Aquatic monitoring programs vary widely in objectives and design. However, each program faces the unifying challenge of assessing conditions and quantifying reasonable expectations for measured indicators. A common approach for setting resource expectations is to define reference conditions that represent areas of least human disturbance or most natural state of a resource characterized by the range of natural variability across a region of interest. Identification of reference sites often relies heavily on professional judgment, resulting in varying and unrepeatable methods. Standardized methods for data collection, site characterization, and reference site selection facilitate greater cooperation among assessment programs and development of assessment tools that are readily shareable and comparable. We illustrate an example that can serve the broader global monitoring community on how to create a consistent and transparent reference network for multiple stream resource agencies. We provide a case study that offers a simple example of how reference sites can be used, at the landscape level, to link upslope management practices to a specific in-channel response. We found management practices, particularly areas with high road densities, have more fine sediments than areas with fewer roads. While this example uses data from only one of the partner agencies, if data were collected in a similar manner they can be combined and create a larger, more robust dataset. We hope that this starts a dialog regarding more standardized ways through inter-agency collaborations to evaluate data. Creating more consistency in physical and biological field protocols will increase the ability to share data.
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http://dx.doi.org/10.1007/s00267-016-0739-6 | DOI Listing |
PLoS One
January 2025
Lawrence Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada.
The world population is aging. Comprehensive Geriatric assessment (CGA) has been proven to improve the well-being of older adults. However, evidence suggests not all clinicians implement these recommendations in their practice; nor do all patients adhere to them.
View Article and Find Full Text PDFEur J Nutr
January 2025
Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.
Plant-based dietary patterns have been demonstrated to reduce the risk of non-communicable disease (NCD), including cardiovascular disease (CVD), type 2 diabetes, cancer, and all-cause mortality. Phenolic compounds (PC), abundant in plant-based foods, have been considered as instrumental in this attenuation of NCD risk. We evaluated the association between dietary intake of PC and the risk of all-cause mortality in a relatively young Mediterranean cohort of 18,173 Spanish participants in the "Seguimiento Universidad de Navarra" (SUN) project, after a median follow-up of 12.
View Article and Find Full Text PDFVaccines (Basel)
January 2025
Pharmaceutical Regulatory Affairs, Department of Pharmaceutical Industry, Graduate School, Chung-Ang University, Seoul 06974, Republic of Korea.
The emergence of more than 40 new infectious diseases since the 1980s has emerged as a serious global health concern, many of which are zoonotic. In response, many international organizations, including the US Centers for Disease Control and Prevention (CDC), the World Health Organization (WHO), and the European Center for Disease Prevention and Control (ECDC), have developed strategies to combat these health threats. The need for rapid vaccine development has been highlighted by Coronavirus disease 2019 (COVID-19), and mRNA technology has shown promise as a platform.
View Article and Find Full Text PDFTomography
January 2025
Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Objectives: Accurate kidney and tumor segmentation of computed tomography (CT) scans is vital for diagnosis and treatment, but manual methods are time-consuming and inconsistent, highlighting the value of AI automation. This study develops a fully automated AI model using vision transformers (ViTs) and convolutional neural networks (CNNs) to detect and segment kidneys and kidney tumors in Contrast-Enhanced (CECT) scans, with a focus on improving sensitivity for small, indistinct tumors.
Methods: The segmentation framework employs a ViT-based model for the kidney organ, followed by a 3D UNet model with enhanced connections and attention mechanisms for tumor detection and segmentation.
Trop Med Infect Dis
January 2025
National Reference Centre for Imported Tropical Diseases, Infectious Diseases Department, Hospital Universitario Ramón y Cajal, IRYCIS, 28034 Madrid, Spain.
Background: Chronic schistosomiasis can lead to significant morbidity. Serology is highly sensitive; however, its role in assessing treatment response is controversial. This study aimed to analyze serological values following treatment of chronic imported schistosomiasis.
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