DOI: 10.5061/dryad.bvq83bkmw
title: A soft sensor-integrated cell stretching device for precise and reproducible mechanotransduction

description: Mechanical stretch is a fundamental regulator of cell fate, yet in-vitro
 replication remains challenging because conventional stretchers deliver
 non-uniform strain and ignore batch-to-batch variations in substrate
 stiffness—so the stress actually experienced by cells varies
 unpredictably. We introduce the first biaxial cell-stretching platform
 that couples an embedded soft resistive micro-channel sensor with
 high-frequency closed-loop control. Real-time deformation read-out (60 Hz)
 drives a 24 kHz actuator loop to compensate for PDMS moduli spanning an
 order of magnitude, delivering user-defined triangular or square waveforms
 (5–20 % amplitude; 0.5–10 s period) with &lt; 2 % steady-state error.
 Closed-loop operation maintains strain-invariant membrane stress within ±
 5 %, reducing well-to-well variability three-fold compared with open-loop
 actuation. Biological validation using immortalized human myoblasts
 exposed to 10 % cyclic stretch for 4 h produced a significant
 up-regulation of YAP/TAZ target genes (C-MYC, MYL9, DIAPH1, ANKRD1; p
 &lt; 0.001), confirming mechanotransductive efficacy. The platform’s
 modular architecture accommodates stiffness-tunable hydrogels and live
 imaging, offering a reproducible tool for mechanobiology, tissue
 engineering, disease modelling and personalised mechanotherapy.
description: # A soft sensor-integrated cell stretching device for precise and
 reproducible mechanotransduction Dataset DOI:
 [10.5061/dryad.bvq83bkmw](10.5061/dryad.bvq83bkmw) ## Description of the
 data and file structure This repository contains MATLAB code and dataset
 used in the study: **Duz, N., Ozturk, E., Akar, S., Kumbay Yildiz, S.,
 Dincer, P., & Uyanik, I.** "A Soft Sensor-Integrated Cell
 Stretching Device for Precise and Reproducible Mechanotransduction" 
 
 There are 7 folders inside the dataset, that contains the cell attachment
 data, mRNA of YAP genes data, triple soft sensor data, triangular and
 square waveforms applied to the soft sensor data (tri-squ data), uniaxial
 and biaxial stretching of the soft sensor data (uni-bi data), closed-loop
 control using soft sensor (stress based) and open-loop control (strain
 based) stretching data (stress-strain data), and finally the visualization
 of displacements on validation membrane data (heatmap data). The data in
 the folders have been used in the manuscripts as in the matlab scripts in
 the corresponding folder. 
 
 ### Files and variables #### File:
 Soft_Sensor-Integrated_Cell_Stretching_Device_Data.zip
 **Description:** The dataset is divided into seven parts: ``` -Cell
 attachment and proliferation data This section includes quantitative data
 related to cell adhesion and proliferation on the stretching membrane. All
 measurements were obtained from static (non-stretched) control groups and
 are used to assess the biocompatibility of the membrane and soft sensor
 materials. -mRNA levels of YAP-responsive genes data This dataset contains
 gene expression results obtained from cell stretching experiments. The
 data specifically report relative mRNA expression levels of YAP-responsive
 markers and are used to evaluate mechanotransduction responses under
 different stretching conditions. -Triple sensor data This section includes
 data collected from experiments in which three microchannels were embedded
 into a single soft strain sensor. The dataset was used to investigate
 strain and stress uniformity across the sensor surface under mechanical
 stretching. -Triangular and Square waveforms data This dataset includes
 time-series measurements obtained by applying triangular and square
 strain-stress waveforms to the soft sensor. The data are used to analyze
 the sensor response and dynamic behavior under different waveform
 profiles. -Uniaxial and biaxial stretching data This section contains data
 collected from experiments applying strain-stress along a single axis
 (uniaxial) and along two orthogonal axes (biaxial). The dataset enables
 direct comparison of mechanical response and strain distribution between
 uniaxial and biaxial stretching modes. -Closed-loop and open-loop
 controlled data This dataset corresponds to the proposed closed-loop,
 sensor-controlled cell stretching system. Soft sensor feedback was used
 for real-time strain regulation, and the data are used to evaluate control
 accuracy and system performance. -Heatmap data This dataset includes the
 data used to generate the heatmap figures presented in the manuscript. The
 displacements of tracked blobs on the validation membrane were measured
 and spatially interpolated to obtain smooth strain maps. The mean and
 variance of the resulting heatmaps were computed and reported in the paper
 to compare different substrates and stretching methods. ``` Each of the
 seven datasets listed above is discussed in the paper. For soft sensor
 related datasets, the MATLAB `.m` files include the code used to generate
 the figures presented in the paper. For others (Cell attachment and mRNA
 level data) the data in the `.csv` files have been used with GraphPad
 Prism and visualized in the manuscript. ## Code/software MATLAB 2023b or
 later ## Notes \- Each folder includes raw data and plotting scripts. \-
 For any questions or clarifications, please contact the corresponding
 author of the paper.