Results 91 to 100 of about 806,463 (274)

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

Molecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova, Zuzana Kozovska, Ondrej Pos, Kristina Pavlov, Sachin Gulati, Peter Makovicky, Kristina Jakic, Monika Burikova, Eva Sedlackova, Barbora Svitkova, Silvia Tyciakova, Vojtech Bystry, Nicolas Blavet, Boris Tichy, Matej Hrnciar, Jaroslav Budis, Miroslav Tomas, Peter Dubovan, Georgina Kolnikova, Veronika Repaska, Nikoleta Mojzesova, Eva Zomborska, Daniel Pindak, Michal Mego, Tomas Szemes, Miroslava Matuskova   +25 more
wiley   +1 more source

Verifying Properties of Binarized Deep Neural Networks

, 2018
Understanding properties of deep neural networks is an important challenge in deep learning. In this paper, we take a step in this direction by proposing a rigorous way of verifying properties of a popular class of neural networks, Binarized Neural ...
Kasiviswanathan, Shiva Prasad, Narodytska, Nina, Ryzhyk, Leonid, Sagiv, Mooly, Walsh, Toby   +4 more
core   +1 more source

RIPK4 function interferes with melanoma cell adhesion and metastasis

Molecular Oncology, EarlyView.
RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski, Sławomir Lasota, Ewelina Madej, Anna A. Brożyna, Małgorzata Szczygieł, Agnieszka Harazin‐Lechowska, Jan Czerbniak, Janusz Rys, Jaroslaw Czyz, Agnieszka Wolnicka‐Glubisz   +9 more
wiley   +1 more source

Dynamic neuron approach to deep neural networks: Decoupling neurons for renormalization group analysis

Physical Review Research
Deep neural network architectures often consist of repetitive structural elements. We introduce an approach that reveals these patterns and can be broadly applied to the study of deep learning.
Donghee Lee, Hye-Sung Lee, Jaeok Yi
doaj   +1 more source

Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression †

Energies, 2018
Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech ...
Gregory D. Merkel, Richard J. Povinelli, Ronald H. Brown   +2 more
doaj   +1 more source

Naked cuticle is essential for Drosophila wing development beyond Wingless signaling

FEBS Open Bio, EarlyView.
Naked cuticle (Nkd), a Wnt signaling inhibitor, assumes extensive roles in Drosophila wing development. Overexpressing Nkd causes smaller, crumpled wings, while also perturbing multiple signaling pathways and developmental genes. A specific region (R1S) is critical for Nkd's function as a signaling integrator, offering new insights for studying its ...
Rui Wang, Ping Wang
wiley   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

A Systematic Exploration of Deep Neural Networks for EDA-Based Emotion Recognition

Information, 2020
Subject-independent emotion recognition based on physiological signals has become a research hotspot. Previous research has proved that electrodermal activity (EDA) signals are an effective data resource for emotion recognition.
Dian Yu, Shouqian Sun
doaj   +1 more source

The Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential

Aging and Cancer, EarlyView.
As a conduit linking all organs, the blood system both reflects and actively drives systemic aging. This review highlights how circulating pro‐aging and antiaging factors and age‐associated hematopoietic stem cell dysfunction contribute to immunosenescence and multi‐organ decline, positioning the hematopoietic system as a target for aging intervention.
Hanqing He, Jianwei Wang
wiley   +1 more source

Learning in Deep Radial Basis Function Networks

Entropy
Learning in neural networks with locally-tuned neuron models such as radial Basis Function (RBF) networks is often seen as instable, in particular when multi-layered architectures are used. Furthermore, universal approximation theorems for single-layered
Fabian Wurzberger, Friedhelm Schwenker
doaj   +1 more source