A rat–human scale-up procedure for the endocrine system

Campetelli, Germán; Lombarte, Mercedes; Biset, Hernan; Rigalli, Alfredo; Basualdo, Marta

doi:10.1016/j.compchemeng.2014.09.015

Cited by 2 publications

(2 citation statements)

References 17 publications

(15 reference statements)

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“…While the physiology of rats is different from humans, research has shown that the endocrine systems of diabetic Sprague-Dawley (SD) rats can be scaled up to be comparable to humans (28). Since the ZDSD rats are closely related to the SD strain, it seems reasonable to assume that the endocrine systems are similar.…”

Section: Discussionmentioning

confidence: 99%

Modeling the Disease Progression from Healthy to Overt Diabetes in ZDSD Rats

Choy

Winter

Karlsson

et al. 2016

AAPS J

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Studying the critical transitional phase between healthy to overtly diabetic in type 2 diabetes mellitus (T2DM) is of interest, but acquiring such clinical data is impractical due to ethical concerns and would require a long study duration. A population model using Zucker diabetic Sprague-Dawley (ZDSD) rats was developed to describe this transition through altering insulin sensitivity (IS, %) as a result of accumulating excess body weight and β-cell function (BCF, %) to affect glucose-insulin homeostasis. Body weight, fasting plasma glucose (FPG), and fasting serum insulin (FSI) were collected biweekly over 24 weeks from ZDSD rats (n = 23) starting at age 7 weeks. A semi-mechanistic model previously developed with clinical data was adapted to rat data with BCF and IS estimated relative to humans. Non-linear mixed-effect model estimation was performed using NONMEM. Baseline IS and BCF were 41% compared to healthy humans. BCF was described with a non-linear rise which peaked at 14 weeks before gradually declining to a negligible level. A component for excess growth reflecting obesity was used to affect IS, and a glucose-dependent renal effect exerted a two- to sixfold increase on the elimination of glucose. A glucose-dependent weight loss effect towards the end of experiment was implemented. A semi-mechanistic model to describe the dynamics of glucose and insulin was successfully developed for a rat population, transitioning from healthy to advanced diabetes. It is also shown that weight loss can be modeled to mimic the glucotoxicity phenomenon seen in advanced hyperglycemia.

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Section: Discussionmentioning

confidence: 99%

Modeling the Disease Progression from Healthy to Overt Diabetes in ZDSD Rats

Choy

Winter

Karlsson

et al. 2016

AAPS J

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“…The current work can be used to complement the study perform by Campetelli et al .,[ 28 ] which relation between a rat-human mathematical model for the endocrine system, will be useful to improve and explore more prediction tasks in discovering alterations in glands, with the advantage of decrease test in animals.…”

Section: Discussionmentioning

confidence: 99%

Prediction of endocrine system affectation in fisher 344 rats by food intake exposed with malathion, applying naïve bayes classifier and genetic algorithms

2016

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Background:Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion.Methods:It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#.Results:There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months.Conclusions:The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands.

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A rat–human scale-up procedure for the endocrine system

Cited by 2 publications

References 17 publications

Modeling the Disease Progression from Healthy to Overt Diabetes in ZDSD Rats

Modeling the Disease Progression from Healthy to Overt Diabetes in ZDSD Rats

Prediction of endocrine system affectation in fisher 344 rats by food intake exposed with malathion, applying naïve bayes classifier and genetic algorithms

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