ALBERT

Description: The management of distal radial fractures is guided by the interpretation of radiographic findings. The aim of this investigation was to determine the intra- and inter-observer reliability of eight traditional...

Description: Recessive mutations in PLA2G6 have been associated with different neurodegenerative disorders, including infantile neuroaxonal dystrophy, neurodegeneration with brain iron accumulation and more recently, early-on...

Description: Background: A variety of DNA binding proteins are involved in regulating and shaping the packing of chromatin. They aid the formation of loops in the DNA that function to isolate different structural domains. A recent experimental technique, Hi-C, provides a method for determining the frequency of such looping between all distant parts of the genome. Given that the binding locations of many chromatin associated proteins have also been measured, it has been possible to make estimates for their influence on the long-range interactions as measured by Hi-C. However, a challenge in this analysis is the predominance of non-specific contacts that mask out the specific interactions of interest. Results: We show that transforming the Hi-C contact frequencies into free energies gives a natural method for separating out the distance dependent non-specific interactions. In particular we apply Principal Component Analysis (PCA) to the transformed free energy matrix to identify the dominant modes of interaction. PCA identifies systematic effects as well as high frequency spatial noise in the Hi-C data which can be filtered out. Thus it can be used as a data driven approach for normalizing Hi-C data. We assess this PCA based normalization approach, along with several other normalization schemes, by fitting the transformed Hi-C data using a pairwise interaction model that takes as input the known locations of bound chromatin factors. The result of fitting is a set of predictions for the coupling energies between the various chromatin factors and their effect on the energetics of looping. We show that the quality of the fit can be used as a means to determine how much PCA filtering should be applied to the Hi-C data. Conclusions: We find that the different normalizations of the Hi-C data vary in the quality of fit to the pairwise interaction model. PCA filtering can improve the fit, and the predicted coupling energies lead to biologically meaningful insights for how various chromatin bound factors influence the stability of DNA loops in chromatin.

Description: Background: Ranunculus arvensis L. (R. arvensis) has long been used to treat a variety of medical conditions such as arthritis, asthma, hay fever, rheumatism, psoriasis, gut diseases and rheumatic pain. Here, we screened R. arvensis for antioxidant activity, phytochemical and high performance liquid chromatography (HPLC) analyses. Methods: The chloroform, chloroform:methanol, methanol, methanol:acetone, acetone, methanol:water and water extracts of R. arvensis were examined for DPPH (1, 1-diphenyl-2-picrylhydrazyl) free radical scavenging assay, hydrogen peroxide scavenging assay, phosphomolybdenum assay, reducing power assay, flavonoid content, phenolic content and high performance liquid chromatography analysis. Results: Significant antioxidant activity was displayed by methanol extract (IC 50 34.71 ± 0.02) in DPPH free radical scavenging assay. Total flavonoids and phenolics ranged 0.96–6.0 mg/g of extract calculated as rutin equivalent and 0.48–1.43 mg/g of extract calculated as gallic acid equivalent respectively. Significant value of rutin and caffeic acid was observed via high performance liquid chromatography. Conclusions: These results showed that extracts of R. arvensis exhibited significant antioxidant activities. Moreover, R. arvensis is a rich source of rutin, flavonoids and phenolics.

Description: High potential of Morus laevigata and Morus serrata has been proposed in the breeding programs for Morus sp. However, due to the lack of dense molecular markers this goal is still in its nascent stage and not yet...

Description: Background: The gut microbiota plays an important role in human health and disease by acting as a metabolic organ. Metagenomic sequencing has shown how dysbiosis in the gut microbiota is associated with human metabolic diseases such as obesity and diabetes. Modeling may assist to gain insight into the metabolic implication of an altered microbiota. Fast and accurate reconstruction of metabolic models for members of the gut microbiota, as well as methods to simulate a community of microorganisms, are therefore needed. The Integrated Microbial Genomes (IMG) database contains functional annotation for nearly 4,650 bacterial genomes. This tremendous new genomic information adds new opportunities for systems biology to reconstruct accurate genome scale metabolic models (GEMs). Results: Here we assembled a reaction data set containing 2,340 reactions obtained from existing genome-scale metabolic models, where each reaction is assigned with KEGG Orthology. The reaction data set was then used to reconstruct two genome scale metabolic models for gut microorganisms available in the IMG database Bifidobacterium adolescentis L2-32, which produces acetate during fermentation, and Faecalibacterium prausnitzii A2-165, which consumes acetate and produces butyrate. F. prausnitzii is less abundant in patients with Crohn's disease and has been suggested to play an anti-inflammatory role in the gut ecosystem. The B. adolescentis model, iBif452, comprises 699 reactions and 611 unique metabolites. The F. prausnitzii model, iFap484, comprises 713 reactions and 621 unique metabolites. Each model was validated with in vivo data. We used OptCom and Flux Balance Analysis to simulate how both organisms interact. Conclusions: The consortium of iBif452 and iFap484 was applied to predict F. prausnitzii's demand for acetate and production of butyrate which plays an essential role in colonic homeostasis and cancer prevention. The assembled reaction set is a useful tool to generate bacterial draft models from KEGG Orthology.

Description: Background: Prokaryotic microbes, the most abundant organisms in the ocean, are remarkably diverse. Despite numerous studies of marine prokaryotes, the zonation of their communities in pelagic zones has been poorly delineated. By exploiting the persistent stratification of the South China Sea (SCS), we performed a 2-year, large spatial scale (10, 100, 1000, and 3000 m) survey, which included a pilot study in 2006 and comprehensive sampling in 2007, to investigate the biological zonation of bacteria and archaea using 16S rRNA tag and shotgun metagenome sequencing. Results: Alphaproteobacteria dominated the bacterial community in the surface SCS, where the abundance of Betaproteobacteria was seemingly associated with climatic activity. Gammaproteobacteria thrived in the deep SCS, where a noticeable amount of Cyanobacteria were also detected. Marine Groups II and III Euryarchaeota were predominant in the archaeal communities in the surface and deep SCS, respectively. Bacterial diversity was higher than archaeal diversity at all sampling depths in the SCS, and peaked at mid-depths, agreeing with the diversity pattern found in global water columns. Metagenomic analysis not only showed differential %GC values and genome sizes between the surface and deep SCS, but also demonstrated depth-dependent metabolic potentials, such as cobalamin biosynthesis at 10 m, osmoregulation at 100 m, signal transduction at 1000 m, and plasmid and phage replication at 3000 m. When compared with other oceans, urease at 10 m and both exonuclease and permease at 3000 m were more abundant in the SCS. Finally, enriched genes associated with nutrient assimilation in the sea surface and transposase in the deep-sea metagenomes exemplified the functional zonation in global oceans. Conclusions: Prokaryotic communities in the SCS stratified with depth, with maximal bacterial diversity at mid-depth, in accordance with global water columns. The SCS had functional zonation among depths and endemically enriched metabolic potentials at the study site, in contrast to other oceans.

Description: Background: Carnitine is a key molecule in energy metabolism that helps transport activated fatty acids into the mitochondria. Its homeostasis is achieved through oral intake, renal reabsorption and de novo biosynthesis. Unlike dietary intake and renal reabsorption, the importance of de novo biosynthesis pathway in carnitine homeostasis remains unclear, due to lack of animal models and description of a single patient defective in this pathway.Case presentationWe identified by array comparative genomic hybridization a 42 months-old girl homozygote for a 221 Kb interstitial deletions at 11p14.2, that overlaps the genes encoding Fibin and butyrobetaine-gamma 2-oxoglutarate dioxygenase 1 (BBOX1), an enzyme essential for the biosynthesis of carnitine de novo. She presented microcephaly, speech delay, growth retardation and minor facial anomalies. The levels of almost all evaluated metabolites were normal. Her serum level of free carnitine was at the lower limit of the reference range, while her acylcarnitine to free carnitine ratio was normal. Conclusions: We present an individual with a completely defective carnitine de novo biosynthesis. This condition results in mildly decreased free carnitine level, but not in clinical manifestations characteristic of carnitine deficiency disorders, suggesting that dietary carnitine intake and renal reabsorption are sufficient to carnitine homeostasis. Our results also demonstrate that haploinsufficiency of BBOX1 and/or Fibin is not associated with Primrose syndrome as previously suggested.

Description: Background: The unattractive appearance of the surface of pear fruit caused by the postharvest disorder friction discolouration (FD) is responsible for significant consumer dissatisfaction in markets, leading to lower returns to growers. Developing an understanding of the genetic control of FD is essential to enable the full application of genomics-informed breeding for the development of new pear cultivars. Biochemical constituents [phenolic compounds and ascorbic acid (AsA)], polyphenol oxidase (PPO) activity, as well as skin anatomy, have been proposed to play important roles in FD susceptibility in studies on a limited number of cultivars. However, to date there has been no investigation on the biochemical and genetic control of FD, employing segregating populations. In this study, we used 250 seedlings from two segregating populations (POP369 and POP356) derived from interspecific crosses between Asian (Pyrus pyrifolia Nakai and P. bretschneideri Rehd.) and European (P. communis) pears to identify genetic factors associated with susceptibility to FD. Results: Single nucleotide polymorphism (SNP)-based linkage maps suitable for QTL analysis were developed for the parents of both populations. The maps for population POP369 comprised 174 and 265 SNP markers for the male and female parent, respectively, while POP356 maps comprised 353 and 398 SNP markers for the male and female parent, respectively. Phenotypic data for 22 variables were measured over two successive years (2011 and 2012) for POP369 and one year (2011) only for POP356. A total of 221 QTLs were identified that were linked to 22 phenotyped variables, including QTLs associated with FD for both populations that were stable over the successive years. In addition, clear evidence of the influence of developmental factors (fruit maturity) on FD and other variables was also recorded. Conclusions: The QTLs associated with fruit firmness, PPO activity, AsA concentration and concentration of polyphenol compounds as well as FD are the first reported for pear. We conclude that the postharvest disorder FD is controlled by multiple small effect QTLs and that it will be very challenging to apply marker-assisted selection based on these QTLs. However, genomic selection could be employed to select elite genotypes with lower or no susceptibility to FD early in the breeding cycle.