Inhibitory postsynaptic actions of taurine, GABA and other amino acids on motoneurons of the isolated frog spinal cord

The actions of glycine, GABA, α-alanine, β-alanine and taurine were studied by intracellular recordings from lumbar motoneurons of the isolated spinal cord of the frog. All amino acids tested produced a reduction in the amplitude of postsynaptic potentials, a blockade of the antidromic action potential and an increase of membrane conductance. Furthermore, membrane polarizations occurred, which were always in the same direction as the IPSP. All these effects indicate a postsynaptic inhibitory action of these amino acids. When the relative strength of different amino acids was compared, taurine had the strongest inhibitory potency, followed by β-alanine, α α-alanine, GABA and glycine. Topically applied strychnine and picrotoxin induced different changes of postsynaptic potentials, indicating that distinct inhibitory systems might be influenced by these two convulsants. Interactions with amino acids showed that picrotoxin selectively diminished the postsynaptic actions of GABA, while strychnine reduced the effects of taurine, glycine, α- and β-alanine. But differences in the susceptibility of these amino acid actions to strychnine could be detected: the action of taurine was more sensitively blocked by strychnine compared with glycine, α- and β-alanine. With regard to these results the importance of taurine and GABA as transmitters of postsynaptic inhibition on motoneurons in the spinal cord of the frog is discussed

Support vector machine model for diagnosis of lymph node metastasis in gastric cancer with multidetector computed tomography: a preliminary study

<p>Abstract</p> <p>Background</p> <p>Lymph node metastasis (LNM) of gastric cancer is an important prognostic factor regarding long-term survival. But several imaging techniques which are commonly used in stomach cannot satisfactorily assess the gastric cancer lymph node status. They can not achieve both high sensitivity and specificity. As a kind of machine-learning methods, Support Vector Machine has the potential to solve this complex issue.</p> <p>Methods</p> <p>The institutional review board approved this retrospective study. 175 consecutive patients with gastric cancer who underwent MDCT before surgery were included. We evaluated the tumor and lymph node indicators on CT images including serosal invasion, tumor classification, tumor maximum diameter, number of lymph nodes, maximum lymph node size and lymph nodes station, which reflected the biological behavior of gastric cancer. Univariate analysis was used to analyze the relationship between the six image indicators with LNM. A SVM model was built with these indicators above as input index. The output index was that lymph node metastasis of the patient was positive or negative. It was confirmed by the surgery and histopathology. A standard machine-learning technique called k-fold cross-validation (5-fold in our study) was used to train and test SVM models. We evaluated the diagnostic capability of the SVM models in lymph node metastasis with the receiver operating characteristic (ROC) curves. And the radiologist classified the lymph node metastasis of patients by using maximum lymph node size on CT images as criterion. We compared the areas under ROC curves (AUC) of the radiologist and SVM models.</p> <p>Results</p> <p>In 175 cases, the cases of lymph node metastasis were 134 and 41 cases were not. The six image indicators all had statistically significant differences between the LNM negative and positive groups. The means of the sensitivity, specificity and AUC of SVM models with 5-fold cross-validation were 88.5%, 78.5% and 0.876, respectively. While the diagnostic power of the radiologist classifying lymph node metastasis by maximum lymph node size were only 63.4%, 75.6% and 0.757. Each SVM model of the 5-fold cross-validation performed significantly better than the radiologist.</p> <p>Conclusions</p> <p>Based on biological behavior information of gastric cancer on MDCT images, SVM model can help diagnose the lymph node metastasis preoperatively.</p

Inflammatory pseudo-tumor of the liver: a rare pathological entity

Inflammatory pseudo-tumor (IPT) of the liver is a rare benign neoplasm and is often mistaken as a malignant entity. Few cases have been reported in the literature and the precise etiology of inflammatory pseudotumor remains unknown. Patients usually present with fever, abdominal pain and jaundice. The proliferation of spindled myofibroblast cells mixed with variable amounts of reactive inflammatory cells is characteristics of IPT. We reviewed the literature regarding possible etiology for IPT with a possible suggested etiology

Micro-tensile testing of reduced-activation ferritic steel F82H irradiated with Fe and He ions

Micro-tensile tests were conducted on reduced-activation ferritic steel F82H specimens after irradiation with Feand He ions. The displacement damage levels were 50 and 200 dpa, and helium concentrations were 0, 2000 and5000 appm. The specimens had dimensions of 8 × 1 × 1 μm for the gage section and they were tension tested atroom temperature in a vacuum. The yield strengths of the unirradiated specimens were close to the literaturevalue reported for a large, unirradiated specimen. The increases in yield strength and ultimate tensile strengthdue to Fe ion irradiation were clearly observed. The loss of work hardening was confirmed for the 200 dpaspecimens (0 or 2000 appmHe). Higher yield strength and ultimate tensile strength were confirmed for the50 dpa/5000 appmHe specimen compared to the no helium specimen (50 dpa/0 appmHe). However, no ap-parent helium effects were confirmed for the 200 dpa/2000 appmHe specimen by the micro-tensile test at roomtemperature