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Sökning: WFRF:(Larsson SC)

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  • Kitagawa, M, et al. (författare)
  • Dual blockade of the lipid kinase PIP4Ks and mitotic pathways leads to cancer-selective lethality
  • 2017
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8:1, s. 2200-
  • Tidskriftsartikel (refereegranskat)abstract
    • Achieving robust cancer-specific lethality is the ultimate clinical goal. Here, we identify a compound with dual-inhibitory properties, named a131, that selectively kills cancer cells, while protecting normal cells. Through an unbiased CETSA screen, we identify the PIP4K lipid kinases as the target of a131. Ablation of the PIP4Ks generates a phenocopy of the pharmacological effects of PIP4K inhibition by a131. Notably, PIP4Ks inhibition by a131 causes reversible growth arrest in normal cells by transcriptionally upregulating PIK3IP1, a suppressor of the PI3K/Akt/mTOR pathway. Strikingly, Ras activation overrides a131-induced PIK3IP1 upregulation and activates the PI3K/Akt/mTOR pathway. Consequently, Ras-transformed cells override a131-induced growth arrest and enter mitosis where a131’s ability to de-cluster supernumerary centrosomes in cancer cells eliminates Ras-activated cells through mitotic catastrophe. Our discovery of drugs with a dual-inhibitory mechanism provides a unique pharmacological strategy against cancer and evidence of cross-activation between the Ras/Raf/MEK/ERK and PI3K/AKT/mTOR pathways via a Ras˧PIK3IP1˧PI3K signaling network.
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  • Larsson, Magnus, et al. (författare)
  • Aerodynamic Identification using Neural Networks
  • 1997
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • The use of neural networks and efficient identification algorithms in aerodynamic modeling could substantially reduce the time and work effort in going from wind tunnel and flight test data to model. The model is globally differentiable and can be inspected in any way desired. A number of structured and black box sigmoid type neural net models have been identified for mainly the C z aerodynamic coefficient in the region 0 ffi ff 60 ffi , where the aerodynamic coefficients behave highly nonlinear. The estimation data has been directly extracted from an existing aerodatabase for a generic fighter aircraft, that also has been used for validation. All available data has been used for estimation and the data is considered noiseless, so only the approximation properties of the different models are tested. Somewhat surprisingly, it is found that pure black box models with the same number of parameters as structured models utilizing physical insight, often perform better.
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