Evidence map›Paper›PMID 40522321›Full record

ArticleeLife2025

Spectral decomposition unlocks ascidian morphogenesis.

Joel Dokmegang, Emmanuel Faure, Patrick Lemaire, Edwin Munro, Madhav Mani

Abstract read
In one paragraph

Article in eLife, 2025. 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

5 authors.

Joel DokmegangNorthwestern University, Evanston, United States.ORCID https://orcid.org/0000-0001-9953-7913
Emmanuel FaureUniversity of Montpellier, Montpellier, France.ORCID https://orcid.org/0000-0003-2787-0885
Patrick LemaireUniversity of Montpellier, Montpellier, France.ORCID https://orcid.org/0000-0003-4925-2009
Edwin MunroUniversity of Chicago, Chicago, United States.
Madhav ManiNorthwestern University, Evanston, United States.ORCID https://orcid.org/0000-0002-5812-4167

Funding

National Science Foundation 1764421National Science Foundation PHY- 2317138Simons Foundation 597491-RWC
6 · The paper itself

Abstract

Describing morphogenesis generally consists in aggregating the multiple high-resolution spatiotemporal processes involved into reproducible low-dimensional morphological processes consistent across individuals of the same species or group. In order to achieve this goal, biologists often have to submit movies issued from live imaging of developing embryos either to a qualitative analysis or to basic statistical analysis. These approaches, however, present noticeable drawbacks as they can be time consuming, hence unfit for scale, and often lack standardization and a firm foundation. In this work, we leverage the power of a continuum mechanics approach and flexibility of spectral decompositions to propose a standardized framework for automatic detection and timing of morphological processes. First, we quantify whole-embryo scale shape changes in developing ascidian embryos by statistically estimating the strain rate tensor field of its time-evolving surface without the requirement of cellular segmentation and tracking. We then apply to this data spectral decomposition in space using spherical harmonics and in time using wavelets transforms. These transformations result in the identification of the principal dynamical modes of ascidian embryogenesis and the automatic unveiling of its blueprint in the form of scalograms that tell the story of development in ascidian embryos.

Indexed as

Image Processing, Computer-AssistedMorphogenesisUrochordataAnimalsEmbryonic DevelopmentEmbryo, Nonmammalianascidiandevelopmental biologygastrulationmorphogenesisneurulationphysics of living systemsspherical harmonicswaveket transform

Identifiers

PMID40522321
PMCPMC12169852

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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.