Results 71 to 80 of about 8,564 (282)
FEBS Letters, EarlyView.We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +1 more source
A High-Capacity Steganography Algorithm Based on Adaptive Frequency Channel Attention Networks
Sensors, 2022 Deep learning has become an essential technique in image steganography. Most of the current deep-learning-based steganographic methods process digital images in the spatial domain.
Shanqing Zhang +4 more
doaj +1 more source
Structural biology of ferritin nanocages
FEBS Letters, EarlyView.Ferritin is a conserved iron‐storage protein that sequesters iron as a ferric mineral core within a nanocage, protecting cells from oxidative damage and maintaining iron homeostasis. This review discusses ferritin biology, structure, and function, and highlights recent cryo‐EM studies revealing mechanisms of ferritinophagy, cellular iron uptake, and ...
Eloise Mastrangelo, Flavio Di Pisa
wiley +1 more source
Comparative performance assessment of deep learning based image steganography techniques
Scientific Reports, 2022 Increasing data infringement while transmission and storage have become an apprehension for the data owners. Even the digital images transmitted over the network or stored at servers are prone to unauthorized access.
Varsha Himthani +5 more
doaj +1 more source
Molecular Oncology, EarlyView.This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan +9 more
wiley +1 more source
Deep Convolutional Neural Network to Detect J-UNIWARD
, 2017 This paper presents an empirical study on applying convolutional neural networks (CNNs) to detecting J-UNIWARD, one of the most secure JPEG steganographic method.
Ioffe Sergey +3 more
core +1 more source
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Molecular Oncology, EarlyView.Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts +8 more
wiley +1 more source
Molecular Oncology, EarlyView.A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira +14 more
wiley +1 more source
Bayesian Neural Networks for Reversible Steganography
IEEE Access, 2022 Recent advances in deep learning have led to a paradigm shift in the field of reversible steganography. A fundamental pillar of reversible steganography is predictive modelling which can be realised via deep neural networks. However, non-trivial errors exist in inferences about some out-of-distribution and noisy data.
openaire +3 more sources
Emerging role of ARHGAP29 in melanoma cell phenotype switching
Molecular Oncology, EarlyView.This study gives first insights into the role of ARHGAP29 in malignant melanoma. ARHGAP29 was revealed to be connected to tumor cell plasticity, promoting a mesenchymal‐like, invasive phenotype and driving tumor progression. Further, it modulates cell spreading by influencing RhoA/ROCK signaling and affects SMAD2 activity. Rho GTPase‐activating protein
Beatrice Charlotte Tröster +3 more
wiley +1 more source