Pith. sign in

REVIEW 4 major objections 5 minor 39 references

Myosin-driven advection and actin reorganization control the geometry of confined actomyosin gel

T0 review · 4 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read Confined frog-egg actin gels take on the shape of the microwell, with myosin-driven flow and polymerization rate controlling size and shape.

desk verdict Solid experimental mapping of confinement-shape transfer to contracted actomyosin gels, with a plausible but partly assumed model mechanism; deserves peer review. read the letter →

arxiv 2505.01717 v1 pith:ISLFB5CD submitted 2025-05-03 cond-mat.soft physics.bio-ph

Archit Negi , Ryota Sakamoto , Makito Miyazaki , Yusuke T. Maeda This is my paper · ORCID
classification cond-mat.softphysics.bio-ph
keywords actomyosingelactivefluidmodelgeometricconfinementmicrowellmyosincontractilityactinpolymerizationcytoskeletonPécletnumber
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

By confining frog-egg actomyosin extracts in microfabricated microwells shaped as circular segments, squares, and letters, this paper shows that the boundary shape is not merely a container: it is transferred to the contracted gel that forms inside. High-speed imaging and particle image velocimetry reveal an inward, myosin-driven actin flow, and the final cluster inherits the well's asymmetry — crescents in semicircular wells, square and even star-like shapes in square wells. The paper argues, with an active fluid model, that this shape transfer is an advective process: myosin contractile stress drives an inward flow that carries actin toward the cluster, while enhanced actin polymerization near the boundary determines how faithfully the wall shape is copied. Because myosin contractility and actin polymerization can be tuned chemically, the authors propose that gel size and shape in confined architectures can be controlled by two parameters: effective contractility and surface polymerization rate. If right, this gives a design rule for making shape-adaptive biomaterials from cytoskeletal motors.

What carries the argument

The load-bearing object is an active fluid model of the actomyosin gel coupled to a phase field for the microwell boundary. The gel is treated as a viscous fluid whose stress has a passive part and an active contractile part proportional to F-actin density, with myosin density assumed proportional to F-actin density so that mass conservation reduces to a single component. The dynamics are three coupled equations: a Stokes-like force balance for the velocity field, a reaction-diffusion-advection equation for actomyosin density with polymerization source and depolymerization sink, and a phase-field equation for the boundary. Two dimensionless parameters carry the argument: the Péclet number, the ratio of myosin-driven advection to diffusion, and the surface polymerization rate, which is taken to be higher near the wall than in the bulk. This model converts the geometric question — does boundary shape reach the cluster? — into a testable statement: the inward advective flux transfers wall asymmetry to the contracting cluster, while the balance of polymerization and contractility decides how round or how faithful to the boundary the final gel is.

What would settle it

Dual-color fluorescence imaging of myosin and F-actin during contraction in a semicircular microwell, quantifying local densities along the flat side and the curved wall, would settle the mechanism: if myosin and F-actin densities drift out of proportion before or during cluster formation, the single-component active fluid model is not the right description. A complementary check is to reconstruct the final cluster by advecting the measured initial density field $\rho$ under the measured velocity field; if the predicted shape disagrees with the observed cluster, then myosin-driven advection alone does not transfer the wall shape.

Watch

Extended reading notes

Core claim

The central claim is that the final shape of a contracting actomyosin gel inside a closed confinement is set by the shape of the confinement itself, transmitted through myosin-driven advection rather than by passive diffusion or spontaneous symmetry breaking alone. In circular microwells the network contracts to a circular cluster, while in semicircular wells it forms a crescent whose roundness decreases monotonically as the flat-side-to-diameter ratio rises from 0 to 1, independent of well diameter. A phase-field active fluid model reproduces the trend: the gel is an active viscous fluid carrying myosin-generated contractile stress, mass conservation is a reaction-diffusion-advection equation for F-actin density with surface-enhanced polymerization, and the phase field imposes the boundary. The paper also claims that the same mechanism works in square and letter-shaped wells, where the cluster copies the boundary, and that two parameters — the Péclet number (advective transport relative to diffusion) and the surface polymerization rate — separately set size and shape: higher contractility shrinks the cluster, higher surface polymerization makes it more asymmetric. Chemical perturbations (cytochalasin D inhibiting polymerization, calyculin A increasing myosin contractility) shift the observed clusters in the direction the model predicts.

Load-bearing premise

The load-bearing premise is that myosin density stays proportional to F-actin density throughout contraction, so one concentration variable represents the whole network; if myosin redistributes independently of the actin filaments in the extract, the advection-based shape transfer predicted by the model would not necessarily occur.

Editorial extensions

If this is right

  • In any confined actomyosin gel with advection-dominated transport, the contracted cluster should inherit the global asymmetry of the wall rather than relaxing to a circle, as seen for crescents, squares, and letter-shaped wells.
  • The two-parameter phase diagram implies that a myosin activator shrinks the gel while leaving shape nearly unchanged, whereas an actin polymerization inhibitor makes the gel rounder without reliably shrinking it.
  • Microwell diameter at fixed shape does not change roundness, so the shape transfer is a geometric effect of boundary asymmetry rather than a size-dependent instability.
  • Because the model reproduces square and letter-shaped compartments, the same design rule should apply to arbitrary polygonal and patterned boundaries: the wall acts as a template whenever advection dominates diffusion.
  • Chemical inhibition or activation of the two molecular processes gives an experimental route to resize and reshape confined cytoskeletal gels on demand.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A test the paper does not run: reconstruct the final cluster by advecting the measured initial F-actin field with the measured velocity field; agreement would directly confirm the advective shape-transfer mechanism, and disagreement would challenge it.
  • If myosin density is truly slaved to F-actin, then interventions that decouple myosin from actin filaments, such as disabling myosin's actin-binding domain, should abolish shape transfer even when the gel still contracts; dual-color imaging of myosin and F-actin during contraction could test this prediction.
  • The corner outgrowths that appear in squares and letters suggest a criterion the model does not spell out: fidelity of shape transfer should depend on local boundary curvature, with sharper corners concentrating advective flux; measuring cluster shape as a function of corner angle would quantify that dependence.
  • The paper's two-parameter description implies a master-curve collapse: plotting roundness and area ratio from many chemical doses against an inferred Péclet number and surface polymerization rate should collapse onto the simulation phase diagrams; this is a quantitative extension the authors do not report.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The manuscript reports an experimental and numerical study of actomyosin networks extracted from Xenopus laevis eggs and confined in microfabricated NOA81 microwells of controlled geometry. The authors show that as the microwell shape changes from circular to semicircular (increasing W/D), the contracted actomyosin cluster changes from circular to crescent-like, quantified by the roundness R = m/M (Figure 1h), while cluster area scales with microwell area (Figure 2). They model the system with an active fluid theory (Eqs. 1–3) that couples force balance, actomyosin mass conservation, and a phase-field boundary, assuming boundary-enhanced actin polymerization (k_bulk^p/k_surf^p = 0.1). With hand-tuned parameters Pe = 50 and k_surf^p = 2.5, the simulations reproduce the experimental roundness trends (Figure 3c,d). Drug perturbations with Cytochalasin D (CytoD) and Calyculin A (CalA) are used to test model predictions: CytoD increases roundness and CalA decreases cluster area (Figure 4). The study is extended to square and more complex microwells (Figure 5), where the model again qualitatively captures cluster shape. The central claim is that asymmetric confinement geometry is transferred to the contracted gel through myosin-driven actin advection, and that tuning contractility and polymerization rate gives control over gel size and shape.

Significance. If the mechanistic claim is established, the paper offers a useful bottom-up design principle for active, shape-adaptive biomaterials and adds to the understanding of geometric control of cytoskeletal organization in cell-sized confinement. The experiments are carefully quantified, including roundness and area measurements over multiple microwell shapes and sizes, and the drug perturbations provide an independent, if partially confounded, test of the model's qualitative predictions. The model is borrowed from the authors' prior work and is not introduced as new theory, but its application to asymmetric and complex confinements is new and generates falsifiable predictions. The phase diagrams in Figures 3f,g and 5e are a genuine strength because they connect model parameters to experimentally accessible perturbations. However, the model's central role in establishing the mechanism rests on two assumptions that are not directly measured in this system: the boundary-enhanced polymerization profile and the proportionality between myosin and F-actin densities.

major comments (4)
  1. [§3(b), Eq. (2)] The boundary-enhanced polymerization profile k_bulk^p/k_surf^p = 0.1 is prescribed in the model and stated to be 'a condition necessary for wave generation' that 'holds for all of the following results,' but no experiment in the NOA81/PEG-PLL microwell system measures the spatial profile of actin polymerization. Since the boundary shape enters the dynamics through this prescribed source term, the simulations could be reproducing the observed shape transfer because the model was given a shape-dependent source rather than because myosin-driven advection alone imprints the boundary geometry. Please provide a direct test of the polymerization profile in the microwells (for example, monomer incorporation or branching-density measurements near the wall), or a robustness check showing that the roundness trend in Figure 3d persists for a substantially smaller k_surf^p/k_bulk^p ratio.
  2. [§3(c,d), Figures 3(c)–3(g)] The two main simulation parameters, Pe = 50 and k_surf^p = 2.5, are chosen after seeing the control experimental roundness values, and the simulations are reported without error bars, number of independent runs, or convergence checks with respect to grid resolution and integration time. As these parameters set the contractile stress and the boundary polymerization rate, the agreement in Figure 3d does not by itself confirm the mechanism. Please report run-to-run variability, a small parameter sweep around Pe=50 and k_surf^p=2.5, and at least a qualitative convergence statement so the reader can judge whether the roundness and area trends are robust.
  3. [Eq. (2) and accompanying text] The model assumes myosin density is proportional to F-actin density, reducing mass conservation to a single component. If myosin in the Xenopus extract redistributes independently of actin (for example, by differential binding, advection, or detachment under contraction), then the advective coupling that the model identifies as the shape-transfer mechanism would not necessarily hold in the experiments. The manuscript does not report any myosin labeling or otherwise justify this proportionality in the microwell geometry. Please add a direct justification or an experimental check (for example, myosin fluorescence in the contracted cluster versus the flow region).
  4. [§4, Figures 4(c), 4(d), and S6] The CytoD and CalA perturbations are presented as clean tests of decreasing k_surf^p and increasing Pe, respectively, but CytoD is known to reduce effective actomyosin contractility, and the text itself acknowledges that the absence of a cluster-size reduction under CytoD 'could be due to the reduction in effective actomyosin contractility upon inhibition of actin polymerization.' This confound weakens the inference that the increased roundness in Figure 4c is specifically a k_surf^p effect. Similarly, the CalA roundness change is described as 'minute (or negligible),' yet Figure S6 shows significant decreases for W/D = 0.0, 0.5, and 1.0; the text should reconcile these statements. Please discuss the confound explicitly and, if possible, add a measurement of myosin activity or actin filament length that separates the two effects.
minor comments (5)
  1. [Figure 1(h) and Figure 2(b,c)] The text reports n = 4 microwells for some averages in Figure 1(i) and Figure 2(c), which is small; please state explicitly in the figure caption or text whether these data points come from independent experiments or repeated fields of view, and consider showing individual data points in the boxplots.
  2. [Materials and Methods, Image analysis] Cluster identification used thresholding and, in some cases, manual identification; please describe the criteria for manual selection and whether the roundness results are sensitive to the threshold choice, as this could affect the quantitative claims.
  3. [Figure 5(b) and 5(d)] The quartic parameter is defined in the Methods but the relationship between its magnitude and the visually distinct star-like shape is not intuitive; a short explanation of why the control value 0.069 and CalA value 0.088 correspond to square versus star-like would improve readability.
  4. [General notation] The symbols k_surf^p, k_bulk^p, Pe, and lambda are used with inconsistent formatting (subscripts and superscripts) in the text and equations; please unify the notation, particularly in the caption of Figure 3.
  5. [§3(d), Figure 3(f)] The text says 'roundness decreased as k_surf^p increased' and 'slightly dependent on Pe,' but the phase diagram in Figure 3(f) appears to show a non-monotonic or weak dependence; please state whether the quoted dependence is the average trend over the plotted region or a qualitative summary.

Circularity Check

2 steps flagged · score 4.0 of 10

Shape transfer in the model is partly built into an unmeasured boundary-enhanced polymerization profile imported from the authors' prior work, and the base parameters Pe=50, ksurf_p=2.5 are selected after matching the control roundness data; the drug experiments provide independent qualitative support.

  1. self citation load bearing [Results, 'Active fluid model reproduces the shape and compressibility' section, paragraph after Eqs. (1)-(3), Figure 3(b)]
    "We also assume the polymerization rate of actin to be higher near the surface of the confinement (ksurf p ) compared to the bulk (kbulk p ), with kbulk p /ksurf p = 0.1 (Figure 3(b)), as polymerization is enhanced at the boundary in lipid droplets,13,25 a condition necessary for wave generation.15 This assumption holds for all of the following results."

    The simulation's central result—cluster shape templated by confinement shape—is produced under an imposed, unmeasured spatial profile of actin polymerization that is itself boundary-shaped. The 'condition necessary for wave generation' is justified by citing ref. 15, a prior paper by the same group (Sakamoto, Miyazaki, Maeda), so the advection-based explanation carries forward an ansatz from the authors' own model rather than being established by an independent measurement in the NOA81/PEG-PLL microwells. The boundary asymmetry is thus inserted into the density production term before the advective flow acts, so the simulation cannot distinguish advection-mediated shape transfer from polymerization-source-mediated shape transfer.

  2. fitted input called prediction [Results, 'Active fluid model reproduces the shape and compressibility' section, paragraph describing Figure 3(c)-(d)]
    "We found that simulations with W/D ratios matching the experiments and with parameters Pe = 50 and ksurf p = 2.5 reproduced qualitatively similar cluster shapes and roundness trends (Figure 3(c), 3(d))."

    The two dimensionless parameters that set the strength of advection and boundary polymerization are not measured in the microwell system; they are chosen after the fact so that the simulation matches the control roundness trend shown in Figure 3(d). The subsequent phase diagrams then 'predict' that lowering ksurf_p or raising Pe changes cluster shape and size, but these are sensitivity analyses around a fitted operating point rather than parameter-free first-principles forecasts. The independent CytoD and CalA experiments do provide genuine qualitative support, so this is partial rather than complete circularity.

full rationale

The empirical core of the paper is not circular: the direct observation that cluster roundness follows microwell shape, the PIV-measured actin flows, and the CytoD/CalA perturbations are independent experimental facts. However, the numerical model used to explain the mechanism imports a boundary-enhanced polymerization profile (k_bulk^p/k_surf^p = 0.1) from the authors' prior work without measuring it in this system, and this profile carries the confinement shape into the density equation before advection acts. The base parameters Pe=50 and ksurf_p=2.5 are chosen post hoc to reproduce the control roundness data. Thus the claim that the shape is transferred 'via myosin-driven actin flow' is not a parameter-free derivation; it is a plausible mechanism whose shape-transfer component is partly encoded in an unmeasured source term. Because the drug perturbations and complex-geometry experiments provide independent qualitative validation, the circularity is partial rather than total.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The central mechanism rests on a single-component active fluid model with two hand-set parameters (Pe, ksurf_p), an assumed boundary-enhanced polymerization ratio, and a fixed viscosity ratio. The model is used to interpret experiments, but its parameters are not independently measured, which is why the circularity burden is non-negligible.

free parameters (4)
  • Péclet number Pe (effective myosin contractility) = 50
    Chosen to reproduce qualitative cluster shapes and roundness trends in simulations; not measured independently from the actomyosin extracts.
  • surface actin polymerization rate ksurf_p = 2.5
    Chosen together with Pe=50 to match experimental roundness trends; not independently measured.
  • ratio kbulk_p/ksurf_p = 0.1
    Assumed based on prior lipid-droplet work (refs 13,25) to create boundary-enhanced polymerization needed for wave generation.
  • viscosity ratio lambda = 1/3
    Assumed following ref 32; not measured in this system.
assumptions (5)
  • domain assumption Actomyosin network can be described as a single-component viscous active fluid with myosin density proportional to F-actin density.
    Underlies Eqs. (1)-(2); if myosin and actin distributions decouple, the model's shape-transfer mechanism is not applicable.
  • domain assumption Actin polymerization is enhanced at the confinement boundary (kbulk_p/ksurf_p = 0.1).
    Necessary for wave generation; taken from previous work on lipid droplets (refs 13,25).
  • domain assumption Active stress f is a function of actomyosin density and the phase field imposes no-flux at the boundary.
    Standard active-fluid modeling choices; cited from refs 15,31.
  • domain assumption Lambda = 1/3 for the viscosity ratio.
    Assumed as in ref 32 to simplify the momentum balance.
  • standard math Numerical solutions of the phase-field equations are converged and representative of the continuum model.
    No convergence study or code is provided, so reliability rests on the authors' implementation.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Myosin-driven advection and actin reorganization control the geometry of confined actomyosin gel." pith.science (2026). https://pith.science/paper/ISLFB5CD

@misc{pith2026250501717,
  author       = {Pith},
  title        = {Pith review of: Myosin-driven advection and actin reorganization control the geometry of confined actomyosin gel},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ISLFB5CD}},
  note         = {Machine review of arXiv:2505.01717}
}
read the original abstract

Harnessing nanoscale motor proteins to actively control material shape is a promising strategy in nanotechnology and material science. One notable system is the actomyosin network, composed of actin filaments and myosin motor proteins, providing a natural platform for constructing contractile, shape-adaptive materials. While the role of actomyosin in shaping cells has been extensively studied, the reverse question - how boundary shape affects the actomyosin system - remains poorly understood. Here, we present a microfabricated system that reveals how geometrical confinement directs the organization of actomyosin networks within microwells. By combining experimental and numerical analysis, we show that the asymmetric shape of the microwells is transferred to contracted actomyosin gels via myosin-driven actin flow. Furthermore, tuning myosin contractility and actin polymerization rate allows control over the size and shape of actomyosin gels. Our findings provide a bottom-up framework for integrating molecular motors and cytoskeletons into confined architectures to create responsive biomaterials.

Figures

Figures reproduced from arXiv: 2505.01717 by the authors.

Figure 2
Figure 2. Confinement geometry determines the compressibility of actomyosin gel. (a) Schematic showing the contraction of the actomyosin network to form a cluster inside the microwell. (b) Dependence of cluster to microwell area ratio (Ac/Aµ) on microwell shape. (c) The cluster area increases as the microwell area increases and microwells with different shapes but similar sizes result in clusters of similar areas. At least n … view at source ↗
Figure 3
Figure 3. Active fluid model reproduces the shape and compressibility. (a) Schematic showing the parameters of the theoretical model. (b) Schematic showing the relation between the surface (k surf p ) and the bulk (k bulk p ) polymerization rates. (c) Numerical simulations of our theoretical model (P e = 50, ksurf p = 2.5) show the cluster shape to be dependent on the confinement shape, in qualitative agreement with the exper… view at source ↗
Figure 4
Figure 4. Active transport and reorganization determines the shape and size of the contracted confined actin cytoskeleton. (a) Effect of chemical perturbations on the cluster formation in mi￾crowells with W/D = 0.85 and D = 350 µm; CytoD is an actin polymerization inhibitor while CalA is a myosin activator. The white lines denote the boundary of the clusters. Schematic diagram showing how the cluster (a) shape and (b) size in… view at source ↗
Figures from the paper (1 more)
Figure 5
Figure 5. Figure 5: Design principles of confined actomyosin gel under spatial constraints of complex geom￾etry. (a) Schematic of actomyosin network in a square microwell. (b) In a square microwell (side length = 270 µm), the cluster shape is also that of a square (quartic parameter= 0.06…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

39 extracted references · 38 canonical work pages

  1. [1]

    W.; Lenz, M.; Gardel, M

    Murrell, M.; Oakes, P. W.; Lenz, M.; Gardel, M. L. Forcing cells into shape: the mechanics of actomyosin contractility. Nature Reviews Molecular Cell Biology 2015, 16, 486--498

    work page 2015

  2. [2]

    C.; Neikirk, K.; Katti, P.; Claypool, S

    Jenkins, B. C.; Neikirk, K.; Katti, P.; Claypool, S. M.; Kirabo, A.; McReynolds, M. R.; Hinton Jr., A. Mitochondria in disease: changes in shapes and dynamics. Trends in Biochemical Sciences 2024, 49, 346--360

    work page 2024

  3. [3]

    Jerabkova-Roda, K.; Marwaha, R.; Das, T.; Goetz, J. G. Organelle morphology and positioning orchestrate physiological and disease-associated processes. Current Opinion in Cell Biology 2024, 86, 102293

    work page 2024

  4. [4]

    Local force and geometry sensing regulate cell functions

    Vogel, V.; Sheetz, M. Local force and geometry sensing regulate cell functions. Nature Reviews Molecular Cell Biology 2006, 7, 265--275

    work page 2006

  5. [5]

    L.; Schwarz, U

    Banerjee, S.; Gardel, M. L.; Schwarz, U. S. The actin cytoskeleton as an active adaptive material. Annual Review of Condensed Matter Physics 2020, 11, 421--439

    work page 2020

  6. [6]

    Nano Letters 2021, 21, 952--958

    Guan, Q.-F.; Han, Z.-M.; Zhu, Y.; Xu, W.-L.; Yang, H.-B.; Ling, Z.-C.; Yan, B.-B.; Yang, K.-P.; Yin, C.-H.; Wu, H.; others Bio-inspired lotus-fiber-like spiral hydrogel bacterial cellulose fibers. Nano Letters 2021, 21, 952--958

    work page 2021

  7. [7]

    Dynamic modes of the cortical actomyosin gel during cell locomotion and division

    Paluch, E.; Sykes, C.; Prost, J.; Bornens, M. Dynamic modes of the cortical actomyosin gel during cell locomotion and division. Trends in Cell Biology 2006, 16, 5--10

    work page 2006

  8. [8]

    Actomyosin clusters as active units shaping living matter

    Kruse, K.; Berthoz, R.; Barberi, L.; Reymann, A.-C.; Riveline, D. Actomyosin clusters as active units shaping living matter. Current Biology 2024, 34, R1045--R1058

    work page 2024

Show all 39 references
  1. [9]

    Sakamoto, R.; Murrell, M. P. Mechanical power is maximized during contractile ring-like formation in a biomimetic dividing cell model. Nature Communications 2024, 15, 9731

    2024

  2. [10]

    C.; Kr \"o ger, M.; Bausch, A

    Schuppler, M.; Keber, F. C.; Kr \"o ger, M.; Bausch, A. R. Boundaries steer the contraction of active gels. Nature Communications 2016, 7, 13120

    2016

  3. [11]

    L.; Eskin, J.; Shekhar, S

    Goode, B. L.; Eskin, J.; Shekhar, S. Mechanisms of actin disassembly and turnover. Journal of Cell Biology 2023, 222, e202309021

    2023

  4. [12]

    Cell-sized spherical confinement induces the spontaneous formation of contractile actomyosin rings in vitro

    Miyazaki, M.; Chiba, M.; Eguchi, H.; Ohki, T.; Ishiwata, S. Cell-sized spherical confinement induces the spontaneous formation of contractile actomyosin rings in vitro. Nature Cell Biology 2015, 17, 480--489

    2015

  5. [13]

    T.; Miyazaki, M

    Sakamoto, R.; Tanabe, M.; Hiraiwa, T.; Suzuki, K.; Ishiwata, S.; Maeda, Y. T.; Miyazaki, M. Tug-of-war between actomyosin-driven antagonistic forces determines the positioning symmetry in cell-sized confinement. Nature Communications 2020, 11, 3063

    2020

  6. [14]

    Sakamoto, R.; Izri, Z.; Shimamoto, Y.; Miyazaki, M.; Maeda, Y. T. Geometric trade-off between contractile force and viscous drag determines the actomyosin-based motility of a cell-sized droplet. Proceedings of the National Academy of Sciences 2022, 119, e2121147119

    2022

  7. [15]

    Sakamoto, R.; Miyazaki, M.; Maeda, Y. T. State transitions of a confined actomyosin system controlled through contractility and polymerization rate. Physical Review Research 2023, 5, 013208

    2023

  8. [16]

    H.; Malik-Garbi, M.; Abu-Shah, E.; Li, J.; Sharma, A.; MacKintosh, F

    Tan, T. H.; Malik-Garbi, M.; Abu-Shah, E.; Li, J.; Sharma, A.; MacKintosh, F. C.; Keren, K.; Schmidt, C. F.; Fakhri, N. Self-organized stress patterns drive state transitions in actin cortices. Science Advances 2018, 4, eaar2847

    2018

  9. [17]

    Symmetry breaking in reconstituted actin cortices

    Abu Shah, E.; Keren, K. Symmetry breaking in reconstituted actin cortices. eLife 2014, 3, e01433

    2014

  10. [18]

    L.; Mogilner, A.; Keren, K

    Malik-Garbi, M.; Ierushalmi, N.; Jansen, S.; Abu-Shah, E.; Goode, B. L.; Mogilner, A.; Keren, K. Scaling behaviour in steady-state contracting actomyosin networks. Nature Physics 2019, 15, 509--516

    2019

  11. [19]

    L.; Mogilner, A.; Keren, K

    Ierushalmi, N.; Malik-Garbi, M.; Manhart, A.; Abu Shah, E.; Goode, B. L.; Mogilner, A.; Keren, K. Centering and symmetry breaking in confined contracting actomyosin networks. eLife 2020, 9, e55368

    2020

  12. [20]

    Size-dependent transition from steady contraction to waves in actomyosin networks with turnover

    Krishna, A.; Savinov, M.; Ierushalmi, N.; Mogilner, A.; Keren, K. Size-dependent transition from steady contraction to waves in actomyosin networks with turnover. Nature Physics 2024, 20, 123--134

    2024

  13. [21]

    M.; Wühr, M.; Anderson, G

    Field, C. M.; Wühr, M.; Anderson, G. A.; Kueh, H. Y.; Strickland, D.; Mitchison, T. J. Actin behavior in bulk cytoplasm is cell cycle regulated in early vertebrate embryos. Journal of Cell Science 2011, 124, 2086--2095

    2011

  14. [22]

    M.; Presler, M.; Horb, M

    W \"u hr, M.; Freeman, R. M.; Presler, M.; Horb, M. E.; Peshkin, L.; Gygi, S. P.; Kirschner, M. W. Deep proteomics of the Xenopus laevis egg using an mRNA-derived reference database. Current Biology 2014, 24, 1467--1475

    2014

  15. [23]

    H.; Kessenbrock, K.; Yu, J

    Riedl, J.; Crevenna, A. H.; Kessenbrock, K.; Yu, J. H.; Neukirchen, D.; Bista, M.; Bradke, F.; Jenne, D.; Holak, T. A.; Werb, Z.; Sixt, M.; Wedlich-Soldner, R. Lifeact: a versatile marker to visualize F-actin. Nature Methods 2008, 5, 605--607

    2008

  16. [24]

    Actin-Network Architecture Regulates Microtubule Dynamics

    Colin, A.; Singaravelu, P.; Théry, M.; Blanchoin, L.; Gueroui, Z. Actin-Network Architecture Regulates Microtubule Dynamics. Current Biology 2018, 28, 2647--2656.e4

    2018

  17. [25]

    Confinement induces actin flow in a meiotic cytoplasm

    Pinot, M.; Steiner, V.; Dehapiot, B.; Yoo, B.-K.; Chesnel, F.; Blanchoin, L.; Kervrann, C.; Gueroui, Z. Confinement induces actin flow in a meiotic cytoplasm. Proceedings of the National Academy of Sciences 2012, 109, 11705--11710

    2012

  18. [26]

    Actin network architecture can ensure robust centering or sensitive decentering of the centrosome

    Yamamoto, S.; Gaillard, J.; Vianay, B.; Guerin, C.; Orhant‐Prioux, M.; Blanchoin, L.; Th\' e ry, M. Actin network architecture can ensure robust centering or sensitive decentering of the centrosome. The EMBO Journal 2022, 41, e111631

    2022

  19. [27]

    Surface Passivation of Norland Optical Adhesive Improves the Guiding Efficiency of Gliding Microtubules in Microfluidic Devices

    Inoue, D. Surface Passivation of Norland Optical Adhesive Improves the Guiding Efficiency of Gliding Microtubules in Microfluidic Devices. Nano Letters 2024, 24, 10790--10795

    2024

  20. [28]

    Araki, S.; Beppu, K.; Kabir, A. M. R.; Kakugo, A.; Maeda, Y. T. Controlling collective motion of kinesin-driven microtubules via patterning of topographic landscapes. Nano Letters 2021, 21, 10478--10485

    2021

  21. [29]

    Zaferani, M.; Song, R.; Petry, S.; Stone, H. A. Building on-chip cytoskeletal circuits via branched microtubule networks. Proceedings of the National Academy of Sciences 2024, 121, e2315992121

    2024

  22. [30]

    Controlling Physical and Biochemical Parameters of Actin Nucleation Using a Patterned Model Lipid Membrane

    Yamazaki, Y.; Miyata, Y.; Morigaki, K.; Miyazaki, M. Controlling Physical and Biochemical Parameters of Actin Nucleation Using a Patterned Model Lipid Membrane. Nano Letters 2024, 24, 1825--1834

    2024

  23. [31]

    V.; Bois, J

    Kumar, K. V.; Bois, J. S.; J \"u licher, F.; Grill, S. W. Pulsatory patterns in active fluids. Physical Review Letters 2014, 112, 208101

    2014

  24. [32]

    Actomyosin Contraction Induces In-Bulk Motility of Cells and Droplets

    Le Goff, T.; Liebchen, B.; Marenduzzo, D. Actomyosin Contraction Induces In-Bulk Motility of Cells and Droplets. Biophysical Journal 2020, 119, 1025--1032

    2020

  25. [33]

    F.; Flanagan, M

    Casella, J. F.; Flanagan, M. D.; Lin, S. Cytochalasin D inhibits actin polymerization and induces depolymerization of actin filaments formed during platelet shape change. Nature 1981, 293, 302--305

    1981

  26. [34]

    Calyculin A, an enhancer of myosin, speeds up anaphase chromosome movement

    Fabian, L.; Troscianczuk, J.; Forer, A. Calyculin A, an enhancer of myosin, speeds up anaphase chromosome movement. Cell & Chromosome 2007, 6, 1

    2007

  27. [35]

    F.; Holz, D.; Adeli Koudehi, M.; Vogel, S

    Litschel, T.; Kelley, C. F.; Holz, D.; Adeli Koudehi, M.; Vogel, S. K.; Burbaum, L.; Mizuno, N.; Vavylonis, D.; Schwille, P. Reconstitution of contractile actomyosin rings in vesicles. Nature Communications 2021, 12, 2254

    2021

  28. [36]

    Sakamoto, R.; Murrell, M. P. Composite branched and linear F-actin maximize myosin-induced membrane shape changes in a biomimetic cell model. Communications Biology 2024, 7, 840

    2024

  29. [37]

    Sakamoto, R.; Murrell, M. P. Active tension and membrane friction mediate cortical flows and blebbing in a model actomyosin cortex. Physical Review Research 2024, 6, 033024

    2024

  30. [38]

    H.; Wu, B.; Veerapaneni, S.; Liu, A

    Wubshet, N. H.; Wu, B.; Veerapaneni, S.; Liu, A. P. Differential regulation of GUV mechanics via actin network architectures. Biophysical Journal 2023, 122, 2068--2081

    2023

  31. [39]

    Particle Image Velocimetry for MATLAB : Accuracy and enhanced algorithms in PIVlab

    Thielicke, W.; Sonntag, R. Particle Image Velocimetry for MATLAB : Accuracy and enhanced algorithms in PIVlab . Journal of Open Research Software 2021, 9, 12 mcitethebibliography main.bib0000664000000000000000000004502715005337062011171 0ustar rootroot@Article Sakamoto2020, au...

    2021

Pith tools

Reviewed August 16, 2026 · model on record in the stance chip above.