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K A Lathrop

Publications and source records attributed to K A Lathrop.

10 recordsLinked to original sources

Nuclear imaging analysis of human low-density lipoprotein biodistribution in rabbits and monkeys.

We have evaluated the biodistribution of human low-density lipoprotein (LDL) radiolabeled with 99mTc or with 123I-tyramine cellobiose in rabbits and in rhesus monkeys. Biodistribution was assessed after intravenous injection of radiolabeled LDL by quantitative analysis of scintigrams, counting of excreta, and counting of tissues at necropsy. Both rabbits and monkeys showed lower renal uptake (123I:99mTc approximately 1:3, as regional percent injected activity corrected for physical decay) and excretion (1:2 to 1:4), but higher hepatic (1.5:1 to 2:1) and cardiac (1.7:1 to 4:1) uptake of 123I than of 99mTc. Adrenals were visualized in normolipemic animals with 123I-tyramine cellobiose-LDL but not with 99mTc-LDL. Hyperlipemic animals showed increased cardiac (up to six-fold) and decreased hepatic activity (by 50%-60%) of both radionuclides. We conclude that 123I-tyramine cellobiose-LDL is better suited than 99mTc-LDL for dynamic studies of LDL metabolism in vivo.

Animals↗

Multiparameter extrapolation of biodistribution data between species.

Values of an inaccessible biological parameter in man may be predicted from values measured in animals by correlating with a parameter accessible in both species, such as body weight, energy production, excretion rate, etc. Predicting toxic effects, from environmental chemicals, of therapeutic doses for drug administration and of radiation absorbed dose from medical and environmental radioactivity depends on the rationalization of relationships between concentration and time when scaling to humans from animal data. For example, the retention of 99mTc, injected intravenously as pertechnetate, reaches 10% in the mouse at about 1 d, but this level occurs in humans at about 7 d. Making a simultaneous transformation between two species for the concentration and time variables by using a method of least-squares fitting, we have derived a series of transformation factors for several species. When correlated with a biological parameter such as body weight, these factors can be used to yield predicted values that are in good agreement with measured values. This system may be used with any related variables, making it useful for predicting other types of biological data.

Animals↗