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The objective of this paper is to communicate a proposed framework for addressing research limitations and communication barriers that contribute to a lack of data for making clinical treatment decisions about medication use in pregnancy. To address this global public health concern, a cross-stakeholder coalition composed of several workstreams is proposed. The intent is to foster collaborative discussion regarding potential solutions to address gaps in communication, engagement, and data generation and collection. Topic areas that require focus include development of awareness initiatives, cultural transformation efforts, collaboration initiatives, research standards, data compilation projects, and new data capture methods. Objectives to aid these efforts are outlined, and collaboration among researchers, regulators, health care providers, and patients is emphasized.
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http://dx.doi.org/10.1177/2168479014522469 | DOI Listing |
Genome Biol
September 2025
Center for Genomic Medicine, Cardiovascular Research Center, , Massachusetts General Hospital Simches Research Center, 185 Cambridge Street, CPZN 5.238,, Boston, MA, 02114, USA.
Background: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.
View Article and Find Full Text PDFEnviron Manage
September 2025
TEMSUS Research Group, Catholic University of Ávila, Ávila, Spain.
Forests have been increasingly affected by natural disturbances and human activities. These impacts have caused habitat fragmentation and a loss of ecological connectivity. This study examines potential restoration pathways that reconnect the five largest forest cores in the Castilla y León region of Spain.
View Article and Find Full Text PDFAnn Biomed Eng
September 2025
Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey.
Purpose: The design and development of ventricular assist devices have heavily relied on computational tools, particularly computational fluid dynamics (CFD), since the early 2000s. However, traditional CFD-based optimization requires costly trial-and-error approaches involving multiple design cycles. This study aims to propose a more efficient VAD design and optimization framework that overcomes these limitations.
View Article and Find Full Text PDFLight Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
View Article and Find Full Text PDFSci Rep
September 2025
Fukushima Renewable Energy Institute, Koriyama, Japan.
Ultra-fast charging stations (UFCS) present a significant challenge due to their high power demand and reliance on grid electricity. This paper proposes an optimization framework that integrates deep learning-based solar forecasting with a Genetic Algorithm (GA) for optimal sizing of photovoltaic (PV) and battery energy storage systems (BESS). A Gated Recurrent Unit (GRU) model is employed to forecast PV output, while the GA maximizes the Net Present Value (NPV) by selecting optimal PV and BESS sizes tailored to weekday and weekend demand profiles.
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