Single‐cell transcriptomics of prostate cancer patient‐derived xenografts reveals distinct features of neuroendocrine (NE) subtypes. Tumours with focal NE differentiation (NED) share transcriptional programmes with adenocarcinoma, differing from large and small cell neuroendocrine prostate cancer (NEPC). Our work defines the molecular landscape of NEPC,
Rosalia Quezada Urban+12 more
wiley +1 more source
Natural and artifical acclimatization to hot environments
R. F. Hellon+3 more
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Leveraging computer vision for predicting collision risks: a cross-sectional analysis of 2019-2021 fatal collisions in the USA. [PDF]
Nguyen QC+11 more
europepmc +1 more source
Decrypting cancer's spatial code: from single cells to tissue niches
Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik+4 more
wiley +1 more source
MORAL AND RELIGIOUS INFLUENCES AS RELATED TO ENVIRONMENT OF STUDENT LIFE. DORMITORY LIFE FOR COLLEGE WOMEN [PDF]
Marion Talbot
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Understanding Perceptions of the Postsimulation Debriefing Learning Environment in Paediatric Trainees. [PDF]
Hoolahan S, Breitbach A.
europepmc +1 more source
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts+8 more
wiley +1 more source
The Criminal: His Personnel and Environment . By August Drähms, with an introduction by C. Lombroso. New York, The Macmillan Co. 1900. 8vo. Pp. 402. [PDF]
Havelock Ellis
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UniROS: ROS-Based Reinforcement Learning Across Simulated and Real-World Robotics. [PDF]
Kapukotuwa J, Lee B, Devine D, Qiao Y.
europepmc +1 more source