Results 81 to 90 of about 428,742 (262)

Intrapatient tumour heterogeneity and clonal evolution in an autopsy study of metastatic salivary gland cancer

Molecular Oncology, EarlyView.
Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche, Niels J. van Ruitenbeek, Charlotte Adang, Luke O'Gorman, Pui Yuen Lee, Willemijn M. Klein, Adriana C. H. van Engen‐van Grunsven, Jack A. Schalken, Sander Bervoets, Gerald W. Verhaegh, Carla M. L. van Herpen   +10 more
wiley   +1 more source

Time–Frequency Parallel and Channel-Adaptive Gating for Multivariate Time Series Prediction

Applied Sciences
In real-world scenarios, multivariate time series data typically presents a variety of complex characteristics simultaneously, including long-term trends, multiple seasonality, sudden event disturbances and random noise. Owing to remarkable discrepancies
Xin He, Zhenwen He
doaj   +1 more source

Somatostatin receptor 4 (SSTR4) is a tumor suppressor in cutaneous and head & neck squamous cell carcinomas

Molecular Oncology, EarlyView.
This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi, Tuan Khang Huynh, Adway Kadam, Zahra Kardan, Yue Yan, Amina Jamal Laham, Sampath Kumar Loganathan   +6 more
wiley   +1 more source

DeepONet-Inspired Architecture for Efficient Financial Time Series Prediction

Mathematics
Financial time series prediction is a fundamental problem in investment and risk management. Deep learning models, such as multilayer perceptrons, Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM), have been widely used in modeling ...
Zeeshan Ahmad, Shudi Bao, Meng Chen
doaj   +1 more source

NAPRT loss promotes lung tumor initiation and growth through AKT signaling independently of NAD+ biosynthesis

Molecular Oncology, EarlyView.
Loss of NAPRT promotes lung tumor initiation and growth through a noncanonical mechanism, independent of its role in NAD+ biosynthesis. Mechanistically, NAPRT depletion activates the mTORC2‐driven AKT/β‐catenin signaling axis to enhance clonogenic and invasive phenotypes. Furthermore, lung‐specific Naprt deletion significantly increases tumor burden in
Myung Joon Oh, Ji Yun Jang, Yoon Jeon, Gi‐Cheon Kim, Hwanho Lee, Jooyoung Lee, Ju‐Hwa Kim, Hakhyun Kim, Minjee Kim, Ho‐Keun Kwon, Ho Lee, Hyun Seok Kim   +11 more
wiley   +1 more source

CNN-Based Time Series Decomposition Model for Video Prediction

IEEE Access
Video prediction presents a formidable challenge, requiring effectively processing spatial and temporal information embedded in videos. While recurrent neural network (RNN) and transformer-based models have been extensively explored to address spatial ...
Jinyoung Lee, Gyeyoung Kim
doaj   +1 more source

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Molecular characterization of covRS mutations in M1UK Streptococcus pyogenes

FEBS Open Bio, EarlyView.
Group A Streptococcus (GAS) acquires covRS mutations driving a hypervirulent bacterial state, frequently associated with invasive disease‐like necrotizing fasciitis. We demonstrate that the newly emerged M1UK GAS lineage can also acquire these mutations.
Jarrad Pritchard, Emma‐Jayne Proctor, Jiawa Wang, Nikolas P. Johnston, Andrew Hayes, Georgia McCorkell, Haibo Yu, Jai Tree, Mark R. Davies, Mark J. Walker, Ronald Sluyter, Stephan Brouwer, Martina L. Sanderson‐Smith   +12 more
wiley   +1 more source

MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis

FEBS Open Bio, EarlyView.
MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss, Ao Li, Eduardo H. Gilglioni, Mayank Bansal, Sumeet Pal Singh, Latifa Bakiri, Alessandra K. Cardozo, Esteban N. Gurzov   +7 more
wiley   +1 more source