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Exploring the Role of Immersive Virtual Reality Simulation in Health Professions Education: Thematic Analysis.
JMIR Med Educ
March 2025
Division of Pulmonary, Critical Care, & Sleep Medicine, Department of Medicine, NYU Grossman School of Medicine, 550 First Avenue, 15th Floor, Medical ICU, New York, NY, 10016, United States, 1 2122635800.
Background: Although technology is rapidly advancing in immersive virtual reality (VR) simulation, there is a paucity of literature to guide its implementation into health professions education, and there are no described best practices for the development of this evolving technology.
Objective: We conducted a qualitative study using semistructured interviews with early adopters of immersive VR simulation technology to investigate use and motivations behind using this technology in educational practice, and to identify the educational needs that this technology can address.
Methods: We conducted 16 interviews with VR early adopters.
In vitro maturation of oocytes (IVM): historical landmarks, current status and future perspectives.
Syst Biol Reprod Med
December 2025
Laboratory of Histology and Embryology, Aristotle University Medical School, Thessaloniki, Greece.
One of the major advancements in fertilization (IVF) has been the development of culture media that enhance gamete maturation and sustain embryo development up to the blastocyst stage. The deep understanding of the mechanisms involved in gametogenesis and the complex sequence of events surrounding nuclear and cytoplasmic maturation has also enabled the development of efficient maturation (IVM) protocols. This review outlines the major landmarks in the history of maturation of oocytes, the advantages and importance of its clinical application in human, especially in patients with Polycystic Ovary Syndrome (PCOS), Resistant Ovary Syndrome, high antral follicle count or oncology patients, as well as the safety and efficacy of the technique.
View Article and Find Full Text PDFRapid Authentication of Plant-Based Milk Alternatives by Coupling Portable Raman Spectroscopy with Machine Learning.
J AOAC Int
March 2025
Department of Chemistry, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, K1S 5B6 Canada.
Background: Plant-based milk alternatives (PBMA) are increasingly popular due to rising lactose intolerance and environmental concerns over traditional dairy products. However, limited efforts have been made to develop rapid authentication methods to verify their biological origin.
Objective: In this study, we developed a rapid, on-site analytical method for the authentication and identification of PBMA made by six different plant species utilizing a portable Raman spectrometer coupled with machine learning.
Assisted Reproductive Technologies in Latin America: the Latin American Registry, 2021.
JBRA Assist Reprod
March 2025
IVI Panama, Ciudad de Panama, Panama.
Research Question: What are the trends and impact of new technologies on the effectiveness and safety of assisted reproductive technology (ART) performed in Latin America during 2021?
Design: This was a retrospective collection of cycle-based multinational data obtained from ART procedures performed by 204 accredited institutions in 16 countries.
Results: In total 127,351 initiated cycles resulted in 20,032 deliveries and 22,708 births. ART utilization showed great variability, from 623.
Research and analysis of differential gene expression in CD34 hematopoietic stem cells in myelodysplastic syndromes.
PLoS One
March 2025
Department of Hematology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi Medical College, Changzhi, Shanxi, China.
Objective: This study aims to investigate and analyze the differentially expressed genes (DEGs) in CD34 + hematopoietic stem cells (HSCs) from patients with myelodysplastic syndromes (MDS) through bioinformatics analysis, with the ultimate goal of uncovering the potential molecular mechanisms underlying pathogenesis of MDS. The findings of this study are expected to provide novel insights into clinical treatment strategies for MDS.
Methods: Initially, we downloaded three datasets, GSE81173, GSE4619, and GSE58831, from the public Gene Expression Omnibus (GEO) database as our training sets, and selected the GSE19429 dataset as the validation set.
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