Myocardial Infarction

 

What is Myocardial Infarction?
Myocardial infarction (MI) occurs when the heart muscle is starved for oxygen long enough that cardiac cells die. Blockage of one or more coronary arteries by formation of a blood clot (thrombus) or slow blood flow, caused by low blood pressure, abnormal heart rhythm or atherosclerosis (narrowing of blood vessels), are the most common causes of MI. 

Why Study Myocardial Infarction?
MI is a life-threatening condition affecting over 3 million people a year. Irreversible damage occurs within 30 minutes of oxygen deprivation, so fast response in MI recognition and treatment is necessary to not only prevent further damage to the heart, but to prevent death. Researchers studying MI are interested in a number of aspects surrounding the event, including risk factors, prevention, treatment (before, during and after MI), and pain management during an event to decrease the workload of the heart. 

Questions Researchers are Asking
  • What markers might be used to predict the event?
  • Can life-style changes (diet, exercise etc.) make a measurable difference?
  • Are there drug therapies or surgical programs that can prevent MI?
  • When should preventative measures be taken?
  • Can the oxygen supply be restored before cell death occurs?
  • If cell death occurs, how can the damage be contained?
  • Is there a way to repair damaged/dead cardiac cells?

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How is Myocardial Infarction Studied?

Animal and cellular models are used to study the various aspects of MI. Animal models used to study MI include mice, rats, rabbits, canines, swine, and non-human primates. These animal models may be used as whole animal models, where measurements like pressure, heart rate and electrocardiogram are used as biomarkers of ischemia and MI.  Additionally, there are a number of models that employ isolated tissues to study the progression of MI.  These isolated systems often need to merge data from multiple sources.

DSI and the Harvard Bioscience family have solutions for cardiomyocyte isolation, isolated heart perfusion, telemetry that measures pressure, heart rate and electrocardiograms in freely moving subjects, as well as hardwired solutions capable of combining telemetry with other systems used in tissue research. Cardiovascular data can be collected and analyzed with the Ponemah Software Platform










Ponemah software, PNM

 

DSI implants are designed for monitoring and collecting data from conscious, freely moving animals.  Implants are offered in different sizes to support a variety of animal species including mice, rats, dogs, swine, and non-human primates. Several telemetry models are capable of monitoring ECG, blood pressure, temperature, and activity simultaneously or individually. 

 
 

 Short durations of functional endpoints are collected non-invasively from chemically or physically restrained animals that are connected to external  devices capable of monitoring surface ECG, blood pressure or third party signals and recording  directly into an acquisition and analysis computer system.


 
 

ECG and blood pressure signals are collected from conscious, freely moving animals wearing a jacket which contains and protects a small JET device capable of monitoring cardiovascular data and transmitting data to an acquisition and analysis computer system.


 


 
 

For mouse to small rabbit hearts, Hugo Sachs perfusion systems are designed for simple and constant flow perfusion for cardiomyocyte isolation from small rodent hearts. Can be adapted for other small rodent organs in situ or ex vivo . Easy to set up, operate and maintain.



 
 
 

Hugo Sachs’ IH series of isolated heart perfusion systems is the gold standard for cardiac physiology measurements in both retrograde heart perfusion and working ejecting heart perfusion modes. Modular in design, our systems provide the flexibility to tailor a system to fit your research needs and the data can be acquired and analyzed in Ponemah, limiting the amount of systems in your lab.

 
 

1080 Myocardial Infarction articles citing DSI in Google Scholar

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