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Direct Use of Plasma or Milk Vitamin A Specific Activity Data to Model Retinol Kinetics and Predict Vitamin A Stores in Theoretical Lactating Women. | LitMetric

Direct Use of Plasma or Milk Vitamin A Specific Activity Data to Model Retinol Kinetics and Predict Vitamin A Stores in Theoretical Lactating Women.

J Nutr

Department of Nutritional Sciences, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA.

Published: January 2023

AI Article Synopsis

  • The study aimed to adapt existing vitamin A modeling techniques to assess vitamin A levels in lactating women, addressing challenges related to estimating breast milk pool sizes.
  • Researchers simulated data for vitamin A in both plasma and breast milk over 49 days after administering a labeled dose to analyze compartmental vitamin A dynamics.
  • Results indicated that using specific activity data from plasma and/or milk accurately predicted total body stores and the relevant scaling coefficient, suggesting a simplified approach for future studies in lactating women.

Article Abstract

Background: Many applications of the Simulation, Analysis and Modeling software use data on the fraction of an orally administered tracer dose (FD) in plasma; thus, researchers must scale-up measured analyte concentration to the total plasma pool. For studies in lactating women, estimating breast milk pool size is challenging.

Objectives: The objectives were to determine whether the standard vitamin A modeling approach using FD data could be modified to use vitamin A specific activity in milk (SAm) and/or plasma (SAp) for compartmental analysis of vitamin A kinetics and status in theoretical lactating women.

Methods: Using 12 previously studied theoretical subjects with a wide range of assigned values for vitamin A total body stores (TBS) and the coefficient ("FaS") needed to predict TBS using a retinol isotope dilution equation, we simulated data for SAp and SAm for 49 d after oral administration of labeled vitamin A. Then we modeled datasets for SAp and SAm, as well as only SAp or SAm, incorporating a linear scaling factor to automatically convert SA to FD and including several physiologically reasonable constraints as input data. As outcomes, we compared model-predicted TBS and FaS to assigned values.

Results: Scaling factors effectively adjusted SA data to adequately predict vitamin A mass in plasma and breast milk pools. Data for SAp and SAm provided model predictions of TBS that were comparable to assigned values (range: 85-107%); using only SAp, ratios ranged from 92% to 108% and for SAm from 85% to 108%. Parallel results were obtained for simulated FaS.

Conclusions: Results show that SA data from plasma and/or milk can be used directly for modeling vitamin A during lactation in theoretical subjects, providing accurate estimates of TBS and FaS. Results suggest that, in free-living lactating women, researchers might measure only SAp or only SAm and adequately describe whole-body vitamin A metabolism and status.

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Source
http://dx.doi.org/10.1093/jn/nxac229DOI Listing

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