The essay examines the scientific representations that unfolded and evolved at the University of Puerto Rico School of Tropical Medicine (STM) under the auspices of Columbia University (1926-1949). This article on the STM's scientific endeavors is the fourth in a historical serial collection about the images and evolution of sciences at the institution and it portrays the diagrammatic representations of special technical research aspects and studies (i.e., personnel, epidemiology, methodology, animal studies, biology, field studies, treatment and immunology, and chemotherapy agents). The essay focuses on the emerged scientific representations and on the nature and evolution of sciences at the School, and has been divided into four sections: a) images of science, b) evolution during the first two eras, c) the third and last era unfolding, and d) special technical studies. In this paper the scientific representations have been brought about mainly through the analyses of research publications in external and local venues. The analysis of the STM's scientific evolution has been organized in three distinct historical stages: 1926-31, 1932-40, and 1941-49. These representations open an exploration pathway for a better understanding of the intricate interrelationships between the techné and the episteme horizons of tropical medical science in Puerto Rico.
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J Med Internet Res
January 2025
Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.
View Article and Find Full Text PDFJCO Glob Oncol
January 2025
Department of Global Pediatric Medicine, St Jude Children's Research Hospital, Memphis, TN.
Purpose: The academic field of global pediatric oncology is expanding as cancer becomes increasingly recognized as a global health priority for children and adolescents. Here, we aimed to explore the representation of authors, the geographic distribution of research, and the research approaches being used in global pediatric oncology.
Methods: Articles published in () and on the topic of global pediatric oncology were analyzed.
Proc Natl Acad Sci U S A
February 2025
Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218.
The hippocampal dentate gyrus (DG) is thought to orthogonalize inputs from the entorhinal cortex (pattern separation) and relay this information to the CA3 region. In turn, attractor dynamics in CA3 perform a pattern completion or error correction operation before sending its output to CA1. In a mouse model of congenital hypoplasia of the DG, a deficiency in the (Wls) gene, specifically in cells expressing , which targets neuronal progenitors, led to an almost total absence of dentate granule cells and modestly impaired performance in spatial tasks.
View Article and Find Full Text PDFScience
January 2025
Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
Social animals live in groups and interact volitionally in complex ways. However, little is known about neural responses under such natural conditions. Here, we investigated hippocampal CA1 neurons in a mixed-sex group of five to 10 freely behaving wild Egyptian fruit bats that lived continuously in a laboratory-based cave and formed a stable social network.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
School of Software, Taiyuan University of Technology, Taiyuan, China.
Personalized cancer drug treatment is emerging as a frontier issue in modern medical research. Considering the genomic differences among cancer patients, determining the most effective drug treatment plan is a complex and crucial task. In response to these challenges, this study introduces the Adaptive Sparse Graph Contrastive Learning Network (ASGCL), an innovative approach to unraveling latent interactions in the complex context of cancer cell lines and drugs.
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