Results 41 to 50 of about 314,053 (305)
Molecular Oncology, EarlyView.Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz +15 more
wiley +1 more source
Achieving Transfer from Mathematics Learning
Education Sciences, 2023 The question of transfer is a special challenge in mathematics teaching because the wide range and fragmentation of the curricula have in many cases fostered an instrumental understanding, which makes transfer difficult for the students. Although promoting a relational learning has been a huge step forward in achieving transfer, understanding usually ...
José Víctor Orón +1 more
openaire +4 more sources
Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
Deep Transfer Metric Learning [PDF]
IEEE Transactions on Image Processing, 2016 Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep
Junlin Hu +3 more
openaire +2 more sources
Dual targeting of RET and SRC synergizes in RET fusion‐positive cancer cells
Molecular Oncology, EarlyView.Despite the strong activity of selective RET tyrosine kinase inhibitors (TKIs), resistance of RET fusion‐positive (RET+) lung cancer and thyroid cancer frequently occurs and is mainly driven by RET‐independent bypass mechanisms. Son et al. show that SRC TKIs significantly inhibit PAK and AKT survival signaling and enhance the efficacy of RET TKIs in ...
Juhyeon Son +13 more
wiley +1 more source
Sports Teaching, Traditional Games, and Understanding in Physical Education: A Tale of Two Stories
Frontiers in Psychology, 2020 Unlike Dickens’s novel, this is not a tale of light and darkness, order and chaos, good and evil…It is, though, a story worth to be told about two standpoints about games and sports, teaching and research, physical education simply put, that have pursued
Raúl Martínez-Santos +3 more
doaj +1 more source
Transferable learning on analog hardware
Science Advances, 2023 While analog neural network (NN) accelerators promise massive energy and time savings, an important challenge is to make them robust to static fabrication error. Present-day training methods for programmable photonic interferometer circuits, a leading analog NN platform, do not produce networks that perform well in the presence of static hardware ...
Sri Krishna Vadlamani +2 more
openaire +3 more sources
Next‐generation proteomics improves lung cancer risk prediction
Molecular Oncology, EarlyView.This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj +4 more
wiley +1 more source
Geological time, biological events and the learning transfer problem
Journal of the Scholarship of Teaching and Learning, 2014 Comprehension of geologic time does not come easily, especially for students who are studying the earth sciences for the first time. This project investigated the potential success of two teaching interventions that were designed to help non-science ...
Claudia C Johnson +4 more
doaj +1 more source
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning [PDF]
, 2020 We propose a novel adaptive transfer learning framework, learning to transfer learn (L2TL), to improve performance on a target dataset by careful extraction of the related information from a source dataset. Our framework considers cooperative optimization of shared weights between models for source and target tasks, and adjusts the constituent loss ...
Zhu, Linchao +3 more
openaire +2 more sources