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Träfflista för sökning "WFRF:(Busch Christer) srt2:(2020-2022)"

Sökning: WFRF:(Busch Christer) > (2020-2022)

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1.
  • Näsvall, Karin, et al. (författare)
  • Host plant diet affects growth and induces altered gene expression and microbiome composition in the wood white (Leptidea sinapis) butterfly
  • 2021
  • Ingår i: Molecular Ecology. - : Wiley. - 0962-1083 .- 1365-294X. ; 30:2, s. 499-516
  • Tidskriftsartikel (refereegranskat)abstract
    • In a time with decreasing biodiversity, especially among insects, a detailed understanding about specific resource utilization strategies is crucial. The physiological and behavioural responses to host switches in phytophagous insects are poorly understood. Earlier studies indicate that a host plant switch might be associated with distinctive molecular and physiological responses in different lineages. Expanding the assessment of such associations across Lepidoptera will reveal if there are general patterns in adaptive responses, or if each switch event is more of a unique character. We investigated host plant preference, fitness consequences, effects on expression profiles and gut microbiome composition in two common wood white (Leptidea sinapis) populations with different host plant preferences from the extremes of the species distribution area (Sweden and Catalonia). Our results show that female Catalonian wood whites lack preference for either host plant (Lotus corniculatus or L. dorycnium), while Swedish females laid significantly more eggs on L. corniculatus. Individuals from both populations reared on L. dorycnium had longer developmental times and smaller body size as adults. This indicates that both environmental and genetic factors determine the choice to use a specific host plant. Gene expression analysis revealed a more pronounced response to host plant in the Catalonian compared to the Swedish population. In addition, host plant treatment resulted in a significant shift in microbiome community structure in the Catalonian population. Together, this suggests that population specific plasticity associated with local conditions underlies host plant utilisation in wood whites.
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2.
  • Walhagen, Peter, et al. (författare)
  • AI based prostate analysis system trained without human supervision to predict patient outcome from tissue samples
  • 2022
  • Ingår i: Journal of Pathology Informatics. - : Elsevier BV. - 2229-5089 .- 2153-3539.
  • Tidskriftsartikel (refereegranskat)abstract
    • In order to plan the best treatment for prostate cancer patients the aggressiveness of the tumor is graded based on visual assessment of tissue biopsies according to the Gleason scale. Recently a number of AI models have been developed that can be trained to do this grading as well as human pathologists. But the accuracy of the AI grading will be limited by the accuracy of the subjective “ground truth” Gleason grades used for the training. We have trained an AI to predict patient outcome directly based on image analysis of a large biobank of tissue samples with known outcome without input of any human knowledge about cancer grading. The model has shown similar and in some cases better ability to predict patient outcome on an independent test-set than expert pathologists doing the conventional grading.
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