RADIATION RECOVERY STUDIES.

Abstract

A spectrum of biological responses for an experimental animal was studied with respect to changes in response patterns following subacute fractionated exposures to Co-60 irradiations. The objectives of these studies were to obtain experimental information and to develop methodologies for its retrieval for the purpose of making general inferences concerning recovery phenomena of mammals subjected to subacute doses of irradiation. A mathematical model was developed to describe time-dependent variations of the biological responses following fractionated exposures to radiations. The values of the parameters of the model are proposed to be functions of the degree of reparable and irreparable damage incurred by the system. The plausibility of the model, as evaluated by a visual comparison of the data and graphic displays of the model in terms of arbitrary values of the parameters is reasonably high. The biological end points studied included clinical hematology, body weights, food consumptions, and gross physiological observations. An evaluation of the usefulness to military commanders of simple LD-50/30-day statistics is made. The tentative conclusion reached is that they are of only slight value when applied to military personnel who will have completed their entire military responsibility within a 1-to-60-day period post-commencement of such application.

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1967
Accession Number
AD0815474

Entities

People

  • George M. Angleton

Organizations

  • Colorado State University

Tags

DTIC Thesaurus Topics

  • Animals
  • Body Weight
  • Hematology
  • Laboratory Animals
  • Mathematical Models
  • Medical Personnel
  • Military Commanders
  • Military Personnel
  • Models
  • Observation
  • Officer Personnel
  • Radiation
  • Recovery
  • Spectra
  • Statistics
  • Test And Evaluation

Readers

  • Computational Modeling and Simulation
  • Exercise and Sports Science.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference