Ultrastructural changes of sheep cumulus-oocyte complexes following different methods of vitrification

To determine the ultrastructural changes of sheep cumulus-oocyte complexes (COCs) following different methods of vitrification, good quality isolated COCs (GV stage) were randomly divided into the non-vitrified control, conventional straw, cryotop and solid surface vitrification groups. In both conventional and cryotop methods, vitrified COCs were respectively loaded by conventional straws and cryotops, and then plunged directly into liquid nitrogen (LN2); whereas in the solid surface group, vitrified COCs were first loaded by cryotops and then cooled before plunging into LN2. Post-warming survivability and ultrastructural changes of healthy COCs in the cryotop group especially in comparison with the conventional group revealed better viability rate and good preservation of the ooplasm organization. However in all vitrification groups except the cryotop group, mitochondria were clumped. Solely in the conventional straw group, the mitochondria showed different densities and were extremely distended. Moreover in the latter group, plenty of large irregular connected vesicles in the ooplasm were observed and in some parts their membrane ruptured. Also, in the conventional and solid surface vitrification groups, cumulus cells projections became retracted from the zona pellucida in some parts. In conclusion, the cryotop vitrification method as compared with other methods seems to have a good post-warming survivability and shows less deleterious effects on the ultrastructure of healthy vitrified-warmed sheep COCs.     

Bioconversion of Hydrocortisone by Cyanobacterium Fischerella ambigua PTCC 1635

Summary The bioconversion of hydrocortisone by a locally isolated strain of cyanobacterium Fischerella ambigua PTCC 1635 was investigated. Fischerella ambigua had not been previously examined for this potential. The fermentation led to production of 11β,17α, 20β, 21-tetrahydroxypregn-4-en-3-one and 11β-hydroxyandrost-4-en-3,17-dione. The metabolites were isolated and purified by chromatographic methods and identified using instrumental analyses.     

Robust Modeling of Differential Gene Expression Data Using Normal/Independent Distributions: A Bayesian Approach

In this paper, the problem of identifying differentially expressed genes under different conditions using gene expression microarray data, in the presence of outliers, is discussed. For this purpose, the robust modeling of gene expression data using some powerful distributions known as normal/independent distributions is considered. These distributions include the Student’s t and normal distributions which have been used previously, but also include extensions such as the slash, the contaminated normal and the Laplace distributions. The purpose of this paper is to identify differentially expressed genes by considering these distributional assumptions instead of the normal distribution. A Bayesian approach using the Markov Chain Monte Carlo method is adopted for parameter estimation. Two publicly available gene expression data sets are analyzed using the proposed approach. The use of the robust models for detecting differentially expressed genes is investigated. This investigation shows that the choice of model for differentiating gene expression data is very important. This is due to the small number of replicates for each gene and the existence of outlying data. Comparison of the performance of these models is made using different statistical criteria and the ROC curve. The method is illustrated using some simulation studies. We demonstrate the flexibility of these robust models in identifying differentially expressed genes.     

Natural flavonoids for the prevention of colon cancer: A comprehensive review of preclinical and clinical studies

Flavonoids comprise a group of natural polyphenols consisting of more than 5,000 subtypes mostly existing in fruits and vegetables. Flavonoids consumption could potentially attenuate the incidence and recurrence risk of colorectal cancers through their antiperoxidative, antioxidant, and anti-inflammatory effects. In addition, these compounds regulate the mitochondrial function, balance the bacterial flora and promote the apoptosis process in cancerous cells. However, some previous data failed to show the effectiveness of flavonoids in reducing the risk of colorectal cancer. In this study, we have reviewed the efficacy of different flavonoids subtypes on the risk of colon cancer and molecular mechanisms involved in this process in both clinical and animal studies. In addition, we tried to elucidate the potential synergy between these compounds and current colorectal cancer treatments.     

Distribution of pathogenicity island markers and virulence factors in new phylogenetic groups of uropathogenic <Emphasis Type="Italic">Escherichia coli</Emphasis> isolates

The present study was aimed at investigating the relationship between the new Clermont’s phylogenetic groups, virulence factors, and pathogenicity island markers (PAIs) among uropathogenic Escherichia coli (UPEC) in Iran. This cross-sectional study was carried out on 140 UPEC isolates collected from patients with urinary tract infections in Bushehr, Iran. All isolates were subjected to phylogenetic typing using a new quadruplex-PCR method. The presence of PAI markers and virulence factors in UPEC strains was evaluated by multiplex PCR. The most predominant virulence gene was fimH (85%), followed by iucC (61.4%), papC (38.6%), hlyA (22.1%), cnf-1 (18.6%), afa (10.7%), papG and neuC (each 9.3%), ibeA (3.6%), and sfa/foc (0.7%). The most common phylogenetic group was related to B2 (39.3%), and the least common to A (0.7%). The most prevalent PAI marker was PAI IV536 (77.14%), while markers for PAI III536 (13.57%), PAI IIJ96 (12.86%), and PAI II536 (12.14%) were the least frequent among the UPEC strains. Meanwhile, the PAI IJ96 marker was not detected. There was a significant association between the phylogenetic group B2 and all the studied virulence genes and PAI markers. To our knowledge, this is the first study to compare the relationship between new phylogenetic groups, virulence genes and PAI markers in UPEC strains in Iran. The phylogenetic group B2 was predominantly represented among the studied virulence genes and PAI markers, indicating the preference of particular strains to carry virulence genes.     

Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space

Abstract

The use of modern data science has recently emerged as a promising new path to tackling the complex challenges involved in the creation of next-generation chemistry and materials. However, despite the appeal of this potentially transformative development, the chemistry community has yet to incorporate it as a central tool in every-day work. Our research program is designed to enable and advance this emerging research approach. It is centred around the creation of a software ecosystem that brings together physics-based modelling, high-throughput in silico screening and data analytics (i.e. the use of machine learning and informatics for the validation, mining and modelling of chemical data). This cyberinfrastructure is devised to offer a comprehensive set of data science techniques and tools as well as a general-purpose scope to make it as versatile and widely applicable as possible. It also emphasises user-friendliness to make it accessible to the community at large. It thus provides the means for the large-scale exploration of chemical space and for a better understanding of the hidden mechanisms that determine the properties of complex chemical systems. Such insights can dramatically accelerate, streamline and ultimately transform the way chemical research is conducted. Aside from serving as a production-level tool, our cyberinfrastructure is also designed to facilitate and assess methodological innovation. Both the software and method development work are driven by concrete molecular design problems, which also allow us to assess the efficacy of the overall cyberinfrastructure.     

How Methylammonium Cations and Chlorine Dopants Heal Defects in Lead Iodide Perovskites

Lead tri‐iodide methylammonium (MAPbI₃) perovskite polycrystalline materials show complex optoelectronic behavior, largely because their 3D semiconducting inorganic framework is strongly perturbed by the organic cations and ubiquitous structural or chemical inhomogeneities. Here, a newly developed time‐dependent density functional theory‐based theoretical formalism is taken advantage of. It treats electron–hole and electron–nuclei interactions on the same footing to assess the many‐body excited states of MAPbI₃ perovskites in their pristine state and in the presence of point chemical defects. It is shown that lead and iodine vacancies yield deep trap states that can be healed by dynamic effects, namely rotation of the methylammonium cations in response to point charges, or through slight changes in chemical composition, namely by introducing a tiny amount of chlorine dopants in the defective MAPbI₃. The theoretical results are supported by photoluminescence experiments on MAPbI_3?mCl_m and pave the way toward the design of defect‐free perovskite materials with optoelectronic performance approaching the theoretical limits.