Results 111 to 120 of about 5,787,644 (326)

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

open access: yesMolecular Oncology, EarlyView.
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice   +16 more
wiley   +1 more source

Anticipated Fiscal Policy and Adaptive Learning [PDF]

open access: yes
We consider the impact of anticipated policy changes when agents form expectations using adaptive learning rather than rational expectations. To model this we assume that agents combine limited structural knowledge with a standard adaptive learning rule.
George W. Evans   +2 more
core  

Medical analysis and diagnosis by neural networks [PDF]

open access: yes, 2010
In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background.
Brause, Rüdiger W.
core  

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

open access: yesMolecular Oncology, EarlyView.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak   +4 more
wiley   +1 more source

Lepskii Principle in Supervised Learning

open access: yes, 2019
In the setting of supervised learning using reproducing kernel methods, we propose a data-dependent regularization parameter selection rule that is adaptive to the unknown regularity of the target function and is optimal both for the least-square ...
Blanchard, Gilles   +2 more
core  

Exploiting metabolic adaptations to overcome dabrafenib treatment resistance in melanoma cells

open access: yesMolecular Oncology, EarlyView.
We show that dabrafenib‐resistant melanoma cells undergo mitochondrial remodeling, leading to elevated respiration and ROS production balanced by stronger antioxidant defenses. This altered redox state promotes survival despite mitochondrial damage but renders resistant cells highly vulnerable to ROS‐inducing compounds such as PEITC, highlighting redox
Silvia Eller   +17 more
wiley   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

open access: yesMolecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix   +13 more
wiley   +1 more source

A Distributed Outstar Network for Spatial Pattern Learning [PDF]

open access: yes, 1993
The distributed outstar, a generalization of the outstar neural network for spatial pattern learning, is introduced. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes.
Carpenter, Gail A.
core   +1 more source

Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin

open access: yesMolecular Oncology, EarlyView.
The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla   +10 more
wiley   +1 more source

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems [PDF]

open access: yes
Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output.
Bond, W. E.   +3 more
core   +1 more source

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