Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli

<p>Abstract</p> <p>Background</p> <p>RNA viruses are responsible for a variety of illnesses among people, including but not limited to the common cold, the flu, HIV, and ebola. Developing new drugs and new strategies for treating diseases caused by these viruses can be an expensive and time-consuming process. Mathematical modeling may be used to elucidate host-pathogen interactions and highlight potential targets for drug development, as well providing the basis for optimizing patient treatment strategies. The purpose of this work was to determine whether a genome-scale modeling approach could be used to understand how metabolism is impacted by the host-pathogen interaction during a viral infection. <it>Escherichia coli</it>/MS2 was used as the host-pathogen model system as MS2 is easy to work with, harmless to humans, but shares many features with eukaryotic viruses. In addition, the genome-scale metabolic model of <it>E. coli </it>is the most comprehensive model at this time.</p> <p>Results</p> <p>Employing a metabolic modeling strategy known as "flux balance analysis" coupled with experimental studies, we were able to predict how viral infection would alter bacterial metabolism. Based on our simulations, we predicted that cell growth and biosynthesis of the cell wall would be halted. Furthermore, we predicted a substantial increase in metabolic activity of the pentose phosphate pathway as a means to enhance viral biosynthesis, while a break down in the citric acid cycle was predicted. Also, no changes were predicted in the glycolytic pathway.</p> <p>Conclusions</p> <p>Through our approach, we have developed a technique of modeling virus-infected host metabolism and have investigated the metabolic effects of viral infection. These studies may provide insight into how to design better drugs. They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.</p

Tales of Emergence - Synthetic Biology as a Scientific Community in the Making

International audienceThis article locates the beginnings of a synthetic biology network and thereby probes the formation of a potential disciplinary community. We consider the ways that ideas of community are mobilized, both by scientists and policy-makers in building an agenda for new forms of knowledge work, and by social scientists as an analytical device to understand new formations for knowledge production. As participants in, and analysts of, a network in synthetic biology, we describe our current understanding of synthetic biology by telling four tales of community making. The first tale tells of the mobilization of synthetic biology within a European context. The second tale describes the approach to synthetic biology community formation in the UK. The third narrates the creation of an institutionally based, funded 'network in synthetic biology'. The final tale de-localizes community-making efforts by focussing on 'devices' that make communities. In tying together these tales, our analysis suggests that the potential community can be understood in terms of 'movements'--the (re)orientation and enrolment of people, stories, disciplines and policies; and of 'stickiness'--the objects and glues that begin to bind together the various constitutive elements of community

Normative productivity of the global vegetation

<p>Abstract</p> <p>Background</p> <p>The biosphere models of terrestrial productivity are essential for projecting climate change and assessing mitigation and adaptation options. Many of them have been developed in connection to the International Geosphere-Biosphere Program (IGBP) that backs the work of the Intergovernmental Panel on Climate Change (IPCC). In the end of 1990s, IGBP sponsored release of a data set summarizing the model outputs and setting certain norms for estimates of terrestrial productivity. Since a number of new models and new versions of old models were developed during the past decade, these normative data require updating.</p> <p>Results</p> <p>Here, we provide the series of updates that reflects evolution of biosphere models and demonstrates evolutional stability of the global and regional estimates of terrestrial productivity. Most of them fit well the long-living Miami model. At the same time we call attention to the emerging alternative: the global potential for net primary production of biomass may be as high as 70 PgC y^-1, the productivity of larch forest zone may be comparable to the productivity of taiga zone, and the productivity of rain-green forest zone may be comparable to the productivity of tropical rainforest zone.</p> <p>Conclusion</p> <p>The departure from Miami model's worldview mentioned above cannot be simply ignored. It requires thorough examination using modern observational tools and techniques for model-data fusion. Stability of normative knowledge is not its ultimate goal – the norms for estimates of terrestrial productivity must be evidence-based.</p

Bigger, Faster, Better? Rhetorics and Practices of Large-Scale Research in Contemporary Bioscience

publication-status: Publishedtypes: ArticleEditorial for Special Issu

Selective Attenuation of Norepinephrine Release and Stress-Induced Heart Rate Increase by Partial Adenosine A1 Agonism

The release of the neurotransmitter norepinephrine (NE) is modulated by presynaptic adenosine receptors. In the present study we investigated the effect of a partial activation of this feedback mechanism. We hypothesized that partial agonism would have differential effects on NE release in isolated hearts as well as on heart rate in vivo depending on the genetic background and baseline sympathetic activity. In isolated perfused hearts of Wistar and Spontaneously Hypertensive Rats (SHR), NE release was induced by electrical stimulation under control conditions (S1), and with capadenoson 6 · 10−8 M (30 µg/l), 6 · 10−7 M (300 µg/l) or 2-chloro-N6-cyclopentyladenosine (CCPA) 10−6 M (S2). Under control conditions (S1), NE release was significantly higher in SHR hearts compared to Wistar (766+/−87 pmol/g vs. 173+/−18 pmol/g, p<0.01). Capadenoson led to a concentration-dependent decrease of the stimulation–induced NE release in SHR (S2/S1 = 0.90±0.08 with capadenoson 6 · 10−8 M, 0.54±0.02 with 6 · 10−7 M), but not in Wistar hearts (S2/S1 = 1.05±0.12 with 6 · 10−8 M, 1.03±0.09 with 6 · 10−7 M). CCPA reduced NE release to a similar degree in hearts from both strains. In vivo capadenoson did not alter resting heart rate in Wistar rats or SHR. Restraint stress induced a significantly greater increase of heart rate in SHR than in Wistar rats. Capadenoson blunted this stress-induced tachycardia by 45% in SHR, but not in Wistar rats. Using a [35S]GTPγS assay we demonstrated that capadenoson is a partial agonist compared to the full agonist CCPA (74+/−2% A1-receptor stimulation). These results suggest that partial adenosine A1-agonism dampens stress-induced tachycardia selectively in rats susceptible to strong increases in sympathetic activity, most likely due to a presynaptic attenuation of NE release

Climate variability of southern Chile since the Last Glacial Maximum : a continuous sedimentological record from Lago Puyehue (40°S)

Author Posting. © Springer, 2007. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Paleolimnology 39 (2008): 179-195, doi:10.1007/s10933-007-9117-y.This paper presents a multi-proxy climate record of an 11 m long core collected in Lago Puyehue (southern Chile, 40°S) and extending back to 18,000 cal yr BP. The multi-proxy analyses include sedimentology, mineralogy, grain size, geochemistry, loss-on-ignition, magnetic susceptibility and radiocarbon datings. Results demonstrate that sediment grain size is positively correlated with the biogenic sediment content and can be used as a proxy for lake paleoproductivity. On the other hand, the magnetic susceptibility signal is correlated with the aluminium and titanium concentrations and can be used as a proxy for the terrigenous supply. Temporal variations of sediment composition evidence that, since the last glacial maximum, the Chilean Lake District was characterized by 3 abrupt climate changes superimposed on a long-term climate evolution. These rapid climate changes are: (1) an abrupt warming at the end of the last glacial maximum at 17,300 cal yr BP; (2) a 13,100-12,300 cal yr BP cold event, ending rapidly and interpreted as the local counter part of the Younger Dryas cold period, and (3) a 3400-2900 cal yr BP climatic instability synchronous with a period of low solar activity. The timing of the 13,100-12,300 cold event is compared with similar records in both hemispheres and demonstrates that this southern hemisphere climate change lags behind the northern hemisphere Younger Dryas cold period by 500 to 1000 years.This research is supported by the Belgian OSTC project EV/12/10B "A continuous Holocene record of ENSO variability in southern Chile"

In Silico Insights into the Symbiotic Nitrogen Fixation in Sinorhizobium meliloti via Metabolic Reconstruction

BACKGROUND: Sinorhizobium meliloti is a soil bacterium, known for its capability to establish symbiotic nitrogen fixation (SNF) with leguminous plants such as alfalfa. S. meliloti 1021 is the most extensively studied strain to understand the mechanism of SNF and further to study the legume-microbe interaction. In order to provide insight into the metabolic characteristics underlying the SNF mechanism of S. meliloti 1021, there is an increasing demand to reconstruct a metabolic network for the stage of SNF in S. meliloti 1021. RESULTS: Through an iterative reconstruction process, a metabolic network during the stage of SNF in S. meliloti 1021 was presented, named as iHZ565, which accounts for 565 genes, 503 internal reactions, and 522 metabolites. Subjected to a novelly defined objective function, the in silico predicted flux distribution was highly consistent with the in vivo evidences reported previously, which proves the robustness of the model. Based on the model, refinement of genome annotation of S. meliloti 1021 was performed and 15 genes were re-annotated properly. There were 19.8% (112) of the 565 metabolic genes included in iHZ565 predicted to be essential for efficient SNF in bacteroids under the in silico microaerobic and nutrient sharing condition. CONCLUSIONS: As the first metabolic network during the stage of SNF in S. meliloti 1021, the manually curated model iHZ565 provides an overview of the major metabolic properties of the SNF bioprocess in S. meliloti 1021. The predicted SNF-required essential genes will facilitate understanding of the key functions in SNF and help identify key genes and design experiments for further validation. The model iHZ565 can be used as a knowledge-based framework for better understanding the symbiotic relationship between rhizobia and legumes, ultimately, uncovering the mechanism of nitrogen fixation in bacteroids and providing new strategies to efficiently improve biological nitrogen fixation

MMPs Regulate both Development and Immunity in the Tribolium Model Insect

BACKGROUND: Matrix metalloproteinases (MMPs) are evolutionarily conserved and multifunctional effector molecules in development and homeostasis. In spite of previous, intensive investigation in vitro and in cell culture, their pleiotrophic functions in vivo are still not well understood. METHODOLOGY/PRINCIPAL FINDINGS: We show that the genetically amenable beetle Tribolium castaneum represents a feasible model organism to explore MMP functions in vivo. We silenced expression of three insect-type Tribolium MMP paralogs and their physiological inhibitors, TIMP and RECK, by dsRNA-mediated genetic interference (RNAi). Knock-down of MMP-1 arrested development during pupal morphogenesis giving phenotypes with altered antennae, compound eyes, wings, legs, and head. Parental RNAi-mediated knock-down of MMP-1 or MMP-2 resulted in larvae with non-lethal tracheal defects and with abnormal intestines, respectively, implicating additional roles of MMPs during beetle embryogenesis. This is different to findings from the fruit fly Drosophila melanogaster, in which MMPs have a negligible role in embryogenesis. Confirming pleiotrophic roles of MMPs our results also revealed that MMPs are required for proper insect innate immunity because systemic knock-down of Tribolium MMP-1 resulted in significantly higher susceptibility to the entomopathogenic fungus Beauveria bassiana. Moreover, mRNA levels of MMP-1, TIMP, and RECK, and also MMP enzymatic activity were significantly elevated in immune-competent hemocytes upon stimulation. To confirm collagenolytic activity of Tribolium MMP-1 we produced and purified recombinant enzyme and determined a similar collagen IV degrading activity as observed for the most related human MMP, MMP-19. CONCLUSIONS/SIGNIFICANCE: This is the first study, to our knowledge, investigating the in vivo role of virtually all insect MMP paralogs along with their inhibitors TIMP and RECK in both insect development and immunity. Our results from the Tribolium model insect indicate that MMPs regulate tracheal and gut development during beetle embryogenesis, pupal morphogenesis, and innate immune defense reactions thereby revealing the evolutionarily conserved roles of MMPs