Evidence map›Paper›PMID 42101022›Full record

ArticleACS nano2026

3D-Printing-Assisted, Microfabricated Devices Reveal Hierarchical and Temporal Mechanosensing in High-Density Fibroblast Culture.

Ghiska Ramahdita, Xiangjun Peng, Mohammad Jafari, Charlene Pobee, Riya Bhakta, Zhuangyu Zhang, Austin C Kellogg, Hsin-Yi Cindy Chou, Missy Pear, Fei Wang and 9 more

Abstract read
In one paragraph

Article in ACS nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

19 authors.

Ghiska RamahditaNSF Science and Technology Center for Engineering Mechanobiology, St. Louis, Missouri 63130, United States.
Xiangjun PengNSF Science and Technology Center for Engineering Mechanobiology, St. Louis, Missouri 63130, United States.
Mohammad JafariNSF Science and Technology Center for Engineering Mechanobiology, Newark, New Jersey 07102, United States.ORCID 0000-0002-0478-2762
Charlene PobeeDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Riya BhaktaDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Zhuangyu ZhangDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.ORCID 0009-0007-1187-2938
Austin C KelloggDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Hsin-Yi Cindy ChouDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Missy PearDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Fei WangDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
David SchuftanDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Yuan HongNSF Science and Technology Center for Engineering Mechanobiology, St. Louis, Missouri 63130, United States.
Michael A DavidDepartment of Mechanical Engineering & Materials Science, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Spencer P LakeDepartment of Mechanical Engineering & Materials Science, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Elliot L ElsonNSF Science and Technology Center for Engineering Mechanobiology, St. Louis, Missouri 63130, United States.
Chao ZhouDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Guy M GeninNSF Science and Technology Center for Engineering Mechanobiology, St. Louis, Missouri 63130, United States.ORCID 0000-0003-3612-4729
Farid AlisafaeiNSF Science and Technology Center for Engineering Mechanobiology, Newark, New Jersey 07102, United States.
Nathaniel HuebschNSF Science and Technology Center for Engineering Mechanobiology, St. Louis, Missouri 63130, United States.ORCID 0000-0002-3329-0214

Funding

Biomaterial Platforms to Model the Role of Mechanical Overload in MYBPC3-Linked Hypertrophic CardiomyopathyR01HL159094 · NHLBI · WASHINGTON UNIVERSITY · PI HUEBSCH, NATHANIEL · 2021 to 2025
$2.0M
The Role of Tension Anisotropy in Fibroblast ActivationR01AR084243 · NIAMS · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI Farid Alisafaei · 2025 to 2026
$633k
NHLBI NIH HHS R01 HL159094NIAMS NIH HHS R01 AR084243
6 · The paper itself

Abstract

Understanding how cells integrate mechanical forces across multiple directions, length scales, and time scales remains a fundamental challenge in mechanobiology. This is particularly important in the context of wound healing, where the timing and duration of the fibroblast-to-myofibroblast transition can determine the healing outcomes. Here, we discovered that fibroblasts in tissue equivalents respond to directional anisotropy in stress through a hierarchical temporal cascade, with individual cell elongation (24 h) preceding collective alignment (48 h), which then drives α-smooth muscle actin expression and myofibroblast transition (96 h). To enable this discovery, we developed a modified hydrogel-assisted stereolithographic elastomer (HASTE) prototyping platform to incorporate a detergent that improves the wettability of template agar hydrogels by poly(dimethylsiloxane) elastomer. This allowed rapid prototyping of intricate three-dimensional (3D) micropost arrays with microscale precision. Using these with engineered microtissues with isotropic (8-post) versus anisotropic (4-post) boundary conditions, we found that cells sense and respond to stress directionality before bulk tissue reorganization occurs. Computational modeling predicted steady-state activation patterns based on initial stress anisotropy rather than magnitude, and our experiments reveal that reaching this state requires sequential mechanosensitive processes operating across distinct time scales. This temporal hierarchy persists even when extensive cell-cell contacts might be expected to mask matrix-mediated mechanical signals. Our findings demonstrate that fibroblast mechanosensing involves mechanical memory encoded through progressive cell and tissue reorganization. Results provide insight into how nanoscale mechanosensing scales up to direct tissue-level organization, with implications for understanding wound healing, fibrosis, and engineering functional tissue replacements.

Indexed as

FibroblastsMechanotransduction, CellularMicrotechnologyPrinting, Three-DimensionalActinsAnimalsDimethylpolysiloxanesHydrogelsMiceActinsbaysilonDimethylpolysiloxanesHydrogelscell–cell contactsmechanosensingpoly(dimethylsiloxane)three-dimensional (3D)α-smooth muscle actin

Identifiers

PMID42101022
PMCPMC13217617

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.