Moving from evidence-based medicine to evidence-based health.

While evidence-based medicine (EBM) has advanced medical practice, the health care system has been inconsistent in translating EBM into improvements in health. Disparities in health and health care play out through patients' limited ability to incorporate the advances of EBM into their daily lives. Assisting patients to self-manage their chronic conditions and paying attention to unhealthy community factors could be added to EBM to create a broader paradigm of evidence-based health. A perspective of evidence-based health may encourage physicians to consider their role in upstream efforts to combat socially patterned chronic disease

Transparency in health economic modeling : options, issues and potential solutions

Economic models are increasingly being used by health economists to assess the value of health technologies and inform healthcare decision making. However, most published economic models represent a kind of black box, with known inputs and outputs but undisclosed internal calculations and assumptions. This lack of transparency makes the evaluation of the model results challenging, complicates comparisons between models, and limits the reproducibility of the models. Here, we aim to provide an overview of the possible steps that could be undertaken to make economic models more transparent and encourage model developers to share more detailed calculations and assumptions with their peers. Scenarios with different levels of transparency (i.e., how much information is disclosed) and reach of transparency (i.e., who has access to the disclosed information) are discussed, and five key concerns (copyrights, model misuse, confidential data, software, and time/resources) pertaining to model transparency are presented, along with possible solutions. While a shift toward open-source models is underway in health economics, as has happened before in other research fields, the challenges ahead should not be underestimated. Importantly, there is a pressing need to find an acceptable trade-off between the added value of model transparency and the time and resources needed to achieve such transparency. To this end, it will be crucial to set incentives at different stakeholder levels. Despite the many challenges, the many benefits of publicly sharing economic models make increased transparency a goal worth pursuing

Cryotomography of budding influenza a virus reveals filaments with diverse morphologies that mostly do not bear a genome at their distal end

Influenza viruses exhibit striking variations in particle morphology between strains. Clinical isolates of influenza A virus have been shown to produce long filamentous particles while laboratory-adapted strains are predominantly spherical. However, the role of the filamentous phenotype in the influenza virus infectious cycle remains undetermined. We used cryo-electron tomography to conduct the first three-dimensional study of filamentous virus ultrastructure in particles budding from infected cells. Filaments were often longer than 10 microns and sometimes had bulbous heads at their leading ends, some of which contained tubules we attribute to M1 while none had recognisable ribonucleoprotein (RNP) and hence genome segments. Long filaments that did not have bulbs were infrequently seen to bear an ordered complement of RNPs at their distal ends. Imaging of purified virus also revealed diverse filament morphologies; short rods (bacilliform virions) and longer filaments. Bacilliform virions contained an ordered complement of RNPs while longer filamentous particles were narrower and mostly appeared to lack this feature, but often contained fibrillar material along their entire length. The important ultrastructural differences between these diverse classes of particles raise the possibility of distinct morphogenetic pathways and functions during the infectious process

TMFoldRec: a statistical potential-based transmembrane protein fold recognition tool.

BACKGROUND: Transmembrane proteins (TMPs) are the key components of signal transduction, cell-cell adhesion and energy and material transport into and out from the cells. For the deep understanding of these processes, structure determination of transmembrane proteins is indispensable. However, due to technical difficulties, only a few transmembrane protein structures have been determined experimentally. Large-scale genomic sequencing provides increasing amounts of sequence information on the proteins and whole proteomes of living organisms resulting in the challenge of bioinformatics; how the structural information should be gained from a sequence. RESULTS: Here, we present a novel method, TMFoldRec, for fold prediction of membrane segments in transmembrane proteins. TMFoldRec based on statistical potentials was tested on a benchmark set containing 124 TMP chains from the PDBTM database. Using a 10-fold jackknife method, the native folds were correctly identified in 77 % of the cases. This accuracy overcomes the state-of-the-art methods. In addition, a key feature of TMFoldRec algorithm is the ability to estimate the reliability of the prediction and to decide with an accuracy of 70 %, whether the obtained, lowest energy structure is the native one. CONCLUSION: These results imply that the membrane embedded parts of TMPs dictate the TM structures rather than the soluble parts. Moreover, predictions with reliability scores make in this way our algorithm applicable for proteome-wide analyses. AVAILABILITY: The program is available upon request for academic use

Dissecting Nucleosome Free Regions by a Segmental Semi-Markov Model

BACKGROUND: Nucleosome free regions (NFRs) play important roles in diverse biological processes including gene regulation. A genome-wide quantitative portrait of each individual NFR, with their starting and ending positions, lengths, and degrees of nucleosome depletion is critical for revealing the heterogeneity of gene regulation and chromatin organization. By averaging nucleosome occupancy levels, previous studies have identified the presence of NFRs in the promoter regions across many genes. However, evaluation of the quantitative characteristics of individual NFRs requires an NFR calling method. METHODOLOGY: In this study, we propose a statistical method to identify the patterns of NFRs from a genome-wide measurement of nucleosome occupancy. This method is based on an appropriately designed segmental semi-Markov model, which can capture each NFR pattern and output its quantitative characterizations. Our results show that the majority of the NFRs are located in intergenic regions or promoters with a length of about 400-600bp and varying degrees of nucleosome depletion. Our quantitative NFR mapping allows for an investigation of the relative impacts of transcription machinery and DNA sequence in evicting histones from NFRs. We show that while both factors have significant overall effects, their specific contributions vary across different subtypes of NFRs. CONCLUSION: The emphasis of our approach on the variation rather than the consensus of nucleosome free regions sets the tone for enabling the exploration of many subtler dynamic aspects of chromatin biology

Role of simian virus 40 in cancer incidence in solid organ transplant patients

Transplant recipients have an increased risk of developing cancer in comparison with the general population. We present here data on cancer development in transplanted subjects who received organs from donors whose DNA was previously examined for the genomic insertion of Simian Virus 40 (SV40). Active follow-up of 387 recipients of solid organs donated by 134 donors, not clinically affected by cancer, was performed through the National Transplant Center (NTC). The average length of follow-up after transplant was 671±219 days (range 0–1085 days). Out of 134 proposed donors, 120 were utilised for organ donation. Of these, 12 (10%) were classified as positive for SV40 genomic insertion. None of the 41 recipients of organs from SV40 positive donors developed a tumour during the follow-up. In all, 11 recipients of organs given by SV40 negative donors developed a tumour (cancer incidence: 0.015 per year). In conclusion, cancer rates observed in our study are comparable to what reported by the literature in transplanted patients. Recipients of solid organs from SV40 positive donors do not have an increased risk of cancer after transplant. The role of SV40 in carcinogenesis in transplanted patients may be minimal

Probing Metagenomics by Rapid Cluster Analysis of Very Large Datasets

BACKGROUND: The scale and diversity of metagenomic sequencing projects challenge both our technical and conceptual approaches in gene and genome annotations. The recent Sorcerer II Global Ocean Sampling (GOS) expedition yielded millions of predicted protein sequences, which significantly altered the landscape of known protein space by more than doubling its size and adding thousands of new families (Yooseph et al., 2007 PLoS Biol 5, e16). Such datasets, not only by their sheer size, but also by many other features, defy conventional analysis and annotation methods. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we describe an approach for rapid analysis of the sequence diversity and the internal structure of such very large datasets by advanced clustering strategies using the newly modified CD-HIT algorithm. We performed a hierarchical clustering analysis on the 17.4 million Open Reading Frames (ORFs) identified from the GOS study and found over 33 thousand large predicted protein clusters comprising nearly 6 million sequences. Twenty percent of these clusters did not match known protein families by sequence similarity search and might represent novel protein families. Distributions of the large clusters were illustrated on organism composition, functional class, and sample locations. CONCLUSION/SIGNIFICANCE: Our clustering took about two orders of magnitude less computational effort than the similar protein family analysis of original GOS study. This approach will help to analyze other large metagenomic datasets in the future. A Web server with our clustering results and annotations of predicted protein clusters is available online at http://tools.camera.calit2.net/gos under the CAMERA project

A Case Study for Large-Scale Human Microbiome Analysis Using JCVI’s Metagenomics Reports (METAREP)

As metagenomic studies continue to increase in their number, sequence volume and complexity, the scalability of biological analysis frameworks has become a rate-limiting factor to meaningful data interpretation. To address this issue, we have developed JCVI Metagenomics Reports (METAREP) as an open source tool to query, browse, and compare extremely large volumes of metagenomic annotations. Here we present improvements to this software including the implementation of a dynamic weighting of taxonomic and functional annotation, support for distributed searches, advanced clustering routines, and integration of additional annotation input formats. The utility of these improvements to data interpretation are demonstrated through the application of multiple comparative analysis strategies to shotgun metagenomic data produced by the National Institutes of Health Roadmap for Biomedical Research Human Microbiome Project (HMP) (http://nihroadmap.nih.gov). Specifically, the scalability of the dynamic weighting feature is evaluated and established by its application to the analysis of over 400 million weighted gene annotations derived from 14 billion short reads as predicted by the HMP Unified Metabolic Analysis Network (HUMAnN) pipeline. Further, the capacity of METAREP to facilitate the identification and simultaneous comparison of taxonomic and functional annotations including biological pathway and individual enzyme abundances from hundreds of community samples is demonstrated by providing scenarios that describe how these data can be mined to answer biological questions related to the human microbiome. These strategies provide users with a reference of how to conduct similar large-scale metagenomic analyses using METAREP with their own sequence data, while in this study they reveal insights into the nature and extent of variation in taxonomic and functional profiles across body habitats and individuals. Over one thousand HMP WGS datasets and the latest open source code are available at http://www.jcvi.org/hmp-metarep

A Nitrile Hydratase in the Eukaryote Monosiga brevicollis

Bacterial nitrile hydratase (NHases) are important industrial catalysts and waste water remediation tools. In a global computational screening of conventional and metagenomic sequence data for NHases, we detected the two usually separated NHase subunits fused in one protein of the choanoflagellate Monosiga brevicollis, a recently sequenced unicellular model organism from the closest sister group of Metazoa. This is the first time that an NHase is found in eukaryotes and the first time it is observed as a fusion protein. The presence of an intron, subunit fusion and expressed sequence tags covering parts of the gene exclude contamination and suggest a functional gene. Phylogenetic analyses and genomic context imply a probable ancient horizontal gene transfer (HGT) from proteobacteria. The newly discovered NHase might open biotechnological routes due to its unconventional structure, its new type of host and its apparent integration into eukaryotic protein networks