Results 61 to 70 of about 9,871,334 (304)
Emerging experimental and computational methods for studying redox‐regulated structural transitions
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Beyond statistical learning? Continuous sequence repetition matters in implicit sequence learning
Typically, statistical learning is investigated by testing the acquisition of specific items or forming general rules. As implicit sequence learning also involves the extraction of regularities from the environment, it can also be considered as an ...
Meier, Beat
core +1 more source
Incremental Learning-to-Learn with Statistical Guarantees
In learning-to-learn the goal is to infer a learning algorithm that works well on a class of tasks sampled from an unknown meta distribution. In contrast to previous work on batch learning-to-learn, we consider a scenario where tasks are presented sequentially and the algorithm needs to adapt incrementally to improve its performance on future tasks ...
Giulia Denevi +3 more
openaire +4 more sources
Pair‐wise comparison of the CellSearch and FETCH enrichment technologies for circulating tumor cells (CTCs) from metastatic breast, prostate, and small cell lung cancer patients shows an increased capture of CTCs using FETCH enrichment. The clinical implementation of circulating tumor cells (CTCs) as a predictive tool for therapy efficacy in the ...
Michiel Stevens +6 more
wiley +1 more source
The committee machine: Computational to statistical gaps in learning a two-layers neural network
NeurIPS 2018 - Thirty-second Conference on Neural Information Processing Systems, Montreal, Canada, December 3-8ISBN: 9781510884472International audienceHeuristic tools from statistical physics have been used in the past to locate the phase transitions ...
Aubin, Benjamin +5 more
core +4 more sources
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
wiley +1 more source
CEACAM1 participation in breast cancer progression
In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin +3 more
wiley +1 more source
Contextual influences on visual statistical learning
Vickery, Timothy J.Visual statistical learning describes the unintentional extraction of statistical regularities from visual environments across time or space, and is typically studied using novel stimuli (e.g., symbols unfamiliar to participants ...
Rogers, Leeland Loew
core +1 more source
Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou +4 more
wiley +1 more source

