Recent advances in cancer biology and therapeutics have underscored the importance of preclinical models in understanding and treating cancer. Nevertheless, current models often fail to capture the complexity and patient-specific nature of human tumors, particularly gliomas. This review examines the strengths and weaknesses of such models, highlighting the need for a new generation of models. Emphasizing the critical role of the tumor microenvironment, tumor, and patient heterogeneity, we propose integrating our advanced understanding of glioma biology with innovative bioengineering and AI technologies to create more clinically relevant, patient-specific models. These innovations are essential for improving therapeutic development and patient outcomes.
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http://dx.doi.org/10.1084/jem.20220808 | DOI Listing |
JMIR Mhealth Uhealth
January 2025
Department of Learning and Workforce Development, The Netherlands Organisation for Applied Scientific Research, Soesterberg, Netherlands.
Background: Wearable sensor technologies, often referred to as "wearables," have seen a rapid rise in consumer interest in recent years. Initially often seen as "activity trackers," wearables have gradually expanded to also estimate sleep, stress, and physiological recovery. In occupational settings, there is a growing interest in applying this technology to promote health and well-being, especially in professions with highly demanding working conditions such as first responders.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
INSERM U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 30 Bd Jean Monnet, Nantes, 44093, France, 33 2 40 08 74 10.
Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of a medical "digital twin" has recently become popular to designate digital representations of patients as a support for a wide range of data science applications. However, the concept is ambiguous when it comes to practical implementations.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
Methods: We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database.
J Sports Sci
January 2025
Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Sogndal, Norway.
Multivariate pattern analysis was recently extended with covariate projections to solve the challenging task of modelling and interpreting associations in the presence of linear dependent multivariate covariates. Within a joint model, this approach allows quantification of the net association pattern between the outcome and the explanatory variables and between the individual covariates and these variables. The aim of this paper is to apply this methodology to establish the net multivariate association pattern between cardiorespiratory fitness (CRF) and a high-resolution linear dependent physical activity (PA) intensity descriptor derived from accelerometry in children and to validate the crucial sub-regions in the PA spectrum predicting CRF.
View Article and Find Full Text PDFConfl Health
January 2025
London School of Hygiene and Tropical Medicine, Department of Non-Communicable Diseases Epidemiology, Keppel street, London, WC1E 7HT, UK.
Background: Non-communicable diseases (NCDs) are the leading cause of death globally, and many humanitarian crises occur in countries with high NCD burdens. Peer support is a promising approach to improve NCD care in these settings. However, evidence on peer support for people living with NCDs in humanitarian settings is limited.
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