Name: Extracting the Youngs Modulus of Native Murine Pulmonary Basement Membranes from Atomic Force Microscopy Derived Force Maps (Video) | JoVE Journal
Uploaded: 2025-01-31T14:45:00.000+00:00
Duration: 10 min 55 s
Description: Learn to extract Young's modulus from murine pulmonary basement membranes using atomic force microscopy and cryosectioning. This method preserves native mechanical properties for cancer invasion studies.

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B.H., and H.C.-S. acknowledge funding from the Bavarian State Ministry of Science and the Arts through the Bavarian Research Focus Herstellung und biophysikalische Charakterisierung von dreidimensionalen Geweben (CANTER) and the Bavarian Academic Forum (BayWISS)-Doctoral Consortium Health Research. The development of the data analysis software CANTER Processing Toolbox was funded by the German Research Foundation as part of subproject 1 (CL 409/4-1/2) of the research consortium Exploring articular cartilage and subchondral bone degeneration and regeneration in osteoarthritis - ExCarBon (FOR2407-1/2). B.H. and H.C.-S. acknowledge funding from the German Research Foundation through the major instrumentation campaign GGA-HAW (INST 99/38-1). This work was further supported by the Danish Cancer Society (R204-A12454 (R.R.)) and the German Research Foundation (539446614 to R.R.).

The authors declare no competing interests.

The mechanical characteristics of BMs have received considerable interest due to their influence on various cellular functions, such as tumor budding, cellular differentiation, cell movement, and the accessibility of chromatin53,63,64,65,66,67,68. Consequently, there exists an unmet gap in the ability to assess BM mechanics in a consistent and measurable way. This protocol aims to enable AFM users to determine the Young&#39;s modulus of pulmonary BMs from healthy or pathological murine lung samples obtained from wildtype or genetically modified mice. The user-friendly graphical user interface based MATLAB application CANTER Processing Toolbox56 facilitates the downstream analysis of AFM data. This protocol is expected to be useful for other researchers conducting studies that could lead to advancements in clinical diagnosis, management, or new treatment strategies for lung disorders.
Critical steps in the protocol include ensuring that during the cryosectioning of the lung specimen, the tissue sections do not thaw at any time to prevent alterations of the mechanical properties due to freeze-thaw cycles. Therefore, it is essential to use only pre-chilled microscope slides to collect the sections and to handle them only within the chamber of the cryotome. The most crucial step during the recording of force maps on an alveolar wall is to utilize the generated slope image, which provides a qualitative overview of the stiffness distribution of the probed area, to identify an appropriate measurement location of the BM. The spatial filtering of the obtained Young&#39;s modulus values constitutes a critical step in the protocol and is a key feature of the CANTER Processing Toolbox. This filtering step enables the researcher to identify the BM, which is situated between two softer cell layers, through its distinctive stiffer footprint and extract the corresponding Young&#39;s modulus values of the BM for further analysis.
This advanced analysis workflow revealed that netrin-4 knockout mice exhibited a substantially (about two-fold) higher Young&#39;s modulus in their pulmonary basement membrane compared to wildtype litter mice53. Thus, the present protocol facilitates the comparative analysis of diverse conditions or groups.
In addition to AFM, numerous methodologies exist for examining the mechanical properties of biomaterials, encompassing optical or magnetic tweezers69,70,71 at the molecular level, micro-indentation techniques72,73 at an intermediate scale and confined or unconfined compression testing74,75 at the macroscopic level. Specifically, pressure myography, tensile testing76,77 and rheology78 have been employed to assess the BM stiffness of vascular samples and reconstituted BM matrices. However, techniques like pressure myography and tensile testing can only assess the mechanical characteristics of complete tissues or whole tissue structures, such as entire blood vessels, which include various cell layers and structural elements. As a result, when using these methods to evaluate BM biomechanics, the mechanical properties of non-BM, such as cellular components, are always superimposed on the BM results, making it difficult to isolate the specific properties of the BM itself.
In this protocol, the feature of interest (BM) is extracted through spatial filtering of the force-map results. A limitation of this approach is the requirement that the feature of interest is discernible and identifiable as a distinct pattern in the obtained Young&#39;s modulus maps or any other available map channel. For instance, the BM in alveolar tissue is identifiable solely due to its interconnected structure, which exhibits a significantly higher Young&#39;s modulus compared to the surrounding cells. Consequently, the BM manifests as a continuous bright stripe in the obtained Young&#39;s modulus maps. Nevertheless, other biological structures exhibit mechanical properties that are not sufficiently distinct from those of the surrounding tissue to enable spatial filtering in the map results. Although the protocol can be combined with other methods to identify structures in the recorded force maps, such as immunofluorescence staining, this approach may yield results that are challenging to interpret. This complication may occur because staining procedures can alter the mechanical properties of tissues. Consequently, any processing or staining of the tissue prior to AFM measurements should be conducted only when no alternative method is available to identify the feature of interest. Moreover, it is important to perform appropriate control experiments comparing the biomechanical properties of stained and unstained samples.
The protocol introduces a method for identifying target structures based on Young&#39;s modulus contrast. Consequently, it may be applied to tissues with an anatomical BM similar to that of the lung, including the thyroid gland, colon, and prostate. (see Extended Data Figure in Hartmann et al.59). While initially developed for analyzing BM mechanics, this protocol and the CANTER Processing Toolbox56 are versatile enough to examine any mechanically distinct and connected region within AFM force maps (refer to instructions at&#160;www.github.com/CANTERhm/CANTER_Processing_Tool/wiki). This broad applicability makes this tool valuable across the AFM field and supports the increasing focus on mechanobiology in the wider scientific community.&#160;

AFM force maps have emerged as a widely utilized technique for determining the nanomechanical properties of a diverse range of biological samples with nanometer spatial resolution and piconewton force sensitivity1,2,3,4,5,6,7,8,9,10,11,12. Pioneering research on the application of AFM measurements to biological samples under physiological conditions was conducted by P. Hansma and colleagues13,14,15,16,17,18,19,20. Subsequently, AFM force measurements were employed to assess the mechanical properties of individual molecules21, living cells and their cytoskeleton9,10,22,23,24,25,26, tissues and tissue sections6,8,11,27,28,29,30,31, as well as biological hydrogels3,4,32. In our research, we used AFM to examine the mechanical properties of biological and chemical bonds18,33,34,35,36,37 and to measure the nanomechanical characteristics of individual cells38,39,40. Moreover, measurements of growth plate cartilage8 demonstrated that the collagen architecture and Young&#39;s modulus of the extracellular matrix (ECM) direct chondrocyte division and, consequently, the growth direction of the murine growth plate during embryonic development. Furthermore, we investigated the changes associated with cartilage degeneration and osteoarthritis in articular cartilage2,41,42,43,44,45,46,47.
In recent years, numerous AFM investigations have examined the mechanical properties of both healthy and pathological pulmonary tissue48,49,50,51,52. However, these investigations primarily examined overall tissue mechanics, not focusing on specific tissue components such as the BM. The BM constitutes a thin layer (100 nm - 400 nm in humans) of a specialized ECM structure that lines the majority of mammalian organs and tissue structures such as neurons, muscles, adipocyte tissues, and blood vessels. We discovered that the mechanical properties of the murine pulmonary BM play a pivotal role during the metastasis formation in a way that a softer BM correlates with a higher survival probability in breast and kidney cancer patients53. Furthermore, this investigation revealed that the secreted extracellular matrix protein netrin-4 decreases the Young&#39;s modulus of the BM through a stoichiometric 1:1 interaction with laminin &#947;1, a key component present in nearly all laminin networks inside BMs40.
Here, we present the visualization of our developed protocol to determine the Young&#39;s modulus (EBM) of the 100 - 200 nm thin murine pulmonary BM. The Young&#39;s modulus of the BM is a measure of its stiffness and is defined as the ratio of stress (force per unit area) versus the resulting axial strain (displacement) during a linear elastic deformation54, in this case, a small compression of the BM by the indenting AFM tip. In an AFM experiment, the force and the displacement (indentation depth) can be obtained from the AFM cantilever deflection and the cantilever position, and Young&#39;s modulus (the stress-strain-relation) can be extracted from the resulting force versus indentation curve by using a suitable elastic model, which accounts for the geometry of the indenting tip (in this case a modified Hertz Model55). The main steps are shown in Figure 1. Initially, this protocol delineates the methodology for preparing and embedding murine lung tissue samples in OCT compound (see step 1), thereby facilitating the subsequent cryosectioning procedure (step 2) that enables the determination of the BM stiffness utilizing AFM force maps. The cryosectioning technique presented here, which utilizes one-sided and double-sided tape, enables the sectioning of lung tissue without the requirement of fixation and without thawing of the section. The detailed AFM procedure for collecting suitable data to assess BM stiffness is outlined in the third section of the protocol. In the next section of the protocol, we explain how the generated force volumes can be automatically analyzed (step 4.1) using an in-house developed MATLAB-based software, the CANTER Processing Toolbox56. In this step, the Young&#39;s modulus is extracted from each recorded force-indentation curve by fitting a modified Hertz model, which is corrected for the indenter geometry, in this case, a four-sided pyramid55. Finally, we describe in steps 4.2 and 4.3 how to apply the Spatial Filtering Tool and the R2 Filtering Tool of the developed toolbox to extract the Young&#39;s modulus values specific to the basement membrane (BM) from the comprehensive set of Young&#39;s modulus values obtained in the force map containing all tissue compartments of the alveolar wall.

<table><tbody><tr><td>1 mL Syringe</td><td>B Braun</td><td>9166017V</td><td>Injekt-F</td></tr><tr><td>10 mL Syringe</td><td>B Braun</td><td>4606108V</td><td>Injekt Luer Solo</td></tr><tr><td>15 mL Falcon tube</td><td>Sarstedt</td><td>62.554.002</td><td>screw cap tube</td></tr><tr><td>Cantilever - MLCT</td><td>Bruker AFM Probes</td><td>3444</td><td>AFM cantilever with a pyramidal tip shape</td></tr><tr><td>Cryotome blades</td><td>Leica Biosystems</td><td>14035843496</td><td>Low-profile disposable blades DB80LX</td></tr><tr><td>Cryotome sample holder</td><td>Leica Biosystems</td><td>14047740044</td><td>Specimen disc 30</td></tr><tr><td>Cyotome</td><td>Leica Biosystems</td><td>CM1950</td><td>Leica Cryostat</td></tr><tr><td>Direct Overlay Extension</td><td>Bruker</td><td></td><td>Software extension for the JPK SPM Software which enables to import the optical image of the inverted microscope into the Data Viewer of the SPM software.</td></tr><tr><td>Disposable base mold</td><td>Science Services</td><td>SA62534-15</td><td>Tissue-Tek Cryomold 15x15x5 mm</td></tr><tr><td>Double-sided tape</td><td>tesa Film</td><td>56661-00002</td><td>Photo Film Tape</td></tr><tr><td>Fixed-Spring Cantilever Holder</td><td>Bruker</td><td></td><td></td></tr><tr><td>Inverted Microscope - Leica DMi8</td><td>Leica Microsystems</td><td></td><td></td></tr><tr><td>JPK Motorized Stage</td><td>Bruker</td><td></td><td></td></tr><tr><td>JPK NanoWizard 4XP BioScience</td><td>Bruker</td><td></td><td></td></tr><tr><td>JPK SPM Software</td><td>Bruker</td><td></td><td></td></tr><tr><td>K5 CMOS Microscope Kamera</td><td>Leica Microsystems</td><td></td><td></td></tr><tr><td>MATLAB</td><td>Mathworks</td><td></td><td>Version R2024a or higher</td></tr><tr><td>MATLAB - Curve Fitting Toolbox&amp;nbsp;</td><td>Mathworks</td><td></td><td></td></tr><tr><td>MATLAB - Image Processing Toolbox</td><td>Mathworks</td><td></td><td></td></tr><tr><td>MATLAB - Signal Processing Toolbox&amp;nbsp;</td><td>Mathworks</td><td></td><td></td></tr><tr><td>MATLAB - Statistics and Machine Learning Toolbox</td><td>Mathworks</td><td></td><td></td></tr><tr><td>Microscope slides</td><td>Carl Roth</td><td>H869.1</td><td>Plain microscope slides for cantilever calibration</td></tr><tr><td>Microscope slides - frosted edge</td><td>Carl Roth</td><td>H870.1</td><td>Microscope slides with frosted edge for cryosectioning</td></tr><tr><td>Needle &amp;oslash;0.9 mm &amp;times; 25 mm</td><td>B Braun</td><td>4657500</td><td>OCT injection&amp;nbsp; into the lung sample</td></tr><tr><td>Needle &amp;oslash;0.9 mm &amp;times; 70 mm</td><td>B Braun</td><td>4665791</td><td>Long needle to apply PBS under the AFM</td></tr><tr><td>OCT compound</td><td>Sakura Finetek</td><td>4583</td><td>Tissue-Tek O.C.T. Compound</td></tr><tr><td>Phosphate Buffered Saline</td><td>Bio&amp;amp;Sell</td><td>BS.L1825</td><td>PBS solution without Ca2+, Mg2+, 500 mL</td></tr><tr><td>QI Advanced Imaging Extension</td><td>Bruker</td><td></td><td>Software extension for the JPK SPM Software which provides for each recorded image pixel the whole underlying force curve.</td></tr><tr><td>Scalpel</td><td>B Braun</td><td>5518083</td><td>Surgical Disposable Scalpel</td></tr><tr><td>Scissors</td><td>Kaut-Bullinger</td><td>M681700</td><td>Precise Scissors 13 cm&amp;nbsp;</td></tr><tr><td>Single-sided tape</td><td>tesa Film</td><td>57330-00000</td><td>crystal clear tape, 33 m x 19 mm</td></tr><tr><td>Slide box</td><td>GWL Storing Systems</td><td>K50W</td><td>Slidebox for 50 slides</td></tr><tr><td>Stereo Microscope - Stemi DR1663</td><td>Zeiss</td><td></td><td></td></tr><tr><td>Tweezers - Vomm SS-SA-ESD</td><td>Eleshop</td><td>ELE002121</td><td></td></tr></tbody></table>

extracting the young's modulus of native murine pulmonary basement membranes from atomic force microscopy derived force maps

Extracting the Young's Modulus of Native Murine Pulmonary Basement Membranes from Atomic Force Microscopy Derived Force Maps

Atomic force microscopy (AFM) allows the characterization of the mechanical properties of a sample with a spatial resolution of several tens of nanometers. Because mammalian cells sense and react to the mechanics of their immediate microenvironment, the characterization of biomechanical properties of tissues with high spatial resolution is crucial for understanding various developmental, homeostatic, and pathological processes. The basement membrane (BM), a roughly 100 - 400 nm thin extracellular matrix (ECM) substructure, plays a significant role in tumor progression and metastasis formation. Although determining Young&#39;s modulus of such a thin ECM substructure is challenging, biomechanical data of the BM provides fundamental new insights into how the BM affects cell behavior and, in addition, offers valuable diagnostic potential. Here, we present a visualized protocol for assessing BM mechanics in murine lung tissue, which is one of the major organs prone to metastasis. We describe an efficient workflow for determining the Young&#39;s modulus of the BM, which is located between the endothelial and epithelial cell layers in lung tissue. The step-by-step instructions comprise murine lung tissue freezing, cryosectioning, and AFM force-map recording on tissue sections. Additionally, we provide a semi-automatic data analysis procedure using the CANTER Processing Toolbox, an in-house developed user-friendly AFM data analysis software. This tool enables automatic loading of recorded force maps, conversion of force versus piezo-extension curves to force versus indentation curves, computation of Young&#39;s moduli, and generation of Young&#39;s modulus maps. Finally, it shows how to determine and isolate Young&#39;s modulus values derived from the pulmonary BM through the use of a spatial filtering tool.

After the identification and measurement of an intact alveolar wall, the primary outcome of this protocol is the filtered Young's modulus values of the BM. It is important to note that it is not possible to find a suitable alveolar wall for AFM measurement in every tissue section. In our experimental observations, approximately 75% of the cryosections derived from murine lung specimens exhibited a quantifiable alveolar wall. To accurately determine the spatial distribution of Young's modulus in a pulmonary BM, we advise to employ force maps spanning either 3 µm x 3 µm or 4 µm x 4 µm. This approach ensures sufficient resolution for examining mouse pulmonary BMs, which typically measure 100 nm - 200 nm in thickness. Therefore, the experimental approach involves capturing 50 x 50 force curves for each force map, yielding a total of 2,500 force curves. Within the force map, the force curves are evenly spaced. This implies that in addition to the Young's modulus of the BM, the tissue structures surrounding the BM are probed even in the small force maps. Therefore, to accurately and selectively determine the Young's modulus exclusively of the pulmonary BM, we implemented a two-step filtering process in this protocol.
The initial filtering step of operator-dependent spatial filtering selects force curve fit results originating from the murine pulmonary BM, comprising approximately 10% to 25% of the total result values contained in the analyzed force map. After this initial spatial filtering, approximately 250 - 625 fit results are retained for further analysis. The next filtering step ensures that only the BM-related results originating from force curves adequately described by the modified Hertz model are included. Therefore, the coefficient of determination (R2) of the modified Hertz model fit is used as the filter criterion. Our empirical experience suggests that keeping results with R2 values higher than 0.96 is suitable for fit results obtained by adhering to this protocol. It is important to note that the R2 value is significantly influenced by the quality (smoothness) and length of the force curve's baseline, the determination of the contact point, and the convergence of the fitted model. Following the application of both filtering procedures, approximately 100 to 500 Young's modulus values typically remain for the BM of a single alveolar wall.
The distribution of these remaining Young's modulus values from the BM can be visualized using a histogram (Figure 4A). It is important to note that the resulting Young's modulus values of the pulmonary BM follow a log-normal distribution, which is commonly observed for random variables that can only attain positive values61. This is visualized by the QQ plot in Figure 4B. Consequently, a normal (Gaussian) distribution can be fitted to the distribution of the log-transformed Young's modulus (E) values. Here, the natural logarithm (ln) was used to transform the E values. The peak position of the distribution (µ) and standard deviation (σ) were extracted from this fit and subsequently retransformed to obtain the representative Young's modulus, denoted as EBM, using the following equation:
<img alt="Exponential function formula \( E_{BM}(\mu) = e^{\mu} \) used in mathematical modeling." src="/files/ftp_upload/67784/67784eq01.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 1">
Note that following the retransformation, the standard deviation interval is no longer symmetrical around the peak value. The negative (σ-) and positive (σ+) edges of the standard deviation interval can be calculated using the following expressions:
<img alt="Static equilibrium, formula σ = e^(μ-σ) - e^μ, equations, physics calculation." src="/files/ftp_upload/67784/67784eq02.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 2">
<img alt="Log-normal distribution equation, σ₊=e^(μ+σ)−e^μ, formula for statistical analysis." src="/files/ftp_upload/67784/67784eq03.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 3">
These equations are a consequence of the fact that the exponential function is the inverse function of the natural logarithm62.
After retransforming the peak value μ = 9.31 and the standard deviation σ = 0.18 determined from the histogram in Figure 4A, the representative Young's modulus value is EBM = 11.05 kPa with a standard deviation interval of [-1.82 kPa, +2.18 kPa]. Alternatively, a log-normal distribution can be fitted to the histogram of untransformed Young's modulus (E) values to determine the characteristic parameters of the distribution.
It is recommended that at least four walls per mouse are analyzed to obtain a robust representative result as we have shown in detail in Hartmann et al.59. To determine the representative Young's modulus EBM for a mouse, the log-transformed values of all four walls were plotted in one combined histogram and µ and σ were determined by fitting a normal distribution. Subsequently, µ and σ are retransformed as previously described to retrieve EBM and the standard deviation interval for the subject mouse.
<img alt="Sample preparation to AFM force volume analysis; includes cryosectioning, data fitting, and analysis." class="xfigimg" src="/files/ftp_upload/67784/67784fig01.jpg" data-altupdatedat="1788304762000" data-alt="Figure 1"> 
Figure 1: Overview of the main protocol steps to determine the Young's modulus of a murine pulmonary basement membrane. The initial step involves obtaining and preparing murine lungs, followed by embedding them. Hence, the lung is injected with a combination of OCT medium and PBS, and then completely immersed in the OCT compound. Afterwards, 15 µm thick lung tissue sections are obtained through cryosectioning with a cryotome. In this protocol, we detail the process of employing one-sided and two-sided adhesive tapes to secure samples in place during the cutting process. Subsequently, the Young's modulus values of the BM are determined through AFM force map measurements on the tissue sections. Following the completion of the force curve analysis process, spatial and R² filtering is applied to isolate the Young's modulus results of the structure of interest, specifically the BM (shown in green in the force map and quantified in the log-transformed Young's modulus distribution). <a href="https://www.jove.com/files/ftp_upload/67784/67784fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Microscopy images of cellular structure; magnified views; scan data; cellular imaging analysis." class="xfigimg" src="/files/ftp_upload/67784/67784fig02.jpg" data-altupdatedat="1788304762000" data-alt="Figure 2"> 
Figure 2: An exemplary force map AFM experiment conducted on a murine lung tissue section. (A) Bright-field microscopy overview image of a murine lung tissue section, enabling the identification of suitable intact alveolar walls situated between two alveoli. On the right side of the image, the triangular-shaped MLCT cantilever F of the AFM is visible. (B) Magnified view of a selected wall within the tissue section. (C) Slope and (D) height channel of an overview 15 x 15 µm map containing 50 x 50 force curves of the alveolar wall. In the slope channel, the BM can be identified as a bright line (white arrow), indicating a structure of increased stiffness within the wall. The height channel confirms the integrity of the wall, showing no evidence of rupture. Following the identification of the BM in the overview 15 x 15 µm map, a smaller 4 x 4 µm map (E: slope channel, F: height channel) with 50 x 50 force curves is recorded. Scale bars: (A) 200 µm and (B-D) 25 µm. The ranges of the color scales of the shown AFM images are (C) 2.36 - 9.29 nN/µm, (D) 0 - 3.38 µm, (E) 2.36 - 9.29 nN/µm (overview image) and 2.42 - 8.37 nN/µm (smaller image), (F) 0 - 3.38 µm (overview image) and 0 - 1.99 µm (smaller image), from dark to bright. Linear color scales were used for all AFM images. <a href="https://www.jove.com/files/ftp_upload/67784/67784fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Young's modulus maps, histograms; elasticity distribution, micromechanics, kPa chart, diagram." class="xfigimg" src="/files/ftp_upload/67784/67784fig03.jpg" data-altupdatedat="1788304762000" data-alt="Figure 3"> 
Figure 3: Visualization of the spatial filtering procedure. (A) The Young's modulus map resulting from the force curve analysis, as it is shown in the Result Filtering Tool to enable the spatial filtering of the results. The BM is identifiable as a bright (high Young's modulus values) stripe surrounded by softer tissue compartments. (B) Histogram of the Young's modulus values corresponding to the unfiltered map (A). After the (C) application of the spatial filter mask (green area), (D) the histogram exclusively comprises Young's modulus values from the green highlighted region, which was identified as the BM. Note that the residual soft values observable on the left side of the histogram can be attributed to poorly converging fits, which will be eliminated in the subsequent R² filtering step. <a href="https://www.jove.com/files/ftp_upload/67784/67784fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Histogram and Q-Q plot of BM Young's modulus (log scale), data distribution and normality assessment." class="xfigimg" src="/files/ftp_upload/67784/67784fig04.jpg" data-altupdatedat="1788304762000" data-alt="Figure 4"> 
Figure 4: Young's modulus distribution of a murine pulmonary BM received by following this protocol. (A) Log-normalized histogram of the resulting BM Young's modulus values (N = 325). By fitting a normal distribution (black solid line), the mean value µ = 9.31 with a standard deviation of σ = 0.18 is determined. Following retransformation, this corresponds to a Young's modulus of the BM of EBM = 11.05 kPa with an asymmetric standard deviation interval of [-1.82 kPa, +2.18 kPa]. (B) QQ Plot of the quantiles of the logarithmized BM Young's modulus values versus the quantiles of a standard normal distribution. This plot demonstrates that, with the exception of some values in the left and right tails of the distribution, the resulting Young's modulus values are mainly log-normal distributed. <a href="https://www.jove.com/files/ftp_upload/67784/67784fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

This protocol visualizes how to prepare cryosections of murine lung tissue, perform atomic force microscopy force map experiments, and analyze the data to determine Young's modulus of the native murine pulmonary basement membrane.

Atomic force microscopy (AFM) allows the characterization of the mechanical properties of a sample with a spatial resolution of several tens of ...

extracting-young-s-modulus-native-murine-pulmonary-basement-membranes

Research

JoVE Journal

Bioengineering

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Learn to extract Young's modulus from murine pulmonary basement membranes using atomic force microscopy and cryosectioning. This method preserves native mechanical properties for cancer invasion studies.

Extracting the Young's Modulus of Native Murine Pulmonary Basement Membranes from Atomic Force Microscopy Derived Force Maps

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