CONTEXT AND OBJECTIVE: Some studies have suggested a wide range of possible mechanisms through which probiotics may play a role in diabetes prevention and treatment. However, the underlying mechanisms are not fully understood. We conducted this study to review the potential mechanisms suggested for the effect of probiotics in diabetes. DESIGN AND SETTING: Narrative review conducted at the Food Security Research Center of Isfahan. METHODS: A search in the electronic databases MEDLINE (PubMed), Cochrane Library, Web of Science and Google scholar was performed up to October 2016. RESULTS:The initial search yielded 1214 reports. After removing duplicates, 704 titles and abstracts were screened. Finally, out of 83 full-text articles that were reviewed for eligibility, 30 articles were included in the final analysis. The anti-diabetic mechanisms for probiotics reported encompass intraluminal and direct effects on the intestinal mucosa and microbiota (n = 13), anti-inflammatory and immunomodulatory effects (n = 10), antioxidative effects (n = 5), effects on endoplasmic reticulum (ER) stress and expression of genes involved in glucose homeostasis and insulin resistance (n = 6), with some studies pointing to more than one mechanism. CONCLUSION: The results may throw some light on the capacity of probiotics as a novel approach towards controlling diabetes. However, further human studies are warranted to elucidate and confirm the potential role of probiotics in diabetes prevention and treatment. Also, it needs to be ascertained whether the effectiveness of probiotics in diabetes prevention and treatment is dependent on the strain of the microorganisms. Os mecanismos antidiabéticos relatados dos probióticos abrangem efeitos intraluminais e diretos na mucosa e microbiota intestinal (n = 13), efeitos anti-inflamatórios e imunomoduladores (n = 10), efeitos antioxidativos (n = 5), efeitos sobre o estresse de retículo endoplasmático (RE) e expressão de genes envolvidos na homeostase da glicose e resistência à insulina (n = 6), com alguns estudos apontando para mais de um mecanismo. CONCLUSÃO: Os resultados podem lançar alguma luz sobre os probióticos como uma nova abordagem no controle do diabetes, no entanto, mais estudos em humanos são justificados para elucidar e confirmar o papel potencial dos probióticos na prevenção e tratamento do diabetes. Além disso, deverá ser determinado se a eficácia dos probióticos na prevenção e tratamento do diabetes é dependente da cepa dos microrganismos. RESUMO IPhD. Doctoral

Recently, interest in targeted cancer therapies via metabolic pathways has been renewed with the discovery that many tumors become dependent on glucose uptake during anaerobic glycolysis. Also the inability of ketone bodies metabolization due to various deficiencies in mitochondrial enzymes is the major metabolic changes discovered in malignant cells. Therefore, administration of a ketogenic diet (KD) which is based on high in fat and low in carbohydrates might inhibit tumor growth and provide a rationale for therapeutic strategies. So, we conducted this systematic review to assess the effects of KD on the tumor cells growth and survival time in animal studies. All databases were searched from inception to November 2015. We systematically searched the PubMed, Scopus, Google Scholars, Science Direct and Cochrane Library according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. To assess the quality of included studies we used SYRCLE's RoB tool. 268 articles were obtained from databases by primary search. Only 13 studies were eligible according to inclusion criteria. From included studies, 9 articles indicate that KD had a beneficial effect on tumor growth and survival time. Tumor types were included pancreatic, prostate, gastric, colon, brain, neuroblastoma and lung cancers. In conclusions, although studies in this field are rare and inconsistence, recent findings have demonstrated that KD can potentially inhibit the malignant cell growth and increase the survival time. Because of differences physiology between animals and humans, future studies in cancer patients treated with a KD are needed.

In many problems in the field of spatial statistics, when modeling the trend functions, predictors or covariates are available and the goal is to build a regression model to describe the relationship between the response and predictors. Generally, in spatial regression models, the trend function is often linear and it is assumed that the response mean is a linear function of predictor values in the same location where the response variable is observed. But, in real applications, the neighboring predictors sometimes provide valuable information about the response variable particulary when the distance between the locations is small. Having considered this subject matter, Heaton and Gelfand [6] suggested using kernel averaged predictors for modeling trend functions in which neighboring predictor information are also used. The models proposed by Heaton an Gelfand seemed to be bound by data normality. So, in many more application problems, spatial response variables follow a skew distribution. Therefore, in this article, skew Gaussian spatial regression model is studied and the performance of the model is presented and evaluated in comparison with Gaussian spatial regression models based on kernel averaged predictors using simulation studies and real examples.