The authors want to thank Dr. Taylor Ware for allowing us to use his environmental DMA.
This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program [W81XWH-15-1-0607]. Opinions, interpretations, conclusions, and recommendations are those of the authors and not necessarily endorsed by the Department of Defense.

1. Preparation of polymer samples for testing
<ol>
	<li>Synthesize the softening thiol-ene polymer according to previous protocols inside a fume hood.1,2,4,18 Briefly, mix quantitative amounts of thiol to alkene monomers with a total of 0.1 wt% photo initiator.
	<ol>
		<li>Prepare a 20 mL glass vial for polymer mixing. Cover the vial in aluminum foil to prevent incident light from contacting the monomer solution and keep at room temperature (RT). Use all chemicals as received without further purification.</li>
		<li>For fully softening polymer, add 50 mol% 1,3,5-triallyl-1,3,5-triazine-2,4,6(1H,3H,5H)-trione (TATATO), 45 mol% trimethylolpropane tris(3-mercaptopropionate) (TMTMP), and 5 mol% Tris[2-(3-mercaptopropionyloxy)ethyl] isocyanurate (TMICN) to the covered vial using a disposable plastic pipette.</li>
		<li>Add 0.1 wt% of the photoinitiatior 2,2-dimethoxy-2-phenylacetophenone (DMPA) to the polymer solution.</li>
		<li>Mix the contents inside the vial thoroughly by planetary speed mixing without exposing the solution to light. 
		NOTE: The polymer solution is sensitive to light and will start to polymerize after 45 to 60 min, even if covered with foil. Therefore, use the polymer solution as quickly as possible after mixing.</li>
	</ol>
	</li>
	<li>Spin coat the polymer solution prepared in section 1.1 as thin films between 5 to 50 &#181;m in thickness on microscopic glass slides or silicon wafers as a carrier substrate according to the spin curve (Figure 2). For 30 &#181;m film thickness, spin at 600 rpm for 30 s. 
	NOTE: When using a different SMP formulation, the spin speed and time may vary depending on the viscosity of the polymer solution.</li>
	<li>Transfer the polymer films on&#160;the carrier substrate immediately after spinning to the crosslinking chamber. Photo-polymerize the films for 60 min under 365 nm UV bulbs and post-cure for 24 h in a vacuum oven at 120 &#176;C to further complete the conversion.</li>
	<li>Cut the cured polymer films into rectangular samples with widths of 4.5 mm and lengths of 50 mm for the DMA testing. Thicknesses may vary from 5 to 50 &#181;m. The samples can be brought into measuring geometry applying two different methods (choose step 1.4.1 or 1.4.2).
	<ol>
		<li>Cut the cured polymer films into rectangles using a CO2 laser. Set the CO2 laser micromachining parameters to 5.0% power (2.0 W) and 10.0% speed (0.254 m/s) (Figure 3A).</li>
		<li>Define the DMA samples using photolithography in a Class 10000 cleanroom facility (Figure 3B). Use the SMP-on-glass or wafer substrates as the starting substrates in the cleanroom.
		<ol>
			<li>Deposit low temperature silicon nitride to act as a hard mask for the following plasma etching processes. Pattern the device outline/shape using standard lithography techniques. Use a plasma etcher with SF6 and O2 plasma to remove the hard mask and SMP layer, respectively.</li>
			<li>After the SMP layer is plasma etched down to the glass slide/wafer, etch the remaining silicon nitride hard mask away in diluted 10:1 HF dip.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Delaminate the test devices from the glass slide/wafer by soaking in deionized water as the last step.</li>
</ol>
2. Machine setup
<ol>
	<li>Use a dynamic mechanical analyzer (DMA) with an immersion system. Equip the machine with the immersion fixture in tension mode (Figure 1). Connect the liquid nitrogen to the machine and enable LN2/air as a gas source for the furnace.</li>
	<li>Write the method for dry measurements with the machine software, including the following three steps: conditioning, oscillation temperature ramp, and conditioning end of test, then set up the parameters as follows:
	<ol>
		<li>Set the following parameters for the conditioning options: mode = active, select &#8220;tension&#8221;, axial force = 0.05 N, set initial value to &#8220;on&#8221;, sensitivity = 0.0 N, proportional force mode = force tracking, compensate for modulus = on, select &#8220;axial force&#8221; then set dynamic force to 25.0%, minimum axial force = 0.05 N, programmed extension below 0.0 Pa, mode enabled, strain adjust = 0.05%, minimum strain = 0.1%, maximum strain = 0.5%, minimum force = 0.05 N, maximum force = 0.2 N.</li>
		<li>Set the following parameters for the oscillation temperature ramp: start temperature = 10 &#176;C, inherit set point = off, soak time = 0.0 s, wait for temperature = on, ramp rate = 2.0 &#176;C/min, end temperature = 100 &#176;C, soak time after ramp = 0.0 s, sampling rate = 1 pts/s, strain % = 0.275%, single point, frequency = 1 Hz.</li>
		<li>Set the following parameters for the conditioning end of test: environmental control = off, axial force adjustment = on, mode disabled, transducer/motor = off.</li>
	</ol>
	</li>
	<li>Write the method for the immersion testing with the machine software including the following four steps: conditioning, oscillation-time, oscillation-temperature ramp, and conditioning-end of test, then set up the parameters as follows:
	<ol>
		<li>Set the following parameters for the conditioning options: mode = active, select &#8220;tension&#8221;, axial force = 0.05 N, set initial value to &#8220;on&#8221;, sensitivity = 0.0 N, proportional force mode = force tracking, compensate for modulus = on, select &#8220;axial force&#8221; and set dynamic force to 25.0%, minimum axial force = 0.05 N, programmed extension below 0.0 Pa, mode enabled, strain adjust = 0.05%, minimum strain = 0.1%, maximum strain = 0.5%, minimum force = 0.05 N, maximum force = 0.2 N.</li>
		<li>Set the following parameters for the oscillation time: temperature = 39.5 &#176;C, inherit set point = off, soak time = 0.0 s, wait for temperature = off, duration = 3600.0 s, sampling rate = 1 pts/s, strain % = 0.275%, single point, frequency = 1 Hz.</li>
		<li>Set the following parameters for the oscillation temperature ramp: start temperature = 10 &#176;C, inherit set point = off, soak time = 300.0 s, wait for temperature = off, ramp rate = 2.0 &#176;C/min, end temperature = 85 &#176;C, soak time after ramp = 300.0 s, sampling rate = 1 pts/s, strain % = 0.275%, single point, frequency = 1 Hz.</li>
		<li>Set the following parameters for the conditioning end of test: environmental control = off, axial force adjustment = on, mode disabled, transducer/motor = off.</li>
	</ol>
	</li>
</ol>
3. Sample loading and unloading for dry measurements
<ol>
	<li>Measure the actual thickness of the polymer specimen for dry (in air) testing with Caliper with 0.001 mm precision.</li>
	<li>Enter the sample name, description, and sample geometry into the software.</li>
	<li>Set the loading gap to 15 mm and load the sample. Make sure to center and align specimen before the clamps are screwed hand tight or use a torque wrench with 0.1 N (Figure 3C).</li>
	<li>Close the furnace and start the measurement using the methods described in section 2.2.</li>
	<li>Wait until the measurement is over. Open the furnace and remove the polymer sample from the machine.</li>
</ol>
4. Sample loading and unloading for immersion testing
<ol>
	<li>Measure the actual thickness of the polymer specimen for immersion testing in PBS with Caliper with 0.001 mm precision.</li>
	<li>Enter the sample name, description, and sample geometry into the software.</li>
	<li>Prepare the setup with the immersion beaker fixed with a clamp at the upper grip (Figure 4A,B).</li>
	<li>Set the loading gap to 15 mm and load the sample (Figure 4C). Make sure to center and align the specimen (Figure 5) before the clamps are screwed hand tight or use a torque wrench with 0.1 N.</li>
	<li>Place the immersion bath on the bottom fixture and screw it tightly (Figure 4D). Fill the bath with RT PBS (Figure 4E), place the lid on top (Figure 4F), close the furnace (Figure 4G), and start the measurement immediately using the methods described in section 2.3. Ensure that the drain is closed (Figure 4H).</li>
	<li>Wait until the measurement is over. Remove the PBS from the immersion baths using the drain. Open the furnace, remove the lid from the beaker, unscrew the immersion beaker, lift it, and remove the polymer sample from the machine.</li>
	<li>Clean the clamps and immersion beaker with de-ironed water to remove any remaining salt from the PBS.</li>
</ol>
5. Measurements
<ol>
	<li>Measure the polymer in air without the immersion beaker. Follow the instructions for sample loading and unloading as described in section 3. Repeat this measurement at least 3x to gather results with statistical relevance.</li>
	<li>Measure the polymer inside the immersion bath following the steps described in section 4. Repeat the measurement at least 3x to gather results with statistical relevance.</li>
</ol>
6. Data interpretation
<ol>
	<li>Open the results tab in the machine software, where the raw data can be viewed in a table format or plotted as a graph.</li>
	<li>Plot the first part of the immersion measurement, the oscillation-time measurement, as storage modulus over time to evaluate the softening kinetics. The curve displays how fast the modulus of the polymer decreases over time while immersed in PBS.</li>
	<li>Note the time at which the modulus levels out. This represents the time for softening under physiological conditions.</li>
	<li>If the polymer is not fully softened after the set immersion time of 1 h, repeat the measurement with increased immersion time.</li>
	<li>Display the oscillation-temperature ramps of the measurements in air and PBS as storage modulus on the left axis and tan delta on the right axis over temperature to display the thermomechanical properties of the polymer before (dry) and after (in PBS) plasticization.</li>
	<li>Plot the data for the dry (air) and PBS measurements together to better display the changes in thermomechanical properties due to plasticization.</li>
	<li>Note the storage modulus of the dry material at 25 &#176;C and of the soaked sample at 37 &#176;C, as these are relevant numbers for evaluating how much the polymer will soften during implantation.</li>
	<li>Note the changes in tan delta peak between the dry and soaked samples.</li>
	<li>Export the data as a .txt or .csv file for further data interpretation and plotting with other software.</li>
</ol>

<ol>
	<li>Garcia-Sandoval, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chronic+softening+spinal+cord+stimulation+arrays.">Chronic softening spinal cord stimulation arrays.</a> Journal of Neural Engineering. 15 (4), 045002 (2018).</li><li>Ecker, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sterilization+of+Thiol-ene/Acrylate+Based+Shape+Memory+Polymers+for+Biomedical+Applications.">Sterilization of Thiol-ene/Acrylate Based Shape Memory Polymers for Biomedical Applications.</a> Macromolecular Materials and Engineering. 302 (2), 1600331 (2017).</li><li>Simon, D. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+and+demonstration+of+an+intracortical+probe+technology+with+tunable+modulus.">Design and demonstration of an intracortical probe technology with tunable modulus.</a> Journal of Biomedical Materials Research Part A. 105 (1), 159-168 (2017).</li><li>Do, D. -. H., Ecker, M., Voit, W. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+a+Thiol-Ene/Acrylate-Based+Polymer+for+Neuroprosthetic+Implants.">Characterization of a Thiol-Ene/Acrylate-Based Polymer for Neuroprosthetic Implants.</a> ACS Omega. 2 (8), 4604-4611 (2017).</li><li>Ware, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thiol-ene/acrylate+substrates+for+softening+intracortical+electrodes.">Thiol-ene/acrylate substrates for softening intracortical electrodes.</a> Journal of Biomedical Materials Research Part B-Applied Biomaterials. 102 (1), 1-11 (2014).</li><li>Ware, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thiol-Click+Chemistries+for+Responsive+Neural+Interfaces.">Thiol-Click Chemistries for Responsive Neural Interfaces.</a> Macromolecular Bioscience. 13 (12), 1640-1647 (2013).</li><li>Ware, T., Simon, D., Rennaker, R. L., Voit, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Smart+Polymers+for+Neural+Interfaces.">Smart Polymers for Neural Interfaces.</a> Polymer Reviews. 53 (1), 108-129 (2013).</li><li>Ware, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fabrication+of+Responsive,+Softening+Neural+Interfaces.">Fabrication of Responsive, Softening Neural Interfaces.</a> Advanced Functional Materials. 22 (16), 3470-3479 (2012).</li><li>Stiller, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chronic+Intracortical+Recording+and+Electrochemical+Stability+of+Thiol-ene/Acrylate+Shape+Memory+Polymer+Electrode+Arrays.">Chronic Intracortical Recording and Electrochemical Stability of Thiol-ene/Acrylate Shape Memory Polymer Electrode Arrays.</a> Micromachines. 9 (10), 500 (2018).</li><li>Biran, R., Martin, D. C., Tresco, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuronal+cell+loss+accompanies+the+brain+tissue+response+to+chronically+implanted+silicon+microelectrode+arrays.">Neuronal cell loss accompanies the brain tissue response to chronically implanted silicon microelectrode arrays.</a> Experimental Neurology. 195 (1), 115-126 (2005).</li><li>Polikov, V. S., Tresco, P. A., Reichert, W. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Response+of+brain+tissue+to+chronically+implanted+neural+electrodes.">Response of brain tissue to chronically implanted neural electrodes.</a> Journal of Neuroscience Methods. 148 (1), 1-18 (2005).</li><li>Lacour, S. P., Courtine, G., Guck, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Materials+and+technologies+for+soft+implantable+neuroprostheses.">Materials and technologies for soft implantable neuroprostheses.</a> Nature Reviews Materials. 1 (10), 16063 (2016).</li><li>Stiller, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Meta-Analysis+of+Intracortical+Device+Stiffness+and+Its+Correlation+with+Histological+Outcomes.">A Meta-Analysis of Intracortical Device Stiffness and Its Correlation with Histological Outcomes.</a> Micromachines. 9 (9), 443 (2018).</li><li>Lecomte, A., Descamps, E., Bergaud, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+review+on+mechanical+considerations+for+chronically-implanted+neural+probes.">A review on mechanical considerations for chronically-implanted neural probes.</a> Journal of Neural Engineering. 15 (3), 031001 (2018).</li><li>Nguyen, J. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanically-compliant+intracortical+implants+reduce+the+neuroinflammatory+response.">Mechanically-compliant intracortical implants reduce the neuroinflammatory response.</a> Journal of Neural Engineering. 11 (5), 056014 (2014).</li><li>Ecker, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+Softening+Polymers+to+Multi-Material+Based+Bioelectronic+Devices.">From Softening Polymers to Multi-Material Based Bioelectronic Devices.</a> Multifunctional Materials. , (2018).</li><li>Hess, A. E., Potter, K. A., Tyler, D. J., Zorman, C. A., Capadona, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Environmentally-controlled+Microtensile+Testing+of+Mechanically-adaptive+Polymer+Nanocomposites+for+ex+vivo+Characterization.">Environmentally-controlled Microtensile Testing of Mechanically-adaptive Polymer Nanocomposites for ex vivo Characterization.</a> Journal of Visualized Experiments. (78), e50078 (2013).</li><li>Black, B. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro+compatibility+testing+of+thiol-ene/acrylate-based+shape+memory+polymers+for+use+in+implantable+neural+interfaces.">In vitro compatibility testing of thiol-ene/acrylate-based shape memory polymers for use in implantable neural interfaces.</a> Journal of Biomedical Materials Research Part A. 106 (11), 2891-2898 (2018).</li><li>Hassler, C., Boretius, T., Stieglitz, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polymers+for+neural+implants.">Polymers for neural implants.</a> Journal of Polymer Science Part B: Polymer Physics. 49 (1), 18-33 (2011).</li></ol>

The authors declare that they have no competing financial interests.

The use of environmental DMA allows the study of the behavior of various polymers used as substrates for neural implants19 or other biomedical devices in solution and to mimic in vivo conditions. This includes, but is not limited to, polyimide, parylene-C, PDMS, and SU-8. Hydrogels and extracellular matrix (ECM) materials can also be investigated using this method. The differences of overall softening of the polymer as well as its softening kinetics can be easily compared between differen...

A new generation of materials used as substrates for neural implants comprises softening shape memory polymers1,2,3,4,5,6,7,8,9. These materials are stiff enough during implantation to overcome critical buckling forces, but they become up to three orders of magnitude softer after implantation in a body environment. It is predicted that these materials show a better device-tissue interaction due to the reduced mismatch in modulus as compared to traditional materials used in neural implants, such as tungsten or silicon. Traditional, stiff devices show inflammatory response after implantation, followed by tissue encapsulation and astroglial scarring which often results in device failure10,11. It is a common assumption that less stiff devices minimize the foreign body response12,13,14. The stiffness of a device is dictated by its cross-sectional area and modulus. Therefore, it is important to reduce both factors to improve the device compliance and, ultimately, the device tissue interaction.
The work on softening polymers was inspired by the work of Nguyen et al.15, who demonstrated that mechanically-compliant intracortical implants reduce the neuroinflammatory response. They have previously used mechanically-adaptive poly(vinyl acetate)/tunicate cellulose nanocrystal (tCNC) nanocomposites (NC), which become compliant after implantation.
The Voit lab, on the other hand, uses the highly tunable system of thiol-ene and thiol-ene/acrylate polymers. These materials are advantageous in that the degree of softening after exposure to in vivo conditions can easily be tuned by the polymer design. By choosing the right polymer composition and crosslink density, the glass transition temperature and Young&#39;s modulus of the polymer can be modified2,4,5,6,8. The underlying effect of the softening is the plasticization of the polymer in an aqueous environment. By having a polymer with a glass transition temperature (Tg) above body temperature when dry (the state during implantation), but below body temperature after being immersed in water or PBS, the resulting stiffness/modulus of the polymer can shift from glassy (stiff) when dry to rubbery (soft) when implanted16.
However, exact and reliable measurements of the softening due to plasticization and the shift of Tg from the dry to wet states have not been able to be measured in the past. Traditional dynamic mechanical analysis is performed in air or inert gases and does not allow for measuring of the thermomechanical properties of polymers inside a solution. In previous studies, the polymers have been immersed in PBS for various amounts of time. Swollen samples were then used to perform dynamic mechanical analysis (DMA)6,7,8. However, since the procedure involves a temperature ramp, samples start to dry during the measurement and do not yield representative data. This is especially true if the sample size becomes smaller. In order to predict the softening of neural probes, it would be necessary to test 5 to 50 &#181;m-thin polymer films, which is not possible with traditional DMA due to the abovementioned drying of the samples during the measurement.
Hess et al.17 have designed a custom-built microtensile testing machine to assess the mechanical properties of mechanically adaptive materials using an environmentally controlled method. They have previously used an airbrush system to spray water on samples during the measurement to prevent them from drying out.
The use of environmental DMA (Figure 1), however, allows for measurement of polymer films in solutions, such as water and PBS, at various temperatures. This allows not only measurement of the polymer&#39;s thermomechanical properties in the soaked/softened state but also measurement of its softening kinetics. Even tensile tests and swelling measurements are possible inside the immersion bath of this machine. This allows for exact studies of the plasticization-induced softening of polymer substrates to predict in vivo behaviors.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1,3,5-Triallyl-1,3,5-triazine-2,4,6(1H,3H,5H)-trione (TATATO)</td>
			<td>Sigma-Aldrich</td>
			<td>114235-100G</td>
			<td></td>
		</tr>
		<tr>
			<td>2,2-Dimethoxy-2-phenylacetophenone (DMPA)</td>
			<td>Sigma-Aldrich</td>
			<td>196118-50G</td>
			<td></td>
		</tr>
		<tr>
			<td>CO2 laser Gravograph LS100</td>
			<td>Gravotech, Inc.</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Corning Large Glass Microscope Slides, 75 x 50mm</td>
			<td>Ted Pella</td>
			<td>26005</td>
			<td></td>
		</tr>
		<tr>
			<td>Environmental DMA: RSA-G2 Solids Analyzer</td>
			<td>TA Instruments</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>ESD Safe Plastic Tweezer, Tips; Flat, Duckbill, 11.5 cm</td>
			<td>Cole Palmer</td>
			<td>EW-07387-17</td>
			<td></td>
		</tr>
		<tr>
			<td>Laurell WS-650-8B spin coater</td>
			<td>Laurell Technologies Corporation</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>liquid nitrogen</td>
			<td>Air gas</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>PBS, 1X Solution, Fisher BioReagents</td>
			<td>Fisher Scientific</td>
			<td>BP243820</td>
			<td></td>
		</tr>
		<tr>
			<td>SHEL LAB vacuum oven</td>
			<td>VWR International</td>
			<td>89409-484</td>
			<td></td>
		</tr>
		<tr>
			<td>Silicon wafer</td>
			<td>University Wafer</td>
			<td></td>
			<td>Mechanical grade</td>
		</tr>
		<tr>
			<td>The RSA-G2 Immersion System</td>
			<td>TA Instruments</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Trimethylolpropane tris(3-mercaptopropionate) (TMTMP)</td>
			<td>Sigma-Aldrich</td>
			<td>381489-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>UVP CL-1000 crosslinking chamber with 365 nm bulbs</td>
			<td>VWR International</td>
			<td>21474-598</td>
			<td></td>
		</tr>
	</tbody>
</table>

environmental dynamic mechanical analysis to predict the softening behavior of neural implants

When using dynamically softening substrates for neural implants, it is important to have a reliable in vitro method to characterize the softening behavior of these materials. In the past, it has not been possible to satisfactorily measure the softening of thin films under conditions mimicking body environment without substantial effort. This publication presents a new and simple method that allows dynamic mechanical analysis (DMA) of polymers in solutions, such as phosphate buffered saline (PBS), at relevant temperatures. The use of environmental DMA allows measurement of the softening effects of polymers due to plasticization in various media and temperatures, which therefore allows a prediction of the materials behavior under in vivo conditions.

The use of environmental DMA allows the analysis of softening kinetics and overall softening capabilities of polymers. By using the temperature-time measuring mode of the protocol, the softening profiles of different polymer formulations can be compared to each other (Figure 6). This method can also be used to quantify softening and swelling rates of polymers. It can be seen in Figure 4 that different polymer formulations may und...

Watch this Scientific Journal Video about Environmental Dynamic Mechanical Analysis to Predict the Softening Behavior of Neural Implants at JoVE.com

Environmental Dynamic Mechanical Analysis to Predict the Softening Behavior of Neural Implants

Sinirsel implantları yumuşatma davranışını tahmin etmek için çevre dinamik mekanik analiz

To allow reliable predictions of the softening of polymeric substrates for neural implants in an in vivo environment, it is important to have a reliable in vitro method. Here, the use of dynamic mechanical analysis in phosphate buffered saline at body temperature is presented.

When using dynamically softening substrates for neural implants, it is important to have a reliable in vitro method to characterize the softening behavior ...

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Research

JoVE Journal

Bioengineering

7.6K Görüntüleme.  University of Texas at Dallas. Bu yöntem, implante edilebilir cihazların malzeme özelliklerinin vücuda yerleştirildiğinde, özellikle de malzemelerin yumuşatılması ile nasıl değişebileceğinin izlenmesine yardımcı olur. Bu tekniğin en büyük avantajı, invivo koşulları taklit eden ve bu nedenle hayvan testi ihtiyacını en aza indiren basit bir in vitro yöntemi sunup. Bu yöntem özellikle implante edilebilir cihazlarda kullanılacak olan malzemenin termomekanik özelliklerini test etmek için ilginçtir...

Video: Environmental Dynamic Mechanical Analysis to Predict the Softening Behavior of Neural Implants

Microfabricated Platforms for Mechanically Dynamic Cell Culture

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or fundamental cell biology studies is limited by current bioreactor technologies, which cannot simultaneously apply a variety of mechanical stimuli to cultured cells. In order to address this issue, we have developed a series of microfabricated platforms designed to screen for the effects of mechanical stimuli in a high-throughput format. In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and further demonstrate how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

Mekanik Dinamik Hücre Kültürü için Microfabricated platformlar

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or ...

Biyomühendislik

Fabrication of Micropatterned Hydrogels for Neural Culture Systems using Dynamic Mask Projection Photolithography

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the need for 3D environments to represent in vitro experiments which better mimic in vivo qualities 1-3. Studies in fields such as cancer research 4, neural engineering 5, cardiac physiology 6, and cell-matrix interaction7,8have shown cell behavior differs substantially between traditional monolayer cultures and 3D constructs.
Hydrogels are used as 3D environments because of their variety, versatility and ability to tailor molecular composition through functionalization 9-12. Numerous techniques exist for creation of constructs as cell-supportive matrices, including electrospinning13, elastomer stamps14, inkjet printing15, additive photopatterning16, static photomask projection-lithography17, and dynamic mask microstereolithography18. Unfortunately, these methods involve multiple production steps and/or equipment not readily adaptable to conventional cell and tissue culture methods. The technique employed in this protocol adapts the latter two methods, using a digital micromirror device (DMD) to create dynamic photomasks for crosslinking geometrically specific poly-(ethylene glycol) (PEG) hydrogels, induced through UV initiated free radical polymerization. The resulting "2.5D" structures provide a constrained 3D environment for neural growth. We employ a dual-hydrogel approach, where PEG serves as a cell-restrictive region supplying structure to an otherwise shapeless but cell-permissive self-assembling gel made from either Puramatrix or agarose. The process is a quick simple one step fabrication which is highly reproducible and easily adapted for use with conventional cell culture methods and substrates.
Whole tissue explants, such as embryonic dorsal root ganglia (DRG), can be incorporated into the dual hydrogel constructs for experimental assays such as neurite outgrowth. Additionally, dissociated cells can be encapsulated in the photocrosslinkable or self polymerizing hydrogel, or selectively adhered to the permeable support membrane using cell-restrictive photopatterning. Using the DMD, we created hydrogel constructs up to ~1mm thick, but thin film (&lt;200 &mu;m) PEG structures were limited by oxygen quenching of the free radical polymerization reaction. We subsequently developed a technique utilizing a layer of oil above the polymerization liquid which allowed thin PEG structure polymerization.
In this protocol, we describe the expeditious creation of 3D hydrogel systems for production of microfabricated neural cell and tissue cultures. The dual hydrogel constructs demonstrated herein represent versatile in vitro models that may prove useful for studies in neuroscience involving cell survival, migration, and/or neurite growth and guidance. Moreover, as the protocol can work for many types of hydrogels and cells, the potential applications are both varied and vast.

Simple techniques are described for the rapid production of microfabricated neural culture systems using a digital micromirror device for dynamic mask projection lithography on regular cell culture substrates. These culture systems may be more representative of natural biological architecture, and the techniques described could be adapted for numerous applications.

Dinamik Maske Projeksiyon Fotolitografi kullanarak Sinir Kültür Sistemleri Micropatterned Hidrojeller Fabrikasyon

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the ...

Graphene Coatings for Biomedical Implants

Atomically smooth graphene as a surface coating has potential to improve implant properties. This demonstrates a method for coating nitinol alloys with nanometer thick layers of graphene for applications as a stent material. Graphene was grown on copper substrates via chemical vapor deposition and then transferred onto nitinol substrates. In order to understand how the graphene coating could change biological response, cell viability of rat aortic endothelial cells and rat aortic smooth muscle cells was investigated. Moreover, the effect of graphene-coatings on cell adhesion and morphology was examined with fluorescent confocal microscopy. Cells were stained for actin and nuclei, and there were noticeable differences between pristine nitinol samples compared to graphene-coated samples. Total actin expression from rat aortic smooth muscle cells was found using western blot. Protein adsorption characteristics, an indicator for potential thrombogenicity, were determined for serum albumin and fibrinogen with gel electrophoresis. Moreover, the transfer of charge from fibrinogen to substrate was deduced using Raman spectroscopy. It was found that graphene coating on nitinol substrates met the functional requirements for a stent material and improved the biological response compared to uncoated nitinol. Thus, graphene-coated nitinol is a viable candidate for a stent material.

Graphene offers potential as a coating material for biomedical implants. In this study we demonstrate a method for coating nitinol alloys with nanometer thick layers of graphene and determine how graphene may influence implant response.

Biyomedikal implantlar için Grafen Kaplamalar

Atomically smooth graphene as a surface coating has potential to improve implant properties. This demonstrates a method for coating nitinol alloys with ...

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, direct visualization of individual viral complexes in their host cellular environment with cryoET is challenging2, due to the infrequent and dynamic nature of viral entry, particularly in the case of HIV-1. While time-lapse live-cell imaging has yielded a great deal of information about many aspects of the life cycle of HIV-13-7, the resolution afforded by live-cell microscopy is limited (~ 200 nm). Our work was aimed at developing a correlation method that permits direct visualization of early events of HIV-1 infection by combining live-cell fluorescent light microscopy, cryo-fluorescent microscopy, and cryoET. In this manner, live-cell and cryo-fluorescent signals can be used to accurately guide the sampling in cryoET. Furthermore, structural information obtained from cryoET can be complemented with the dynamic functional data gained through live-cell imaging of fluorescent labeled target.
In this video article, we provide detailed methods and protocols for structural investigation of HIV-1 and host-cell interactions using 3D correlative high-speed live-cell imaging and high-resolution cryoET structural analysis. HeLa cells infected with HIV-1 particles were characterized first by confocal live-cell microscopy, and the region containing the same viral particle was then analyzed by cryo-electron tomography for 3D structural details. The correlation between two sets of imaging data, optical imaging and electron imaging, was achieved using a home-built cryo-fluorescence light microscopy stage. The approach detailed here will be valuable, not only for study of virus-host cell interactions, but also for broader applications in cell biology, such as cell signaling, membrane receptor trafficking, and many other dynamic cellular processes.

We describe a correlative microscopy method that combines high-speed 3D live-cell fluorescent light microscopy and high-resolution cryo-electron tomography. We demonstrate the capability of the correlative method by imaging dynamic, small HIV-1 particles interacting with host HeLa cells.

Dinamik Etkileşimler 3D Yapısal Analiz için karşılıklı Mikroskopi

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, ...

Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Blood, as a non-Newtonian biofluid, represents the focus of numerous studies in the hemorheology field. Blood constituents include red blood cells, white blood cells and platelets that are suspended in blood plasma. Due to the abundance of the RBCs (40% to 45% of the blood volume), their behavior dictates the rheological behavior of blood especially in the microcirculation. At very low shear rates, RBCs are seen to assemble and form entities called aggregates, which causes the non-Newtonian behavior of blood. It is important to understand the conditions of the aggregates formation to comprehend the blood rheology in microcirculation. The protocol described here details the experimental procedure to determine quantitatively the RBC aggregates in microcirculation under constant shear rate, based on image processing. For this purpose, RBC-suspensions are tested and analyzed in 120 x 60 &#181;m poly-dimethyl-siloxane (PDMS) microchannels. The RBC-suspensions are entrained using a second fluid in order to obtain a linear velocity profile within the blood layer and thus achieve a wide range of constant shear rates. The shear rate is determined using a micro Particle Image Velocimetry (&#181;PIV) system, while RBC aggregates are visualized using a high speed camera. The videos captured of the RBC aggregates are analyzed using image processing techniques in order to determine the aggregate sizes based on the images intensities.

The protocol described details an experimental procedure to quantify Red Blood Cell (RBC) aggregates under a controlled and constant shear rate, based on image processing techniques. The goal of this protocol is to relate RBC aggregate sizes to the corresponding shear rate in a controlled microfluidic environment.

Kırmızı Kan Hücresi Toplama Dinamik Soruşturma Kontrollü mikroakışkan Çevre

Blood, as a non-Newtonian biofluid, represents the focus of numerous studies in the hemorheology field. Blood constituents include red blood cells, white ...

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances (EPS). The EPS serves as a physical and protective scaffold that houses the bacterial cells and consists of a variety of materials that includes proteins, exopolysaccharides and DNA. The composition of the EPS may change, which remodels the mechanic properties of the biofilm to further develop or support alternative biofilm structures, such as streamers, as a response to environmental cues. Despite this, there are little quantitative descriptions on how EPS components contribute to the mechanical properties and function of biofilms. Rheology, the study of the flow of matter, is of particular relevance to biofilms as many biofilms grow in flow conditions and are constantly exposed to shear stress. It also provides measurement and insight on the spreading of the biofilm on a surface. Here, particle-tracking microrheology is used to examine the viscoelasticity and effective crosslinking roles of different matrix components in various parts of the biofilm during development. This approach allows researchers to measure mechanic properties of biofilms at the micro-scale, which might provide useful information for controlling and engineering biofilms.

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Particle-tracking microrheology investigates the viscoelasticity of materials. Here, the technique is used to determine the viscoelasticity, creep compliance and effective crosslinking roles of different matrix components of a bacterial biofilm. The matrix consists of polymeric substances secreted by the bacteria and its components determine biofilm structure and mechanical properties.

Parçacık izleme Microrheology tarafından Biyofilmler Mekanik Özelliklerinin Yerinde Haritalama

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances ...

Microbiologically Induced Calcite Precipitation Mediated by Sporosarcina pasteurii

The particular bacterium under investigation here (S. pasteurii) is unique in its ability, under the right conditions, to induce the hydrolysis of urea (ureolysis) in naturally occurring environments through secretion of an enzyme urease. This process of ureolysis, through a chain of chemical reactions, leads to the formation of calcium carbonate precipitates. This is known as Microbiologically Induced Calcite Precipitation (MICP). The proper culture protocols for MICP are detailed here. Finally, visualization experiments under different modes of microscopy were performed to understand various aspects of the precipitation process. Techniques like optical microscopy, Scanning Electron Microscopy (SEM) and X-Ray Photo-electron Spectroscopy (XPS)&#160;were employed to chemically characterize the end-product. Further, the ability of these precipitates to clog pores inside a natural porous medium was demonstrated through a qualitative experiment where sponge bars were used to mimic a pore-network with a range of length scales. A sponge bar dipped in the culture medium containing the bacterial cells hardens due to the clogging of its pores resulting from the continuous process of chemical precipitation. This hardened sponge bar exhibits superior strength when compared to a control sponge bar which becomes compressed and squeezed under the action of an applied external load, while the hardened bar is able to support the same weight with little deformation.

Microbiologically Induced Calcite Precipitation Mediated by Sporosarcina pasteurii

Protocols for microbiologically induced calcite precipitation (MICP) using the bacterium Sporosarcina pasteurii are presented here. The precipitated calcium carbonate was characterized through optical microscopy and scanning electron microscopy (SEM). It is also shown that exposure to MICP increases the compressive strength of sponge.

Mikrobiyolojik Kalsit Yağış Bağlı tarafından Aracılı<em&gt; Sporosarcina pasteurii</em

The particular bacterium under investigation here (S. pasteurii) is unique in its ability, under the right conditions, to induce the hydrolysis of urea ...

Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice

Ovarian cancer is characterized by extensive peritoneal metastasis, with tumor spheres commonly found in the malignant ascites. This is associated with poor clinical outcomes and currently lacks effective treatment. Both the three-dimensional (3D) environment and the dynamic mechanical forces are very important factors in this metastatic cascade. However, traditional cell cultures fail to recapitulate this natural tumor microenvironment. Thus, in vivo-like models that can emulate the intraperitoneal environment are of obvious importance. In this study, a new microfluidic platform of the peritoneum was set up to mimic the situation of ovarian cancer spheroids in the peritoneal cavity during metastasis. Ovarian cancer spheroids generated under a non-adherent condition were cultured in microfluidic channels coated with peritoneal mesothelial cells subjected to physiologically relevant shear stress. In summary, this dynamic 3D ovarian cancer-mesothelium microfluidic platform can provide new knowledge on basic cancer biology and serve as a platform for potential drug screening and development.

To study ovarian tumor progression in a physiologically relevant model, multicellular spheroids were cultured in a microdevice under simulated fluid flow. This dynamic 3D model emulates the intraperitoneal environment with the cellular and mechanical components where ovarian cancer metastasis occurs.

Dinamik 3D Periton microdevice Modelleme Yumurtalık Kanseri Multisellüler Sfero Davranış

Ovarian cancer is characterized by extensive peritoneal metastasis, with tumor spheres commonly found in the malignant ascites. This is associated with ...

Biaxial Mechanical Characterizations of Atrioventricular Heart Valves

Extensive biaxial mechanical testing of the atrioventricular heart valve leaflets can be utilized to derive&#160;optimal parameters used in constitutive models, which provide a mathematical representation of the mechanical function of those structures. This presented biaxial mechanical testing protocol involves (i) tissue acquisition, (ii) the preparation of tissue specimens, (iii) biaxial mechanical testing, and (iv) postprocessing of the acquired data. First, tissue acquisition requires obtaining porcine or ovine hearts from a local Food and Drug Administration-approved abattoir for later dissection to retrieve the valve leaflets. Second, tissue preparation requires using tissue specimen cutters on the leaflet tissue to extract a clear zone for testing. Third, biaxial mechanical testing of the leaflet specimen requires the use of a commercial biaxial mechanical tester, which consists of force-controlled, displacement-controlled, and stress-relaxation testing protocols to characterize the leaflet tissue&#39;s mechanical properties. Finally, post-processing requires the use of data image correlation techniques and force and displacement readings to summarize the tissue&#39;s mechanical behaviors in response to external loading. In general, results from biaxial testing demonstrate that the leaflet tissues yield a nonlinear, anisotropic mechanical response. The presented biaxial testing procedure is advantageous to other methods since the method presented here allows for a more comprehensive characterization of the valve leaflet tissue under one unified testing scheme, as opposed to separate testing protocols on different tissue specimens. The proposed testing method has its limitations in that shear stress is potentially present in the tissue sample. However, any potential shear is presumed negligible.

This protocol involves characterizations of atrioventricular valve leaflets with force-controlled, displacement-controlled, and stress-relaxation biaxial mechanical testing procedures. Results acquired with this protocol can be used for constitutive model development to simulate the mechanical behavior of functioning valves under a finite element simulation framework.

Atriyoventriküler kalp kapakları biaxial mekanik karakterizasyonu

Extensive biaxial mechanical testing of the atrioventricular heart valve leaflets can be utilized to derive&#160;optimal parameters used in constitutive ...

A Microfluidic Platform for Stimulating Chondrocytes with Dynamic Compression

Mechanical stimuli are known to modulate biological functions of cells and tissues. Recent studies have suggested that compressive stress alters growth plate cartilage architecture and results in growth modulation of long bones of children. To determine the role of compressive stress in bone growth, we created a microfluidic device actuated by pneumatic pressure, to dynamically (or statically) compress growth plate chondrocytes embedded in alginate hydrogel cylinders. In this article, we describe detailed methods for fabricating and characterizing this device. The advantages of our protocol are: 1) Five different magnitudes of compressive stress can be generated on five technical replicates in a single platform, 2) It is easy to visualize cell morphology via a conventional light microscope, 3) Cells can be rapidly isolated from the device after compression to facilitate downstream assays, and 4) The platform can be applied to study mechanobiology of any cell type that can grow in hydrogels.

This article provides detailed methods for fabricating and characterizing a pneumatically actuating microfluidic device for chondrocyte compression.

Dinamik Sıkıştırma ile Chondrocytes Uyarıcı için Bir Mikroakışkan Platform

Mechanical stimuli are known to modulate biological functions of cells and tissues. Recent studies have suggested that compressive stress alters growth ...