Streptozotocin-Induced Diabetes Models: Pathophysiological Mechanisms and Fetal Outcomes

Glucose homeostasis is controlled by endocrine pancreatic cells, and any pancreatic disturbance can result in diabetes. Because 8% to 12% of diabetic pregnant women present with malformed fetuses, there is great interest in understanding the etiology, pathophysiological mechanisms, and treatment of gestational diabetes. Hyperglycemia enhances the production of reactive oxygen species, leading to oxidative stress, which is involved in diabetic teratogenesis. It has also been suggested that maternal diabetes alters embryonic gene expression, which might cause malformations. Due to ethical issues involving human studies that sometimes have invasive aspects and the multiplicity of uncontrolled variables that can alter the uterine environment during clinical studies, it is necessary to use animal models to better understand diabetic pathophysiology. This review aimed to gather information about pathophysiological mechanisms and fetal outcomes in streptozotocin-induced diabetic rats. To understand the pathophysiological mechanisms and factors involved in diabetes, the use of pancreatic regeneration studies is increasing in an attempt to understand the behavior of pancreatic beta cells. In addition, these studies suggest a new preventive concept as a treatment basis for diabetes, introducing therapeutic efforts to minimize or prevent diabetes-induced oxidative stress, DNA damage, and teratogenesis.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Estadual Paulista, UNESP, Grad Program Gynecol Obstet & Mastol, Lab Expt Res Gynecol & Obstet,Botucatu Med Sch, BR-18618970 Botucatu, SP, BrazilUniv Estadual Paulista, UNESP, Botucatu Med Sch, Dept Gynecol & Obstet, BR-18618970 Botucatu, SP, BrazilUniv Estadual Paulista, UNESP, Grad Program Gynecol Obstet & Mastol, Lab Expt Res Gynecol & Obstet,Botucatu Med Sch, BR-18618970 Botucatu, SP, BrazilUniv Estadual Paulista, UNESP, Botucatu Med Sch, Dept Gynecol & Obstet, BR-18618970 Botucatu, SP, Brazi

Effects of exposure to cigarette smoke prior to pregnancy in diabetic rats

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to evaluate the effects of cigarette smoke exposure before pregnancy on diabetic rats and their offspring development.</p> <p>Methods</p> <p>Diabetes was induced by streptozotocin and cigarette smoke exposure was conducted by mainstream smoke generated by a mechanical smoking device and delivered into a chamber. Diabetic female Wistar rats were randomly distributed in four experimental groups (n minimum = 13/group): nondiabetic (ND) and diabetic rats exposed to filtered air (D), diabetic rats exposed to cigarette smoke prior to and into the pregnancy period (DS) and diabetic rats exposed to cigarette smoke prior to pregnancy period (DSPP). At day 21 of pregnancy, rats were killed for maternal biochemical determination and reproductive outcomes.</p> <p>Results</p> <p>The association of diabetes and cigarette smoke in DSPP group caused altered glycemia at term, reduced number of implantation and live fetuses, decreased litter and maternal weight, increased pre and postimplantation loss rates, reduced triglyceride and VLDL-c concentrations, increased levels of thiol groups and MDA. Besides, these dams presented increased SOD and GSH-Px activities. However, the increased antioxidant status was not sufficient to prevent the lipid peroxidation observed in these animals.</p> <p>Conclusion</p> <p>Despite the benefits stemming from smoking interruption during the pregnancy of diabetic rats, such improvement was insufficient to avoid metabolic alterations and provide an adequate intrauterine environment for embryofetal development. Therefore, these results suggest that it is necessary to cease smoking extensive time before planning pregnancy, since stopping smoking only when pregnancy is detected may not contribute effectively to fully adequate embryofetal development.</p

Evidence of the antioxidant effect of medicinal plants used in the treatment of diabetes mellitus in animals: An update

Diabetes mellitus (DM) is a syndrome of multiple etiology characterized by chronic hyperglycemia. This hyperglycemia induces increased production of reactive oxygen species (ROS) and decreased antioxidant defenses. Due to complications caused by diabetes, a large number of people have chosen medicinal plant-based alternative therapies to alleviate its effects. Thus, in this literature review, several experimental studies with the use of diabetic animals were analyzed to demonstrate the antioxidant effects of these plants and to verify if the titles and abstracts provided in the papers are compatible with the aims of our search.Laboratório de Pesquisa Experimental de Ginecologia e Obstetrícia Departamento de Ginecologia e Obstetrícia Faculdade de Medicina de Botucatu - Unesp, Distrito de Rubião Júnior, s/n, CEP: 18603-970, BotucatuLaboratório de Pesquisa Experimental de Ginecologia e Obstetrícia Departamento de Ginecologia e Obstetrícia Faculdade de Medicina de Botucatu - Unesp, Distrito de Rubião Júnior, s/n, CEP: 18603-970, Botucat

ForestEyes Project - Citizen Science and Machine Learning to detect deforested areas in tropical forests

The conservation of tropical forests is urgent and necessary due to the important role they play in the global ecosystem. Several governmental and private initiatives were created to detect deforestation in tropical forests through analyses of remote sensing images, which demands skilled labor and different ways to deal with a great amount of data. Citizen Science could be used to mitigate these challenges, as it consists of nonspecialized volunteers collecting, analyzing, and classifying data to solve technical and scientific problems. In this sense, this work proposes the ForestEyes Project 1, which aims to combine citizen science and machine learning for deforestation detection. The volunteers classify remote sensing images, and these data are used as the training set for classification algorithms. The volunteers classified more than 5, 000 tasks from remote sensing images of the Brazilian Legal Amazon, and the results were compared to a groundtruth from the Amazon Deforestation Monitoring Project PRODES. The volunteers achieved good labeling of the remote sensing data, even for recent deforestation tasks, building high-confidence labeled collections as they selected the most relevant samples and discarded noisy segments that might disrupt machine learning techniques. Finally, the proposed methodology is promising, and with improvements, it could be able to generate complementary information to official monitoring programs or even generate information for areas not yet monitored.</jats:p

BLOOD and PLACENTAL OXIDATIVE STRESS ASSESSMENT IN RATS WITH MILD DIABETES

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP