Evidence map›Paper›PMID 41774806›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Stochasticity in mammalian cell growth rates drives cell-to-cell variability independently of cell size and divisions.

Ethan Levien, Joon Ho Kang, Kuheli Biswas, Scott R Manalis, Ariel Amir, Teemu P Miettinen

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

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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

6 authors.

Ethan Levien *Department of Mathematics, Dartmouth College, Hanover, NH 03755.ORCID 0000-0001-6825-2966
Joon Ho Kang *Department of Mechanical Engineering, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0000-0003-4165-7538
Kuheli BiswasDepartment of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel.ORCID 0000-0001-8123-4818
Scott R ManalisKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0001-5223-9433
Ariel AmirDepartment of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel.ORCID 0000-0003-2611-0139
Teemu P MiettinenKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0002-5975-200X

Funding

National Research Foundation of Korea (NRF) RS-2024-00342400Wellcome Trust (WT) 110275/Z/15/Z
6 · The paper itself

Abstract

Cell growth rates exhibit cell-intrinsic cell-to-cell variability, which influences cell fitness and size homeostasis from bacteria to cancer. It remains unclear whether this variability arises from stochasticity in cell growth or division processes, or from cell-size-dependent growth regulation. To separate these potential sources of growth variability, single-cell growth rates need to be examined across different timescales. Here, we study cell size and growth regulation by tracking lymphocytic leukemia cell mass accumulation with high precision and minute-scale temporal resolution along long ancestral lineages. We first show that correlations between growth rates and cell-size nor asymmetric divisions explain cell-to-cell growth variability. We then isolate growth fluctuations by smoothing and detrending the growth rate dynamics using a Gaussian process regression. We find that these growth fluctuations drive cell-to-cell growth variability within ancestral lineages despite being independent of cell divisions, cell cycle, and cell size. Overall, our results provide a quantitative framework for understanding single-cell growth rates, and indicate that cell-intrinsic long-term patterns in growth are a byproduct of short-term growth fluctuations.

Indexed as

Cell DivisionCell ProliferationCell SizeAnimalsCell CycleHumansModels, BiologicalSingle-Cell AnalysisStochastic Processescell divisionscell growthcell sizecellular noiseheterogeneity

Identifiers

PMID41774806
PMCPMC12974516

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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.