Evidence map›Paper›PMID 42782446›Full record

ReviewAdvances in experimental medicine and biology2026

Physical Frameworks and Theories on How Autonomous Biological Oscillators Synchronize.

Fabio Echegaray-Iturra, Evelyn Tang

Abstract readReview
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In one paragraph

Review in Advances in experimental medicine and biology, 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

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

2 authors.

Fabio Echegaray-IturraDepartment of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA.
Evelyn TangCenter for Theoretical Biological Physics and the Department of Physics and Astronomy, Rice University, Houston, TX, USA. e.tang@rice.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rhythms and oscillations are widely observed in biological systems. However, it is unclear how such noisy systems can produce robust and consistent timing, or how individual molecules or time-keeping systems couple together to produce macroscopically observable rhythms. Here, we focus on the synchronization of oscillatory processes at different scales: from the sub-cellular to the cellular and intercellular levels. Using examples from the circadian rhythms in cyanobacteria, cell cycle in eukaryotes, the firing of neurons, and from other emerging findings on the frontier of autonomous clocks, we discuss different paradigms of coupling or entrainment. We then highlight different methods of analysis from deterministic to stochastic approaches. Specifically, we discuss methods to quantify synchronization and its possible physical mechanisms, as well as prevailing mathematical models. Lastly, we close with a discussion of suggestions for new experiments or theoretical investigation.

Indexed as

Biological ClocksCircadian RhythmModels, BiologicalAnimalsCell CycleCyanobacteriaHumansNeuronsStochastic ProcessesAutonomous oscillatorsBiological clocksCell cycle oscillatorChemical couplingCircadian rhythmsCoupled oscillatorsDeterministic oscillationsEntrainmentKuramoto modelMechanical couplingPhase lockingStochastic modelingStochastic oscillationsSynchronization

Identifiers

PMID42782446

What OpenQuestion holds

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Registered trials

None linked

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.