Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452136 | PMC |
| http://dx.doi.org/10.1093/noajnl/vdac139 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Automated scoring to assess RAD51-mediated homologous recombination in ovarian patient-derived tumor organoids.
Lab Invest
January 2025
Université de Caen Normandie, INSERM U1086 ANTICIPE, Caen, France; UNICANCER, Comprehensive Cancer Center François Baclesse, Caen, France; Université de Caen Normandie, US PLATON- ORGAPRED core facility, Caen, France; Université de Caen Normandie, US PLATON, UNICANCER, Comprehensive Cancer Center François Baclesse- Biological Resource Center 'OvaRessources', Caen, France. Electronic address:
PARP inhibitors (PARPi) have been shown to improve progression-free survival, particularly in homologous recombination deficient (HRD) ovarian cancers. Identifying patients eligible to PARPi is currently based on next-generation sequencing (NGS), but the persistence of genomic scars in tumors after restoration of HR or epigenetic changes can be a limitation. Functional assays could thus be used to improve this profiling and faithfully identify HRD tumors.
View Article and Find Full Text PDFAssessing learning, behaviour, and stress level in goats while testing a virtual fencing training protocol.
Animal
December 2024
Venn Research Association for the Promotion of Virtual Fencing in Tyrol and the Alpine region. Brixnerstraße 1, 6020 Innsbruck, Austria.
Virtual fencing (VF) is a modern fencing technology using Global Positioning System-enabled collars which emit acoustic signals and, if the animal does not respond, electric pulses. Studies with cattle indicate successful learning and no distinct negative impact on the animals' behaviours and stress level. However, the number of studies testing VF with goats is relatively small.
View Article and Find Full Text PDFSupporting rotational grazing systems with virtual fencing: paddock transitions, beef heifer performance, and stress response.
Animal
December 2024
Department of Crop Sciences, Grassland Science, Georg-August-University Göttingen, Von-Siebold-Strasse 8, 37075 Göttingen, Germany; Centre for Biodiversity and Sustainable Land Use, Büsgenweg 1, 37075 Göttingen, Germany.
Animal welfare is integral to sustainable livestock production, and pasture access for cattle is known to enhance welfare. Despite positive welfare impacts, high labour requirements hinder the adoption of sustainable grazing practices such as rotational stocking management. Virtual fencing (VF) is an innovative technology for simplified, less laborious grazing management and remote animal monitoring, potentially facilitating the expansion of sustainable livestock production.
View Article and Find Full Text PDFA study on how to improve students' continuance intention in landscape architecture conservation course within a virtual learning environment based on SVVR.
Acta Psychol (Amst)
January 2025
Department of Culture and Arts Management, Honam University, 62399 Gwangju, South Korea. Electronic address:
With the rapid pace of global urbanization, preserving natural landscapes has become increasingly critical. However, urbanization presents significant environmental risks worsened by decreased ecological consciousness. This has led to a pressing demand for education in landscape conservation.
View Article and Find Full Text PDFA multiscale molecular structural neural network for molecular property prediction.
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!