Niet-landbouwkundig gebruik van gewasbeschermingsmiddelen : schatting van terreintypen en verbruik voor de eindevaluatie van de Nota duurzame gewasbescherming

In 2009 is een onderzoek gedaan naar het verbruik van gewasbeschermingsmiddelen en biociden buiten de landbouw. Deze cijfers zijn bedoeld om in een latere fase de relatieve bijdrage van het niet-landbouwkundig verbruik van middelen aan de waterkwaliteit in te kunnen schatten. Areaalcijfers voor de typen grondgebruik en categorieën objecten werden verzameld uit diverse bodem- en grondgebruikstatistieken. De volgende vormen van grondgebruik zijn onderscheiden: wegen, waterwegen, defensieterreinen, spoorwegen, bedrijfsterreinen, agrarische bedrijfsterreinen, woningen, landgoederen, volkstuinen, tuincentra, bos en natuur, openbaar groen, recreatie, sportterreinen. Het totale verbruik in 2008 werd geschat op 245 ton actieve stof toegepast op in totaal 1,7 miljoen ha. Dit komt overeen met een gebruik van 0,14 kg werkzame stof per ha. Ten opzichte van 1998 was het geschatte verbruik in 2008 licht gedaald (-3%) terwijl het areaal licht toegenomen (+ 5%) was

Feasibility of using teleradiology to improve tuberculosis screening and case management in a district hospital in Malawi.

Malawi has one of the world's highest rates of human immunodeficiency virus (HIV) infection (10.6%), and southern Malawi, where Thyolo district is located, bears the highest burden in the country (14.5%). Tuberculosis, common among HIV-infected people, requires radiologic diagnosis, yet Malawi has no radiologists in public service. This hinders rapid and accurate diagnosis and increases morbidity and mortality

A distantly supervised dataset for automated data extraction from diagnostic studies

International audienceSystematic reviews are important in evidencebased medicine, but are expensive to produce.Automating or semi-automating the data extractionof index test, target condition, and referencestandard from articles has the potentialto decrease the cost of conducting systematicreviews of diagnostic test accuracy, but relevanttraining data is not available. We create adistantly supervised dataset of approximately90,000 sentences, and let two experts manuallyannotate a small subset of around 1,000sentences for evaluation. We evaluate the performanceof BioBERT and logistic regressionfor ranking the sentences, and compare theperformance for distant and direct supervision.Our results suggest that distant supervision canwork as well as, or better than direct supervisionon this problem, and that distantly trainedmodels can perform as well as, or better thanhuman annotators

Distinct gene loci control the host response to influenza H1N1 virus infection in a time-dependent manner

<p>Abstract</p> <p>Background</p> <p>There is strong but mostly circumstantial evidence that genetic factors modulate the severity of influenza infection in humans. Using genetically diverse but fully inbred strains of mice it has been shown that host sequence variants have a strong influence on the severity of influenza A disease progression. In particular, C57BL/6J, the most widely used mouse strain in biomedical research, is comparatively resistant. In contrast, DBA/2J is highly susceptible.</p> <p>Results</p> <p>To map regions of the genome responsible for differences in influenza susceptibility, we infected a family of 53 BXD-type lines derived from a cross between C57BL/6J and DBA/2J strains with influenza A virus (PR8, H1N1). We monitored body weight, survival, and mean time to death for 13 days after infection. <it>Qivr5</it> (quantitative trait for influenza virus resistance on chromosome 5) was the largest and most significant QTL for weight loss. The effect of <it>Qivr5</it> was detectable on day 2 post infection, but was most pronounced on days 5 and 6. Survival rate mapped to <it>Qivr5</it>, but additionally revealed a second significant locus on chromosome 19 (<it>Qivr19</it>). Analysis of mean time to death affirmed both <it>Qivr5</it> and <it>Qivr19</it>. In addition, we observed several regions of the genome with suggestive linkage. There are potentially complex combinatorial interactions of the parental alleles among loci. Analysis of multiple gene expression data sets and sequence variants in these strains highlights about 30 strong candidate genes across all loci that may control influenza A susceptibility and resistance.</p> <p>Conclusions</p> <p>We have mapped influenza susceptibility loci to chromosomes 2, 5, 16, 17, and 19. Body weight and survival loci have a time-dependent profile that presumably reflects the temporal dynamic of the response to infection. We highlight candidate genes in the respective intervals and review their possible biological function during infection.</p