Testing the leanocentric locking-point theory by in silico partial lipectomy

Guanyu Wang

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PDF(914 KB)
Quant. Biol. ›› 2021, Vol. 9 ›› Issue (1) : 73-83. DOI: 10.15302/J-QB-021-0233
RESEARCH ARTICLE
RESEARCH ARTICLE

Testing the leanocentric locking-point theory by in silico partial lipectomy

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Abstract

Background: The lipostatic set-point theory, ascribing fat mass homeostasis to leptin mediated central feedback regulation targeting the body’s fat storage, has caused a variety of conundrums. We recently proposed a leanocentric locking-point theory and the corresponding mathematical model, which not only resolve these conundrums but also provide valuable insights into weight control and health assessment. This paper aims to further test the leanocentric theory.

Methods: Partial lipectomy is a touchstone to test both the leanocentric and lipostatic theories. Here we perform in silico lipectomy by using a mathematical model embodying the leanocentric theory to simulate the long-term body fat change after removing some fat cells in the body.

Results: The mathematical modeling uncovers a phenomenon called post-surgical fat loss, which was well-documented in real partial lipectomy surgeries; thus, the phenomenon can serve as an empirical support to the leanocentric theory. On the other hand, the leanocentric theory, but not the lipostatic theory, can well explain the post-surgical fat loss.

Conclusions: The leanocentric locking-point theory is a promising theory and deserves further testing. Partial lipectomy surgeries are beneficial to obese patients for quite a long period.

Keywords

leanocentric locking-point theory / lipostatic set-point theory / weight stability / fat mass homeostasis / partial lipectomy

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Guanyu Wang. Testing the leanocentric locking-point theory by in silico partial lipectomy. Quant. Biol., 2021, 9(1): 73‒83 https://doi.org/10.15302/J-QB-021-0233

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ACKNOWLEDGMENTS

This work was partly supported by the National Natural Science Foundation of China (Nos. 61773196 and 32070681), 2019 Key Projects of Ministry of Science and Technology of China (No. 2019YFA09006000), Guangdong Provincial Key Laboratory of Computational Science and Material Design (No. 2019B030301001), and Shenzhen Research Funds (No. JCYJ20170817104740861), Shenzhen Peacock Plan (No. KQTD2016053117035204), and by Center for Computational Science and Engineering of Southern University of Science and Technology.

COMPLIANCE WITH ETHICS GUIDELINES

The author Guanyu Wang declare that they have no conflict of interests.
This article does not contain any studies with human or animal subjects performed by the authors.

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