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A Contemporary Warming/Restraining Device for Efficient Tail Vein Injections in a Murine Fungal Sepsis Model
Published on: November 6, 2020
Buprenorphine Markedly Elevates a Panel of Surrogate Markers in a Murine Model of Sepsis
Weiqiang Chen1,2, Max Brenner1,2, Monowar Aziz1,2
1The Feinstein Institute for Medical Research, Northwell Health, Manhasset, New York.
Abstract:
Sepsis can be simulated in animals by perforating the cecum via a surgical procedure termed "cecal ligation and puncture" (CLP), which induces similar inflammatory responses as observed during the clinical course of human sepsis. In addition to anesthetic agents, many Institutional Animal Care and Use Committees often recommend the use of additional analgesic agents (such as opioid) to further augment the initial anesthetic effects. However, emerging evidence suggest that a commonly recommended opioid, buprenorphine, dramatically elevated circulating interleukin (IL)-6 levels, and reduced animal survival in male C57BL/6 mice, but not in female mice possibly due to the complex interference of estrous cycles, fueling an ongoing debate regarding the possible impact of analgesic administration on the sepsis-induced systemic inflammation. As per the recommendation of a local government agency, we performed a pilot study and confirmed that repetitive administration of buprenorphine indeed markedly elevated circulating levels of four sepsis surrogate markers (e.g., IL-6, KC, monocyte chemoattractant protein-1, and granulocyte-colony stimulating factor) in 20% to 60% of septic animals. This complication may adversely jeopardize our ability to use the CLP model to reliably simulate human sepsis, and to understand the complex mechanism underlying the pathogenesis of lethal sepsis. Thus, for experimental sepsis studies set to survey systemic inflammation and animal lethality at relatively later stages (e.g., at 24 h post CLP and beyond), we strongly recommend not to repetitively administer buprenorphine to eliminate its potential complication to animal sepsis models.
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