Allele mining in β-lactoglobulin gene of Capra hircus

β-Lactoglobulin (β-LG) genetic polymorphisms are important and well known due to their effects on quantitative traits and technological properties of milk. At the DNA level, polymerase chain reaction (PCR)-single-strand conformation polymorphism (SSCP) allows for the detection of unknown polymorphisms at β-LG loci. Here we describe the usefulness of the PCR-SSCP technique for β-LG typing. In the present study, we amplified and sequenced the part of promoter region and all the seven exons containing the entire coding and untranslated region for the β-lactoglobulin gene in best dairy goat breeds of India namely: Jamunapari and Jakhrana. Nine polymorphisms were detected, one in the l promoter region, four in the introns and four in the exons of the β-lactoglobulin gene. All polymorphisms were single nucleotide substitutions. The polymorphisms in the coding region did not produce any amino acid change.Key words: β-Lactoglobulin gene, dairy goats, polymorphism, single nucleotide polymorphism (SNP), single strand conformational polymorphism (SSCP)

ACOX2 deficiency: A disorder of bile acid synthesis with transaminase elevation, liver fibrosis, ataxia, and cognitive impairment

Acyl CoA Oxidase 2 (ACOX2) encodes branched-chain acyl-CoA oxidase, a peroxisomal enzyme believed to be involved in the metabolism of branched-chain fatty acids and bile acid intermediates. Deficiency of this enzyme has not been described previously. We report an 8-y-old male with intermittently elevated transaminase levels, liver fibrosis, mild ataxia, and cognitive impairment. Exome sequencing revealed a previously unidentified homozygous premature termination mutation (p.Y69*) in ACOX2 Immunohistochemistry confirmed the absence of ACOX2 expression in the patient's liver, and biochemical analysis showed marked elevation of intermediate bile acids upstream of ACOX2. These findings define a potentially treatable inborn error of bile acid biosynthesis caused by ACOX2 deficiency

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

Asymmetry to symmetry transition of Fano line-shape: Analytical derivation

An analytical derivation of Fano line-shape asymmetry ratio has been presented here for a general case. It is shown that Fano line-shape becomes less asymmetric as \q is increased and finally becomes completely symmetric in the limiting condition of q equal to infinity. Asymmetry ratios of Fano line-shapes have been calculated and are found to be in good consonance with the reported expressions for asymmetry ratio as a function of Fano parameter. Application of this derivation is also mentioned for explanation of asymmetry to symmetry transition of Fano line-shape in quantum confined silicon nanostructures.Comment: 3 figures, Latex files, Theoretica

OSTα deficiency: A disorder with cholestasis, liver fibrosis and congenital diarrhea

Solute carrier family 51 alpha subunit (SLC51A ) encodes the alpha subunit of the heteromeric organic solute transporter alpha–beta (OSTα–OSTβ), an important contributor to intestinal bile acid (BA) reabsorption in the enterohepatic circulation.1, 2 Here, we identified the first case of OSTα deficiency in a child with unexplained elevated liver transaminases, cholestasis, and congenital diarrhea

Characterisation of the bacterial and fungal communities associated with different lesion sizes of Dark Spot Syndrome occurring in the Coral Stephanocoenia intersepta

The number and prevalence of coral diseases/syndromes are increasing worldwide. Dark Spot Syndrome (DSS) afflicts numerous coral species and is widespread throughout the Caribbean, yet there are no known causal agents. In this study we aimed to characterise the microbial communities (bacteria and fungi) associated with DSS lesions affecting the coral Stephanocoenia intersepta using nonculture molecular techniques. Bacterial diversity of healthy tissues (H), those in advance of the lesion interface (apparently healthy AH), and three sizes of disease lesions (small, medium, and large) varied significantly (ANOSIM R = 0.052 p,0.001), apart from the medium and large lesions, which were similar in their community profile. Four bacteria fitted into the pattern expected from potential pathogens; namely absent from H, increasing in abundance within AH, and dominant in the lesions themselves. These included ribotypes related to Corynebacterium (KC190237), Acinetobacter (KC190251), Parvularculaceae (KC19027), and Oscillatoria (KC190271). Furthermore, two Vibrio species, a genus including many proposed coral pathogens, dominated the disease lesion and were absent from H and AH tissues, making them candidates as potential pathogens for DSS. In contrast, other members of bacteria from the same genus, such as V. harveyii were present throughout all sample types, supporting previous studies where potential coral pathogens exist in healthy tissues. Fungal diversity varied significantly as well, however the main difference between diseased and healthy tissues was the dominance of one ribotype, closely related to the plant pathogen, Rhytisma acerinum, a known causal agent of tar spot on tree leaves. As the corals’ symbiotic algae have been shown to turn to a darker pigmented state in DSS (giving rise to the syndromes name), the two most likely pathogens are R. acerinum and the bacterium Oscillatoria, which has been identified as the causal agent of the colouration in Black Band Disease, another widespread coral disease

A Formalism for the Systematic Treatment of Rapidity Logarithms in Quantum Field Theory

Many observables in QCD rely upon the resummation of perturbation theory to retain predictive power. Resummation follows after one factorizes the cross section into the rele- vant modes. The class of observables which are sensitive to soft recoil effects are particularly challenging to factorize and resum since they involve rapidity logarithms. In this paper we will present a formalism which allows one to factorize and resum the perturbative series for such observables in a systematic fashion through the notion of a "rapidity renormalization group". That is, a Collin-Soper like equation is realized as a renormalization group equation, but has a more universal applicability to observables beyond the traditional transverse momentum dependent parton distribution functions (TMDPDFs) and the Sudakov form factor. This formalism has the feature that it allows one to track the (non-standard) scheme dependence which is inherent in any scenario where one performs a resummation of rapidity divergences. We present a pedagogical introduction to the formalism by applying it to the well-known massive Sudakov form factor. The formalism is then used to study observables of current interest. A factorization theorem for the transverse momentum distribution of Higgs production is presented along with the result for the resummed cross section at NLL. Our formalism allows one to define gauge invariant TMDPDFs which are independent of both the hard scattering amplitude and the soft function, i.e. they are uni- versal. We present details of the factorization and resummation of the jet broadening cross section including a renormalization in pT space. We furthermore show how to regulate and renormalize exclusive processes which are plagued by endpoint singularities in such a way as to allow for a consistent resummation.Comment: Typos in Appendix C corrected, as well as a typo in eq. 5.6

Segmentation of Fluorescence Microscopy Cell Images Using Unsupervised Mining

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu’s threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu’s threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications

Efficient Non-Viral Reprogramming of Myoblasts to Stemness with a Single Small Molecule to Generate Cardiac Progenitor Cells

The current protocols for generation of induced pluripotent stem (iPS) cells involve genome integrating viral vectors which may induce tumorgenesis. The aim of this study was to develop and optimize a non-viral method without genetic manipulation for reprogramming of skeletal myoblasts (SMs) using small molecules

2D-Qsar for 450 types of amino acid induction peptides with a novel substructure pair descriptor having wider scope

<p>Abstract</p> <p>Background</p> <p>Quantitative structure-activity relationships (QSAR) analysis of peptides is helpful for designing various types of drugs such as kinase inhibitor or antigen. Capturing various properties of peptides is essential for analyzing two-dimensional QSAR. A descriptor of peptides is an important element for capturing properties. The atom pair holographic (APH) code is designed for the description of peptides and it represents peptides as the combination of thirty-six types of key atoms and their intermediate binding between two key atoms.</p> <p>Results</p> <p>The substructure pair descriptor (SPAD) represents peptides as the combination of forty-nine types of key substructures and the sequence of amino acid residues between two substructures. The size of the key substructures is larger and the length of the sequence is longer than traditional descriptors. Similarity searches on C5a inhibitor data set and kinase inhibitor data set showed that order of inhibitors become three times higher by representing peptides with SPAD, respectively. Comparing scope of each descriptor shows that SPAD captures different properties from APH.</p> <p>Conclusion</p> <p>QSAR/QSPR for peptides is helpful for designing various types of drugs such as kinase inhibitor and antigen. SPAD is a novel and powerful descriptor for various types of peptides. Accuracy of QSAR/QSPR becomes higher by describing peptides with SPAD.</p