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Method Article

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

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DOI:

10.3791/63873

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May 5th, 2022

 ,  ,  ,  ,  ,  , 
1Department of Medicine I, University Hospital Munich, Ludwig-Maximilians University Munich (LMU), 2DZHK (German Centre for Cardiovascular Research), Partner Site Munich, Munich Heart Alliance (MHA), 3Institute of Cardiovascular Physiology and Pathophysiology, Biomedical Center, Ludwig-Maximilians-University, 4Institute of Surgical Research at the Walter-Brendel-Centre of Experimental Medicine, University Hospital Munich, Ludwig-Maximilians University Munich (LMU)

* These authors contributed equally

In This Article

Summary

Electrocardiogram (ECG) is the key variable to understanding cardiac electrophysiology. Physical exercise has beneficial effects but may also be harmful in the context of cardiovascular diseases. This manuscript provides a method of recording real-time ECG during exercise, which can serve to investigate its effects on cardiac electrophysiology in mice.

Abstract

Regular physical exercise is a major contributor to cardiovascular health, influencing various metabolic as well as electrophysiological processes. However, in certain cardiac diseases such as inherited arrhythmia syndromes, e.g., arrhythmogenic cardiomyopathy (ACM) or myocarditis, physical exercise may have negative effects on the heart leading to a proarrhythmogenic substrate production. Currently, the underlying molecular mechanisms of exercise-related proarrhythmogenic remodeling are largely unknown, thus it remains unclear which frequency, duration, and intensity of exercise can be considered safe in the context of disease(s).

The proposed method allows to study proarrhythmic/antiarrhythmic effects of physical exercise by combining treadmill training with real-time monitoring of the ECG. Implantable telemetry devices are used to continuously record the ECG of freely moving mice over a period of up to 3 months both at rest and during treadmill training. Data acquisition software with its analysis modules is used to analyze basic ECG parameters such as heart rate, P wave duration, PR interval, QRS interval, or QT duration at rest, during and after training. Furthermore, heart rate variability (HRV) parameters and occurrence of arrhythmias are evaluated. In brief, this manuscript describes a step-by-step approach to experimentally explore exercise induced effects on cardiac electrophysiology, including potential proarrhythmogenic remodeling in mouse models.

Introduction

Regular physical activity is important for a healthy life. Certain cardiovascular conditions, however, lead to situations where this common-sense agreement is at least questionable. In patients with myocarditis, current data even shows adverse effects of exercise and, thus, it is recommended to pause all exercise for a certain period in these patients1,2,3. In other cardiovascular diseases (CVD) such as inherited arrhythmia syndromes comparatively less evidence on the appropriate level of exercise exists4,5,6,7, making clinical counselling in these cases, mostly for young and physically active patients, very challenging.

Adverse remodeling leading to reduced contractility and heart failure and proarrhythmogenic remodeling leading to arrhythmias and sudden cardiac death have been suggested as hallmarks of exercise-associated harmful effects on the heart8. A large number of studies indicate beneficial effects of moderate exercise over a broad spectrum of different diseases9,10. Extensive training, however, may have detrimental effects on the heart leading to arrhythmias especially in otherwise healthy athletes11. Although structural remodeling processes leading to a vulnerable proarrhythmic substrate production may underlie this paradox situation as demonstrated in marathon runners12, the specific mechanisms of exercise-related adverse remodeling both in healthy people and in patients with cardiovascular diseases remain largely unknown.

In animals, especially in mice, several suitable models have been developed to mimic a broad range of cardiovascular diseases13,14. Also, various exercise models and training protocols have been established in mice15,16,17, including motorized treadmill training, voluntary wheel running (VWR), and swimming17,18. Evaluation of cardiac electrophysiology by ECG monitoring classically depends on a direct conducting connection between the animal and some sort of detection device. Thus, either animals need to be anesthetized, e.g., to obtain ECG recordings using sharp electrodes19, or animals need to be immobilized by a restrainer 20, or data quality is reduced due to motion artifacts, e.g., when using paw-electrodes21 or conductive platforms22 allowing only basic analysis. Thus, none of the above-mentioned approaches are compatible with training protocols and consequently prevent studies on exercise-related mechanisms leading to adverse remodeling in mice. Implantable telemetry devices can overcome these hurdles and are nowadays the most powerful tool and gold standard to evaluate murine electrophysiology in vivo in conscious and moving animals23,24. Current telemetry hardware solutions have been developed to monitor mice in their cages25,26, and commonly require a receiver to be placed underneath the cage for data acquisition, thus making real-time monitoring outside these circumstances challenging. Here we provide an approach to investigate the effects of exercise on cardiac electrophysiology and arrhythmogenesis by real-time ECG recording during treadmill training in mice using implanted telemetry devices. All parameters obtained were analyzed as previously described by Tomsits et al.23.

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Protocol

All animal procedures were conducted in accordance with the guidelines of the Animal Care and Ethics committee of the University of Munich and all procedures were approved by the Government of Bavaria, Munich, Germany (ROB-55.2-2532.Vet_02-16-200). Four male wildtype in-house bred C57BL/6N mice were used in this study.

1. Preparation and surgical implantation of the transmitter

NOTE: For a detailed protocol of transmitter preparation and implantation refer to McCauley et al.26.

  1. Preparation of the transmitter
    1. Use new transmitters directly as these are sterile. If transmitters are reused, clean the device by placing it in saline to get rid of bloodstains, remove any fragments of tissue adhering to the transmitter and the lead electrodes. Following the initial cleaning, if necessary, submerge the transmitter in a 1% cleaning solution (see Table of Materials) for 4 h to further clean the transmitter.
    2. Activate the transmitter by placing the supplied magnet in close proximity. Following activation, test the signal from the transmitter using a radio device at 530 Hz AM frequency. A sharp and clear beep indicates the transmitter is activated, whereas an inactivated transmitter does not give any signal.
  2. Surgical preparation and implantation
    NOTE: All surgical procedures must be carried out under clean and sterile conditions.
    1. Disinfect all surfaces and reusable equipment prior to use and use sterile disposables, e.g., gauze, gloves, etc.
    2. Prepare the leads of the transmitter by shortening to optimal lengths, the negative (white) lead to approximately 3.5 cm and the positive (red) lead to 2.5 cm. Remove the red and white insulation sheath on the tip of the electrodes by making a small cut to expose 5-7 mm of the conducting wire.
      NOTE: These lengths are suggested for 9-12-week-old BALB/c or C57BL/6 mice, weighing ~25 g. Adjust if the animals used in the study are larger/heavier.
    3. Note the weight of the transmitter and the body weight of the mouse. Also, note the serial number and calibration values of the transmitter provided by DSI.
      NOTE: The body weight of the animal is used to calculate doses of anesthetics and analgesics. The initial body weight is also used as reference to evaluate animal recovery post-surgery.
    4. Anaesthetize the mouse in an induction chamber connected to an isoflurane vaporizer flushed with 2%-3% isoflurane (vol/vol) driven by 1 L/min of 100% oxygen. Wait for full narcosis onset and check toe-pinch and lid reflex to ensure proper depth of narcosis before proceeding.
    5. Next, place the anaesthetized animal in a supine position and use ointment (see Table of Materials) to prevent eye dryness during the procedure. Carry out the surgical procedure under clean conditions on a surgical suite to maintain the body temperature of the mouse at 37 °C. Insert a rectal probe as temperature sensor.
    6. Maintain the anesthesia by continuous isoflurane (1.5%-2%) application. Inject fentanyl (0.50 µg/g) intraperitoneally for analgesia. Connect an adsorber to the ventilation setup to avoid excess gas to escape into the operating room (recommended).
    7. Insert needle ECG electrodes in both arms and the grounding electrode into the left leg of the mouse to obtain a lead I ECG configuration to monitor the ECG during surgery and to obtain baseline ECG.
    8. Shave the abdomen and chest and disinfect the area of surgery using chlorhexidine/alcohol (see Table of Materials). Use tweezers to tighten the skin and perform a 1.5-2 cm ventral midline abdominal incision using scissors (laparotomy).
    9. Make a subcutaneous pocket (ca 1 mm) in the upper-right chest and lower-left chest below the heart for placing the electrode leads, as shown in Figure 1.
    10. Place the transmitter body gently in the peritoneum above the intestine. Insert a 14 G needle subcutaneously from both pockets in the upper-right chest and lower-left chest pocket made earlier to create a tunnel for electrode positioning.
    11. Guide the red and white electrodes through the needle to place them in a lead II configuration. Position and fix the electrode tips with 6.0 sutures, positive electrode (red) in the lower-left chest and the negative electrode (white) in the upper-right chest.
    12. Suture all the incisions using 6.0 sutures and apply disinfectant (see Table of Materials) on the wounds. Move the animal to a recovery cage (only one animal/cage) and place it under a heat source to maintain body temperature until full recovery of narcosis. Only after full recovery and the ability to maintain sternal recumbency the animal may be placed back into company if required.
    13. Provide the animal with a sufficient dose of analgesics and antibiotics post-surgery. Use carprofen (5 µg/g) as analgesic and enrofloxacin (5 µg/g) as antibiotic. Monitor the wound at regular intervals to ensure there is no inflammation or wound dehiscence occurrence.
    14. After 7-10 days of post-surgery recovery period, the animal is ready to undergo treadmill training. Ensure that wounds are properly healed, and the mouse is healthy before starting the training.
      ​NOTE: After finalization of the experimental period, the use of telemetry transmitters does not require a specific euthanasia method. The choice of method depends on subsequent analysis and its specific requirements for tissue condition as well as on local animal care rules and regulations and approval of the respective local ethics committee.

2. Data acquisition

  1. Prearrangements
    1. To start data acquisition, place the animal cage on the signal receiver. Connect the signal receiver to the data acquisition system consisting of a data exchange matrix and a signal interface. Connect the data acquisition system to a computer with the acquisition software for data visualization (see setup details in Figure 2A).
    2. Start the software and confirm username and license on the following screen, and then click Continue. Click on Hardware to set up the transmitter and signal receiver device. Select Edit Physio Tel/HD (MX2) Configuration to open a configuration window.
    3. Select MX2 Configuration in the list view of the configuration tab to see all the available transmitters and their serial numbers in the available column. Click-and-drag the implanted transmitter from the available column to the selected column.
      NOTE: If a transmitter is listed in the selected column, it is also added to the MX2 configuration in the configuration tab on the far left.
    4. Colored icons next to the transmitter's serial number indicate the status. Check status for all transmitters: green with checkmark = transmitter is synchronized and ready; red with exclamation mark = transmitter currently not available, e.g., is currently configured in an experiment on another system; yellow = transmitter is synchronizing or does not have any receivers connected. Make sure there is green light indicating nominal data transfer.
    5. To configure the transmitter, select the serial number of the added transmitter and click on Create New Implant. Select ETA-F10 from the dropdown menu of the implant model to see implant details.
    6. Select the model and serial number of the receiver from a far-left menu of the receiver(s) associated with the implant. A list of plugged and connected receivers appears under this menu with a checkbox.
    7. Click on Search for ETA Implant to assign a signal receiver to the implanted transmitter. Open the signal type menu and select ECG with a sample rate of 1,000 Hz. Enter the calibration values on the back of the implant's packaging. Select Save & Exit.
    8. Click on Setup in the menu bar and select Subject Setup. A dialog box with subject details will appear. Enter the desired file name, which will be saved in subject setup.
    9. Select the gender of the animal and select Mouse from the drop-down menu of species. Open the analysis drop-down menu and select ECG (module). Change default labeling to ECG and units to mV if desired. Select the Trigger adjacent to ECG.
    10. Click on ECG under the subject name within the far-right menu to open the channel details menu. Select the desired ECG Parameters such as Num (Cycle number), HR (Heart rate), or intervals such as PR-I, QT-I, RR-I, QRS, etc. from the parameter list.
    11. To set up the display, click on Setup in the menu bar and select Experiment Setup. A setup dialog box appears. Select the Graph Setup from the far-right menu to define up to 16 graphical windows providing both raw data, e.g., ECG signals and derived parameters, e.g., XY loop, HR trend. To display the ECG, select the Enable Page checkbox for page 1.
  2. Treadmill training with simultaneous real-time ECG recording
    1. Prepare an experimental setup as shown in Figure 2B for a 2-lane treadmill with real-time ECG monitoring during training.
      NOTE: A 5-lane rodent treadmill (see Table of Materials) for training is recommended. The setup consists of a conveyor belt divided into five running compartments and a control unit with touchscreen. Each running compartment is formed by a transparent Plexiglas box with a lid, mounted on the conveyor belt. Each compartment has an electric shock grid where short electrical pulses act as stimulus to keep the animal running. Each compartment is individually connected to the control unit to enable compartment specific adjustment of shock intensity. The control unit can display the distance run, the number of shocks and the total duration of shocks. Since all compartments share the same conveyor belt, the speed and inclination can only be adjusted for all compartments at the same time.
    2. To enable good signal transduction during training, place the signal receiver on top of the box establishing the running lane with the animal as shown in Figure 2B. The exact position of the signal receiver on the running lane differs between individual animals due to different signal/noise ratios.
      1. Move the signal receiver until the optimal position on the running lane is found. Do so by running a test experiment with an animal under training and note the position with best signal/noise ratio. Use this optimal position for the actual experiment.
        NOTE: Due to the size of the signal receiver and placement of the receiver normal to the axis of the running lanes (as shown in Figure 2B), only two animals can train at the same time with ECG monitoring in this configuration.
    3. Divide the treadmill training into the following two phases.
      1. Acclimatization phase: time during which the animal is adapted to the training conditions. Perform a 1-week acclimatization protocol as shown in Table 1 with the speed of running and the time of training for each day as described.
      2. Training phase: Post acclimatization train the animal at a fixed speed for a fixed time per day for a total of X days. For this protocol, perform a 5-day training regime over 3 weeks with constant speed of 25 cm/s and a duration of 60 min/day (Table 2). After 5 days of training, provide a 2-day break before the next week of training.
        NOTE: X defines the total number of days of training and is defined based on the experimental objective.
    4. Switch on the treadmill. Set the treadmill slope, speed, and shock intensity according to the training protocol. Use an upward slope of 5°, which leads to a moderate level of stress (recommended). Use the same inclination for the acclimatization phase and training phase.
      NOTE: The inclination of the treadmill defines training intensity; choose the desired inclination. The training protocol can vary based on the experimental objective.
    5. Press on Settings in the control unit and select Grid Test. This opens a grid size selection screen. Select Mice. A Grid test screen will appear with two sub-tests: shock test and cleaning test. Press on Start to begin the shock test. A message warning the user of test shocks will appear. To begin the test, confirm the warning by touching the screen.
    6. Place the conductive part of the sponge accessory provided with the treadmill on the grid of the treadmill. Place it until the word Pass appears on screen. Test all grids like this. The test will end automatically after all lanes successfully pass it but can be stopped anytime by the user by pressing the Stop button.
    7. To continue with the cleaning test, press the >> button and Start and wait for the test to run. This test will also stop automatically as soon as all lanes have passed it. If the test fails, a warning message will appear on screen. Touch the message to see the result.
      NOTE: These tests are done to check cleanliness and function of the grid. Grids must be clean to ensure good animal detection and subsequently correct delivery of the electrical stimulus if needed. If the test fails, clean the grids, check whether all the cables are connected properly and repeat the test.
    8. Transfer the animal to the running compartment. Place the signal receiver on the transparent box and connect the signal receiver via the connecting cable to the data acquisition system, which consists of a data exchange matrix and a signal interface, which in turn connects to a computer with the acquisition software running to view the ECG signal during the experiment.
    9. Press Start to enter the running mode. Animals will receive a short electrical impulse when in contact with the electric grid, which will forward the animal toward the running lane. Use minimal shock intensity of 0.1 mA. This is sufficient to motivate the animals but is not visible in the ECG recording. Try placing food pellets outside the running lines within the view of the animal to keep it motivated.
      NOTE: The range given by the manufacturer for electrical shocks is 0.1 mA-2 mA. Increase in shock intensity may be necessary in different mouse strains or under different experimental conditions, nevertheless, we do recommend using the lowest shock intensity possible. Alternatively, to reduce overall electric shocks, try to keep the animal on the running lane by gently pushing it, e.g., with cotton ear buds or by stimulating it with a gentle puff of compressed air. If animals are trained well, the electric grid and the running lane can be separated by a piece of Styrofoam to avoid unwanted shocks.
    10. If an animal does not train and cannot be motivated even with electric shock, remove it from the training protocol for that day if there is no amelioration within the first 15 min of the experiment.
    11. Upon completion, allow the animal to rest for 5 min post-training before transferring it back to the cage. Remove the signal receiver from the transparent box and place it back underneath the cage as shown in Figure 2A. Turn off the treadmill to avoid any unwanted shocks.
    12. Clean the treadmill belt, the running compartments, and the electric grid with non-alcoholic cleaning agent. Clean lanes lead to better training results.
      ​NOTE: During training, it is important to constantly clean the lanes, as animals stop running on dirty lanes. We use cotton ear buds to get rid of animal feces while training.

3. Data analysis

NOTE: Depending on the individual research aims, various parameters can be obtained and analyzed. This protocol focusses on two aspects: analysis of quantitative ECG traits and the occurrence of arrhythmias before, during, and after training using an approach previously described by Tomsits etal.23; and analysis of heart rate variability (HRV)27.

  1. ECG analysis
    1. For a detailed description, refer to Tomsits et al.23. In brief, start the software, confirm the username and serial number of the software license, and click on Continue.
    2. To open a file with the extension. PnmExp, click on Load Experiment. The browse for folder dialog opens, select the file, and click on Open.
    3. Go to Actions/ Start review in the toolbar and select the Load Review Data dialog box, which provides an overview of all the subjects and their recorded signals within the previously selected experiment.
    4. Select the file to analyze by clicking on the checkbox next to its name in the Subjects panel on the left side of the screen. To analyze the ECG, select the checkbox next to ECG in the signal types panel.
    5. Select either the entire recording or define a range or duration using the time range option. Click on OK to load the selected data set into review and windows for events and parameters open automatically.
    6. To display the ECG, click on Graph Setup in the menu toolbar to open a new window. Select Primary in signal type, enter Time 0:00:00:01, and then select the desired Labelling, Unit of display, and Low and High axis limits by entering the respective text boxes. Confirm by clicking on the Enable Page checkbox and the defined ECG tracing window appears.
    7. Adjust X-axis and Y-axis dimensions of the ECG by double clicking. Left click into the trace to show wave annotation and recognize and annotate each segment of the trace, P, Q, R, T wave, correctly.
      NOTE: If annotations are not correct, several options, QRS, PT, Advanced, Noise, Marks, Notes, Precision, can be used to optimize, e.g., the Analyze/ Attributes option using the right click. For a detailed description refer to Tomsits et al.23.
    8. Select the required ECG parameters from the parameter window and copy to a spreadsheet or a statistics software for further analysis.
  2. Arrhythmia detection
    1. For arrhythmia detection, click on Experiment/Data Insights to open a new data insight window.
    2. Define customized search rules to screen the recording in the search panel. Create a new search by selecting Create New Search after a right click within the search list.
    3. In the dropdown menu of the entry dialog, define the respective search rule and click on OK to add this search rule to the list. To apply search rules, click and drag them to the channel of interest on the left.
    4. In the results panel, each section within the ECG recording to which the rule applies is displayed. For a detailed overview on different search rules, refer to Tomsits et al.23. For two exemplary rules, bradycardia and tachycardia, see the definition and description below.
      ​NOTE: For these search rules, murine physiologic heart rate is defined according to Kaese et al.28 as 500-724 beats/min, corresponding to a cycle length of 82-110 ms.
      1. Bradycardia: In a two-step approach, identify every individual RR interval longer than 120 ms. Since bradycardia requires more than a single elongated RR interval, define an additional search rule to only identify 20 consecutive RR intervals longer than 120 ms as bradycardia as follows: Bradycardia-single as Value (HRcyc0) <500, and Bradycardia as Series (Bradycardia-single, 1) >=20. Click on OK to add this search rule to the list.
      2. Following the same approach for tachycardia, define Tachycardia-single as Value (HRcyc0) >724, identifying every individual RR interval that is shorter than 82 ms, and then add the additional search rule Tachycardia as Series (Tachycardia-single, 1) >=20. Click on OK to add this search rule to the list.
  3. Heart rate variability analysis
    NOTE: The heart rate variability (HRV) analysis is not done in the acquisition software and requires exporting data from the acquisition software in a readable format. Here, we provide a short step-by step guide for data export in the widely used European data format (EDF).
    1. Start the software, confirm username and serial number, and click on Continue.
    2. To export the ECG trace for e.g., HRV analysis, click on Experiment and select Export to EDF. In the Export to EDF window, select the animal number, check ECG, select a time range for which data will be exported and click on Export.
      NOTE: There is no limit to the exported time range set by the software, more data will just take longer to process. It is also possible to split up exports into sections, e.g., 24 h and reintegrate them at a later timepoint if needed.
    3. Start the analysis software used for HRV analysis (see Table of Materials), click on File and select Open to load the desired EDF file.
    4. Click on HRV and select Settings. This will open a window to set various parameters. Under beat detection, select the species for which HRV analysis is done. Selection of the species will set the values for histogram bin width, pRR threshold and SDARR averaging value within the Analysis panel to a predefined standard.
    5. Select HRV and choose Report View. Copy the results to a statistics software for further statistical analysis.
    6. Signal quality can be significantly lower during training phases. If so, manually select cycles with visible P and QRS for subsequent analysis. Exclude bad data marks and data marks without clear P waves from the analysis. Do this under the careful consideration of an experienced ECG analyst to avoid eliminating good data points.

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Results

Depending on individual research objectives, subsequent analysis of obtained telemetry data will differ widely. Here, we demonstrate feasibility of the method by obtaining good quality data recorded during training periods and provide exemplary results of ECGs and heart rate variability analyses before, during, and after training. Data are presented as mean ± standard error of mean (SEM), all statistical analyses were conducted with a suitable statistical software (see Table of Materials). Statistical si...

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Discussion

Current guidelines recommend regular physical activity as it has been demonstrated to be an important modifier of cardiovascular risk factors30. There is also a growing body of evidence that moderate physical activity may protect against atrial fibrillation (AF) both in primary and secondary prevention31,32,33. On the contrary, endurance athletes such as marathon runners have a higher risk to develop AF i...

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Disclosures

The authors have nothing to disclose.

Acknowledgements

This work was supported by the German Research Foundation (DFG; Clinician Scientist Program in Vascular Medicine (PRIME), MA 2186/14-1 to P. Tomsits), the German Centre for Cardiovascular Research (DZHK; 81X2600255 to S. Clauss), the Corona Foundation (S199/10079/2019 to S. Clauss), and the ERA-NET on Cardiovascular Diseases (ERA-CVD; 01KL1910 to S. Clauss). The funders had no role in manuscript preparation.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
14-gauge needleSterican584125
Any mousee.g. Jackson Laboratories
BepanthenBayer1578675
Carprofen 0.005 mg/µLZoetis53716-49-7
Data Exchange Matrix 2.0 (MX2)Data Science InternationalManages communication between PhysioTel and PhysioTel HD telemetry implants and the acquisition computer.
Enrofloxacin 25 mg/mlBaytril400614.00.00
Fentanyl 0.5 mg/10 mLBraun Melsungen
Fine forcepsFine Science Tools11295-51
Five Lane Treadmill for MousePanlab - Harvard Apparatus76-0896Includes treadmill unit, touchscreen control unit, a sponge , and cables
Iris scissorsFine Science Tools14084-08
Isoflurane 1 mL/mLCp-Pharma31303
Isoflurane vaporizer systemHugo Sachs Elektronik34-0458, 34-1030, 73-4911, 34-0415, 73-4910Includes an induction chamber, a gas evacuation unit and charcoal filters
LabChart Pro 8.1.16ADInstruments
MagnetData Science International
Modified Bain circuitHugo Sachs Elektronik73-4860Includes an anesthesia mask for mice
Modular connectorsData Science InternationalConnecting cables between Reciever, Signal Interface and Matrix 2.0 (MX2)
Novafil s 5-0Medtrocin/Covidien88864555-23
Octal BioAmpADInstrumentsFE238-0239Amplifier for recording Surface ECG
OcteniseptSchülke121418
Oxygen 5 LLinde2020175Includes a pressure regulator
PhysioTel ETA-F10 transmitterData Science International
PhysioTel receiver RPC-1Data Science InternationalSignal reciever
Ponemah 6.42Data Science InternationalECG Analysis Software
PowerlabADInstruments3516-1277Suface ECG Acquisition hardware device. Includes ECG electrode leads
Prism 8.0.1Graph Pad
Radio Device (Sony AF/AM)Sony
Signal InterfaceData Science InternationalAcquires and synchronizes digital signals with telemetry data in Ponemah v6.x.
Spring scissorsFine Science Tools91500-09
Surgical platformKent ScientificSURGI-M
Tergazyme 1%Alconox13051.0Commercial cleaning solution
TweezersKent ScientificINS600098-2

References

  1. Halle, M., et al. Myocarditis in athletes: A clinical perspective. European Journal of Preventive Cardiology. , (2020).
  2. Maron, B. J., et al. Eligibility and disqualification recommendations for competitive athletes with cardiovascular abnormalities: Task force 3: Hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy and other cardiomyopathies, and myocarditis: A scientific statement from the American Heart Association and American College of Cardiology. Circulation. 132 (22), 273-280 (2015).
  3. Caforio, A. L. P., et al. Current state of knowledge on aetiology, diagnosis, management, and therapy of myocarditis: a position statement of the European Society of Cardiology Working Group on Myocardial and Pericardial Diseases. European Heart Journal. 34 (33), 2636-2648 (2013).
  4. Eberly, L., Garg, L., Vidula, M., Reza, N., Krishnan, S. Running the risk: Exercise and arrhythmogenic cardiomyopathy. Current Treatment Options in Cardiovascular Medicine. 23 (10), 64(2021).
  5. Lang, C. N., Steinfurt, J., Odening, K. E. Avoiding sports-related sudden cardiac death in children with congenital channelopathy: Recommendations for sports activities. Herz. 42 (2), 162-170 (2017).
  6. Maron, B. J., et al. Recommendations for physical activity and recreational sports participation for young patients with genetic cardiovascular diseases. Circulation. 109 (22), 2807-2816 (2004).
  7. Martinez-Sole, J., et al. Facts and gaps in exercise influence on arrhythmogenic cardiomyopathy: New insights from a meta-analysis approach. Frontiers in Cardiovascular Medicine. 8, 702560(2021).
  8. Sharma, S., Merghani, A., Mont, L. Exercise and the heart: the good, the bad, and the ugly. European Heart Jorunal. 36 (23), 1445-1453 (2015).
  9. Guasch, E., Mont, L. Diagnosis, pathophysiology, and management of exercise-induced arrhythmias. Nature Reviews. Cardiology. 14 (2), 88-101 (2017).
  10. Konhilas, J. P., et al. Exercise can prevent and reverse the severity of hypertrophic cardiomyopathy. Circulation Research. 98 (4), 540-548 (2006).
  11. Trivedi, S. J., et al. Differing mechanisms of atrial fibrillation in athletes and non-athletes: alterations in atrial structure and function. European Heart Journal. Cardiovascular Imaging. 21 (12), 1374-1383 (2020).
  12. Clauss, S., et al. MicroRNAs as biomarkers for acute atrial remodeling in marathon runners (The miRathon study--A sub-study of the Munich marathon study). PLoS One. 11 (2), 0148599(2016).
  13. Clauss, S., et al. Animal models of arrhythmia: classic electrophysiology to genetically modified large animals. Nature Reviews. Cardiology. 16 (8), 457-475 (2019).
  14. Schüttler, D., et al. Animal models of atrial fibrillation. Circulation Research. 127 (1), 91-110 (2020).
  15. Poole, D. C., et al. Guidelines for animal exercise and training protocols for cardiovascular studies. American Journal of Physiology. Heart and Circulatory Physiology. 318 (5), 1100-1138 (2020).
  16. Pynn, M., Schafer, K., Konstantinides, S., Halle, M. Exercise training reduces neointimal growth and stabilizes vascular lesions developing after injury in apolipoprotein e-deficient mice. Circulation. 109 (3), 386-392 (2004).
  17. Wang, Y., Wisloff, U., Kemi, O. J. Animal models in the study of exercise-induced cardiac hypertrophy. Physiological Research. 59 (5), 633-644 (2010).
  18. Massett, M. P., Matejka, C., Kim, H. Systematic review and meta-analysis of endurance exercise training protocols for mice. Frontiers in Physiology. 12, 782695(2021).
  19. Ha, T. W., Oh, B., Kang, J. O. Electrocardiogram recordings in anesthetized mice using lead II. Journal of Visualized Experiments: JoVE. (160), e61583(2020).
  20. Mongue-Din, H., Salmon, A., Fiszman, M. Y., Fromes, Y. Non-invasive restrained ECG recording in conscious small rodents: a new tool for cardiac electrical activity investigation. Pflugers Archiv: European Journal of Physiology. 454 (1), 165-171 (2007).
  21. Chu, V., et al. Method for non-invasively recording electrocardiograms in conscious mice. BMC Physiology. 1, 6(2001).
  22. Sato, S. Multi-dry-electrode plate sensor for non-invasive electrocardiogram and heart rate monitoring for the assessment of drug responses in freely behaving mice. Journal of Pharmacological and Toxicological Methods. 97, 29-35 (2019).
  23. Tomsits, P., et al. Analyzing long-term electrocardiography recordings to detect arrhythmias in mice. Journal of Visualized Experiments: JoVE. (171), e62386(2021).
  24. Gkrouzoudi, A., Tsingotjidou, A., Jirkof, P. A systematic review on the reporting quality in mouse telemetry implantation surgery using electrocardiogram recording devices. Physiology & Behavior. 244, 113645(2022).
  25. Russell, D. M., McCormick, D., Taberner, A. J., Malpas, S. C., Budgett, D. M. A high bandwidth fully implantable mouse telemetry system for chronic ECG measurement. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2011, 7666-7669 (2011).
  26. McCauley, M. D., Wehrens, X. H. Ambulatory ECG recording in mice. Journal of Visualized Experiments: JoVE. (39), e1739(2010).
  27. Thireau, J., Zhang, B. L., Poisson, D., Babuty, D. Heart rate variability in mice: a theoretical and practical guide. Experimental Physiology. 93 (1), 83-94 (2008).
  28. Kaese, S., Verheule, S. Cardiac electrophysiology in mice: a matter of size. Frontiers in Physiology. 3, 345(2012).
  29. Roussel, J., et al. The complex QT/RR relationship in mice. Scientific Reports. 6, 25388(2016).
  30. Visseren, F. L. J., et al. ESC Guidelines on cardiovascular disease prevention in clinical practice: Developed by the Task Force for cardiovascular disease prevention in clinical practice with representatives of the European Society of Cardiology and 12 medical societies With the special contribution of the European Association of Preventive Cardiology (EAPC). European Heart Journal. 42 (34), 3227(2021).
  31. Buckley, B. J. R., Lip, G. Y. H., Thijssen, D. H. J. The counterintuitive role of exercise in the prevention and cause of atrial fibrillation. American Journal of Physiology. Heart and Circulatory Physiology. 319 (5), 1051-1058 (2020).
  32. Elliott, A. D., et al. Association between physical activity and risk of incident arrhythmias in 402 406 individuals: evidence from the UK Biobank cohort. European Heart Journal. 41 (15), 1479-1486 (2020).
  33. Qureshi, W. T., et al. Cardiorespiratory fitness and risk of incident atrial fibrillation: Results from the Henry Ford Exercise Testing (FIT) project. Circulation. 131 (21), 1827-1834 (2015).
  34. Abdulla, J., Nielsen, J. R. Is the risk of atrial fibrillation higher in athletes than in the general population? A systematic review and meta-analysis. Europace: European pacing, arrhythmias, and cardiac electrophysiology of the European Society of Cardiology. 11 (9), 1156-1159 (2009).
  35. Centurion, O. A., et al. The association between atrial fibrillation and endurance physical activity: How much is too much. Journal of Atrial Fibrillation. 12 (3), 2167(2019).
  36. Calvo, N., et al. Emerging risk factors and the dose-response relationship between physical activity and lone atrial fibrillation: a prospective case-control study. Europace: European pacing, arrhythmias, and cardiac electrophysiology of the European Society of Cardiology. 18 (1), 57-63 (2016).
  37. Khan, H., et al. Cardiorespiratory fitness and atrial fibrillation: A population-based follow-up study. Heart Rhythm. 12 (7), 1424-1430 (2015).
  38. Morseth, B., et al. Physical activity, resting heart rate, and atrial fibrillation: the Tromso Study. European Heart Journal. 37 (29), 2307-2313 (2016).
  39. Hulsmans, M., et al. Macrophages facilitate electrical conduction in the heart. Cell. 169 (3), 510-522 (2017).
  40. Xiao, L., et al. Ibrutinib-mediated atrial fibrillation attributable to inhibition of C-terminal Src kinase. Circulation. 142 (25), 2443-2455 (2020).
  41. Clauss, S., et al. Characterization of a porcine model of atrial arrhythmogenicity in the context of ischaemic heart failure. PLoS One. 15 (5), 0232374(2020).
  42. Renner, S., et al. Porcine models for studying complications and organ crosstalk in diabetes mellitus. Cell and Tissue Research. 380 (2), 341-378 (2020).
  43. Schuttler, D., et al. A practical guide to setting up pig models for cardiovascular catheterization, electrophysiological assessment and heart disease research. Lab Animal (NY). 51 (2), 46-67 (2022).
  44. De Wijs-Meijler, D. P., et al. Surgical placement of catheters for long-term cardiovascular exercise testing in swine. Journal of Visualized Experiments: JoVE. (108), e53772(2016).
  45. Borzsei, D., et al. Multiple applications of different exercise modalities with rodents. Oxidative Medicine and Cellular Longevity. 2021, 3898710(2021).
  46. Kaplan, M. L., et al. Cardiac adaptations to chronic exercise in mice. The American Journal of Physiology. 267 (3), Pt 2 1167-1173 (1994).
  47. Fewell, J. G., et al. A treadmill exercise regimen for identifying cardiovascular phenotypes in transgenic mice. The American Journal of Physiology. 273 (3), Pt 2 1595-1605 (1997).
  48. Kemi, O. J., Loennechen, J. P., Wisloff, U., Ellingsen, O. Intensity-controlled treadmill running in mice: cardiac and skeletal muscle hypertrophy. Journal of Applied Physiology. 93 (4), Bethesda. Md. 1301-1309 (2002).

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Mouse ModelsReal-Time ECGImplantable TelemetryHeart Rate VariabilityArrhythmia DetectionCardiac ElectrophysiologySignal ReceiverExercise Physiology
Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
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