Diet Supplementation with Fish-Derived Extracts Suppresses Diabetes and Modulates Intestinal Microbiome in a Murine Model of Diet-Induced Obesity

Metabolic syndrome-related diseases affect millions of people worldwide. It is well established that changes in nutritional habits and lifestyle can improve or prevent metabolic-related pathologies such as type-2 diabetes and obesity. Previous reports have shown that nutritional supplements have the capacity to limit glucose intolerance and suppress diabetes development. In this study, we investigated the effect of dietary supplementation with fish-derived extracts on obesity and type 2 diabetes and their impact on gut microbial composition. We showed that nutritional supplements containing Fish Complex (FC), Fish Complex combined with Cod Powder (FC + CP), or Cod Powder combined with Collagen (CP + C) improved glucose intolerance, independent of abdominal fat accumulation, in a mouse model of diet-induced obesity and type 2 diabetes. In addition, collagen-containing supplements distinctly modulate the gut microbiome in high-fat induced obesity in mice. Our results suggest that fish-derived supplements suppress diet-induced type 2 diabetes, which may be partly mediated through changes in the gut microbiome. Thus, fish-derived supplements and particularly the ones containing fish collagen have potential beneficial properties as dietary supplements in managing type 2 diabetes and metabolic syndrome via modulation of the gut microbiome.     

Effect of insecticide injection on pyruvate kinase of the insect Tenebrio molitor (Coleopteran)

In the present study, we report on the changes observed in the kinetic properties of pyruvate kinase (PK) from whole body homogenate in the three developmental stages of the insect Tenebrio molitor after insecticide or acetone injection, and after injury and 24 h starvation. The apparent K_m value of the enzyme towards phosphoenolpyruvate was higher in the pupae stage than in the rest developmental stages although the same enzyme type appears to be present throughout the life span of the insect as judged by its V_max and sensitivity towards ATP and Alanine. The highest specific activity, twice as high as that of larvae and pupae, was observed in adults. Starvation resulted to activation of the enzyme by increasing the K_m value in the two feeding stages, namely larvae and adult, while injury had the opposite effect. Acetone injection did not have any significant effect at any stage. Insecticide injection had varying effects, depending upon the developmental stage, the dose and the type of the insecticide. In larvae, low doses of methyl paraoxon and methyl parathion activated the enzyme but as the dose increased the K_m value returned to normal levels. Low dose of decamethrin activated the enzyme also but at high dose it caused a severe inactivation as judged by a fivefold increase of the observed K_m. In pupae, decamethrin had no effect, methyl parathion had similar effects to those observed in larvae, and methyl paraoxon caused activation of the enzyme at any dose given. In the adult stage none of the injected insecticides had any effect on the K_m value although V_max and specific activity were significantly altered.     

An Efficient Approach to Spatiotemporal Analysis and Modeling of Air Pollution Data

A statistically efficient approach is adopted for modeling spatial time-series of large data sets. The estimation of the main diagnostic tool such as the likelihood function in Gaussian spatiotemporal models is a cumbersome task when using extended spatial time-series such as air pollution. Here, using the Innovation Algorithm, we manage to compute it for many spatiotemporal specifications. These specifications refer to the spatial periodic-trend, the spatial autoregressive moving average, the spatial autoregressive integrated and fractionally integrated moving average Gaussian models. Our method is applied to daily pollutants over a large metropolitan area like Athens. In the applied part of our paper, we first diagnose temporal and spatial structures of data using non-likelihood based criteria, such as the empirical autocorrelation and covariance functions. Second, we use likelihood and non-likelihood based criteria to select a spatiotemporal model among various specifications. Finally, using kriging we regionalize the resulting parameter estimates of the best-fitted model in space at any unmonitored location in the Athens region. The results show that a specific autoregressive integrated moving average spatiotemporal model can optimally perform in within and out of spatial sample estimation. Supplemental materials for this article are available from the journal website.     

Transcriptional profiling of antimicrobial peptides avian β-defensins in the chicken ovary during sexual maturation and in response to Salmonella enteritidis infection

Avian β-defensins (AvβDs) are antimicrobial peptides that play significant roles in the innate immune system in chickens. The aim of this study was to identify the types of AvβDs expressed in the chicken ovary, to investigate the effects of sexual maturation in the ovarian mRNA abundance and to determine the changes in their expression levels as a result to Salmonella enteritidis (SE) infection. RNA was extracted from the ovary of healthy prepubertal, sexually mature and aged birds, as well as from sexually mature and aged SE infected birds. Real-time PCR analysis revealed that 11 AvβDs genes were expressed in the chicken ovary. A significant up regulation of AvβD1, 3, 4, 5, 7 and 11 was observed in the ovary of sexually mature and aged birds. Furthermore, a significant up-regulation of AvβD4, 5, 7, 11 and 12 was observed in the ovary of SE infected sexually mature birds. These results suggest that the mRNA expression of at least six AvβDs increase with age in the ovary of laying hens, and that at least five AvβDs show an induction in their expression in response to SE infection, indicating an AvβD-mediated immune response mechanism in the chicken ovary.     

Determination of self-incompatible genotypes in 21 cultivated sweet cherry cultivars in Greece and implications for orchard cultivation

Summary

Sweet cherry is self-incompatible due to having a gametophytic self-incompatibility system. S alleles in the style and pollen determine possible crossing relationships. Knowledge of the S allele constitution of cultivars is important for sweet cherry growers and breeders. Recently, molecular methods have been developed to distinguish between S alleles in sweet cherry.The S allele genotypes of 21 sweet cherry cultivars widely grown in Greece, including 19 not previously genotyped, were determined based on their S-RNase gene sequences using PCR analysis. Eight different S alleles in ten combinations were distinguished and two new S-genotypes (S₁S₁₃ and S₄S₃₀) were documented. Four alleles, S₁, S₃, S₄, and S₉ were widespread and together were responsible for 85% of the S-haplotypes. Therefore many of the cultivar combinations were semi-compatible. In Greece, semi-compatibility was shown to correlate with low yields. However, the cultivar ‘Hybrid Tragana Edessis x Unknown’ (S₃S₁₃) and the cultivar ‘Kapsiotika’ (S₂S₅) carry rare S-haplotypes and are therefore fully cross-compatible with most of the cultivars analysed.