Three months after the operation, he developed pneumothorax, and bubbles were detected inside the fat. The pneumothorax was cured conservatively, and the bubbles disappeared spontaneously after 10 months. It is rare that the patient with bubbles in the covering tissue observed for a long time is cured conservatively, suggesting the significance of the stump pad.

Design of continuous-time recurrent neural networks with piecewise-linear activation function for generation of prescribed sequences of bipolar vectors.

A recurrent neural network (RNN) can generate a sequence of patterns as the temporal evolution of the output vector. This paper focuses on a continuous-time RNN model with a piecewise-linear activation function that has neither external inputs nor hidden neurons, and studies the problem of finding the parameters of the model so that it generates a given sequence of bipolar vectors. First, a sufficient condition for the model to generate the desired sequence is derived, which is expressed as a system of linear inequalities in the parameters. Next, three approaches to finding solutions of the system of linear inequalities are proposed: One is formulated as a convex quadratic programming problem and others are linear programming problems. Then, two types of sequences of bipolar vectors that can be generated by the model are presented. Finally, the case where the model generates a periodic sequence of bipolar vectors is considered, and a sufficient condition for the trajectory of the state vector to converge to a limit cycle is provided.

[A case of advanced gastric cancer that a medical therapy effect was provided grade 3 by a histopathological diagnosis after long-term chemotherapy].

A 64-year-old man underwent long-term chemotherapy for advanced gastric cancer with para-aortic lymph node metastasis (cT3 N3 M0 P0, cStage IV). S-1 (120 mg/day) was orally administered for 14 days and CDDP (60 mg/m2) was administered 10 times by intravenous drip on day 8. Next, paclitaxel (PTX 80 mg/m2) was administered 12 times by intravenous drip on days 1, 8 and 15. After 10 S-1/CDDP courses and 12 paclitaxel courses, the lymph node swelling decreased in size, but the tumor increased. CPT-11 (100 mg/m2) was administered as third-line therapy by intravenous drip on days 1, 8, 15 and 22. A partial response (PR) was obtained after 2 courses, but due to severe pyloric stenosis, a food passage disorder appeared. We performed distal gastrectomy with D2 lymph node dissection. The histological diagnosis revealed a complete disappearance of cancer cells in the stomach and lymph nodes.

Global convergence of SMO algorithm for support vector regression.

Global convergence of the sequential minimal optimization (SMO) algorithm for support vector regression (SVR) is studied in this paper. Given l training samples, SVR is formulated as a convex quadratic programming (QP) problem with l pairs of variables. We prove that if two pairs of variables violating the optimality condition are chosen for update in each step and subproblems are solved in a certain way, then the SMO algorithm always stops within a finite number of iterations after finding an optimal solution. Also, efficient implementation techniques for the SMO algorithm are presented and compared experimentally with other SMO algorithms.

Global convergence of decomposition learning methods for support vector machines.

Decomposition methods are well-known techniques for solving quadratic programming (QP) problems arising in support vector machines (SVMs). In each iteration of a decomposition method, a small number of variables are selected and a QP problem with only the selected variables is solved. Since large matrix computations are not required, decomposition methods are applicable to large QP problems. In this paper, we will make a rigorous analysis of the global convergence of general decomposition methods for SVMs. We first introduce a relaxed version of the optimality condition for the QP problems and then prove that a decomposition method reaches a solution satisfying this relaxed optimality condition within a finite number of iterations under a very mild condition on how to select variables.

Rigorous proof of termination of SMO algorithm for support vector machines.

Sequential minimal optimization (SMO) algorithm is one of the simplest decomposition methods for learning of support vector machines (SVMs). Keerthi and Gilbert have recently studied the convergence property of SMO algorithm and given a proof that SMO algorithm always stops within a finite number of iterations. In this letter, we point out the incompleteness of their proof and give a more rigorous proof.

Phosphorylation of 4E-BP1 predicts sensitivity to everolimus in gastric cancer cells.

We studied the effect of everolimus, an inhibitor of the mammalian target of rapamycin (mTOR) on human gastric cancer cell lines. Cell proliferation in 3 of 8 cell lines was effectively inhibited by everolimus. Basal phosphorylation level of 4E-BP1 (T37/46, T70) was significantly higher in everolimus-sensitive cells than in everolimus-resistant cells. In subcutaneous xenograft model, immunohistochemistry analysis revealed that everolimus-sensitive cells expressed high levels of phospho-4E-BP1 (T37/46). In conclusion, phosphorylation of 4E-BP1 may be a predictive biomarker of everolimus sensitivity in gastric cancer.