Yeast gene CMR1/YDL156W is consistently co-expressed with genes participating in DNA-metabolic processes in a variety of stringent clustering experiments

© 2013 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited.The binarization of consensus partition matrices (Bi-CoPaM) method has, among its unique features, the ability to perform ensemble clustering over the same set of genes from multiple microarray datasets by using various clustering methods in order to generate tunable tight clusters. Therefore, we have used the Bi-CoPaM method to the most synchronized 500 cell-cycle-regulated yeast genes from different microarray datasets to produce four tight, specific and exclusive clusters of co-expressed genes. We found 19 genes formed the tightest of the four clusters and this included the gene CMR1/YDL156W, which was an uncharacterized gene at the time of our investigations. Two very recent proteomic and biochemical studies have independently revealed many facets of CMR1 protein, although the precise functions of the protein remain to be elucidated. Our computational results complement these biological results and add more evidence to their recent findings of CMR1 as potentially participating in many of the DNA-metabolism processes such as replication, repair and transcription. Interestingly, our results demonstrate the close co-expressions of CMR1 and the replication protein A (RPA), the cohesion complex and the DNA polymerases α, δ and ɛ, as well as suggest functional relationships between CMR1 and the respective proteins. In addition, the analysis provides further substantial evidence that the expression of the CMR1 gene could be regulated by the MBF complex. In summary, the application of a novel analytic technique in large biological datasets has provided supporting evidence for a gene of previously unknown function, further hypotheses to test, and a more general demonstration of the value of sophisticated methods to explore new large datasets now so readily generated in biological experiments.National Institute for Health Researc

Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight clusters that focus on their cores or wide clusters that overlap and contain all possibly relevant genes. In this paper, a new clustering paradigm is proposed. In this paradigm, all three eventualities of a gene being exclusively assigned to a single cluster, being assigned to multiple clusters, and being not assigned to any cluster are possible. These possibilities are realised through the primary novelty of the introduction of tunable binarization techniques. Results from multiple clustering experiments are aggregated to generate one fuzzy consensus partition matrix (CoPaM), which is then binarized to obtain the final binary partitions. This is referred to as Binarization of Consensus Partition Matrices (Bi-CoPaM). The method has been tested with a set of synthetic datasets and a set of five real yeast cell-cycle datasets. The results demonstrate its validity in generating relevant tight, wide, and complementary clusters that can meet requirements of different gene discovery studies.National Institute for Health Researc

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Lactobacillus casei Shirota probiotic drinks reduce antibiotic associated diarrhoea in patients with spinal cord injuries who regularly consume proton pump inhibitors: a subgroup analysis of the ECLISP multicentre RCT

Study design This was a sub-group analysis of a multicentre, randomised, placebo-controlled, double-blind trial (ECLISP trial) Objectives To assess the efficacy of a probiotic containing at least 6.5 x 109 live Lactobacillus casei Shirota (LcS) in preventing antibiotic associated diarrhoea (AAD) in patients with spinal cord injury (SCI) who consumed proton pump inhibitor (PPI) regularly. LcS or placebo was given once daily for the duration of an antibiotic course and continued for 7 days thereafter. The trial was registered with ISRCTN:13119162. Setting Three SCI centres (National Spinal Injuries Centre, Midland Centre for Spinal Injuries and Princess Royal Spinal Cord Injuries Centre) in the United Kingdom Methods Between November 2014, and November 2019, 95 eligible consenting SCI patients (median age: 57; IQ range: 43-69) were randomly allocated to receive LcS (n = 50) or placebo (n = 45). The primary outcome is the occurrence of AAD up to 30 days after finishing LcS/placebo. Results The LcS group had a significantly lower incidence of AAD at 30 days after finishing the antibiotic course (28.0 v 53.3%, RR: 95% CI:0.53, 0.31-0.89; z = 2.5, p = 0.01). Multivariate logistic regression analysis identified that LcS can reduce the risk of AAD at 30 days (OR: 0.36, 95% CI 0.13, 0.99,p < 0.05). No intervention-related adverse events were reported during the study. Conclusions LcS has the potential to prevent AAD in what could be considered a defined vulnerable group of SCI patients on regular PPL A confirmatory, randomised, placebo-controlled study is needed to confirm this apparent therapeutic success to translate it into appropriate clinical outcomes

Towards tunable consensus clustering for studying functional brain connectivity during affective processing

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package “UNCLES” available on http://cran.r-project.org/web/packages/UNCLES/index.html

Hybrid manager-professionals' identity work : the maintenance and hybridization of medical professionalism in managerial contexts

We examine the ‘identity work’ of manager–professional ‘hybrids’, specifically medical professionals in managerial roles in the British National Health Service, to maintain and hybridize their professional identity and wider professionalism in organizational and policy contexts affected by managerialist ideas. Empirically, we differentiate between ‘incidental hybrids’, who represent and protect traditional institutionalized professionalism while temporarily in hybrid roles, and ‘willing hybrids’, who developed hybrid professional–managerial identities during formative identity work or later in reaction to potential professional identity violations. Questions about willing hybrids' professional identities led them to challenge and disrupt institutionalized professionalism, and use and integrate professionalism and managerialism, creating more legitimate hybrid professionalism in their managerial context. By aligning professionalism with their personal identity, and regulating and auditing other professionals, willing hybrids also position hybrids collectively as elite within their profession

SMART: Unique splitting-while-merging framework for gene clustering

Copyright @ 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named “splitting merging awareness tactics” (SMART), which does not require any a priori knowledge of either the number of clusters or even the possible range of this number. Unlike existing self-splitting algorithms, which over-cluster the dataset to a large number of clusters and then merge some similar clusters, our framework has the ability to split and merge clusters automatically during the process and produces the the most reliable clustering results, by intrinsically integrating many clustering techniques and tasks. The SMART framework is implemented with two distinct clustering paradigms in two algorithms: competitive learning and finite mixture model. Nevertheless, within the proposed SMART framework, many other algorithms can be derived for different clustering paradigms. The minimum message length algorithm is integrated into the framework as the clustering selection criterion. The usefulness of the SMART framework and its algorithms is tested in demonstration datasets and simulated gene expression datasets. Moreover, two real microarray gene expression datasets are studied using this approach. Based on the performance of many metrics, all numerical results show that SMART is superior to compared existing self-splitting algorithms and traditional algorithms. Three main properties of the proposed SMART framework are summarized as: (1) needing no parameters dependent on the respective dataset or a priori knowledge about the datasets, (2) extendible to many different applications, (3) offering superior performance compared with counterpart algorithms.National Institute for Health Researc

Impact of Scottish vocational qualifications on residential child care : have they fulfilled the promise?

This article will present findings from a doctoral study exploring the impact of 'SVQ Care: Promoting Independence (level III)' within children's homes. The study focuses on the extent to which SVQs enhance practice and their function within a 'learning society'. A total of 30 staff were selected from seven children's homes in two different local authority social work departments in Scotland. Each member of staff was interviewed on four separate occasions over a period of 9 months. Interviews were structured using a combination of repertory grids and questions. Particular focus was given to the assessment process, the extent to which SVQs enhance practice and the learning experiences of staff. The findings suggest that there are considerable deficiencies both in terms of the SVQ format and the way in which children's homes are structured for the assessment of competence. Rather than address the history of failure within residential care, it appears that SVQs have enabled the status quo to be maintained whilst creating an 'illusion' of change within a learning society

A study into the effect of Lactobacillus casei Shirota in preventing antibiotic associated diarrhoea including Clostridioides difficile infection in patients with spinal cord injuries: a multicentre randomised, double-blind, placebo-controlled trial.

Background Antibiotic Associated Diarrhoea (AAD) and Clostridioides Difficile Infection (CDI) are of major concern in spinal cord injury (SCI) rehabilitation. Methods A multi-centre, randomized, double-blind, placebo-controlled (the ECLISP) trial, was conducted in three tertiary spinal cord injury centre in the UK to assess the efficacy of consuming a probiotic beverage containing at least 6.5 × 109 live Lactobacillus casei Shirota (LcS) in preventing AAD and CDI and in patients with SCI and to determine whether proton pump inhibitors (PPI) and under nutrition-risk are risk factors for AAD/CDI. LcS or placebo was given once daily for the duration of an antibiotic course and continued for 7 days thereafter. Follow up was set at 7 and 30 days after the antibiotic course finished. The primary outcome was occurrence of AAD up to 30 days after finishing LcS/placebo. This trial is completed and registered (ISRCTN:13119162). Findings Between November 2014, and November 2019, 359 consenting adult SCI patients (median age: 53.3; range: 18–88 years), from 3 SCI centres responsible for providing approximate 45–50% of UK SCI service, with a requirement for antibiotics due to infection were randomly allocated to receive LcS (n = 181) or placebo (n = 178). Overall, no statistical difference was seen in occurrence of the primary outcomes of AAD at 30 days follow up (45% v 42.1%, RR: 1.071, 0.8-1.4, p = 0.639). In the secondary analyses LcS was associated with a lower risk of AAD at 7 (19% v 35.7%, RR: 0.53, 0.29–0.99, p = 0.040) and 30 days follow up (28% v 52.2%, RR: 0.54, 0.32–0.91, p = 0.015) in the participants who took PPI regularly. Under nutrition-risk was associated with an increased risk of AAD at 7 (RR: 1.76, 1.28–2.44) and 30 days follow up (RR: 1.69, 1.30–2.0). No intervention-related adverse events were reported during the study. Interpretation The present study indicates that LcS could not prevent AAD/CDI in unselected SCI patients. LcS might have the potential to prevent AAD in the higher risk group of patients on regular PPI. Confirmatory studies are needed to allow translation of this apparent therapeutic success into improved clinical outcomes

Cmr1/WDR76 defines a nuclear genotoxic stress body linking genome integrity and protein quality control

DNA replication stress is a source of genomic instability. Here we identify ​changed mutation rate 1 (​Cmr1) as a factor involved in the response to DNA replication stress in Saccharomyces cerevisiae and show that ​Cmr1—together with ​Mrc1/​Claspin, ​Pph3, the chaperonin containing ​TCP1 (CCT) and 25 other proteins—define a novel intranuclear quality control compartment (INQ) that sequesters misfolded, ubiquitylated and sumoylated proteins in response to genotoxic stress. The diversity of proteins that localize to INQ indicates that other biological processes such as cell cycle progression, chromatin and mitotic spindle organization may also be regulated through INQ. Similar to ​Cmr1, its human orthologue ​WDR76 responds to proteasome inhibition and DNA damage by relocalizing to nuclear foci and physically associating with CCT, suggesting an evolutionarily conserved biological function. We propose that ​Cmr1/​WDR76 plays a role in the recovery from genotoxic stress through regulation of the turnover of sumoylated and phosphorylated proteins