Postprocessing in machine learning and data mining

  • Bruha I
  • Famili A
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Abstract

OBJECTIVE: To examine the hypotheses that increasing concentrations of interleukin-1 (IL-1) or tumor necrosis factor alpha (TNFalpha) inhibit the integrative repair of the knee meniscus in an in vitro model system, and that inhibitors of these cytokines will enhance repair.METHODS: Explants (8 mm in diameter) were harvested from porcine medial menisci. To simulate a full-thickness defect, a 4-mm-diameter core was removed and reinserted. Explants were cultured for 14, 28, or 42 days in the presence of 0-1,000 pg/ml of IL-1 or TNFalpha. Explants were also cultured in the presence of IL-1 or TNFalpha with IL-1 receptor antagonist (IL-1Ra) or TNF monoclonal antibody (mAb). At the end of the culture period, biomechanical testing, cell viability, and histologic analyses were performed to quantify the extent of repair.RESULTS: Mechanical testing revealed increased repair strength, cell accumulation, and tissue formation at the interface over time under control conditions. Pathophysiologic concentrations of both IL-1 and TNFalpha significantly decreased repair strength, cell migration, and tissue formation at the interface. The addition of IL-1Ra or TNF mAb to explants prevented the effects of IL-1 or TNFalpha, respectively.CONCLUSION: Our findings document that physiologically relevant concentrations of IL-1 and TNFalpha inhibit meniscal repair in vitro and therefore may also inhibit meniscal repair during arthritis or following joint injury. The finding that IL-1Ra and TNF mAb promoted integrative meniscal repair in an inflammatory microenvironment suggests that intraarticular delivery of IL-1Ra and/or TNF mAb may be useful clinically to promote meniscal healing following injury.

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APA

Bruha, I., & Famili, A. (2000). Postprocessing in machine learning and data mining. ACM SIGKDD Explorations Newsletter, 2(2), 110–114. https://doi.org/10.1145/380995.381059

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