Results 101 to 110 of about 3,393,857 (266)

Proof of Credibility: A Blockchain Approach for Detecting and Blocking Fake News in Social Networks

International Journal of Advanced Computer Science and Applications, 2019
Rumors and misleading information detection and prevention still represent a big challenge against social network developers and researchers. Since newsworthy information propagation is a traditional behavior of most of the users in social media, then ...
M. Torky, Emad Nabil, Wael Said
semanticscholar   +1 more source

Time, the final frontier

Molecular Oncology, EarlyView.
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain, Michal Dibus, Omkar Joshi, Guillaume Jacquemet   +3 more
wiley   +1 more source

Inhibitor of DNA binding‐1 is a key regulator of cancer cell vasculogenic mimicry

Molecular Oncology, EarlyView.
Elevated expression of transcriptional regulator inhibitor of DNA binding 1 (ID1) promoted cancer cell‐mediated vasculogenic mimicry (VM) through regulation of pro‐angiogenic and pro‐cancerous genes (e.g. VE‐cadherin (CDH5), TIE2, MMP9, DKK1). Higher ID1 expression also increased metastases to the lung and the liver.
Emma J. Thompson, Emma L. Dorward, Kristyn Jurrius, Nathalie Nataren, Markus Tondl, Kay K. Myo Min, Michaelia P. Cockshell, Anahita Fouladzadeh, John Toubia, Mark DeNichilo, Delphine Merino, Claudine S. Bonder   +11 more
wiley   +1 more source

Chemoresistome mapping in individual breast cancer patients unravels diversity in dynamic transcriptional adaptation

Molecular Oncology, EarlyView.
This study used longitudinal transcriptomics and gene‐pattern classification to uncover patient‐specific mechanisms of chemotherapy resistance in breast cancer. Findings reveal preexisting drug‐tolerant states in primary tumors and diverse gene rewiring patterns across patients, converging on a few dysregulated functional modules. Despite receiving the
Maya Dadiani, Gilgi Friedlander, Gili Perry, Nora Balint‐Lahat, Shlomit Gilad, Dana Morzaev‐Sulzbach, Anjana Shenoy, Noa Bossel Ben‐Moshe, Anya Pavlovsky, Rinat Bernstein‐Molho, Eytan Domany, Iris Barshack, Tamar Geiger, Bella Kaufman, Einav Nili Gal‐Yam   +14 more
wiley   +1 more source

Tonic signaling of the B‐cell antigen‐specific receptor is a common functional hallmark in chronic lymphocytic leukemia cell phosphoproteomes at early disease stages

Molecular Oncology, EarlyView.
B‐cell chronic lymphocytic leukemia (B‐CLL) and monoclonal B‐cell lymphocytosis (MBL) show altered proteomes and phosphoproteomes, analyzed using mass spectrometry, protein microarrays, and western blotting. Identifying 2970 proteins and 316 phosphoproteins, including 55 novel phosphopeptides, we reveal BCR and NF‐kβ/STAT3 signaling in disease ...
Paula Díez, Pablo Juanes‐Velasco, Marina L. García‐Vaquero, Conrad Droste, Alicia Landeira‐Viñuela, Miguel Alcoceba, Helena Fidalgo‐Gómez, Sara Misiego‐Herrero, Almudena Navarro‐Bailón, Mónica Baile, José M. Bastida, Jose Manuel Sanchez‐Santos, Rafael Góngora, Julia Almeida, Marcos Gonzalez‐Diaz, Alberto Orfao, Javier De Las Rivas, Manuel Fuentes   +17 more
wiley   +1 more source

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 more
wiley   +1 more source

Digital Light Processing of 2D Lattice Composites for Tunable Self‐Sensing and Mechanical Performance

Advanced Engineering Materials, EarlyView., 2023
The study presents the mechanical and in situ sensing performance of digital light processing‐enabled 2D lattice nanocomposites under monotonic tensile and repeated cyclic loading, and provides guidelines for the design of architectures suitable for strain sensors and smart lightweight structures.
Omar Waqas Saadi, Mohammed Ayaz Uddin, Andreas Schiffer, Shanmugam Kumar   +3 more
wiley   +1 more source

METTL3 knockout accelerates hepatocarcinogenesis via inhibiting endoplasmic reticulum stress response

FEBS Open Bio, EarlyView.
Liver‐specific knockout of N6‐methyladenosine (m6A) methyltransferase METTL3 significantly accelerated hepatic tumor initiation under various oncogenic challenges, contrary to the previously reported oncogenic role of METTL3 in liver cancer cell lines or xenograft models. Mechanistically, METTL3 deficiency reduced m6A deposition on Manf transcripts and
Bo Cui, Silin Tu, Haibo Li, Zhancheng Zeng, Ruiqi Xiao, Jing Guo, Xiaoqi Liang, Chang Liu, Lijie Pan, Wenjie Chen, Mian Ge, Xiaofen Zhong, Linsen Ye, Huaxin Chen, Qi Zhang, Yan Xu   +15 more
wiley   +1 more source

Investigation of the Uniformity of Gel Shrinkage by Imaging Tracer Particles Using X‐Ray Microtomography

Advanced Engineering Materials, EarlyView., 2023
A novel method for tracking structural changes in gels using widely accessible microcomputed tomography is presented and validated for various hydro‐, alco‐, and aerogels. The core idea of the method is to track positions of micrometer‐sized tracer particles entrapped in the gel and relate them to the density of the gel network.
Anja Hajnal, Mimololorun Lucy Aiyelari, Martin Dirauf, Pavel Gurikov   +3 more
wiley   +1 more source

Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks [PDF]

arXiv
This article introduces Perception-Informed Neural Networks (PrINNs), a framework designed to incorporate perception-based information into neural networks, addressing both systems with known and unknown physics laws or differential equations. Moreover, PrINNs extend the concept of Physics-Informed Neural Networks (PINNs) and their variants, offering a
arxiv