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Deep Learning for Biomarker Discovery in Cancer Genomes.
bioRxiv
January 2025
Else Kroener Fresenius Center for Digital Health, University of Technology Dresden, Dresden, Germany.
Background: Genomic data is essential for clinical decision-making in precision oncology. Bioinformatic algorithms are widely used to analyze next-generation sequencing (NGS) data, but they face two major challenges. First, these pipelines are highly complex, involving multiple steps and the integration of various tools.
View Article and Find Full Text PDFDeep learning models reveal the link between dynamic brain connectivity patterns and states of consciousness.
Sci Rep
December 2024
BAOBAB Unit, NeuroSpin center, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Decoding states of consciousness from brain activity is a central challenge in neuroscience. Dynamic functional connectivity (dFC) allows the study of short-term temporal changes in functional connectivity (FC) between distributed brain areas. By clustering dFC matrices from resting-state fMRI, we previously described "brain patterns" that underlie different functional configurations of the brain at rest.
View Article and Find Full Text PDFDespite progress in youth involvement in mental health research, considerable gaps remain in our understanding, conceptualisation, and implementation of involving children and young people in this field. This Editorial Perspective reflects on how these gaps present challenges to our research practices and often serve as barriers to meaningfully involving youth voices and experiences into the research process. We take a critical perspective to recent advances in the field of youth involvement in mental health research, reflected by the studies included in this special issue, and highlight examples of good practice paving the way for more equitable and inclusive approaches.
View Article and Find Full Text PDFA fusion analytic framework for investigating functional brain connectivity differences using resting-state fMRI.
Front Neurosci
December 2024
Graduate Program in Cognitive Science, Yonsei University, Seoul, Republic of Korea.
Introduction: Functional magnetic resonance imaging (fMRI) data is highly complex and high-dimensional, capturing signals from regions of interest (ROIs) with intricate correlations. Analyzing such data is particularly challenging, especially in resting-state fMRI, where patterns are less identifiable without task-specific contexts. Nonetheless, interconnections among ROIs provide essential insights into brain activity and exhibit unique characteristics across groups.
View Article and Find Full Text PDFCell stretching devices integrated with live cell imaging: a powerful approach to study how cells react to mechanical cues.
Prog Biomed Eng (Bristol)
December 2024
Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, via Campi 213/A, 41125 Modena, Italy.
Mechanical stimuli have multiple effects on cell behavior, affecting a number of cellular processes including orientation, proliferation or apoptosis, migration and invasion, the production of extracellular matrix proteins, the activation and translocation of transcription factors, the expression of different genes such as those involved in inflammation and the reprogramming of cell fate. The recent development of cell stretching devices has paved the way for the study of cell reactions to stretching stimuli, reproducing physiological situations that are experienced by cells in many tissues and related to functions such as breathing, heart beating and digestion. In this work, we review the highly-relevant contributions cell stretching devices can provide in the field of mechanobiology.
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