Technology Transfer in Forest Pest Management: A Case History

The current approach being used in the spruce budworm technology transfer program for the Lake States is described. During 1981-1982, we concentrated on needs assessment surveys and the development and packaging of materials in five areas: general manual, chemical control handbook, silviculture handbook, instruction manual for remote sensing workshops, and technical reports on budworm impact on spruce-fir stands. We present a list of factors that researchers and technology transfer specialists should consider when plan- ning a research and technology transfer program in forest pest management

Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types.

Isoforms of human miRNAs (isomiRs) are constitutively expressed with tissue- and disease-subtype-dependencies. We studied 10 271 tumor datasets from The Cancer Genome Atlas (TCGA) to evaluate whether isomiRs can distinguish amongst 32 TCGA cancers. Unlike previous approaches, we built a classifier that relied solely on \u27binarized\u27 isomiR profiles: each isomiR is simply labeled as \u27present\u27 or \u27absent\u27. The resulting classifier successfully labeled tumor datasets with an average sensitivity of 90% and a false discovery rate (FDR) of 3%, surpassing the performance of expression-based classification. The classifier maintained its power even after a 15× reduction in the number of isomiRs that were used for training. Notably, the classifier could correctly predict the cancer type in non-TCGA datasets from diverse platforms. Our analysis revealed that the most discriminatory isomiRs happen to also be differentially expressed between normal tissue and cancer. Even so, we find that these highly discriminating isomiRs have not been attracting the most research attention in the literature. Given their ability to successfully classify datasets from 32 cancers, isomiRs and our resulting \u27Pan-cancer Atlas\u27 of isomiR expression could serve as a suitable framework to explore novel cancer biomarkers

MINTbase v2.0: a comprehensive database for tRNA-derived fragments that includes nuclear and mitochondrial fragments from all The Cancer Genome Atlas projects.

MINTbase is a repository that comprises nuclear and mitochondrial tRNA-derived fragments (\u27tRFs\u27) found in multiple human tissues. The original version of MINTbase comprised tRFs obtained from 768 transcriptomic datasets. We used our deterministic and exhaustive tRF mining pipeline to process all of The Cancer Genome Atlas datasets (TCGA). We identified 23 413 tRFs with abundance of ≥ 1.0 reads-per-million (RPM). To facilitate further studies of tRFs by the community, we just released version 2.0 of MINTbase that contains information about 26 531 distinct human tRFs from 11 719 human datasets as of October 2017. Key new elements include: the ability to filter tRFs on-the-fly by minimum abundance thresholding; the ability to filter tRFs by tissue keywords; easy access to information about a tRF\u27s maximum abundance and the datasets that contain it; the ability to generate relative abundance plots for tRFs across cancer types and convert them into embeddable figures; MODOMICS information about modifications of the parental tRNA, etc. Version 2.0 of MINTbase contains 15x more datasets and nearly 4x more distinct tRFs than the original version, yet continues to offer fast, interactive access to its contents. Version 2.0 is available freely at http://cm.jefferson.edu/MINTbase/

The turbulent wake of a monopile foundation

publisher: Elsevier articletitle: The turbulent wake of a monopile foundation journaltitle: Renewable Energy articlelink: http://dx.doi.org/10.1016/j.renene.2016.02.050 content_type: article copyright: Copyright © 2016 Elsevier Ltd. All rights reserved

Increased susceptibility to Trichuris muris infection and exacerbation of colitis in Mdr1a-/- mice

AIM: To investigate the influence of Trichuris muris (T. muris ) infection in a mouse model of genetic susceptibility to inflammatory bowel disease, Mdr1a-/-. METHODS: Mdr1a-/- mice were housed under specific pathogen free conditions to slow the development of colitis and compared to congenic FVB controls. Mice were infected with approximately 200 embryonated ova from T. muris and assessed for worm burden and histological and functional markers of gut inflammation on day 19 post infection. RESULTS: Mdr1a-/- mice exhibited a marked increase in susceptibility to T. muris infection with a 10-fold increase in colonic worm count by day 19 pi compared to FVB controls. Prior to infection, Mdr1a-/- exhibited low-level mucosal inflammation with evidence of an enhanced Th1 environment. T. muris infection accelerated the progression of colitis in Mdr1a-/- as evidenced by marked increases in several indicators including histological damage score, mucosal CD4+ T-cell and DC infiltration and dramatically increased production of proinflammatory cytokines. CONCLUSION: These data provide further evidence of the complex interaction between T. muris and an inflammatory bowel disease (IBD)-susceptible host which may have relevance to the application of helminth therapy in the treatment of human IBD

21st century fisheries management: a spatio-temporally explicit tariff-based approach combining multiple drivers and incentivising responsible fishing

Abstract Kraak, S. B. M., Reid, D. G., Gerritsen, H. D., Kelly, C. J., Fitzpatrick, M., Codling, E. A., and Rogan, E. 2012. 21st century fisheries management: a spatio-temporally explicit tariff-based approach combining multiple drivers and incentivising responsible fishing. – ICES Journal of Marine Science, 69: 590–601. Traditionally fisheries management has focused on biomass and mortality, expressed annually and across large management units. However, because fish abundance varies at much smaller spatio-temporal scales, fishing mortality can potentially be controlled more effectively if managed at finer scale. The ecosystem approach requires more indicators at finer scales as well. Incorporating ecosystem targets would need additional management tools with potentially conflicting results. We present a simple, integrated, management approach that provides incentives for “good behaviour”. Fishers would be given a number of fishing-impact credits, called real-time incentives (RTIs), to spend according to spatio-temporally varying tariffs per fishing day. RTI quotas and tariffs could be based on commercial stocks and ecosystem targets. Fishers could choose how to spend their RTIs, e.g. by limited fishing in high-catch or sensitive areas or by fishing longer in lower-catch or less sensitive areas. The RTI system does not prescribe and forbid, but instead allows fishers to fish wherever and whenever they want; ecosystem costs are internalized and fishers have to take them into account in their business decisions. We envisage no need for traditional landings or catch quotas for the fleets while operating under the scheme. The approach could facilitate further devolution of responsibility to industry.</jats:p

Tandem machine learning for the identification of genes regulated by transcription factors

BACKGROUND: The identification of promoter regions that are regulated by a given transcription factor has traditionally relied upon the identification and distributions of binding sites recognized by the factor. In this study, we have developed a tandem machine learning approach for the identification of regulatory target genes based on these parameters and on the corresponding binding site information contents that measure the affinities of the factor for these cognate elements. RESULTS: This method has been validated using models of DNA binding sites recognized by the xenobiotic-sensitive nuclear receptor, PXR/RXRα, for target genes within the human genome. An information theory-based weight matrix was first derived and refined from known PXR/RXRα binding sites. The promoter region of candidate genes was scanned with the weight matrix. A novel information density-based clustering algorithm was then used to identify clusters of information rich sites. Finally, transformed data representing metrics of location, strength and clustering of binding sites were used for classification of promoter regions using an ensemble approach involving neural networks, decision trees and Naïve Bayesian classification. The method was evaluated on a set of 24 known target genes and 288 genes known not to be regulated by PXR/RXRα. We report an average accuracy (proportion of correctly classified promoter regions) of 71%, sensitivity of 73%, and specificity of 70%, based on multiple cross-validation and the leave-one-out strategy. The performance on a test set of 13 genes showed that 10 were correctly classified. CONCLUSION: We have developed a machine learning approach for the successful detection of gene targets for transcription factors with high accuracy. The method has been validated for the transcription factor PXR/RXRα and has the potential to be extended to other transcription factors

Characterization of Environmental Levels of Pesticide Residues in Household Air and Dust Samples near a Bioenergy Plant Using Treated Seed as Feedstock

Exposure to neonicotinoid insecticides is associated with adverse human health outcomes. There is environmental contamination in Saunders County, Nebraska, due to the accumulation of fungicides and insecticides from a now-closed ethanol plant using seed corn as stock. A pilot study quantified environmental contamination in nearby houses from residual pesticides by measuring dust and air (indoor/outdoor) concentrations of neonicotinoids and fungicides at the study site (households within two miles of the plant) and control towns (20–30 miles away). Air (SASS® 2300 Wetted-Wall Air Sampler) and surface dust (GHOST wipes with 4 × 4-inch template) samples were collected from eleven study households and six controls. Targeted analysis quantified 13 neonicotinoids, their transformation products and seven fungicides. Sample extracts were concentrated using solid phase extraction (SPE) cartridges, eluted with methanol and evaporated. Residues were redissolved in methanol–water (1:4) prior to analysis, with an Acquity H-Class ultraperformance liquid chromatograph (UPLC) and a Xevo triple quadrupole mass spectrometer. We compared differences across chemicals in air and surface dust samples at the study and control sites by dichotomizing concentrations above or below the detection limit, using Fisher’s exact test. A relatively higher detection frequency was observed for clothianidin and thiamethoxam at the study site for the surface dust samples, similarly for thiamethoxam in the air samples. Our results suggest airborne contamination (neonicotinoids and fungicides) from the ethanol facility at houses near the pesticide contamination