ArticleRadiation research2022
Animal Care in Radiation Medical Countermeasures Studies.
Article in Radiation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Breaking through the radiation dilemma: development and clinical translation of anti-radiation drugs.Pharmaceutical science advances · 2026Review
- Advancing the 3Rs in bone tissue engineering: emergingFrontiers in physiology · 2026Review
- Host microbiome depletion attenuates biofluid metabolite responses following radiation exposure.PloS one · 2024Article
- Impact of a Short-Term High-Fat Diet on Lifespan and Tumorigenesis After Early-Life Exposure to Radiation.Dose-response : a publication of International Hormesis SocietyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Animal models are necessary to demonstrate the efficacy of medical countermeasures (MCM) to mitigate/treat acute radiation syndrome and the delayed effects of acute radiation exposure and develop biodosimetry signatures for use in triage and to guide medical management. The use of animal models in radiation research allows for the simulation of the biological effects of exposure in humans. Robust and well-controlled animal studies provide a platform to address basic mechanistic and safety questions that cannot be conducted in humans. The U.S. Department of Health and Human Services has tasked the National Institute of Allergy and Infectious Diseases (NIAID) with identifying and funding early- through advanced-stage MCM development for radiation-induced injuries; and advancement of biodosimetry platforms and exploration of biomarkers for triage, definitive dose, and predictive purposes. Some of these NIAID-funded projects may transition to the Biomedical Advanced Research and Development Authority (BARDA), a component of the Office of the Assistant Secretary for Preparedness and Response in the U.S. Department of Health and Human Services, which is tasked with the advanced development of MCMs to include pharmacokinetic, exposure, and safety assessments in humans. Guided by the U.S. Food and Drug Administration's (FDA) Animal Rule, both NIAID and BARDA work closely with researchers to advance product and device development, setting them on a course for eventual licensure/approval/clearance of their approaches by the FDA. In August 2020, NIAID partnered with BARDA to conduct a workshop to discuss currently accepted animal care protocols and examine aspects of animal models that can influence outcomes of studies to explore MCM efficacy for potential harmonization. This report provides an overview of the two-day workshop, which includes a series of special topic presentations followed by panel discussions with subject-matter experts from academia, industry partners, and select governmental agencies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.