Evidence map›Paper›PMID 42395412›Full record

ArticlebioRxiv : the preprint server for biology2026

State-dependent energy conversion produces degenerate dissipation in active actomyosin networks.

Zachary Gao Sun, Juanjuan Zheng, A Pasha Tabatabai, Joost J Vlassak, Michael Murrell

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for 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

5 authors.

Zachary Gao SunDepartment of Physics, Yale University, 217 Prospect Street, New Haven, Connecticut 06511, USA.ORCID 0000-0003-3658-109X
Juanjuan ZhengJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
A Pasha TabatabaiSystems Biology Institute, Yale University, 850 West Campus Drive, West Haven, Connecticut, 06516, USA.
Joost J VlassakJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
Michael MurrellDepartment of Physics, Yale University, 217 Prospect Street, New Haven, Connecticut 06511, USA.ORCID 0000-0001-6788-2077

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In non-equilibrium (active) systems, increased driving is commonly assumed to produce proportionally greater energy dissipation. Using picowatt-sensitive calorimetry, entropy-production analysis, rheology, and microscopy in reconstituted actomyosin networks, we show that this relationship breaks down as the material reorganizes under motor activity. Dissipation initially increases with myosin abundance but subsequently decreases despite continued network stiffening, indicating that energetic cost becomes regulated by the evolving mechanical state rather than actuator abundance alone. Comparing catch-bond (α-actinin) and slip-bond (fascin) crosslinked networks reveals that bond mechanics shift the critical motor concentration at which this transition occurs, marking the onset of state-dependent energy conversion. Although these networks generate distinct active stresses and mechanical states, they can exhibit comparable dissipation rates, revealing that state-dependent energy conversion can produce degenerate dissipation, whereby mechanically distinct states exhibit similar energetic costs. These findings demonstrate that dissipation in active materials is governed not only by the magnitude of driving but also by the mechanical state that emerges in response to that driving, providing an experimental example of state-dependent energy conversion far from equilibrium.

Identifiers

PMID42395412
PMCPMC13320965

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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.