Evidence map›Paper›PMID 39935178›Full record

ArticleBiophysical journal2025

Stochastic analysis of human ovarian aging and menopause timing.

Anupam Mondal, Evelina Tcherniak, Anatoly B Kolomeisky

Abstract read
In one paragraph

Article in Biophysical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Anupam MondalCenter for Theoretical Biological Physics, Rice University, Houston, Texas; Department of Chemistry, Rice University, Houston, Texas.
Evelina TcherniakDepartment of Chemistry, Rice University, Houston, Texas.
Anatoly B KolomeiskyCenter for Theoretical Biological Physics, Rice University, Houston, Texas; Department of Chemistry, Rice University, Houston, Texas; Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas. Electronic address: tolya@rice.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Menopause marks a critically important biological event that ends a woman's fertility. It is a result of ovarian aging and depletion of ovarian reserve. Although many aspects of these processes are now well understood, the overall dynamic picture remains unclear. Here, we present a novel theoretical framework to analyze human ovarian aging dynamics and menopause timing. Our method is based on stochastic analysis of underlying processes stimulated by observing follicles sequentially transitioning between different stages during ovulation. This allows us to obtain a fully quantitative description of ovarian aging and menopause timing consistent with available experimental observations. Our model accurately predicts the average age of menopause across geographically diverse human populations. Theoretical analysis suggests a universal relation between the initial follicle reserve, the depletion rates, and the threshold that triggers menopause. In addition, it is found that the distributions of menopause times are quite narrow, and it is proposed that this might be a result of a precise regulation due to the synchronization of transitions between different stages of follicles. Our theoretical approach not only quantitatively explains the dynamics of human ovarian aging and menopause timing but also provides important insights into individual variability in ovarian aging. It can be used as a powerful tool for predicting menopause timing and investigating complex processes of reproductive aging.

Indexed as

AgingMenopauseModels, BiologicalOvaryAdultFemaleHumansMiddle AgedOvarian FollicleStochastic ProcessesTime Factors

Identifiers

PMID39935178
PMCPMC11993922

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.