The data is in the form of representative figures and an excel data sheet for all the assessed parameters.
A. Weight Bearing (Approximate Time: 120 minutes)
1. Acclimatize mice in the behavioral testing room approximately 15-20 minutes prior to testing. It is recommended to expose mice to the testing environment for at least 2 days prior to experimentation.
2. Clean surfaces of testing chambers and equipment with 70% ethanol and allow surfaces to dry completely before placing mice.
3. The device should be placed and maintained on a flat, sturdy surface or bench top. Installation and power requirements are described in more detail by the manufacturer (https://stoeltingco.com/Neuroscience/Ugo-Basile-Incapacitance-Tester~10547, accessed 12/12/2022).
4. Connect the device to an appropriate power outlet and initiate using the power button.
5. Adjust the duration of recording to the desired length (in seconds); presently, we recorded for a period of 5 seconds in triplicate.
6. Press “Start” on the screen.
7. Press “zero” to tare the pressure-sensitive plates prior to calibration (with dedicated, standard weights) or data acquisition.
8. Place mice into the testing chamber, oriented with hind paws on pressure-sensitive plates and fore paws on elevated interior surface. Allow the mouse to explore the chamber until it has stopped for >5 s intervals.
9. Reorient the mouse onto pressure-sensitive plates with each hind paw evenly placed, then initiate recording.
10. The weight-bearing capacity of each hind paw is automatically measured and averaged, then the device display will indicate the final value for each paw to the nearest 0.1 g.
11. Record these values separately, then repeat to obtain triplicate values for each subject.
12. Calculate stance instability by determining the absolute (>0) difference between left and right hind paw weight bearing as a percentage of total weight-bearing capacity (sum of left and right recordings).
B. Gait analysis
B.1 Calibration Procedure (Approximate Time: 5 minutes)
1. To appropriately calibrate MouseWalker software for quantitative gait analysis, the scale for pixel size (pixels/cm) must be determined empirically.
2. Make a demarcation of fixed length (e.g., 2 cm) or place a translucent metric ruler on the surface of the MouseWalker walkway, matching the side of the mouse placement.
3. Capture reference length with either video or still image capture, while preserving camera location and position for subsequent recordings.
4. Using ImageJ (NIH) software, open the video or image file with the ruler or marking. Within the “Analyze” drop-down toolbar, select “Set Scale” and input the known distance and unit in cm to calculate the pixel per cm parameter.
5. Save this parameter for the MouseWalker software setup.
B.2 Recording procedures (Approximate Time: 60 minutes)
1. Acclimatize the mice in a darkened testing room 15 minutes before starting the experiment. Appropriate acclimatization is crucial, especially given that low light is required for proper light detection. It is recommended to expose mice to the testing environment for at least 2 days prior to experimentation.
2. Prepare the MouseWalker apparatus for recording. All MouseWalker surfaces are thoroughly disinfected between use, and acrylic surfaces for light interference recording are cleaned with 70% ethanol to maintain clarity and remove any debris/dust. Allow the surfaces to dry completely before starting the experiment.
3. Initiate a light controller for light interference (white light) in the acrylic walkway and background light. Set the background light color to “blue” at the highest light intensity, however light intensity and color should be determined empirically.
4. Video is acquired using a high-speed CMOS camera (Lumenera) connected to the central workstation via a USB 3.0 connection. Set camera position, iris size, and focus before recording and maintain parameters for all recordings – iris size should be adjusted to allow sufficient light for detection of the mouse body and surface disruption of the light path in the walkway. Field of view, frame rate (>60 frames per second, FPS), file type (.avi), and recording interface are controlled using StreamPix6 software. To ensure proper analysis of videos and reduce file size, the field of view should only comprise inside boundaries of the walkway.
6. Following setup, gently place the mouse at one end of the MouseWalker. Allow the mouse to acclimate to the walkway (>5 minutes), some mice may start walking immediately and others will need more time before starting to walk. Avoid excessive sounds and movement during recording to reduce experimental noise and allow mice to walk calmly.
7. Record a video of each mouse moving in a continuous line across the walkway. Eliminate recordings in which mice are running (all four paws are simultaneously out of contact with the walkway), mice do not complete the entire crossing, or unexpected waste (e.g., feces, urine) obscures the field of view. Four replicate videos are recorded for analysis of each mouse. Note, the direction of movement is not important for video analysis.
8. Save videos with an appropriate title for subject ID, experimental conditions, replicate number, and date.
9. Review the recorded videos for clarity and accuracy before completion of mouse recording, if additional videos are required, repeat from step 6.
10. Arrange videos from each experiment into corresponding folders for clarity and ease of access.
11. Proceed with video analysis.
B.3 Video Analysis with MouseWalker Software (Approximate Time: 30 minutes)
1. The MouseWalker software and documentation are open-source and available free of charge 8.
2. Download the necessary files and save them onto an appropriate, local hard disk.
3. Verify MATLAB installation and that the necessary plug-ins are ready. Run MATLAB.
4. In MATLAB, direct to the local address for the MouseWalker file and select “Run” to initiate the program interface (Figure 2).
5. It is critical to set calibration before importing and analyzing videos. Select “Setting” from the toolbar on the top right and input video parameters; these may vary depending on setup (e.g., working distance between camera and apparatus, workstation computational power, etc.).
6. First, set the frame rate; herein, we recorded at approximately 60 frames per second (FPS). Notably, higher frame rates may achieve greater video quality but require larger file storage.
7. Set the scale (pixels/cm) using the value acquired in the calibration procedure.
8. Other settings may be adjusted for robustness depending on size, age, strain, color, and other physical features of subjects. For reference, we include our optimized settings for the detection of average-sized (~25 g body weight) adults (>2 months), wild-type and hemophilia, and dark-furred mice.
9. From the input directory, select the video folder to be analyzed, ideally containing one video at a time.
10. From the output directory, select the desired location to save output data. The input folder may be selected to maintain consistent locations for raw video and analyzed data files.
11. Select “Load” and allow sufficient time for the video file to be opened by the software.
12. Select “Auto” to initiate automatic frame-by-frame detection of mouse features (I.e., mouse body, nose, tail, right forepaw (RF), left forepaw (LF), right hind paw (RH), left hind paw (LH), which are annotated in a video preview window.
13. Allow automatic tracking to continue until the final frame. Alternatively, if the mouse extends beyond the field of view before the video’s end, wait until the mouse’s nose reaches the end of the field of view, then select “Cancel”.
14. Following automatic tracking, return selection to the first video frame by manually typing the frame number or using arrow buttons. Evaluate automatic detection of physical features frame-by-frame. Incorrect features can be removed and manually defined. In the case of a misplaced right forepaw, select the “RF” button to undo the incorrectly identified feature, then select the “RF” button again, which will change the mouse pointer to a cursor symbol. With the cursor symbol, select the correct position for RF to place a new label.
15. After verifying the labeling is correct for all frames in which features are visible, select “Evaluate”. This will generate the analysis data and compile values into a Microsoft Excel file in the assigned output directory folder.