We would like to acknowledge the following NIH funding sources: DC016030 and DC019902. We would also like to thank the members of the Speech &#38; Neurodevelopment Lab and the families who participated in our numerous studies.

Northeastern University&#39;s institutional review board has approved studies using the NNS device with human subjects (15-06-29; 16-04-06; 17-08-19). Informed consent was obtained from the children&#39;s caregivers. All research personnel have completed human subject training prior to collecting any data with the NNS device. The SNL team has generated several training resources and protocols for new research personnel to complete prior to data collection using the NNS device. These training sessions include reviewing the following protocol.
1. NNS device setup
<ol>
	<li>Open the transportable case (Figure 1) and remove the following device components: DAC and its power cord, customized pressure transducer box (NNS box) with pacifier receiver handle and gray cable attached, laptop computer and the USB cord that connects it to the DAC, and pacifier.</li>
	<li>Plug in the following components: the power cord into the DAC and a three-pronged power outlet, a grey cable connected to the NNS box into the first front round port of the DAC, and a USB cord into the laptop computer and DAC (Figure 2).</li>
	<li>Turn on the DAC using the power switch in its back and log onto the laptop/computer.</li>
</ol>
2. NNS device calibration
<ol>
	<li>Remove the pressure calibrator and 1 mL syringe from the case.</li>
	<li>Unscrew the black pacifier receiver from the handle. Screw the handle onto the pressure calibrator so that the handle is horizontal with the pressure calibrator (Figure 3A-C).</li>
	<li>Draw the syringe plunger fully out and then screw it into the upper position on the pressure calibrator. The syringe should be perpendicular to the pressure calibrator (Figure 3D).</li>
	<li>On the laptop computer, open the spreadsheet labeled SNL Suck Analyzer Calibration File. 
	NOTE: This file contains formulas that assess pressure variability between the data acquisition and analysis application and pressure calibrator device measured in psi. There is a box in the upper left corner for data entry, which is used to enter data readings from the pressure calibrator and the LabChart Calibration File (described below).
	<ol>
		<li>Right-click the tab that reads Duplicate and Rename as Date and select Move or Copy.</li>
		<li>In the Move or Copy pop-up window, click the box Create a Copy within the SNL Suck Analyzer Calibration File and then click Ok.</li>
		<li>Double-click the tab that was just copied and rename it as the current date.</li>
	</ol>
	</li>
	<li>Open the data acquisition and analysis file on the laptop computer&#39;s desktop labeled Calibration File. 
	NOTE: Ensure the spreadsheet is still viewable on the laptop computer screen, which may require minimizing and re-arranging the spreadsheet and data acquisition and analysis application windows.</li>
	<li>Press the Power button on the pressure calibrator device to turn it on.</li>
	<li>On the laptop computer, select Start on the Calibration File while the NNS box gear is at Zero. Check the waveform sampling across time on the file. 
	NOTE: The NNS box has two setting options: Zero and Sample. Ensure that it is set to Zero before starting calibration. The file&#39;s Start button will only activate when the file is opened after the DAC has been powered on. If the file is opened and the Start button cannot be clicked, close the file, power on the DAC, and reopen the file.</li>
	<li>In their respective cells in the spreadsheet (i.e., under the DAC Program and Red Calibrator columns), record the value at the top right corner of the Calibration File and the value on the pressure calibrator device while psi is at 0.00 (Figure 4A).</li>
	<li>Turn the gear from Zero to Sample on the NNS box. Wait approximately 15 s to allow adequate time for the pressure transducer to change recording functions.</li>
	<li>Slowly depress the syringe plunger until the pressure calibrator reaches a value as close to 0.2 psi as possible, and then fill in the Calibration File with the pressure calibrator values in their respective cells in the spreadsheet.</li>
	<li>Repeat step 2.10. for the following psi values: 0.4, 0.6, and 0.8 (Figure 4A).</li>
	<li>Once all values are inputted into the spreadsheet, click Stop in the Calibration File. In the spreadsheet, check the Slope and Goodness of Fit cells located to the right of the table that was used to plug in the psi values from the data acquisition and analysis application and the calibration device (Figure 4B). If both cells are highlighted in green, the calibration was successful; proceed to step 2.13. 
	NOTE: If one or both cells are red, clear the values in the psi measurement cells in the spreadsheet, turn the NNS box from Sample to Zero, close out the Calibration File, turn off the pressure calibrator by pressing the Power button, fully unscrew the syringe off the pressure calibrator, and pull the syringe plunger fully out before screwing it back on. Repeat steps 2.5. - 2.12.</li>
	<li>Close the Calibration File without saving, turn the gear on the NNS box to Zero, and turn the pressure calibrator off by pressing the Power button.</li>
	<li>Unscrew the syringe off the pressure calibrator. Pull the syringe plunger fully out again and then screw it back on the pressure calibrator.</li>
	<li>On the computer&#39;s desktop, select and open the file labeled Master Settings File. On the top channel in the file, click the arrow for drop-down options on Suck Pressure and select Arithmetic. 
	NOTE: Ensure the spreadsheet is still viewable on the laptop/computer screen, which may require minimizing and re-arranging the spreadsheet and data acquisition and analysis application windows.</li>
	<li>Within the parentheses of the Formula text box in the data acquisition and analysis file, type in the values from the spreadsheet that are located in the blue cells above the Slope and Goodness of Fit cells (Figure 4C). Click OK on the file.</li>
	<li>Turn the pressure calibrator back on using the Power button. Press Start on the Master Settings File. Turn the NNS box back to Sample and wait for 15 s.</li>
	<li>Depress the syringe plunger as close to 0.5 psi as read on the pressure calibrator.</li>
	<li>Scroll to the right within the spreadsheet and record the Master Settings File value under the cell labeled DAC and the pressure calibrator&#39;s value under the cell labeled Calibrator (Figure 4D). If the percentage error cell is highlighted in green, the calibration is successfully completed. If it is red, clear the data entered in this step and restart the calibration process from step 2.13.</li>
	<li>Click Stop on the Master Settings File. Turn the NNS box to Zero. Save the Master Settings File by selecting File, then Save as Settings. Name the file as the date of successful calibration.</li>
	<li>In the spreadsheet, select File &#62; Save and then File &#62; Close.</li>
	<li>Turn off the pressure calibrator by pressing the Power button. Unscrew the handle and syringe from the pressure calibrator and screw the black receiver back on the handle. Turn off, unplug, and pack up device components back in the case.</li>
</ol>
3. Collecting non-nutritive suck data
<ol>
	<li>Complete steps 1.1. - 1.3. for NNS device setup.</li>
	<li>Wash hands, put on latex gloves, and attach a newly opened pacifier to the pacifier receiver (Figure 5).</li>
	<li>Open the data acquisition and analysis file on the laptop computer&#39;s desktop with the latest calibration date. Once the file is opened, select Start.</li>
	<li>Turn the NNS box gear from Zero to Sample. Wait approximately 15 s to allow adequate time for the pressure transducer to change recording functions.</li>
	<li>Offer the pacifier to the child in a comfortable position and hold it for them to suck on for 2-5 min (or however long is tolerable for the child and comfortable with their caregiver). 
	NOTE: Preferable positions to measure NNS in children would be optimal feeding positions for their age. The researcher or a caregiver can offer the child the pacifier (Figure 6).</li>
	<li>When the child is finished or 5 min has passed, retrieve the pacifier handle from whoever was holding it for the child and press Stop on the file. Change the NNS box gear from Sample to Zero.</li>
	<li>Remove the pacifier from the receiver and safely dispose of it following any institutional sanitary protocols. Safely remove and dispose of gloves and wash hands.</li>
	<li>Save the file by selecting Save as and name the file with the participant&#39;s ID number and the date of data collection. Save the file to the desktop of the laptop computer.</li>
	<li>Turn off, unplug, and pack up device components back in the case.</li>
</ol>
4. Analyzing non-nutritive sucks amples
<ol>
	<li>Using a desktop or laptop that has the data acquisition and analysis software, open up the participant&#39;s NNS data file on the desktop by double-clicking on it.</li>
	<li>Manually identify suck bursts using the following criteria: NNS bursts having more than one suck cycle, each suck cycle having an amplitude of at least 1 cmH2O, and waveforms within 1000 ms of each other being considered as part of the same suck burst (Figure 7). 
	NOTE: It is helpful to modify the view of the waveform (click the Set horizontal scaling box on the bottom right of the screen to have zoom-in and out options) to better identify NNS cycles from noise. The analysis is completed in a 50:1 view. It is important to note as we explore NNS across populations, these criteria may change as various populations exhibit altered NNS patterns.</li>
	<li>To set peak analysis settings, select Peak Analysis, then Settings, then Table Options. Check the T Start, T End, Height, Peak Area, and Period boxes. All other boxes should be unchecked.</li>
	<li>Use the cursor to click and drag a box around the first NNS burst identified with the criteria described in step 4.2.</li>
	<li>Click Analyze (as part of peak analysis options in the top toolbar), which will identify peaks with parameters specified in step 4.3.</li>
	<li>Click the Burst Analysis Macro button, which will generate a pop-up data pad menu.</li>
	<li>In the data pad, insert a row in the column above the data by right clicking that column, selecting Insert Row for the first NNS burst, and typing Min 0-1 (or whichever minute the first burst occurs in).</li>
	<li>Continue steps 4.4. - 4.6. until all NNS bursts have been selected. Continue to keep track of the minute in which bursts occur by characterizing the specific minute (e.g., Min 1-2, Min 2-3) in the data pad.</li>
	<li>Once the analysis is complete, select File &#62; Save As, and save the analyzed NNS file as the participant ID, date, and researcher initials. Additionally, select File &#62; Export &#62; Data Pad Only as Text File &#62; Save to save the data pad file separately. 
	NOTE: It is important to save the raw NNS file, analyzed NNS file, and text file.</li>
	<li>Process the text file through a custom NNS burst macro. This produces an analyzed text file that contains the following burst variables: duration, frequency, height (amplitude), burst count, cycles/burst, and cycles/minute for each NNS burst. It also contains an average for the two consecutive minutes of NNS with the highest cycle count, which is often used for final analyses. Adjust depending on what analysis window needs to be analyzed.</li>
</ol>

A Custom-Made Pressure Transducer System to Record Non-Nutritive Suck Bursts

The authors have no conflicts of interest.

The NNS device has several limitations that are important to acknowledge. Although NNS provides critical insight into feeding9, there is a considerable amount of extrapolation from NNS to feeding performance. Solutions to this limitation have included research teams pairing NNS results with actual feeding observations and comprehensive feeding-related questionnaires for caregivers to more fully capture how NNS relates to feeding18. In addition, an infant can have a well-pat...

Non-nutritive suck (NNS) is one of the first occurring behaviors that an infant can perform with their mouth soon after birth and therefore has the potential to provide meaningful insights into brain development1. NNS refers to sucking movements without nutritional intake (e.g., sucking on a pacifier) and is characterized by a series of rhythmic expressions and suction movements of the jaw and tongue with pause breaks for breathing. Common parameters of NNS have been noted to include an average NNS burst (series of suck cycles) of 6-12 suck cycles with an intra-burst frequency of two sucks per second2; however, NNS features vary among clinical populations3,4 and dynamically change during the first year of life5. These changes are attributed to the growth of the oral cavity and associated anatomy, maturation of feeding skills and neurodevelopment, and experiences. The neural bases of NNS mainly include the suck central pattern generator in the central gray of the brainstem, comprising an intricate network of interneurons and the facial and trigeminal motor neuron nuclei6. A coordinated NNS also relies on intact neural pathways among cortical and brainstem regions to modulate its performance to sensory stimuli7,8, which makes NNS a viable indicator of early neural function and development.
NNS measures are linked to feeding success in premature infants9,10, and both sucking and feeding outcomes have been linked to subsequent motor, communication, and cognitive development11,12,13. In a retrospective study that characterized 23 preschool-aged children with language and motor impairments, 87% had a history of early feeding issues, which included difficulties in sucking11. Nutritive sucking performance immediately following birth and caregiver reports of feeding difficulties were significantly associated with multiple domains of neurodevelopment in children 18 months of age12,14. Interestingly, the sensitivity and specificity of feeding performance were higher than ultrasound assessment of the brain on neurodevelopmental outcome measures12. In another study, sucking/oral motor performance scores assessed via the neonatal oral-motor assessment scale15 in early infancy were associated with motor skills, language, and measures of intelligence at 2 and 5 years of age in a cohort of children born prematurely13,16.
Given that sucking and feeding can be sensitive indicators of neurodevelopmental outcomes throughout childhood, there is a critical need for accessible, accurate, and quantitative assessment of NNS to help identify children at risk for delayed and disordered development to provide early intervention. This need led to the design and research utilization of the Speech &#38; Neurodevelopment Lab&#39;s (SNL) NNS device. This portable device includes a pacifier attached to the end of an easy-to-hold handle, connected to a customized pressure transducer designed in-house, and connected to a data acquisition center (DAC). The DAC connects to a laptop, and the data is recorded via data acquisition and analysis software. The pressure transducer measures pressure changes inside the pacifier and converts it into a voltage signal. The DAC contains converters that change the analog voltage signal to digital values in cmH2O that are visualized and recorded via the data acquisition and analysis software. NNS outcome measures that can be analyzed from the suck signal waveform include NNS duration (how long a suck burst lasts measured in s), amplitude (measured as peak height subtracted by peak-trough in cmH2O), cycles/burst (number of suck cycles within a burst), frequency (intra-burst frequency measured in Hz), cycles (number of suck cycles that occur in a min), and bursts (number of suck bursts that occur in a min).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Case</td>
			<td>Pelican</td>
			<td>1560</td>
			<td></td>
		</tr>
		<tr>
			<td>Data Acquisition and Analysis Software/LabChart</td>
			<td>ADInstruments</td>
			<td>8.1.25</td>
			<td></td>
		</tr>
		<tr>
			<td>Data Acquisition Center (PowerLab 2/26)</td>
			<td>ADInstruments</td>
			<td>ML826</td>
			<td></td>
		</tr>
		<tr>
			<td>Laptop</td>
			<td>Dell</td>
			<td>Latitude 5480</td>
			<td></td>
		</tr>
		<tr>
			<td>Pressure Calibrator</td>
			<td>Meriam Process Technologies</td>
			<td>M101</td>
			<td></td>
		</tr>
		<tr>
			<td>Soothie Pacifier</td>
			<td>Phillips Avent</td>
			<td>SCF190/01</td>
			<td></td>
		</tr>
		<tr>
			<td>Syringe</td>
			<td>CareTouch</td>
			<td>CTSLL1</td>
			<td></td>
		</tr>
	</tbody>
</table>

non-nutritive suck parameters measurements using a custom pressure transducer system

The non-nutritive suck (NNS) device is a transportable, user-friendly pressure transducer system that quantifies infants' NNS behavior on a pacifier. Recording and analysis of the NNS signal using our system can provide measures of an infant's NNS burst duration (s), amplitude (cmH2O), and frequency (Hz). Accurate, reliable, and quantitative assessment of NNS has immense value in serving as a biomarker for future feeding, speech-language, cognitive, and motor development. The NNS device has been used in numerous research lines, some of which have included measuring NNS features to investigate the effects of feeding-related interventions, characterizing NNS development across populations, and correlating sucking behaviors with subsequent neurodevelopment. The device has also been used in environmental health research to examine how exposures in utero can influence infant NNS development. Thus, the overarching goal in research and clinical utilization of the NNS device is to correlate NNS parameters with neurodevelopmental outcomes to identify children at risk for developmental delays and provide rapid early intervention.

The NNS device has been used in numerous published studies that incorporate NNS outcome measures17,18,19. In the example data shown in Figure 7, bursts have been manually identified with the following criteria: more than one suck cycle per burst, cycles having at least an amplitude of 1 cmH2O, and suck waveforms within 1000 ms of each other. Once bursts are identified, the custom Macro ou...

Read this Scientific Article Protocol about Author Spotlight: Implications of Non-Nutritive Sucking on Speech Emergence and Infant Development at JoVE.com

Author Spotlight: Implications of Non-Nutritive Sucking on Speech Emergence and Infant Development

The non-nutritive suck (NNS) device can easily collect and quantify NNS features using a pacifier connected to a pressure transducer and recorded through a data acquisition system and laptop. Quantification of NNS parameters can provide valuable insight into a child's current and future neurodevelopment.

Non-Nutritive Suck Parameters Measurements Using a Custom Pressure Transducer System

The non-nutritive suck (NNS) device is a transportable, user-friendly pressure transducer system that quantifies infants' NNS behavior on a pacifier. ...

non-nutritive-suck-parameters-measurements-using-custom-pressure

Research

JoVE Journal

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548 Views.  Northeastern University. The non-nutritive suck (NNS) device can easily collect and quantify NNS features using a pacifier connected to a pressure transducer and recorded through a data acquisition system and laptop. Quantification of NNS parameters can provide valuable insight into a child's current and future neurodevelopment.

Video: Author Spotlight: Implications of Non-Nutritive Sucking on Speech Emergence and Infant Development

Developing Custom Chinese Hamster Ovary-host Cell Protein Assays using Acoustic Membrane Microparticle Technology

Custom assays for unique proteins are often limited to time consuming manual detection and quantitation techniques such as ELISA or Western blots due to the complexity of development on alternate platforms. BioScale's proprietary Acoustic Membrane MicroParticle (AMMP) technology allows sandwich immunoassays to be easily developed for use on the ViBE platform, providing better sensitivity, reproducibility, and automated operation. Provided as an example, this protocol outlines the procedure for developing a custom Chinese Hamster Ovary- Host Cell Protein (CHO-HCP) assay. The general principles outlined here can be followed for the development of a wide variety of immunoassays.
An AMMP assay measures antigen concentration by measuring changes in oscillation frequency caused by the binding of microparticles to the sensor surface to calculate. It consists of four major components: (1) a cartridge that contains a functionalized eight sensor chip (2) antibody labeled magnetic microparticles, (3) hapten tagged antibody that binds to the surface of the functionalized chip (4) samples containing the antigen of interest. BioScale's biosensor is a resonant device that contains eight individual membranes with separate fluidic paths. The membranes change oscillation frequency in response to mass accumulating on the surface and this frequency change is used to quantitate the amount of added mass.
To facilitate use in a wide variety of immunoassays the sensor is functionalized with an anti-hapten antibody. Assay specific antibodies are modified through the covalent conjugation of a hapten tag to one antibody and biotin to the other. The biotin label is used to bind the antibody to streptavidin coupled magnetic beads which, in combination with the hapten-tagged antibody, are used to capture the analyte in a sandwich. The complex binds to the chip through the anti-hapten/hapten interaction. At the end of each assay run the sensors are cleaned with a dilute acid enabling the sequential analysis of columns from a 96-well plate.
Here, we present the method for developing a custom CHO-HCP AMMP assay for bioprocess development. Developing AMMP assays or modifying existing assays into AMMP assays can provide better performance (reproducibility, sensitivity) in complex samples and reduced operator time. The protocol shows the steps for development and the discussion section reviews representative results. For a more in-depth explanation of assay optimization and customization parameters contact BioScale. This kit offers generic bioprocess development assays such as Residual Protein A, Product titer, and CHO-HCP.

Development of custom assays on the ViBE platform for more sensitive, reproducible, automated results in complex matrices is described. The universal cartridge allows assays to be easily adapted for use with custom assays. This versatility enables rapid development and validation of novel assays or automated versions of existing manual assays, exemplified in this video.

Custom assays for unique proteins are often limited to time consuming manual detection and quantitation techniques such as ELISA or Western blots due to ...

Multiplexed Single-molecule Force Proteolysis Measurements Using Magnetic Tweezers

The generation and detection of mechanical forces is a ubiquitous aspect of cell physiology, with direct relevance to cancer metastasis1, atherogenesis2 and wound healing3. In each of these examples, cells both exert force on their surroundings and simultaneously enzymatically remodel the extracellular matrix (ECM). The effect of forces on ECM has thus become an area of considerable interest due to its likely biological and medical importance4-7.
	Single molecule techniques such as optical trapping8, atomic force microscopy9, and magnetic tweezers10,11 allow researchers to probe the function of enzymes at a molecular level by exerting forces on individual proteins. Of these techniques, magnetic tweezers (MT) are notable for their low cost and high throughput. MT exert forces in the range of ~1-100 pN and can provide millisecond temporal resolution, qualities that are well matched to the study of enzyme mechanism at the single-molecule level12. Here we report a highly parallelizable MT assay to study the effect of force on the proteolysis of single protein molecules. We present the specific example of the proteolysis of a trimeric collagen peptide by matrix metalloproteinase 1 (MMP-1); however, this assay can be easily adapted to study other substrates and proteases.

In this article we describe the use of magnetic tweezers to study the effect of force on enzymatic proteolysis at the single molecule level in a highly parallelizable manner.

The  generation and detection of mechanical forces is a ubiquitous aspect of cell physiology,  with direct relevance to cancer metastasis1, atherogenesis2 ...

Bacterial Detection &amp; Identification Using Electrochemical Sensors

Electrochemical sensors are widely used for rapid and accurate measurement of blood glucose and can be adapted for detection of a wide variety of analytes. Electrochemical sensors operate by transducing a biological recognition event into a useful electrical signal. Signal transduction occurs by coupling the activity of a redox enzyme to an amperometric electrode. Sensor specificity is either an inherent characteristic of the enzyme, glucose oxidase in the case of a glucose sensor, or a product of linkage between the enzyme and an antibody or probe.
Here, we describe an electrochemical sensor assay method to directly detect and identify bacteria. In every case, the probes described here are DNA oligonucleotides. This method is based on sandwich hybridization of capture and detector probes with target ribosomal RNA (rRNA). The capture probe is anchored to the sensor surface, while the detector probe is linked to horseradish peroxidase (HRP). When a substrate such as 3,3',5,5'-tetramethylbenzidine (TMB) is added to an electrode with capture-target-detector complexes bound to its surface, the substrate is oxidized by HRP and reduced by the working electrode. This redox cycle results in shuttling of electrons by the substrate from the electrode to HRP, producing current flow in the electrode.

We describe an electrochemical sensor assay method for rapid bacterial detection and identification. The assay involves a sensor array functionalized with DNA oligonucleotide capture probes for ribosomal RNA (rRNA) species-specific sequences. Sandwich hybridization of target rRNA with the capture probe and a horseradish peroxidase-linked DNA oligonucleotide detector probe produces a measurable amperometric current.

Electrochemical  sensors are widely used for rapid and accurate measurement of blood glucose and  can be adapted for detection of a wide variety of ...

Flexural Rigidity Measurements of Biopolymers Using Gliding Assays

Microtubules are cytoskeletal polymers which play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires microtubules that are stiff and straight enough to span a significant fraction of the cell diameter. As a result, the microtubule persistence length, a measure of stiffness, has been actively studied for the past two decades1. Nonetheless, open questions remain: short microtubules are 10-50 times less stiff than long microtubules2-4, and even long microtubules have measured persistence lengths which vary by an order of magnitude5-9.
	Here, we present a method to measure microtubule persistence length. The method is based on a kinesin-driven microtubule gliding assay10. By combining sparse fluorescent labeling of individual microtubules with single particle tracking of individual fluorophores attached to the microtubule, the gliding trajectories of single microtubules are tracked with nanometer-level precision. The persistence length of the trajectories is the same as the persistence length of the microtubule under the conditions used11. An automated tracking routine is used to create microtubule trajectories from fluorophores attached to individual microtubules, and the persistence length of this trajectory is calculated using routines written in IDL.
	This technique is rapidly implementable, and capable of measuring the persistence length of 100 microtubules in one day of experimentation. The method can be extended to measure persistence length under a variety of conditions, including persistence length as a function of length along microtubules. Moreover, the analysis routines used can be extended to myosin-based acting gliding assays, to measure the persistence length of actin filaments as well.

A method to measure the persistence length or flexural rigidity of biopolymers is described. The method uses a kinesin-driven microtubule gliding assay to experimentally determine the persistence length of individual microtubules and is adaptable to actin-based gliding assays.

Microtubules are cytoskeletal polymers which  play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires ...

Cultivation of Mammalian Cells Using a Single-use Pneumatic Bioreactor System

Recent advances in mammalian, insect, and stem cell cultivation and scale-up have created tremendous opportunities for new therapeutics and personalized medicine innovations. However, translating these advances into therapeutic applications will require in vitro systems that allow for robust, flexible, and cost effective bioreactor systems. There are several bioreactor systems currently utilized in research and commercial settings; however, many of these systems are not optimal for establishing, expanding, and monitoring the growth of different cell types. The culture parameters most challenging to control in these systems include, minimizing hydrodynamic shear, preventing nutrient gradient formation, establishing uniform culture medium aeration, preventing microbial contamination, and monitoring and adjusting culture conditions in real-time. Using a pneumatic single-use bioreactor system, we demonstrate the assembly and operation of this novel bioreactor for mammalian cells grown on micro-carriers. This bioreactor system eliminates many of the challenges associated with currently available systems by minimizing hydrodynamic shear and nutrient gradient formation, and allowing for uniform culture medium aeration. Moreover, the bioreactor&#8217;s software allows for remote real-time monitoring and adjusting of the bioreactor run parameters. This bioreactor system also has tremendous potential for scale-up of adherent and suspension mammalian cells for production of a variety therapeutic proteins, monoclonal antibodies, stem cells, biosimilars, and vaccines.

Using a pneumatic bioreactor, we demonstrate the assembly, operation, and performance of this single-use bioreactor system for the growth of mammalian cells.

Recent advances in mammalian, insect, and stem cell cultivation and scale-up have created tremendous opportunities for new therapeutics and personalized ...

Rapid Scan Electron Paramagnetic Resonance Opens New Avenues for Imaging Physiologically Important Parameters In Vivo

We demonstrate a superior method of 2D spectral-spatial imaging of stable radical reporter molecules at 250 MHz using rapid-scan electron-paramagnetic-resonance (RS-EPR), which can provide quantitative information under in vivo conditions on oxygen concentration, pH, redox status and concentration of signaling molecules (i.e., OH&#8226;, NO&#8226;). The RS-EPR technique has a higher sensitivity, improved spatial resolution (1 mm), and shorter acquisition time in comparison to the standard continuous wave (CW) technique. A variety of phantom configurations have been tested, with spatial resolution varying from 1 to 6 mm, and spectral width of the reporter molecules ranging from 16 &#181;T (160 mG) to 5 mT (50 G). A cross-loop bimodal resonator decouples excitation and detection, reducing the noise, while the rapid scan effect allows more power to be input to the spin system before saturation, increasing the EPR signal. This leads to a substantially higher signal-to-noise ratio than in conventional CW EPR experiments.

Rapid Scan Electron Paramagnetic Resonance Opens New Avenues for Imaging Physiologically Important Parameters In Vivo

A new electron paramagnetic resonance (EPR) method, rapid scan EPR (RS-EPR), is demonstrated for 2D spectral spatial imaging which is superior to the traditional continuous wave (CW) technique and opens new venues for in vivo imaging. Results are demonstrated at 250 MHz, but the technique is applicable at any frequency.

We demonstrate a superior method of 2D spectral-spatial imaging of stable radical reporter molecules at 250 MHz using rapid-scan ...

Fabrication of Custom Agarose Wells for Cell Seeding and Tissue Ring Self-assembly Using 3D-Printed Molds

Engineered tissues are being used clinically for tissue repair and replacement, and are being developed as tools for drug screening and human disease modeling. Self-assembled tissues offer advantages over scaffold-based tissue engineering, such as enhanced matrix deposition, strength, and function. However, there are few available methods for fabricating 3D tissues without seeding cells on or within a supporting scaffold. Previously, we developed a system for fabricating self-assembled tissue rings by seeding cells into non-adhesive agarose wells. A polydimethylsiloxane (PDMS) negative was first cast in a machined polycarbonate mold, and then agarose was gelled in the PDMS negative to create ring-shaped cell seeding wells. However, the versatility of this approach was limited by the resolution of the tools available for machining the polycarbonate mold. Here, we demonstrate that 3D-printed plastic can be used as an alternative to machined polycarbonate for fabricating PDMS negatives. The 3D-printed mold and revised mold design is simpler to use, inexpensive to produce, and requires significantly less agarose and PDMS per cell seeding well. We have demonstrated that the resulting agarose wells can be used to create self-assembled tissue rings with customized diameters from a variety of different cell types. Rings can then be used for mechanical, functional, and histological analysis, or for fabricating larger and more complex tubular tissues.

This protocol describes a platform for fabricating self-assembled tissue rings in variable sizes using a customized 3D-printed plastic mold. PDMS negatives are cured in the 3D-printed mold; then agarose is cast in the cured PDMS negatives. Cells are seeded into the resulting agarose wells where they aggregate into tissue rings.

Engineered tissues are being used clinically for tissue repair and replacement, and are being developed as tools for drug screening and human disease ...

Material Formation of Recombinant Spider Silks through Aqueous Solvation using Heat and Pressure

Many spiders produce seven types of silks. Six of the silks are fiber in form when produced by the spiders. These fibers are not water soluble. In order to reproduce the remarkable mechanical properties of spider silks, they must be produced in heterologous hosts as spiders are both territorial and cannibalistic. The synthetic analogs of spider silk also tend to be insoluble in aqueous solutions. Thus, a large percentage of research in recombinant spider silks rely upon organic solvents that are detrimental to large scale production of materials. Our group&#8217;s method forces the solvation of these recombinant spider silks into water. Remarkably, when these proteins are prepared using this method of heat and pressure, a wide range of material forms can be prepared from the same solution of recombinant spider silk proteins (rSSp) including: films, fibers, sponge, hydrogel, lyogel, and adhesives. This article demonstrates the production of the solvated rSSp and material forms in a manner that is more easily understood than from written materials and methods alone.

Here, we present a protocol to produce water soluble recombinant spider silk protein solutions and the material forms that can be formed from those solutions.

Many spiders produce seven types of silks. Six of the silks are fiber in form when produced by the spiders. These fibers are not water soluble. In order ...

Biaxial Basal Tone and Passive Testing of the Murine Reproductive System Using a Pressure Myograph

The female reproductive organs, specifically the vagina and cervix, are composed of various cellular components and a unique extracellular matrix (ECM). Smooth muscle cells exhibit a contractile function within the vaginal and cervical walls. Depending on the biochemical environment and the mechanical distension of the organ walls, the smooth muscle cells alter the contractile conditions. The contribution of the smooth muscle cells under baseline physiological conditions is classified as a basal tone. More specifically, a basal tone is the baseline partial constriction of smooth muscle cells in the absence of hormonal and neural stimulation. Furthermore, the ECM provides structural support for the organ walls and functions as a reservoir for biochemical cues. These biochemical cues are vital to various organ functions, such as inciting growth and maintaining homeostasis. The ECM of each organ is composed primarily of collagen fibers (mostly collagen types I, III, and V), elastic fibers, and glycosaminoglycans/proteoglycans. The composition and organization of the ECM dictate the mechanical properties of each organ. A change in ECM composition may lead to the development of reproductive pathologies, such as pelvic organ prolapse or premature cervical remodeling. Furthermore, changes in ECM microstructure and stiffness may alter smooth muscle cell activity and phenotype, thus resulting in the loss of the contractile force.
In this work, the reported protocols are used to assess the basal tone and passive mechanical properties of the nonpregnant murine vagina and cervix at 4-6 months of age in estrus. The organs were mounted in a commercially available pressure myograph and both pressure-diameter and force-length tests were performed. Sample data and data analysis techniques for the mechanical characterization of the reproductive organs are included. Such information may be useful for constructing mathematical models and rationally designing therapeutic interventions for women&#8217;s health pathologies.

This protocol utilized a commercially available pressure myograph system to perform pressure myograph testing on the murine vagina and cervix. Utilizing media with and without calcium, the contributions of the smooth muscle cells (SMC) basal tone and passive extracellular matrix (ECM) were isolated for the organs under estimated physiological conditions.

The female reproductive organs, specifically the vagina and cervix, are composed of various cellular components and a unique extracellular matrix (ECM). ...

Rapid Fabrication of Custom Microfluidic Devices for Research and Educational Applications

Microfluidic devices allow for the manipulation of fluids, particles, cells, micro-sized organs or organisms in channels ranging from the nano to submillimeter scales. A rapid increase in the use of this technology in the biological sciences has prompted a need for methods that are accessible to a wide range of research groups. Current fabrication standards, such as PDMS bonding, require expensive and time consuming lithographic and bonding techniques. A viable alternative is the use of equipment and materials that are easily affordable, require minimal expertise and allow for the rapid iteration of designs. In this work we describe a protocol for designing and producing PET-laminates (PETLs), microfluidic devices that are inexpensive, easy to fabricate, and consume significantly less time to generate than other approaches to microfluidics technology. They consist of thermally bonded film sheets, in which channels and other features are defined using a craft cutter. PETLs solve field-specific technical challenges while dramatically reducing obstacles to adoption. This approach facilitates the accessibility of microfluidics devices in both research and educational settings, providing a reliable platform for new methods of inquiry.

Here we present a protocol to design and fabricate custom microfluidic devices with minimal financial and time investment. The aim is to facilitate the adoption of microfluidic technologies in biomedical research laboratories and educational settings.