High-Throughput Screening Model to Quantify Re-Epithelialization Kinetics

doi:10.1038/protex.2019.015

Method Article

High-Throughput Screening Model to Quantify Re-Epithelialization Kinetics

https://doi.org/10.1038/protex.2019.015

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In vitro scratch assays provide an attractive method to study the regulation and mechanisms of epithelial cell proliferation and migration that are involved in wound repair. The assay is performed by introducing a scratch into a confluent cell monolayer and monitoring the re-epithelialization of the “wound” by acquiring images over time. Despite improvements to the method over the past years, high-throughput screenings often require the integration of multiple image analysis and data extraction software tools. We developed a high-throughput image-based scratch assay and an automated processing pipeline that employs a mathematical model to describe re-epithelialization kinetics. We implemented a processing pipeline in Galaxy called KREAP that provides an open source web-based platform to enable scientists from diverse backgrounds to perform reproducible and quantitative repair data analyses in less than 45 minutes.

Cell biology

Computational biology and bioinformatics

Biological techniques

Microbiology

Scratch assay

image analysis

high-throughput

re-epithelialization

cell migration

modeling

microscopy

In vitro scratch assays have been frequently employed to test the influence of bioactive substances on the processes of cell migration and proliferation^3-9. These assays are carried out in multiwell plates and commonly rely on the manual introduction of a scratch in a confluent epithelial cell monolayer using a sterile pipette tip, razor blade, scraper or needle. The remaining epithelial cells will then migrate and proliferate into the scratched area until cell-cell contacts are reestablished^10,11. In order to standardize and increase the throughput, significant improvements have been made to the in vitro wounding tools and methods, including the use of hand-guided pin or pipette tip arrays, robotically driven scratching-pin devices, chemically induced wounds, and laser ablation^14,15. Furthermore, the assays have evolved from examining images acquired manually at fixed-time points to the use of automated fluorescent microscopy to monitor live cells expressing fluorescent markers¹⁰. Likewise, manual quantification of the scratched area has been substituted by the implementation of automated image segmentation algorithms that facilitate the analysis of high-throughput screenings¹⁷. Despite all these improvements, data analysis has been usually limited to the calculation of wound closure^17,18, disregarding the kinetic information inherent to the healing process. In addition, effective processing and quantification of high-throughput image-based assays involve the integration of multiple image analysis and data extraction software tools that often require computer programming skills and/or purchase of a commercial license, increasing total experimental costs². Here we present the procedure of an optimized high-throughput scratch assay using high-content microscopy and a mathematical model to quantify the kinetics of epithelial wound repair in individual wells through the calculation of biologically relevant parameters. The assay can be used for screening chemical compounds, bacterial suspensions², and other bioactive substances for their effect on re-epithelialization kinetics. Furthermore, we developed the Kinetic Re-Epithelialization Analysis Pipeline (KREAP) that we implemented in Galaxy, thus providing an end-to-end workflow integrating different validated tools for reproducible image analysis, cell enumeration, re-epithelialization modeling, and HTML reporting¹⁹. KREAP is available for download and use as a virtual machine for both large and small-scale laboratories (https://erasmusmc-bioinformatics.github.io/KREAP/).

Development of the protocol: Quantification of re-epithelialization kinetics

In order to quantify the re-epithelialization kinetics of gingival cells (i.e. Ca9-22 cell line) exposed to different bacterial suspensions using our standardized scratch assay, we developed an automated image segmentation pipeline using CellProfiler 2.2.0 (http://www.cellprofiler.org/) which identifies and records the location of each cell within the well over time². Given that the number of cells moving into the scratched area over time can be represented by a sigmoidal curve, we used a modified form of the Gompertz function²⁰ to quantify the kinetics of wound repair. The modified Gompertz function consists of three biologically comprehensible parameters: lag time (λ parameter, in minutes), repair rate (μ_m parameter, cells/minute), and maximum number of infiltrating cells at the plateau of the growth curve (A parameter, in cells). This function was fitted through the number of infiltrating cells over time by a nonlinear least squares regression using the Levenberg-Marquardt algorithm²¹ to reduce the sum of the squares of the errors between the modeled and measured data points in an iterative manner. Using this approach, we were able to obtain excellent and accurate fits, characterized by goodness of fit (R²) values close to one and low root-mean-square errors (RMSE), respectively.

Experimental design

Selection of suitable cell line. For automated microscopy, it is preferable to select a cell line that grows in a single layer of cells, rather than in multilayers. Furthermore, it is important to evaluate the expression of relevant receptors (e.g. Toll-like receptors, epidermal growth factor receptor, etc.) in the candidate cell line as well as its responsiveness to chemical stimuli. Cells with a long doubling time (e.g. Caco-2 cell line) are less suitable for this set-up as they will require long periods of imaging. In addition, epithelial cell lines that form strong tight-junctions (e.g. Caco-2 cell line) may not allow the introduction of regular and reproducible scratches and for that reason are not ideal for this assay.

Controls. Titration curves of the controls need to be carried out on each cell line to determine the optimal concentrations resulting in a large dynamic range between the positive and negative controls (Figure 1 and Supplementary Fig. 1). A non-treated control should be included as a reference to determine whether the screened substances have a stimulating or attenuating effect on re-epithelialization kinetics.

Z’ factor calculation. The overall quality of each assay can be assessed by calculation of the Z’ factor¹⁶ defined by the means and variability of the positive and negative controls (Figure 1).

Limitations

The modified Gompertz function was implemented to describe positive growth curves. Therefore, if the growth curves resulting from a particular treatment does not resemble a sigmoidal curve, the modified Gompertz function cannot be used to calculate the kinetic parameters. This is often the case of treatments that lead to strong inhibitory effects on re-epithelialization where only few cells migrate into the scratched area during the timeframe of the assay. The KREAP “Data-Modeling” tool flags the wells from which the parameter values could not be retrieved and the user can then examine the curves resulting from the measured data points over time as well as the image segmentation output (also see https://erasmusmcbioinformatics.github.io/KREAP/use_kreap_model_error). Some treatments may induce cell death after the plateau of the growth curve has been reached, leading to a reduction in the number of infiltrating cells towards the end of the assay and lower R² values (< 0.9). These adverse effects can be identified by inspection of the re-epithelialization curves generated by the KREAP tool that compares the measured and modeled data points. R² values lower than 0.9 are also flagged by KREAP to alert the user to examine the re-epithelialization curves.

• Oral epithelial cell lines, e.g. Ca9-22 (National Institute of Biomedical Innovation JCRB Cell Bank, cat. no. JCRB0625), HO-1-N-1 (National Institute of Biomedical Innovation JCRB Cell Bank, cat. no. JCRB0831)

• Skin keratinocytes, e.g. HaCat (AddexBio, cat. no. T0020001) ! CAUTION. The cell lines should be routinely checked to ensure that they are authentic and not cross-contaminated (e.g. using short-tandem repeat analysis) or infected with mycoplasma (PCR-based detection).

• Cell culture medium, e.g. Dulbecco's Modified Eagle Medium (DMEM), DMEM/F12 (1:1) or Keratinocyte-Serum Free Medium (SFM) Gibco, cat. no. 61965-026, 31331-028, 17005-034

• Heat inactivated fetal calf serum (FCS) (Gibco, cat. no. 10500)

• Penicillin-Streptomycin 100X (Sigma, P0781-20ML)

• 0.25% Trypsin EDTA (1x) (Gibco, 25200-056)

• Sterile phosphate-buffered saline (PBS) (Gibco, 18912-014)

• CellTracker™ Red CMTPX (Molecular Probes, cat no. C34552) (optional)

• Hoechst 33342 (Molecular Probes, cat no. H1399) ! CAUTION. Hoechst stains are known mutagens and should be handled with care.

• Human transforming growth factor α (hTGFα; R&D Systems, cat. no. 239-A-100)

• Human epidermal growth factor (hEGF, Gibco, cat. no. PHG0311)

• Inhibitor of p38 (SB203580; Cell Signaling Technology, cat. no. 5633)

• Inhibitor of MEK1/2 (U0126, Cell Signaling Technology, cat. no. 9903) ! CAUTION. The MEK1/2 inhibitor \(U0126) may cause irritation to eyes, skin, and mucous membranes.

REAGENT SETUP

Cell growth media. Add penicillin-streptomycin to the cell culture media to a final concentration of 1x and the inactivated FCS to a final concentration of 10%. Store at 4ºC.

Hoechst 33342 stock solution (10 mg/ml) and working solution (1 mg/ml). To prepare the stock solution, dissolve 100 mg lyophilized dye in 10 ml dimethyl sulfoxide (DMSO). Divide the stock solution into aliquots to avoid repeated freeze-thaw cycles. Store at -20ºC protected from light. This solution is stable for at least one year according to the manufacturer. To prepare the working solution, add 100 µl of the stock solution into 900 µl PBS and store at 2-6 ºC for a maximum of three months.

CellTracker™ Red CMTPX stock solution (100 µM). Dissolve 50 µg lyophilized dye in 730 µl DMSO. Divide the solution into aliquots to avoid repeated freeze-thaw cycles. Store at -20ºC protected from light. This solution is stable for at least three months. Lyophilized dye is stable for at least one year according to the manufacturer.

hTGFα stock solution (10 µg/ml). Reconstitute 100 µg hTGFα in 1 ml 10 mM filter-sterilized acetic acid. Add this solution into 9 ml DMEM to obtain the stock solution. Divide into aliquots and store at -20ºC to avoid repeated freeze-thaw cycles. According to the manufacturer, this solution is stable for at least three months.

hEGF stock solution (10 µg/ml). Reconstitute 100 µg hEGF in 1 ml sterile PBS. Add this solution into 9 ml DMEM containing heat inactivated FCS to obtain the stock solution. Divide into aliquots and store at -20ºC to avoid repeated freeze-thaw cycles. According to the manufacturer, this solution is stable for one year.

SB203580 stock solution (10 mM). Reconstitute 5 mg of lyophilized inhibitor in 1.32 ml DMSO. Divide into aliquots and store at -20ºC to avoid repeated freeze-thaw cycles.

U0126 stock solution (10 mM). Reconstitute 5 mg of lyophilized inhibitor in 1.32 ml DMSO. Divide into aliquots and store at -20ºC to avoid repeated freeze-thaw cycles.

• 75 cm² cell culture flasks (Corning Incorporated, cat. no. 430641U)

• Tissue culture-treated 96-well plates (BD Falcon, cat. no. 353219)

• Tissue culture-treated 96-well plates with flat bottom (Corning Incorporated, cat. no. 3599)

• Tissue culture-treated 96-well plates with round bottom (Corning Incorporated, cat. no. 3799)

• Multichannel pipette, 8-channel, 100 µl (Eppendorf Research Plus, cat. no. 3122000035)

• Disposable serological pipette 5 ml, 10 ml and 25 ml (Corning Incorporated, cat. no. 4051, 4101, and 4251)

• Reagent Reservoir 50 ml (Corning Incorporated, cat. no. 4870)

• Pipette 10 µl, 200 µl and 1 ml (Eppendorf Research Plus, cat. no. 3120000020, 3120000054, and 3120000062)

• Filter sterile tips 10 µl, 200 µl and 1 ml (Corning Incorporated, 4807, 4823, and 4809)

• Tips for multichannel pipette 2-200 µl (Eppendorf, cat. no. 0030073.428)

• Counting chamber (Brand, cat. no. 719520)

• HTSScratcher (Peira, https://www.peira.be/platforms/oncology-platforms)

• Laminar flow cabinet

• Laboratory vacuum pump

• Inverted microscope, e.g. Zeiss, Axiovert 40CFL

• Automated fluorescent microscope with controlled temperature and atmosphere, e.g. BD Pathway 855 Bioimaging System or similar

• Humidified tissue culture incubator (Thermo-Scientific, Forma Direct Heat CO₂ Incubator)

• KREAP (Kinetic Re-epithelialization Analysis Pipeline) virtual machine (https://erasmusmc-bioinformatics.github.io/KREAP/)

EQUIPMENT SETUP

Fluorescence Microscope. Hoechst 33342 and CellTracker™ Red CMTPX images should be acquired using an excitation filter of 350 nm and 577 nm, respectively. Bright-field images serve as visual control for cell morphology and vitality. The microscope should be programmed to acquire fluorescent and bright-field images of the same field of each well every 20-30 minutes (recommended, but the time intervals can be adjusted according to the user’s needs and cell line) using a 4x objective (40x magnification).

Cell culturing and seeding of cells. TIMING 3-7 days depending on the cell line

1. Grow low-passage epithelial cells to 70-80% confluence in 75 cm² tissue culture flasks. Ca9-22 and HaCat cells should be grown in DMEM supplemented with 10% FCS, 100 U/ml penicillin and 100 μg/ml streptomycin. HO-1-N-1 cells should be cultured in DMEM/F12 (1:1) supplemented with 10% FCS, 100 U/ml penicillin and 100 μg/ml streptomycin.

CRITICAL STEP. Always wear gloves when handling cells and work in a laminar flow cabinet. The cell culture environment should be kept clean, i.e. in absence of bacteria, molds and mycoplasma.

2. Discard the growth culture media and wash the cells with 6 ml PBS.

3. Discard the PBS and add 2 ml trypsin/EDTA and incubate at 37ºC for 3-5 minutes.

CRITICAL STEP. Verify complete detachment of the cells under an inverted microscope.

4. Add 8 ml of supplemented growth media into the flask and gently resuspend the cells by gently pipetting up and down.

5. Take an aliquot of the cell suspension and determine the cell counts using a counting chamber. Dilute the cell suspensions in the corresponding growth media. The Ca9-22 cell suspension should be diluted to obtain 3.5 x 10⁵ cells/ml; whereas HO-1-N-1 and HaCat cell suspensions should be diluted to obtain 3.0 x 10⁵ cells/ml.

CRITICAL STEP. The number of cells required to form an intact monolayer within the standardized timeframe depends on the cell type and thus, should be pre-determined for each cell line.

6. Mix the cell suspension gently and add the suspension into a reagent reservoir.

7. Using a multichannel pipette, add 100 µl of the cell suspension into each well of a 96-well plate with flat bottom (BD Falcon; recommended for imaging using the BD Pathway 855 Bioimaging System).

8. Incubate for 16 hours in a humidified incubator at 37ºC with 5% CO₂.

Cell starvation. TIMING 2 hours (might vary for other cell lines)

9. Replace the growth media by 100 µl starvation media (i.e. FCS-free media) by aspiration of the culture medium without disturbing the cell monolayers. HaCat cells should be starved in keratinocyte serum-free medium (SFM). Starvation of Ca9-22 cells should be performed in FCS-free DMEM/F12, whereas HO-1-N-1 cells should be starved in FCS-free DMEM. SFM is not recommended when using Ca9-22 or HO-1-N-1 cells as it was shown to promote significant cell migration and proliferation in our setup that restricted the detection of exogenously added stimulatory compounds.

CRITICAL STEP. The duration and the media used during starvation need to be optimized for each cell line. FCS deprivation should minimize cell migration and proliferation without inducing apoptosis or cell detachment. ? TROUBLESHOOTING

10. Incubate the cells (Ca9-22, HO-1-N-1 or HaCat cells) for 2 hours in a humidified incubator at 37ºC with 5% CO₂.

Preparation of master plate with treatment and control samples. TIMING 1.5 hours

11. Prepare the treatments that you wish to test for their effect on re-epithelialization kinetics. An example of bacterial preparations is provided in Figure 2. Initial screenings can be performed in duplicates, but refined studies should be carried out with at least three technical replicates in two or more independent experiments.

CRITICAL STEP. All treatments should be diluted in the starvation media.

12. Prepare the positive and negative controls as indicated in Figure 3.

CRITICAL STEP. Optimal concentrations of the controls should be determined by performing a titration for the target cell lines (Supplementary Fig. 1) and should result in a large dynamic range between the positive and negative controls (Figure 1). ? TROUBLESHOOTING

13. Prepare a master plate by adding 120 μl of each sample into the corresponding well.

CRITICAL STEP. Exclude outer wells to avoid any possible edge-specific artifacts, e.g. due to evaporation of the medium. It is also recommended to add the samples into the wells in a randomized manner.

Fluorescent labelling with live-compatible dyes. TIMING 25 minutes

14. Prepare a solution of starvation media with the fluorescent dyes. Add 10 μl of Hoechst 33342 working solution and optionally 100 μl of CellTracker™ Red CMTPX stock solution into 5 ml starvation media to obtain a final concentration of 2 μg/ml and 2 μM, respectively.

CRITICAL STEP. Nuclear labelling with Hoechst 33342 stain is crucial for accurate image segmentation and feature extraction with the automated image analysis pipeline presented in this protocol. Labelling of cellular cytoplasm with CellTracker™ Red CMTPX can be performed to visualize cell boundaries. The concentrations of these dyes may need to be adjusted depending on the selected cell line. When using a different cell line, check that addition of the dyes at the desired concentration does not result in adverse effects in re-epithelialization kinetics. ? TROUBLESHOOTING

15. Add the labelling solution into a reagent reservoir and carefully aspirate the starvation media from the cells using a vacuum pump without disturbing the cell monolayer.

16. Add 50 μl of the solution to each of the wells and incubate at 37ºC with 5% CO₂ for 20 minutes.

Scratch assay and imaging. TIMING 5-16 hours depending on the cell line

17. After 20 minutes of incubation with the labelling solution, perform a scratch in the cell monolayers of each well using the HTSScratcher to assure equally sized and reproducible scratches. Place the plate on the platform, slide the plate under the 96-pin array, press the array towards the bottom of the wells, and slide the array from left to right 3 times. Release pressure from the array and remove the plate from the platform.

CRITICAL STEP. Rinse the array with water followed by ethanol before and after each experiment. ? TROUBLESHOOTING

18. Carefully aspirate the liquid from each well using the vacuum pump and wash the cells with 100 µl PBS. Repeat this step one more time.

19. Aspirate the PBS out and immediately transfer 100 µl of each sample from the master plate to the corresponding wells in the assay plate using a multichannel pipette.

CRITICAL STEP. Add 100-200 µl PBS in the outer wells to avoid differential evaporation of the samples. ? TROUBLESHOOTING

20. Start image acquisition. For the Ca9-22 or HO-1-N-1 cell lines, we recommend programming the microscope to acquire images every 20 minutes for a total of 5 hours. For the HaCat cell line, imaging intervals can be adjusted to 60 minutes for a total of 14-16 hours.

CRITICAL STEP. The duration of the assay may vary depending on the cell line and can be determined by the time required for the positive control to achieve wound closure.

Image and data analysis. TIMING 45 minutes

21. For first time users, download the virtual machine (VM) containing the Kinetic Re-Epithelialization Analysis Pipeline (KREAP) toolbox as well as the VM player for your operating system via https://erasmusmc-bioinformatics.github.io/KREAP/. Import the VM into the player following the step-by-step instructions provided in the manual on the website.

22. Create an index file (.txt) and a compressed plate folder (.zip) containing the acquired images organized in separate folders for each well. Indications on how to create these files are provided at https://erasmusmc-bioinformatics.github.io/KREAP/file_formats.

23. Upload the compressed folder and index file into the Galaxy history via the “Get data” tool.

CRITICAL STEP. Set the compressed folder’s type to .zip in the upload menu.

24. Run the KREAP Image Analysis tool to perform automated image segmentation. The results are reported in an HTML format and can be downloaded and stored locally. A manual is provided at https://erasmusmc-bioinformatics.github.io/KREAP/use_kreap_analysis. ? TROUBLESHOOTING

25. Run the KREAP Data-Modeling tool to quantify re-epithelialization kinetics. The results are reported in an HTML format and can be downloaded and stored locally. A manual is provided at https://erasmusmc-bioinformatics.github.io/KREAP/use_kreap_modeling.

CRITICAL STEP. Remember to set the time interval \(min) between images in the index file. ? TROUBLESHOOTING

Cell culturing and seeding of cells

Step 1, growing cells to 70-80% confluence in 75 cm2 tissue culture flasks: 3-7 days depending on starting point and doubling time.

Step 2-7, seeding cells in 96-well plates: ~15 minutes.

Step 8, growing of cells into a cell monolayer: 16 hours (overnight).

Cell starvation

Step 9-10, cell starvation: 2 hours (might vary depending on the cell line).

Preparation of master plate (can be done in parallel with cell starvation)

Steps 11-13, preparation of master plate with treatment and control samples: 1.5 hours.

Fluorescent labelling (last 20 minutes of cell starvation)

Steps 14-16, labelling of cells with fluorescent dyes: 25 minutes.

Scratch assay and imaging

Step 17, performing scratches in the cell monolayers: less than 1 minute.

Step 18-19, washing cells with PBS and addition of treatments into assay plate: ~5-7 minutes.

Step 20, image acquisition: 5-16 hours (may vary depending on the cell line).

Image and data analysis

Step 21, downloading and importing the KREAP toolbox into the VM player: ~1 hour (only required once).

Step 22-23, creating and uploading input files for analysis with the KREAP toolbox: ~15 minutes.

Step 24, performing automated image analysis of a 96-well plate: ~30 minutes.

Step 25, determining re-epithelialization kinetics: less than 1 minute.

See Figure 4 for troubleshooting.

Representative growth curves for each of the target cell lines generated with the measured and modeled number of infiltrating cells over time upon treatment with the positive (i.e. hTGFα and hEGF) and negative (i.e. p38 and MEK1/2 inhibitors) controls at the recommended concentrations are provided in Figure 5. As an example, we employed this protocol to analyze the influence of Lactobacillus rhamnosus GG (LGG) and Porphyromonas gingivalis (W83) on re-epithelialization of gingival cells. Ca9-22 cells were exposed to three dosages (MOI 5, 50 and 500) of these bacteria and the re-epithelialization kinetics were determined using the KREAP toolbox. Addition of LGG at the intermediate dosage tested led to an increased repair rate (P = 0.03) (Figure 6a) and a significantly higher number of cells inside the scratched area as compared to the non-treated control (Figure 6b, c). However, higher dosages of LGG resulted in reduced re-epithelialization. This could be attributed to the acidification of the media (down to pH 5) by LGG fermentation products, leading to cell death and suppressed wound closure, which was clearly reflected by the modeled A parameter (i.e. maximum number of cells) (Figure 6b). In contrast, we obtained a clear negative dosage effect upon exposure of gingival cells to increasing dosages of P. gingivalis (Figure 6a, b). At the higher dosage tested, P. gingivalis led to reduced migration of cells into the scratched area, resulting in a significantly lower number of infiltrated cells (P < 0.001) as illustrated by the A parameter (Figure 6b, c). Nonetheless, we also showed that the repair rate (μ_m) was not significantly influenced by any of the P. gingivalis preparations (Figure 6a). After introduction of the scratch in the cell monolayer, the cells were not immediately affected by the presence of P. gingivalis (MOI 500) and started to migrate into the scratched area in an attempt to restore cell-cell contacts. However, during the course of the experiment migration of cells into the scratched area eventually ceased, resulting in an unresolved wound (Figure 6c) and a low A parameter value.

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We thank Prof. Joost Schalkwijk (Faculty of Medical Sciences, Radboud University, NL) for providing us with the HaCat keratinocyte cell line. Moreover, we want to acknowledge Koos Oosterhaven and Zeger Kruiswijk (NIZO Food Research, Ede, NL) for providing us with the Lactobacillus rhamnosus GG strain as well as Dr. Alexa M. G. A. Laheij (Academic Centre for Dentistry Amsterdam, Amsterdam, NL) for providing P. gingivalis W83.

The authors declare that they have no competing financial interests.

supplement0.png
Supplementary Fig. S2 Human transforming growth factor α (hTGFα) promotes re-epithelialization through p38 and MEK1/2 activation Stimulation of Ca9-22 cells with hTGFα in combination with either inhibitor reduced the repair rate (μ~m~ parameter) to an intermediate level. Addition of hTGFα in combination with both inhibitors decreased the repair rate to the level of the non-treated control, indicating that hTGFα can promote both migration and proliferation through activation of p38 and MEK1/2, respectively. Significant differences from the non-treated control were assessed by a one-way ANOVA using a Dunnett’s test for multiple comparisons (n = 6; ====, P < 0.05; ==**==, P < 0.0001).
supplement0.png
Supplementary Fig. S1 Optimal control concentrations on each target cell line Human transforming growth factor α (hTGF) and human epidermal growth factor (hEGF) were used as positive controls. Inhibitors of p38 and MEK1/2 were used in combination as negative control. The repair rate is represented by the μ~m~ parameter, whereas the A parameter represents the maximum number of cells inside the scratched area. The overall re-epithelialization performance (μ~m~A) was calculated relative to the non-treated control. (a) Ca9-22 gingival cell line. (b) HO-1-N-1 buccal cell line. (c) HaCat keratinocyte cell line. Significant differences from the non-treated control were assessed by a one-way ANOVA using a Dunnett’s test for multiple comparisons (n ≥ 3; ====, P < 0.05; ====, P < 0.01; ==*==, P < 0.0001).

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High-Throughput Screening Model to Quantify Re-Epithelialization Kinetics

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Introduction

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Anticipated Results

References

Acknowledgements

Additional Declarations

Supplementary Files

Associated Publications

Status:

Version 1

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