Results 61 to 70 of about 5,186,076 (313)
Historiography of Science and History of Science
From the Editor Historiography of Science and History of ...
openaire +3 more sources
The History of Science Section and the Progress of Science [PDF]
n ...
openaire +4 more sources
Single‐cell insights into the role of T cells in B‐cell malignancies
Single‐cell technologies have transformed our understanding of T cell–tumor cell interactions in B‐cell malignancies, revealing new T‐cell subsets, functional states, and immune evasion mechanisms. This Review synthesizes these findings, highlighting the roles of T cells in pathogenesis, progression, and therapy response, and underscoring their ...
Laura Llaó‐Cid
wiley +1 more source
Winter 2017 - HIPS Newsletter [PDF]
https://nsuworks.nova.edu/cahss_hips_newsletter/1003/thumbnail ...
Department of History and Political Science
core +1 more source
Report on a Boston University Conference December 7-8, 2012 on 'How Can the History and Philosophy of Science Contribute to Contemporary U.S. Science Teaching?' [PDF]
This is an editorial report on the outcomes of an international conference sponsored by a grant from the National Science Foundation (NSF) (REESE-1205273) to the School of Education at Boston University and the Center for Philosophy and History of ...
Benétreau-Dupin, Yann, Garik, Peter
core +2 more sources
Journal of the History of Medicine and Allied Sciences [PDF]
Derrick Vail
openalex +2 more sources
In the adult T‐cell leukemia/lymphoma (ATL) cell line ED, the human T‐cell leukemia virus type 1 (HTLV‐1) provirus was integrated into the intron of the ift81 gene in the antisense orientation. Despite this integration, both the intact ift81 and the viral oncogene hbz were simultaneously expressed, likely due to the functional insufficiency of viral ...
Mayuko Yagi+5 more
wiley +1 more source
Fall 2017 - HIPS Newsletter [PDF]
https://nsuworks.nova.edu/cahss_hips_newsletter/1004/thumbnail ...
Department of History and Political Science
core +1 more source
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan+2 more
wiley +1 more source