Results 111 to 120 of about 1,983,602 (251)
Targeting the EpCAM‐AXL axis to overcome drug resistance in lung cancer
Lung cancer cells often evade therapy by hijacking signaling pathways. We reveal that cleaved EpCAM (sEpCAM) stabilizes the oncogenic protein AXL, driving NF‐κB and STAT3‐mediated chemoresistance. This EpCAM‐AXL axis identifies a high‐risk patient subset with poor prognosis.
Alexa Guerrero‐Alba +5 more
wiley +1 more source
LVRF (lymphatic and vascular resistance factor) is a VEGFA splice variant upregulated in response to anti‐angiogenic therapy that fosters tumor adaptation through enhanced vascularization, lymphangiogenesis, and metastatic dissemination. Targeting LVRF with fully human neutralizing antibodies disrupts these processes and limits resistant tumor growth ...
Marion David +12 more
wiley +1 more source
Due to the large fluctuations of the boundaries and internal variations of the lesion regions in medical image segmentation, current methods may have difficulty capturing sufficient global contexts effectively to deal with these inherent challenges ...
Lifang Chen +4 more
doaj +1 more source
The multifaceted roles of lysosomes in cancer
Lysosomes support cancer cell adaptation by integrating macromolecule degradation and nutrient recycling with nutrient sensing, inter‐organelle communication and immune regulation. These interconnected functions can promote tumour growth, stress tolerance and therapy resistance, while also creating context‐dependent vulnerabilities that may be ...
Jia Li, Kevin M. Ryan
wiley +1 more source
Differentiation of matrix functionals using triangular factorization [PDF]
In various applications, it is necessary to differentiate a matrix functional w(A(x)), where A(x) is a matrix depending on a parameter vector x. Usually, the functional itself can be readily computed from a triangular factorization of A(x).
Anderssen, R.S. +2 more
core
Approximate low-rank factorization with structured factors
An approximate rank revealing factorization problem with structure constraints on the normalized factors is considered. Examples of structure, motivated by an application in microarray data analysis, are sparsity, nonnegativity, periodicity, and ...
Niranjan, Mahesan, Markovsky, Ivan
core +1 more source
Traditional wet experiments to identify drug–target interactions (DTIs) are costly and time consuming. Therefore, machine learning-based methods are commonly used to speed up the identification process.
Junjun Zhang, Tingfeng Zeng
doaj +1 more source
The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński +12 more
wiley +1 more source
Matrix factorization over semirings [PDF]
Semiring is an algebraic structure with which some problems that are nonlinear in classical algebra, can be solved in a linear manner. By matrix factorization, decomposing input matrix into two (or more) matrices, various problems in data mining and ...
Horvat , Veronika, Horvat, Veronika
core +1 more source
Cisplatin‐resistant cancer cells survive DNA‐damaging platinum‐based treatment yet remain sensitive to CuET‐induced proteotoxic stress. The distinct mechanism of action allows CuET to overcome and eliminate cisplatin‐resistant tumour cells, unless highly expressed metallothioneins (MTs) interfere with CuET, thereby highlighting MT levels as candidate ...
Stefanos Arampatzis +20 more
wiley +1 more source

