Oxidative stress is defined as an imbalance between production of free radicals and reactive metabolites or [reactive oxygen species (ROS)] and their elimination by through protective mechanisms, including (antioxidants). This Such imbalance leads to damage of cells and important biomolecules and cells, with hence posing a potential adverse impact on the whole organism. At the center of the day-to-day biological response to oxidative stress is the Kelch-like ECH-associated protein 1 (Keap1) - nuclear factor erythroid 2-related factor 2 (Nrf2)- antioxidant response elements (ARE) pathway, which regulates the transcription of many several antioxidant genes that preserve cellular homeostasis and detoxification genes that process and eliminate carcinogens and toxins before they can cause damage. The redox-sensitive signaling system Keap1/Nrf2/ARE plays a key role in the maintenance of cellular homeostasis under stress, inflammatory, carcinogenic, and pro-apoptotic conditions, which allows us to consider it as a pharmacological target. Herein, we review and discuss the recent advancements in the regulation of the Keap1/Nrf2/ARE system, and its role under physiological and pathophysiological conditions, e.g. such as in exercise, diabetes, cardiovascular diseases, cancer, neurodegenerative disorders, stroke, liver and kidney system, etc. and such.

AIM: Residual stress and strain are important for gastrointestinal function and relate to the geometric configuration, the loading conditions and the zerostress state of the gastrointestinal tract. The purpose of this project is to provide morphometric data and residual strains for the rat small intestine (n=11). METHODS:To approach the no-load state, the intestine was surgically excised, transferred to an organ bath and cut transversely into short ring-shaped segments. Each ring was cut radially for obtaining the zero-stress state. The residual stress can be characterised by an opening angle. The strain difference between the zero-stress state and the no-load state is called residual strain.

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Functional activation of NMDA receptors requires co-activation of glutamate-and glycine-binding sites. D-serine is considered to be an endogenous ligand for the glycine site of NMDA receptors. Using a combination of a rat formalininduced conditioned place avoidance (F-CPA) behavioral model and whole-cell patch-clamp recording in rostral anterior cingulate cortex (rACC) slices, we examined the effects of D-amino acid oxidase (DAAO), an endogenous D-serine-degrading enzyme, and 7-chlorokynurenate (7Cl-KYNA), an antagonist of the glycine site of NMDA receptors, on pain-related aversion. Degradation of endogenous D-serine with DAAO, or selective blockade of the glycine site of NMDA receptors by 7Cl-KYNA, effectively inhibited NMDA-evoked currents in rACC slices. Intra-rACC injection of DAAO (0.1 U) and 7Cl-KYNA (2 and 0.2 mM, 0.6 lL per side) 20 min before F-CPA conditioning greatly attenuated F-CPA scores, but did not affect formalin-induced acute nociceptive behaviors and electric foot shock-induced conditioned place avoidance. This study reveals for the first time that endogenous D-serine plays a critical role in painrelated aversion by activating the glycine site of NMDA receptors in the rACC. Furthermore, these results extend our hypothesis that activation of NMDA receptors in the rACC is necessary for the acquisition of specific pain-related negative emotion. Thus a new and promising strategy for the prevention of chronic pain-induced emotional disturbance might be raised. Keywords: conditioned place avoidance, glycine site of N-methyl-D-aspartate receptors, pain-related negative affect, rat, rostral anterior cingulate cortex, whole-cell recording. J. Neurochem. (2006Neurochem. ( ) 96, 1636Neurochem. ( -1647 Emotional distress is the most disruptive and undesirable feature of painful experiences. Clinical observations are increasingly indicating that patients with chronic pain suffer as much from emotional disturbance as from pain sensation per se. Physiological arousal and hypersensitivity to pain cause varying severities and qualities of negative affect, such as fear, anxiety, anger, aversion, depression and even a suicidal tendency, and these negative affective states in turn enhance pain perception (Alabsi and Rokke 1991;Rhudy and Meagher 2000). Although the neural structures, pathways, physiology and biochemistry associated with 'pain sensation' have been relatively well established in the past four decades, the underlying mechanisms of 'pain affect' remain unclear.Accumulating evidence from morphological, electrophysiological, neuroimaging and behavioral studies, as well as clinical observations, indicate that the anterior cingulate cortex (ACC) is a key structure that contributes to pain negative affect or unpleasantness. In early clinical reports, patients with surgical ablation of the ACC still felt pain, but

Diabetic nephropathy is one of the most significant microvascular complications in patients with type 2 diabetics. The concise mechanism of diabetic nephropathy is unknown and there is no successful treatment. The objective of study was to investigate effects of Chinese herbs (Tangshen Formula) on diabetic nephropathy in Otsuka Long-Evans Tokushima Fatty (OLETF) rats. OLETF rats and LETO rats were divided into four groups: LETO control, OLETF diabetics, OLETF diabetics treated with Tangshen Formula, and OLETF diabetics treated with Monopril. Body weight, blood glucose, and 24 h urinary proteins were measured once every four weeks. Blood samples and kidney tissues were obtained for analyses of total cholesterol, triglyceride, whole blood viscosity, plasma viscosity, and pathohistological examination at 36 and 56 weeksrespectively. Untreated OLETF rats displayed diabetic nephropathy over the study period. Treatment of OLETF rats with Tangshen Formula attenuated the increases in blood glucose, body weight, 24 h urinary protein content, serum total cholesterol, whole blood viscosity and plasma viscosity at certain time. Treatment with Tangshen Formula also reduced glomerulosclerotic index and interstitial fibrotic index seen in OLETF rats. In conclusion, Tangshen Formula could attenuate the development of diabetic nephropathy in OLETF rat diabetic model.

Acupuncture is one of the most effective alternative medical treatments in pain management with the advantages of simple application, low cost and minimal side effects. However its scientific evidence and laws of action are not very clear in cancer pain relieving. The aim of this study was to examine the immediate and therapeutic anti-hyperalgesic effect of electro-acupuncture (EA) on a mouse model of cutaneous cancer pain. B16-BL6 melanoma cells were inoculated into the plantar region of unilateral hind paw and the thermal hyperalgesia was measured by using radiant heat test and hot plate test. C57BL/6 mice showed moderate and marked hyperalgesia during days 8-12 and from day 14 after the orthotopic inoculation of B16-BL6 melanoma cells into the hind paw. Single EA on day 8 after inoculation showed significant analgesic effect immediately after the treatment, the analgesic effect reached its maximum within 15-30min and declined to its minimum at 50min after EA treatment. Single EA treatment on day 20 showed no significant analgesic effect; Repeated EA treatments (started from day 8, once every other day) showed therapeutic analgesic effect, while it showed no therapeutic effect when started from day 16, a relatively late stage of this cancer pain model. The results demonstrated that EA had anti-hyperalgesic effect on early stage of cutaneous cancer pain but not on late stage. These results indicated a tight correlation of EA anti-hyperalgesic effects with the time window of cancer pain.

Breast cancer is type of tumor that occurs in the tissues of the breast. It is most common type of cancer found in women around the world and it is among the leading causes of deaths in women. This paper presents the comparative analysis of machine learning, deep learning and data mining techniques being used for the prediction of breast cancer. Many researchers have put their efforts on breast cancer diagnoses and prognoses, every technique has different accuracy rate and it varies for different situations, tools and datasets being used. Our main focus is to comparatively analyze different existing Machine Learning and Data Mining techniques in order to find out the most appropriate method that will support the large dataset with good accuracy of prediction. The main purpose of this review is to highlight all the previous studies of machine learning algorithms that are being used for breast cancer prediction and this paper provides the all necessary information to the beginners who want to analyze the machine learning algorithms to gain the base of deep learning.

Backgrounds: Compelling evidence has emerged to support a close relationship between metabolic syndrome and esophageal cancer (EC).Aims: Using five baseline metabolism-related markers, we constructed a metabolic risk score (MRS), aiming to test whether MRS can improve the prediction of postsurgical EC-specific mortality over traditional demographic and clinicopathologic characteristics.Methods: Total 2535 EC patients who received three-field lymphadenectomy were enrolled from January 2000 to December 2010, and they were followed up until December 2015.Results: All EC patients were randomly split into derivation group (n=1512, 60%) and validation group (n=1014, 40%). MRS was generated in derivation group by adopting the Framingham 'points' system and shrinkage method, and it ranged from -9 to 17. EC-specific mortality risk increased with the increase of MRS, and adjusted estimates were more obvious in patients with upper tertile (MRS>6) than patients with lower MRS (≤2) in either derivation (hazard ratio [HR]=2.28, 95% confidence interval [CI]: 1.90-2.73, P<0.001) or validation group (HR=2.11, 95% CI: 1.66-2.67, P<0.001) or both groups (HR=2.37, 95% CI: 1.95-2.88, P<0.001). In Kaplan-Meier curve, cumulative survival rates differed significantly across tertiles of MRS. Further analysis indicated that MRS can improve classification accuracy and discriminatory ability over clinicopathologic parameters.Conclusions: Our findings supported the usefulness of baseline MRS in predicting the prognosis of postsurgical EC-specific mortality.