Evidence map›Paper›PMID 41893945›Full record

ArticleJournal of biological physics2026

Elucidating motion patterns in sperm cell motion with dynamic mode decomposition.

Petr Šimánek, Jakub Hořenín, Islam S M Khalil, Veronika Magdanz, Anke Klingner, Alexander Kovalenko

Abstract read
In one paragraph

Article in Journal of biological physics, 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
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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

6 authors.

Petr ŠimánekFaculty of Information Technology, Czech Technical University in Prague, Prague, 16000, Czech Republic. simanpe2@fit.cvut.cz.
Jakub HořenínFaculty of Information Technology, Czech Technical University in Prague, Prague, 16000, Czech Republic.
Islam S M KhalilRAM-Robotics and Mechatronics, University of Twente, Twente, 7522 NH, The Netherlands.
Veronika MagdanzDepartment of Systems Design Engineering, Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, N2L 3G1, ON, Canada.
Anke KlingnerDepartment of Physics, German University in Cairo, Cairo, 11835, Egypt.
Alexander KovalenkoFaculty of Information Technology, Czech Technical University in Prague, Prague, 16000, Czech Republic. alexander.kovalenko@fit.cvut.cz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study employs dynamic mode decomposition (DMD) to elucidate the underlying mechanisms contributing to the enhanced motility observed in sperm bundles, primarily focusing on the role of flagellar synchronization. The decomposition reveals that synchronized flagellar movements might be a key factor enabling sperm cells to attain higher velocities when connected in bundles. Through DMD, periodical characteristics of individual periodical motion patterns, such as frequency, amplitude, and modal growth/decay rates (from DMD eigenvalues), are characterized, elucidating main parameters of the dynamic behavior of these biological systems, such as dominant frequencies of periodical motion, as well as amplitudes and velocities. The implications of this research extend beyond understanding sperm bundle dynamics, as the methodology is adaptable for identifying healthy sperm cells based on their motility patterns. Additionally, the approach holds potential for broader applications in studying other flagellar-driven microorganisms, providing a valuable tool for comparative analysis across various species.

Indexed as

SpermatozoaSperm MotilityAnimalsFlagellaMaleModels, BiologicalBiological microorganismsDynamical systemsDynamic mode decompositionPeriodical pattern analysisSperm motility

Identifiers

PMID41893945
PMCPMC13031697

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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.