Results 81 to 90 of about 1,703,706 (235)
Mutant p53R273H disrupts PDPK1 homodimerization and contributes to PDPK1 activation
Molecular Oncology, EarlyView.How mutant p53R273H drives AKT signaling is unclear. We show that p53R273H, but not wild‐type, directly binds PDPK1 via a mutation‐dependent conformational change. This interaction disrupts inhibitory PDPK1 homodimerization and enhances AKT phosphorylation.
Mei Chee Lim +11 more
wiley +1 more source
Multivariable feedback particle filter [PDF]
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012 In recent work it is shown that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear filtering combined with Mean-Field Game formalisms. The resulting feedback particle filter (FPF) offers significant variance improvements; in particular, the algorithm can be applied to systems that
Tao Yang 0017 +3 more
openaire +4 more sources
Data Fusion-Based Multi-Object Tracking for Unconstrained Visual Sensor Networks
IEEE Access, 2018 Camera node perception capability is one of the crucial issues for visual sensor networks, which belongs to the field of Internet of Things. Multi-object tracking is an important feature in analyzing object trajectories across multiple cameras, thus ...
Xiaoyan Jiang +7 more
doaj +1 more source
Targeting the EpCAM‐AXL axis to overcome drug resistance in lung cancer
Molecular Oncology, EarlyView.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
Model Adaptation for Prognostics in a Particle Filtering Framework [PDF]
International Journal of Prognostics and Health Management, 2011 One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated.
Bhaskar Saha, Kai Goebel
doaj
Improved Parallel Resampling Methods for Particle Filtering
IEEE Access, 2019 Particle filter techniques are common methods used to estimate the evolving state of nonlinear, non-Gaussian time-variant systems by utilizing a periodic sequence of noisy measurements.
Matthew A. Nicely, B. Earl Wells
doaj +1 more source
Reprogramming tumor cells with LCOR mRNA nanotherapy to enhance immunotherapy
Molecular Oncology, EarlyView.LCOR (Ligand‐dependent corepressor) mRNA encapsulated in polymeric nanoparticles restores LCOR activity in tumor cells, constraining aggressive tumor cell states and increasing tumor immunogenicity. This reprogramming makes tumor cells more vulnerable to T‐cell attack and enhances their response to immune‐checkpoint immunotherapy.
Gabriel Serra‐Mir +9 more
wiley +1 more source
Molecular Oncology, EarlyView.This paper shows that size‐exclusion chromatography and sequential centrifugation applied to seminal plasma enrich for different populations of extracellular vesicles. This may significantly affect the detection and analysis of extracellular vesicle‐associated cancer biomarkers.
Elen Telumyan +8 more
wiley +1 more source
Particle Filters for Markov Switching Stochastic Volatility Models [PDF]
This paper proposes an auxiliary particle filter algorithm for inference in regime switching stochastic volatility models in which the regime state is governed by a first-order Markov chain.
Boda Kang, Yun Bao, Carl Chiarella
core
Identifying Uncertainty Distributions and Confidence Regions of Power Plant Parameters
IEEE Access, 2017 Power system operators, when obtaining a model's parameter estimates; require additional information to guide their decision on a model's acceptance.
Tetiana Bogodorova +3 more
doaj +1 more source