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Sökning: WFRF:(Zhang Huiping) > (2024)

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1.
  • Chen, Hongxia, et al. (författare)
  • PRL2 Phosphatase Promotes Oncogenic KIT Signaling in Leukemia Cells through Modulating CBL Phosphorylation
  • 2024
  • Ingår i: Molecular Cancer Research. - 1541-7786. ; 22:1, s. 94-103
  • Tidskriftsartikel (refereegranskat)abstract
    • Receptor tyrosine kinase KIT is frequently activated in acute myeloid leukemia (AML). While high PRL2 (PTP4A2) expression is correlated with activation of SCF/KIT signaling in AML, the underlying mechanisms are not fully understood. We discovered that inhibition of PRL2 significantly reduces the burden of oncogenic KIT-driven leukemia and extends leukemic mice survival. PRL2 enhances oncogenic KIT signaling in leukemia cells, promoting their proliferation and survival. We found that PRL2 dephosphorylates CBL at tyrosine 371 and inhibits its activity toward KIT, leading to decreased KIT ubiquitination and enhanced AKT and ERK signaling in leukemia cells.
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2.
  • Huang, Huiping, 1991, et al. (författare)
  • Joint DOA Estimation and Distorted Sensor Detection Under Entangled Low-Rank and Row-Sparse Constraints
  • 2024
  • Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. ; , s. 12851-12855
  • Konferensbidrag (refereegranskat)abstract
    • The problem of joint direction-of-arrival estimation and distorted sensor detection has received a lot of attention in recent decades. Most state-of-the-art work formulated such a problem via low-rank and row-sparse decomposition, where the low-rank and row-sparse components were treated in an isolated manner. Such a formulation results in a performance loss. Differently, in this paper, we entangle the low-rank and row-sparse components by exploring their inherent connection. Furthermore, we take into account the maximal distortion level of the sensors. An alternating optimization scheme is proposed to solve the low-rank component and the sparse component, where a closed-form solution is derived for the low-rank component and a quadratic programming is developed for the sparse component. Numerical results exhibit the effectiveness and superiority of the proposed method.
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  • Resultat 1-2 av 2

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