Genome-wide linkage analysis of inguinal hernia in pigs using affected sib pairs

BACKGROUND: Inguinal and scrotal hernias are of great concern to pig producers, and lead to poor animal welfare and severe economic loss. Selection against these conditions is highly preferable, but at this time no gene, Quantitative Trait Loci (QTL), or mode of inheritance has been identified in pigs or in any other species. Therefore, a complete genome scan was performed in order to identify genomic regions affecting inguinal and scrotal hernias in pigs. Records from seedstock breeding farms were collected. No clinical examinations were executed on the pigs and there was therefore no distinction between inguinal and scrotal hernias. The genome scan utilised affected sib pairs (ASP), and the data was analysed using both an ASP test based on Non-parametric Linkage (NPL) analysis, and a Transmission Disequilibrium Test (TDT). RESULTS: Significant QTLs (p < 0.01) were detected on 8 out of 19 porcine chromosomes. The most promising QTLs, however, were detected in SSC1, SSC2, SSC5, SSC6, SSC15, SSC17 and SSCX; all of these regions showed either statistical significance with both statistical methods, or convincing significance with one of the methods. Haplotypes from these suggestive QTL regions were constructed and analysed with TDT. Of these, six different haplotypes were found to be differently transmitted (p < 0.01) to healthy and affected pigs. The most interesting result was one haplotype on SSC5 that was found to be transmitted to hernia pigs with four times higher frequency than to healthy pigs (p < 0.00005). CONCLUSION: For the first time in any species, a genome scan has revealed suggestive QTLs for inguinal and scrotal hernias. While this study permitted the detection of chromosomal regions only, it is interesting to note that several promising candidate genes, including INSL3, MIS, and CGRP, are located within the highly significant QTL regions. Further studies are required in order to narrow down the suggestive QTL regions, investigate the candidate genes, and to confirm the suggestive QTLs in other populations. The haplotype associated with inguinal and scrotal hernias may help in achieving selection against the disorder

Extraction of pure components from overlapped signals in gas chromatography-mass spectrometry (GC-MS)

Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for the identification and quantification of trace chemicals in complex mixtures. When complex samples are analyzed by GC-MS it is common to observe co-elution of two or more components, resulting in an overlap of signal peaks observed in the total ion chromatogram. In such situations manual signal analysis is often the most reliable means for the extraction of pure component signals; however, a systematic manual analysis over a number of samples is both tedious and prone to error. In the past 30 years a number of computational approaches were proposed to assist in the process of the extraction of pure signals from co-eluting GC-MS components. This includes empirical methods, comparison with library spectra, eigenvalue analysis, regression and others. However, to date no approach has been recognized as best, nor accepted as standard. This situation hampers general GC-MS capabilities, and in particular has implications for the development of robust, high-throughput GC-MS analytical protocols required in metabolic profiling and biomarker discovery. Here we first discuss the nature of GC-MS data, and then review some of the approaches proposed for the extraction of pure signals from co-eluting components. We summarize and classify different approaches to this problem, and examine why so many approaches proposed in the past have failed to live up to their full promise. Finally, we give some thoughts on the future developments in this field, and suggest that the progress in general computing capabilities attained in the past two decades has opened new horizons for tackling this important problem

Contribution mapping: a method for mapping the contribution of research to enhance its impact.

Background: At a time of growing emphasis on both the use of research and accountability, it is important for research funders, researchers and other stakeholders to monitor and evaluate the extent to which research contributes to better action for health, and find ways to enhance the likelihood that beneficial contributions are realized. Past attempts to assess research 'impact' struggle with operationalizing 'impact', identifying the users of research and attributing impact to research projects as source. In this article we describe Contribution Mapping, a novel approach to research monitoring and evaluation that aims to assess contributions instead of impacts. The approach focuses on processes and actors and systematically assesses anticipatory efforts that aim to enhance contributions, so-called alignment efforts. The approach is designed to be useful for both accountability purposes and for assisting in better employing research to contribute to better action for health.Methods: Contribution Mapping is inspired by a perspective from social studies of science on how research and knowledge utilization processes evolve. For each research project that is assessed, a three-phase process map is developed that includes the main actors, activities and alignment efforts during research formulation, production and knowledge extension (e.g. dissemination and utilization). The approach focuses on the actors involved in, or interacting with, a research project (the linked actors) and the most likely influential users, who are referred to as potential key users. In the first stage, the investigators of the assessed project are interviewed to develop a preliminary version of the process map and first estimation of research-related contributions. In the second stage, potential key-users and other informants are interviewed to trace, explore and triangulate possible contributions. In the third stage, the presence and role of alignment efforts is analyzed and the preliminary results are shared with relevant stakeholders for feedback and validation. After inconsistencies are clarified or described, the results are shared with stakeholders for learning, improvement and accountability purposes.Conclusion: Contribution Mapping provides an interesting alternative to existing methods that aim to assess research impact. The method is expected to be useful for research monitoring, single case studies, comparing multiple cases and indicating how research can better be employed to contribute to better action for health. © 2012 Kok and Schuit; licensee BioMed Central Ltd

Carbon inputs from Miscanthus displace older soil organic carbon without inducing priming

The carbon (C) dynamics of a bioenergy system are key to correctly defining its viability as a sustainable alternative to conventional fossil fuel energy sources. Recent studies have quantified the greenhouse gas mitigation potential of these bioenergy crops, often concluding that C sequestration in soils plays a primary role in offsetting emissions through energy generation. Miscanthus is a particularly promising bioenergy crop and research has shown that soil C stocks can increase by more than 2 t C ha−1 yr−1. In this study, we use a stable isotope (13C) technique to trace the inputs and outputs from soils below a commercial Miscanthus plantation in Lincolnshire, UK, over the first 7 years of growth after conversion from a conventional arable crop. Results suggest that an unchanging total topsoil (0–30 cm) C stock is caused by Miscanthus additions displacing older soil organic matter. Further, using a comparison between bare soil plots (no new Miscanthus inputs) and undisturbed Miscanthus controls, soil respiration was seen to be unaffected through priming by fresh inputs or rhizosphere. The temperature sensitivity of old soil C was also seen to be very similar with and without the presence of live root biomass. Total soil respiration from control plots was dominated by Miscanthus-derived emissions with autotrophic respiration alone accounting for ∼50 % of CO2. Although total soil C stocks did not change significantly over time, the Miscanthus-derived soil C accumulated at a rate of 860 kg C ha−1 yr−1 over the top 30 cm. Ultimately, the results from this study indicate that soil C stocks below Miscanthus plantations do not necessarily increase during the first 7 years

Global fire emissions buffered by the production of pyrogenic carbon

Landscape fires burn 3–5 million km2 of the Earth’s surface annually. They emit 2.2 Pg of carbon per year to the atmosphere, but also convert a significant fraction of the burned vegetation biomass into pyrogenic carbon. Pyrogenic carbon can be stored in terrestrial and marine pools for centuries to millennia and therefore its production can be considered a mechanism for long-term carbon sequestration. Pyrogenic carbon stocks and dynamics are not considered in global carbon cycle models, which leads to systematic errors in carbon accounting. Here we present a comprehensive dataset of pyrogenic carbon production factors from field and experimental fires and merge this with the Global Fire Emissions Database to quantify the global pyrogenic carbon production flux. We found that 256 (uncertainty range: 196–340) Tg of biomass carbon was converted annually into pyrogenic carbon between 1997 and 2016. Our central estimate equates to 12% of the annual carbon emitted globally by landscape fires, which indicates that their emissions are buffered by pyrogenic carbon production. We further estimate that cumulative pyrogenic carbon production is 60 Pg since 1750, or 33–40% of the global biomass carbon lost through land use change in this period. Our results demonstrate that pyrogenic carbon production by landscape fires could be a significant, but overlooked, sink for atmospheric CO2

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

The intellectual structure and substance of the knowledge utilization field: A longitudinal author co-citation analysis, 1945 to 2004

<p>Abstract</p> <p>Background</p> <p>It has been argued that science and society are in the midst of a far-reaching renegotiation of the social contract between science and society, with society becoming a far more active partner in the creation of knowledge. On the one hand, new forms of knowledge production are emerging, and on the other, both science and society are experiencing a rapid acceleration in new forms of knowledge utilization. Concomitantly since the Second World War, the science underpinning the knowledge utilization field has had exponential growth. Few in-depth examinations of this field exist, and no comprehensive analyses have used bibliometric methods.</p> <p>Methods</p> <p>Using bibliometric analysis, specifically first author co-citation analysis, our group undertook a domain analysis of the knowledge utilization field, tracing its historical development between 1945 and 2004. Our purposes were to map the historical development of knowledge utilization as a field, and to identify the changing intellectual structure of its scientific domains. We analyzed more than 5,000 articles using citation data drawn from the Web of Science^®. Search terms were combinations of knowledge, research, evidence, guidelines, ideas, science, innovation, technology, information theory and use, utilization, and uptake.</p> <p>Results</p> <p>We provide an overview of the intellectual structure and how it changed over six decades. The field does not become large enough to represent with a co-citation map until the mid-1960s. Our findings demonstrate vigorous growth from the mid-1960s through 2004, as well as the emergence of specialized domains reflecting distinct collectives of intellectual activity and thought. Until the mid-1980s, the major domains were focused on innovation diffusion, technology transfer, and knowledge utilization. Beginning slowly in the mid-1980s and then growing rapidly, a fourth scientific domain, evidence-based medicine, emerged. The field is dominated in all decades by one individual, Everett Rogers, and by one paradigm, innovation diffusion.</p> <p>Conclusion</p> <p>We conclude that the received view that social science disciplines are in a state where no accepted set of principles or theories guide research (<it>i.e.</it>, that they are pre-paradigmatic) could not be supported for this field. Second, we document the emergence of a new domain within the knowledge utilization field, evidence-based medicine. Third, we conclude that Everett Rogers was the dominant figure in the field and, until the emergence of evidence-based medicine, his representation of the general diffusion model was the dominant paradigm in the field.</p

Sustained acceleration of soil carbon decomposition observed in a 6-year warming experiment in a warm-temperate forest in southern Japan

To examine global warming’s effect on soil organic carbon (SOC) decomposition in Asian monsoon forests, we conducted a soil warming experiment with a multichannel automated chamber system in a 55-year-old warm-temperate evergreen broadleaved forest in southern Japan. We established three treatments: control chambers for total soil respiration, trenched chambers for heterotrophic respiration (R(h)), and warmed trenched chambers to examine warming effect on R(h). The soil was warmed with an infrared heater above each chamber to increase soil temperature at 5 cm depth by about 2.5 °C. The warming treatment lasted from January 2009 to the end of 2014. The annual warming effect on R(h) (an increase per °C) ranged from 7.1 to17.8% °C(−1). Although the warming effect varied among the years, it averaged 9.4% °C(−1) over 6 years, which was close to the value of 10.1 to 10.9% °C(−1) that we calculated using the annual temperature–efflux response model of Lloyd and Taylor. The interannual warming effect was positively related to the total precipitation in the summer period, indicating that summer precipitation and the resulting soil moisture level also strongly influenced the soil warming effect in this forest

Epistemic geographies of climate change: science, space and politics

Anthropogenic climate change has been presented as the archetypal global problem, identified by the slow work of assembling a global knowledge infrastructure, and demanding a concertedly global political response. But this ‘global’ knowledge has distinctive geographies, shaped by histories of exploration and colonialism, by diverse epistemic and material cultures of knowledge-making, and by the often messy processes of linking scientific knowledge to decision-making within different polities. We suggest that understanding of the knowledge politics of climate change may benefit from engagement with literature on the geographies of science. We review work from across the social sciences which resonates with geographers’ interests in the spatialities of scientific knowledge, to build a picture of what we call the epistemic geographies of climate change. Moving from the field site and the computer model to the conference room and international political negotiations, we examine the spatialities of the interactional co-production of knowledge and social order. In so doing, we aim to proffer a new approach to the intersections of space, knowledge and power which can enrich geography’s engagements with the politics of a changing climate