An intronic deletion in megakaryoblastic leukemia 1 is associated with hyperproliferation of B cells in triplets with Hodgkin lymphoma

Megakaryoblastic leukemia 1 (MKL1) is a coactivator of serum response factor and together regulate transcription of actin cytoskeleton genes. MKL1 is associated with hematologic malignancies and immunodeficiency, but its role in B cells is unexplored. Here we examined B cells from monozygotic triplets with an intronic deletion in MKL1, two of whom were previously treated for Hodgkin lymphoma. To investigate MKL1 and B cell responses in HL pathogenesis, we generated Epstein Barr virus-transformed lymphoblastoid cell lines from the triplets and two controls. While cells from the Hodgkin lymphoma treated patients had a phenotype close to healthy controls, cells from the undiagnosed triplet had increased MKL1 mRNA, increased MKL1 protein, and elevated expression of MKL1-dependent genes. This was associated with elevated actin content, increased cell spreading, decreased expression of CD11a integrin molecules, and delayed aggregation. Moreover, cells from the undiagnosed triplet proliferated faster, displayed a higher proportion of cells with hyperploidy, and formed large tumors in vivo. This phenotype was reversible by inhibiting MKL1 activity. Interestingly, cells from the triplet treated for Hodgkin lymphoma in 1985 contained two subpopulations: one with high expression of CD11a that behaved like control cells and the other with low expression of CD11a that formed large tumors in vivo similar to cells from the undiagnosed triplet. This implies that pre-malignant cells had re-emerged a long time after treatment. Together, these data suggest that dysregulated MKL1 activity participates in B cell transformation and Hodgkin lymphoma pathogenesis

Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation

Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates

Dynamic summarization of bibliographic-based data

<p>Abstract</p> <p>Background</p> <p>Traditional information retrieval techniques typically return excessive output when directed at large bibliographic databases. Natural Language Processing applications strive to extract salient content from the excessive data. Semantic MEDLINE, a National Library of Medicine (NLM) natural language processing application, highlights relevant information in PubMed data. However, Semantic MEDLINE implements manually coded schemas, accommodating few information needs. Currently, there are only five such schemas, while many more would be needed to realistically accommodate all potential users. The aim of this project was to develop and evaluate a statistical algorithm that automatically identifies relevant bibliographic data; the new algorithm could be incorporated into a dynamic schema to accommodate various information needs in Semantic MEDLINE, and eliminate the need for multiple schemas.</p> <p>Methods</p> <p>We developed a flexible algorithm named Combo that combines three statistical metrics, the Kullback-Leibler Divergence (KLD), Riloff's RlogF metric (RlogF), and a new metric called PredScal, to automatically identify salient data in bibliographic text. We downloaded citations from a PubMed search query addressing the genetic etiology of bladder cancer. The citations were processed with SemRep, an NLM rule-based application that produces semantic predications. SemRep output was processed by Combo, in addition to the standard Semantic MEDLINE genetics schema and independently by the two individual KLD and RlogF metrics. We evaluated each summarization method using an existing reference standard within the task-based context of genetic database curation.</p> <p>Results</p> <p>Combo asserted 74 genetic entities implicated in bladder cancer development, whereas the traditional schema asserted 10 genetic entities; the KLD and RlogF metrics individually asserted 77 and 69 genetic entities, respectively. Combo achieved 61% recall and 81% precision, with an F-score of 0.69. The traditional schema achieved 23% recall and 100% precision, with an F-score of 0.37. The KLD metric achieved 61% recall, 70% precision, with an F-score of 0.65. The RlogF metric achieved 61% recall, 72% precision, with an F-score of 0.66.</p> <p>Conclusions</p> <p>Semantic MEDLINE summarization using the new Combo algorithm outperformed a conventional summarization schema in a genetic database curation task. It potentially could streamline information acquisition for other needs without having to hand-build multiple saliency schemas.</p

The calcium channel β2 (CACNB2) subunit repertoire in teleosts

© 2008 Ebert et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

The impact of land use/land cover scale on modelling urban ecosystem services

Context Urbanisation places increasing stress on ecosystem services; however existing methods and data for testing relationships between service delivery and urban landscapes remain imprecise and uncertain. Unknown impacts of scale are among several factors that complicate research. This study models ecosystem services in the urban area comprising the towns of Milton Keynes, Bedford and Luton which together represent a wide range of the urban forms present in the UK. Objectives The objectives of this study were to test (1) the sensitivity of ecosystem service model outputs to the spatial resolution of input data, and (2) whether any resultant scale dependency is constant across different ecosystem services and model approaches (e.g. stock- versus flow-based). Methods Carbon storage, sediment erosion, and pollination were modelled with the InVEST framework using input data representative of common coarse (25 m) and fine (5 m) spatial resolutions. Results Fine scale analysis generated higher estimates of total carbon storage (9.32 vs. 7.17 kg m−2) and much lower potential sediment erosion estimates (6.4 vs. 18.1 Mg km−2 year−1) than analyses conducted at coarser resolutions; however coarse-scale analysis estimated more abundant pollination service provision. Conclusions Scale sensitivities depend on the type of service being modelled; stock estimates (e.g. carbon storage) are most sensitive to aggregation across scales, dynamic flow models (e.g. sediment erosion) are most sensitive to spatial resolution, and ecological process models involving both stocks and dynamics (e.g. pollination) are sensitive to both. Care must be taken to select model data appropriate to the scale of inquiry

Rs1888747 polymorphism in the FRMD3 gene, gene and protein expression: Role in diabetic kidney disease

© 2016 Buffon et al. Background: We carried out a case-control study in patients with type 2 diabetes mellitus (T2DM) to evaluate the association between seven single nucleotide polymorphisms (SNPs) previously described to be linked to diabetic kidney disease (DKD) in type 1 diabetes mellitus (T1DM). Additionally, we evaluated gene and protein expression related to the polymorphism associated with DKD. Methods: The association study included 1098 T2DM patients (718 with DKD and 380 without DKD). Out of the 13 polymorphisms associated with DKD in a previous study with T1DM, seven were chosen for evaluation in this sample: rs1888747, rs9521445, rs39075, rs451041, rs1041466, rs1411766 and rs6492208. The expression study included 91 patients who underwent nephrectomy. Gene expression was assessed by RT-qPCR and protein expression in kidney samples was quantified by western blot and it localization by immunohistochemistry. Results: The C/C genotype of rs1888747 SNP was associated with protection for DKD (OR = 0.6, 95 % CI 0.3-0.9; P = 0.022). None of the other SNPs were associated with DKD. rs1888747 is located near FRMD3 gene. Therefore, FRMD3 gene and protein expression were evaluated in human kidney tissue according to rs1888747 genotypes. Gene and protein expression were similar in subjects homozygous for the C allele and in those carrying the G allele. Conclusions: Replication of the association between rs1888747 SNP and DKD in a different population suggests that this link is not the result of chance. rs1888747 SNP is located at the FRMD3 gene, which is expressed in human kidney. Therefore, this gene is a candidate gene for DKD. However, in this study, no rs1888747 genotype or specific allele effect on gene and/or protein expression of the FRMD3 gene was demonstrated

Quantifying the impact of human immunodeficiency virus-1 escape from cytotoxic T-lymphocytes.

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In vivo magnetic resonance spectroscopy: basic methodology and clinical applications

The clinical use of in vivo magnetic resonance spectroscopy (MRS) has been limited for a long time, mainly due to its low sensitivity. However, with the advent of clinical MR systems with higher magnetic field strengths such as 3 Tesla, the development of better coils, and the design of optimized radio-frequency pulses, sensitivity has been considerably improved. Therefore, in vivo MRS has become a technique that is routinely used more and more in the clinic. In this review, the basic methodology of in vivo MRS is described—mainly focused on 1H MRS of the brain—with attention to hardware requirements, patient safety, acquisition methods, data post-processing, and quantification. Furthermore, examples of clinical applications of in vivo brain MRS in two interesting fields are described. First, together with a description of the major resonances present in brain MR spectra, several examples are presented of deviations from the normal spectral pattern associated with inborn errors of metabolism. Second, through examples of MR spectra of brain tumors, it is shown that MRS can play an important role in oncology

Synthesising practice guidelines for the development of community-based exercise programmes after stroke

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.Multiple guidelines are often available to inform practice in complex interventions. Guidance implementation may be facilitated if it is tailored to particular clinical issues and contexts. It should also aim to specify all elements of interventions that may mediate and modify effectiveness, including both their content and delivery. We conducted a focused synthesis of recommendations from stroke practice guidelines to produce a structured and comprehensive account to facilitate the development of community-based exercise programmes after stroke.National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) for the South West Peninsul