Results 91 to 100 of about 228,260 (299)

From energy provision to protein synthesis: Tunnelling nanotubes as mediators of intercellular metabolic cooperation in cancer

open access: yesFEBS Open Bio, EarlyView.
The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley   +1 more source

Guided Disentangled Representation Learning from Audio data for Transfer Learning

open access: yes
In the field of machine learning, disentangled representation learning seeks to map high-dimensional data into a low-dimensional space where the underlying variational factors are both disentangled and easily separable.
Haque, Kazi Nazmul
core   +1 more source

Web2Vec: Phishing Webpage Detection Method Based on Multidimensional Features Driven by Deep Learning

open access: yesIEEE Access, 2020
Phishing is a kind of online attack that attempts to defraud sensitive information of network users. Current phishing webpage detection methods mainly use manual feature collection, and there are problems that feature extraction is complicated and the ...
Jian Feng   +3 more
doaj   +1 more source

Pathways and pitfalls: a qualitative study of student experiences in biomedical science education

open access: yesFEBS Open Bio, EarlyView.
Biomedical science students from underrepresented backgrounds face barriers including financial strain, disrupted laboratory access and cultural exclusion. Peer networks provide vital support when institutional systems are difficult to navigate. To create inclusive learning environments and achieve academic success, educators should blend active, hands‐
Olivia J. Russell   +8 more
wiley   +1 more source

DyHNet: Learning Dynamic Heterogeneous Network Representations

open access: yesInformation Sciences, 2022
Abstract Many real-world networks, such as social networks, contain structuralheterogeneity and experience temporal evolution. However, while therehas been growing literature on network representation learning, only afew have addressed the need to learn representations for dynamic hetero-geneous networks. The objective of our work in this paper
Hoang Nguyen   +3 more
openaire   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

open access: yesAging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel   +4 more
wiley   +1 more source

NodeVector: A Novel Network Node Vectorization with Graph Analysis and Deep Learning

open access: yesApplied Sciences
Network node embedding captures structural and relational information of nodes in the network and allows for us to use machine learning algorithms for various prediction tasks on network data that have an inherently complex and disordered structure ...
Volkan Altuntas
doaj   +1 more source

Artificial Intelligence and Mental Well‐Being in Adult Education: Implications for Practice and Professional Responsibility

open access: yesNew Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley   +1 more source

Review of Visual Representation Learning [PDF]

open access: yesJisuanji kexue
Representation learning is an important step of artificial intelligence algorithm,where well designed representation can boost downstream tasks.With the development of deep learning in computer vision,visual representation learning has become ...
WANG Shuaiwei, LEI Jie, FENG Zunlei, LIANG Ronghua
doaj   +1 more source

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi   +2 more
wiley   +1 more source

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