Postnatal Pancreatic Islet β Cell Function and Insulin Sensitivity at Different Stages of Lifetime in Rats Born with Intrauterine Growth Retardation

Epidemiological studies have linked intrauterine growth retardation (IUGR) to the metabolic diseases, consisting of insulin resistance, type 2 diabetes, obesity and coronary artery disease, during adult life. To determine the internal relationship between IUGR and islet β cell function and insulin sensitivity, we established the IUGR model by maternal nutrition restriction during mid- to late-gestation. Glucose tolerance test and insulin tolerance test(ITT) in vivo and glucose stimulated insulin secretion(GSIS) test in vitro were performed at different stages in IUGR and normal groups. Body weight, pancreas weight and pancreas/body weight of IUGR rats were much lower than those in normal group before 3 weeks of age. While the growth of IUGR rats accelerated after 3 weeks, pancreas weight and pancreas/body weight remained lower till 15 weeks of age. In the newborns, the fasting glucose and insulin levels of IUGR rats were both lower than those of controls, whereas glucose levels at 120 and 180 min after glucose load were significantly higher in IUGR group. Between 3 and 15 weeks of age, both the fasting glucose and insulin levels were elevated and the glucose tolerance was impaired with time in IUGR rats. At age 15 weeks, the area under curve of insulin(AUCi) after glucose load in IUGR rats elevated markedly. Meanwhile, the stimulating index of islets in IUGR group during GSIS test at age 15 weeks was significantly lower than that of controls. ITT showed no significant difference in two groups before 7 weeks of age. However, in 15-week-old IUGR rats, there was a markedly blunted glycemic response to insulin load compared with normal group. These findings demonstrate that IUGR rats had both impaired pancreatic development and deteriorated glucose tolerance and insulin sensitivity, which would be the internal causes why they were prone to develop type 2 diabetes

Epigenomic and functional analyses reveal roles of epialleles in the loss of photoperiod sensitivity during domestication of allotetraploid cottons

Abstract Background Polyploidy is a pervasive evolutionary feature of all flowering plants and some animals, leading to genetic and epigenetic changes that affect gene expression and morphology. DNA methylation changes can produce meiotically stable epialleles, which are transmissible through selection and breeding. However, the relationship between DNA methylation and polyploid plant domestication remains elusive. Results We report comprehensive epigenomic and functional analyses, including ~12 million differentially methylated cytosines in domesticated allotetraploid cottons and their tetraploid and diploid relatives. Methylated genes evolve faster than unmethylated genes; DNA methylation changes between homoeologous loci are associated with homoeolog-expression bias in the allotetraploids. Significantly, methylation changes induced in the interspecific hybrids are largely maintained in the allotetraploids. Among 519 differentially methylated genes identified between wild and cultivated cottons, some contribute to domestication traits, including flowering time and seed dormancy. CONSTANS (CO) and CO-LIKE (COL) genes regulate photoperiodicity in Arabidopsis. COL2 is an epiallele in allotetraploid cottons. COL2A is hypermethylated and silenced, while COL2D is repressed in wild cottons but highly expressed due to methylation loss in all domesticated cottons tested. Inhibiting DNA methylation activates COL2 expression, and repressing COL2 in cultivated cotton delays flowering. Conclusions We uncover epigenomic signatures of domestication traits during cotton evolution. Demethylation of COL2 increases its expression, inducing photoperiodic flowering, which could have contributed to the suitability of cotton for cultivation worldwide. These resources should facilitate epigenetic engineering, breeding, and improvement of polyploid crops

Estimation of distributions involving unobservable events: The case of optimal search with unknown Target Distributions

We consider the problem of estimating the parameters of a distribution when the underlying events are themselves unobservable. The aim of the exercise is to perform a task (for example, search a web-site or query a distributed database) based on a distribution involving the state of nature, except that we are not allowed to observe the various "states of nature" involved in this phenomenon. In particular, we concentrate on the task of searching for an object in a set of N locations (or bins) {C 1, C 2, C N }, in which the probability of the object being in the location C i is p i , where P = [p 1, p 2, p N ] T is called the Target Distribution. Also, the probability of locating the object in the bin within a specified time, given that it is in the bin, is given by a function called the Detection function, which, in its most common instantiation, is typically, specified by an exponential function. The intention is to allocate the available resources so as to maximize the probability of locating the object. The handicap, however, is that the time allowed is limited, and thus the fact that the object is not located in bin C i within a specified time does not necessarily imply that the object is not in C i . This problem has applications in searching large databases, distributed databases, and the world-wide web, where the location of the files sought for are unknown, and in developing various military and strategic policies. All of the research done in this area has assumed the knowledge of the {p i }. In this paper we consider the problem of obtaining error bounds, estimating the Target Distribution, and allocating the search times when the {p i } are unknown. To the best of our knowledge, these results are of a pioneering sort - they are the first available results in this area, and are particularly interesting because, as mentioned earlier, the events concerning the Target Distribution, in themselves, are unobservable

An experimental study of fault slips under unloading condition in coal mines

Abstract To investigate the mechanism of fault slips in coal mines, a biaxial shear experiment was carried out under unloading condition based on the fault F16 in Yima city, China. Two rock samples were used in the experiment and each sample was composed of two triangular sandstone blocks which were put together to simulate the fault. One rock sample was used to do fault slip tests and it was called slip-test sample. The other sample for comparison with the slip-test one was untested, and it was named non-slip-test sample. During the biaxial shear experiment of the slip-test sample, normal and shear strains near the fault, acoustic emission (AE) signals, and the sliding displacement were measured. After the experiment, microscopic profiles of fault surfaces of both rock samples were examined by scanning electron microscope (SEM). In addition, a numerical simulation was conducted to model the slip of the fault F16. The results indicate that: (1) three fault slips occurred during the biaxial shear experiment, and the shear stress, normal and shear strains in the first slip showed the maximum variation among three slips; (2) Shear strains near the two ends of the fault had a more significate variation than that in the middle part, and the typical trend of shear strains was first dropping, then increasing rapidly, and then falling slowly to a specific value during the first slip; (3) The first slip had the largest sliding displacement of 29.89 μm, and in the first slip three phases including slow slip, main shock and aftershock occurred based on AE monitoring results. (4) On the fault surface of non-slip-test sample, microstructures such as bulges, voids and veins were ubiquitous and notable, making the fault surface much rough, while similar microstructures were few and the fault surface of the slip-test sample was flattened after fault slips; (5) The slipping direction in the shallow part and deep part of the fault F16 were opposite during mining