The latent process decomposition of cDNA microarray data sets

We present a new computational technique (a software implementation, data sets, and supplementary information are available at http://www.enm.bris.ac.uk/lpd/) which enables the probabilistic analysis of cDNA microarray data and we demonstrate its effectiveness in identifying features of biomedical importance. A hierarchical Bayesian model, called latent process decomposition (LPD), is introduced in which each sample in the data set is represented as a combinatorial mixture over a finite set of latent processes, which are expected to correspond to biological processes. Parameters in the model are estimated using efficient variational methods. This type of probabilistic model is most appropriate for the interpretation of measurement data generated by cDNA microarray technology. For determining informative substructure in such data sets, the proposed model has several important advantages over the standard use of dendrograms. First, the ability to objectively assess the optimal number of sample clusters. Second, the ability to represent samples and gene expression levels using a common set of latent variables (dendrograms cluster samples and gene expression values separately which amounts to two distinct reduced space representations). Third, in contrast to standard cluster models, observations are not assigned to a single cluster and, thus, for example, gene expression levels are modeled via combinations of the latent processes identified by the algorithm. We show this new method compares favorably with alternative cluster analysis methods. To illustrate its potential, we apply the proposed technique to several microarray data sets for cancer. For these data sets it successfully decomposes the data into known subtypes and indicates possible further taxonomic subdivision in addition to highlighting, in a wholly unsupervised manner, the importance of certain genes which are known to be medically significant. To illustrate its wider applicability, we also illustrate its performance on a microarray data set for yeast

Strengthening the ethical assessment of placebo-controlled surgical trials : three proposals

Peer reviewedPublisher PD

Are we practising what we preach and are we all singing from the same hymn sheet?:An exploration of teaching in paediatric caries management across UK dental schools

Background: The evidence underpinning caries management for children has progressed dramatically over the past 20 years. Anecdotally, this is not reflected in the teaching provided to undergraduate dental students, with the ongoing teaching of outdated methods within some dental schools. Aim: To capture the current undergraduate teaching provision and clinical treatment experience requirement relative to caries management in paediatric dentistry in UK dental schools. Design: Cross-sectional analysis of current teaching methods on paediatric caries management was obtained using a piloted online data collection form. Question content included current caries teaching methods, assessment of student exposure and competence. The results were analysed descriptively. Results: Of the 16 UK dental schools, 14 participated. Discrepancy in teaching content was apparent. Many schools (n = 9) taught biological caries management through therapeutic fissure sealants, yet this was not reflected in assessment and clinical requirements. Some schools (n = 4) taught amalgam placement in children, and most (n = 12) operatively taught treatments that would no longer be routinely provided in general dental practice in the UK, including primary tooth pulpotomy. Conclusion: There is substantial variation in the paediatric caries management techniques that are taught across UK dental schools, demonstrating a need for a national consensus to address these disparities.</p

Design of Marine Protected Areas on high seas and territorial waters of rockall bank

Fisheries closures are rapidly being developed to protect vulnerable marine ecosystems worldwide. Satellite monitoring of fishing vessel activity indicates that these closures can work effectively with good compliance by international fleets even in remote areas. Here we summarise how remote fisheries closures were designed to protect Lophelia pertusa habitat in a region of the NE Atlantic that straddles the EU fishing zone and the high seas. We show how scientific records, fishers' knowledge and surveillance data on fishing activity can be combined to provide a powerful tool for the design of Marine Protected Areas. © Inter-Research 2009

Bloom syndrome: research and data priorities for the development of precision medicine as identified by some affected families

Bloom syndrome (BS) is a rare, autosomal recessive genetic disorder characterized by short stature, a skin rash associated with sun exposure, and an elevated likelihood of developing cancers of essentially all types, beginning at an early age. Cancer is the leading cause of death for persons with BS, and its early onset results in a reported median lifespan of <30 years. With fewer than 300 documented cases since BS was first described in 1954, its rarity has challenged progress in advancing both the care of and the cure for persons with BS. Presently, there are no known clinically actionable targets specific to persons with this cancer predisposition syndrome, despite the fact that standard cancer treatments are often contraindicated or must be substantially modified for persons with BS. Herein, Zachary Rogers recounts his experience as a cancer patient with BS contemplating a substantially customized chemotherapy regimen that highlights the need for development of individualized treatments in the BS community. We also outline a patient-centered research and community action road map with the goal of improving and prolonging the lives of persons with Bloom syndrome, including the facilitation of precision medicine development specific to this condition

Rethinking norms in educational practices to promote appreciation of variation: Lessons from human anatomy

Across disciplines, teaching approaches and educational resources that are based on norms prevail—a norm is defined as a standard or typical practice, convention, or procedure. Although norms often have a historical basis and may be used to simplify complex content, their frequent use in education often disregards and disvalues variation. Variation can present valuable learning opportunities for students, promoting the development of problem solving and critical thinking skills, and humanizing their learning. An example of norms and variation in the discipline of gross anatomy is the frequent use of the “standard human body” in teaching. This idealized view typically does not account for anatomical variations despite their prevalence across the human population. This practice can contribute to alienation within gross anatomy classrooms, with students not feeling represented in the images and terms that they are exposed to. The main aim of this study is to investigate the impact of anatomical variations in gross anatomy courses to inform the creation of updated educational resources. A scoping review was conducted to explore teaching approaches for, and student outcomes of, including anatomical variations in undergraduate, graduate, and professional gross anatomy courses. Scoping reviews are a valuable approach in educational research to systematically explore available evidence related to a problem, elucidate knowledge gaps, and inform updated inclusive practices. Awareness of the norms present in one’s discipline can inform the intentional inclusion of variations in educational approaches and resources, contributing to the inclusion and appreciation of diversity within and across fields of study

HIPred:an integrative approach to predicting haploinsufficient genes

Abstract Motivation A major cause of autosomal dominant disease is haploinsufficiency, whereby a single copy of a gene is not sufficient to maintain the normal function of the gene. A large proportion of existing methods for predicting haploinsufficiency incorporate biological networks, e.g. protein-protein interaction networks that have recently been shown to introduce study bias. As a result, these methods tend to perform best on well-studied genes, but underperform on less studied genes. The advent of large genome sequencing consortia, such as the 1000 genomes project, NHLBI Exome Sequencing Project and the Exome Aggregation Consortium creates an urgent need for unbiased haploinsufficiency prediction methods. Results Here, we describe a machine learning approach, called HIPred, that integrates genomic and evolutionary information from ENSEMBL, with functional annotations from the Encyclopaedia of DNA Elements consortium and the NIH Roadmap Epigenomics Project to predict haploinsufficiency, without the study bias described earlier. We benchmark HIPred using several datasets and show that our unbiased method performs as well as, and in most cases, outperforms existing biased algorithms. Availability and Implementation HIPred scores for all gene identifiers are available at: https://github.com/HAShihab/HIPred. Supplementary information Supplementary data are available at Bioinformatics online. </jats:sec

Formation of plasma around a small meteoroid: simulation and theory

High‐power large‐aperture radars detect meteors by reflecting radio waves off dense plasma that surrounds a hypersonic meteoroid as it ablates in the Earth's atmosphere. If the plasma density profile around the meteoroid is known, the plasma's radar cross section can be used to estimate meteoroid properties such as mass, density, and composition. This paper presents head echo plasma density distributions obtained via two numerical simulations of a small ablating meteoroid and compares the results to an analytical solution found in Dimant and Oppenheim (2017a, https://doi.org/10.1002/2017JA023960, 2017b, https://doi.org/10.1002/2017JA023963). The first simulation allows ablated meteoroid particles to experience only a single collision to match an assumption in the analytical solution, while the second is a more realistic simulation by allowing multiple collisions. The simulation and analytical results exhibit similar plasma density distributions. At distances much less than λT, the average distance an ablated particle travels from the meteoroid before a collision with an atmospheric particle, the plasma density falls off as 1/R, where R is the distance from the meteoroid center. At distances substantially greater than λT, the plasma density profile has an angular dependence, falling off as 1/R^2 directly behind the meteoroid, 1/R^3 in a plane perpendicular to the meteoroid's path that contains the meteoroid center, and exp - 1.5(/λ)2/3/ in front of the meteoroid. When used for calculating meteoroid masses, this new plasma density model can give masses that are orders of magnitude different than masses calculated from a spherically symmetric Gaussian distribution, which has been used to calculate masses in the past.This work was supported by NSF grants AGS-1244842 and AGS-1056042. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant ACI-1548562. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper; URL: http://www.tacc.utexas.edu. Simulation-produced data are archived at TACC and available upon request. (AGS-1244842 - NSF; AGS-1056042 - NSF; ACI-1548562 - National Science Foundation)First author draf