Results 71 to 80 of about 49,884 (221)

Knowledge-enhanced graph transformer with contrastive learning for drug-drug interaction prediction

Machine Learning with Applications
Background: Adverse drug-drug interactions (DDIs) remain a critical public health concern, responsible for approximately 125,000 deaths annually in the United States and accounting for nearly 30% of all adverse drug events.
Masoud Amiri, Bahador Makkiabadi
doaj   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source

Exploratory mixed-methods analysis of the determinants of use of health research evidence among planning teams in Tanzania

BMJ Open
Introduction Achieving universal health coverage requires the use of health research evidence in decision-making; however, this remains understudied in lower and middle-income countries (LMICs) such as Tanzania.
Albino Kalolo, Pius Kagoma, Richard Mongi   +2 more
doaj   +1 more source

Stimulator of interferon genes agonist augmented antitumor immunity of osimertinib in Egfr‐mutated lung cancer

Molecular Oncology, EarlyView.
Combining osimertinib with the STING agonist ADU‐S100 activates innate and adaptive immunity to overcome the non‐inflamed microenvironment of Egfr‐mutant lung cancer. This combination increases NK and CD8+ T‐cell infiltration, associated with activation of the STING‐IRF3 pathway and local immunogenic cell death.
Jun Nishimura, Tadahiro Kuribayashi, Johannes Brägelmann, Sachi Okawa, Masataka Taoka, Shunta Mori, Tomoka Nishimura, Takaaki Tanaka, Go Makimoto, Kiichiro Ninomiya, Kammei Rai, Eiki Ichihara, Ryohei Katayama, Katsuyuki Hotta, Masahiro Tabata, Yosuke Togashi, Yoshinobu Maeda, Martin L. Sos, Katsuyuki Kiura, Kadoaki Ohashi   +19 more
wiley   +1 more source

An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids

Energies
The increasing complexity of modern smart power distribution systems (SPDSs) has made anomaly detection a significant challenge, as these systems generate vast amounts of heterogeneous and time-dependent data.
Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami   +4 more
doaj   +1 more source

Loss of IGF‐1R impairs DNA‐PKcs recruitment to chromatin leading to defective end‐joining

Molecular Oncology, EarlyView.
IGF‐1R promotes radioresistance by facilitating DNA‐PKcs recruitment to chromatin, enabling non‐homologous end‐joining (NHEJ) repair of double‐strand breaks. Inhibition or loss of IGF‐1R disrupts this recruitment to damage sites, driving compensatory reliance on microhomology‐mediated end‐joining (MMEJ) repair.
Matthew O. Ellis, Jack V. Mills, Wojciech Niedzwiedz, Valentine M. Macaulay   +3 more
wiley   +1 more source

Conducting water-energy-food nexus studies: what, why, and how

Scientific Reports
The increasing pressure on resources and the persistent failure to address global malnutrition are evident challenges. A significant contributing factor is the decline in the quality of production resources, particularly water.
Ebrahim Farmandeh, Shahla Choobchian, Shobeir Karami   +2 more
doaj   +1 more source

COLLT: A Multi-Task Optimization Framework for Clarification-Oriented Tool Learning in Legal Large Language Models

Mathematics
Tool-augmented Large Language Models (LLMs) have demonstrated remarkable capabilities in language understanding and generation across various domains, with notable progress in legal applications.
Kaixin Yang, Jingyun Sun, Zhenxing Wang, Chang Xu   +3 more
doaj   +1 more source

Finding novel vulnerabilities of hypomorphic BRCA1 alleles

Molecular Oncology, EarlyView.
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder, Klaas de Lint, Hồ Mỹ Phúc Võ, Mariana M. Góis, Rosalie A. Kampen, Marta San Martin Alonso, Ilse Nootenboom, Veronica Garzero, Tiemen J. Wendel, Rob M. F. Wolthuis, Sylvie M. Noordermeer   +10 more
wiley   +1 more source

An Interpretable Stacked Deep Learning Model for Diagnosis of Brain Tumor with Transparent Learning Dynamics

Machine Learning and Knowledge Extraction
The diagnosis and treatment planning for brain tumors remain a complex task in medical imaging, largely due to the intricate structure of such abnormalities.
K. Kaivalya, N. Thirupathi Rao, Aditya Pal, Hari Mohan Rai, B. Omkar Lakshmi Jagan   +4 more
doaj   +1 more source