B Y Jacobs1, K Dunnigan2, M Pires-Fernandes3, K D Allen4. 1. J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA. Electronic address: byjacobs@bme.ufl.edu. 2. J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA. Electronic address: katherine.m.dunnigan@gmail.com. 3. J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA. Electronic address: mpiresfernandes1@ufl.edu. 4. J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA. Electronic address: kyle.allen@bme.ufl.edu.
Abstract
OBJECTIVE: In rodent osteoarthritis (OA) models, behavioral changes are often subtle and require highly sensitive methods to detect these changes. Gait analysis is one assay that may provide sensitive, quantitative measurement of these behavioral changes. To increase detection sensitivity of gait assessments relative to spatiotemporal gait collection alone, we combined our spatiotemporal and dynamic gait collection systems. Using this combined system, gait was assessed in the rat medial meniscus transection (MMT) model and monoiodoacetate (MIA) injection model of knee OA. DESIGN: 36 male Lewis rats were separated into MMT (n = 8), medial collateral ligament transection (MCLT) (n = 8), skin incision (n = 4), MIA injection (n = 8), and saline injection (n = 8) groups. After initiation of OA, gait data were collected weekly in each group out to 4 weeks. RESULTS: The MMT and MIA injection models produced unique pathologic gait profiles, with MMT animals developing a shuffling gait and MIA injection animals exhibiting antalgic gait. Spatiotemporal changes were also observed in the MMT model at week 1 (P < 0.01), but were not observed in the MIA injection model until week 3 (P < 0.01). Dynamic gait changes were observed in both models as early as 1 week post-surgery (P < 0.01). CONCLUSION: Combined analysis of spatiotemporal and dynamic gait data increased detection sensitivity for gait modification in two rat OA models. Analyzing the combined gait data provided a robust characterization of the pathologic gait produced by each model. Furthermore, this characterization revealed different patterns of gait compensations in two common rat models of knee OA.
OBJECTIVE: In rodent osteoarthritis (OA) models, behavioral changes are often subtle and require highly sensitive methods to detect these changes. Gait analysis is one assay that may provide sensitive, quantitative measurement of these behavioral changes. To increase detection sensitivity of gait assessments relative to spatiotemporal gait collection alone, we combined our spatiotemporal and dynamic gait collection systems. Using this combined system, gait was assessed in the rat medial meniscus transection (MMT) model and monoiodoacetate (MIA) injection model of knee OA. DESIGN: 36 male Lewis rats were separated into MMT (n = 8), medial collateral ligament transection (MCLT) (n = 8), skin incision (n = 4), MIA injection (n = 8), and saline injection (n = 8) groups. After initiation of OA, gait data were collected weekly in each group out to 4 weeks. RESULTS: The MMT and MIA injection models produced unique pathologic gait profiles, with MMT animals developing a shuffling gait and MIA injection animals exhibiting antalgic gait. Spatiotemporal changes were also observed in the MMT model at week 1 (P < 0.01), but were not observed in the MIA injection model until week 3 (P < 0.01). Dynamic gait changes were observed in both models as early as 1 week post-surgery (P < 0.01). CONCLUSION: Combined analysis of spatiotemporal and dynamic gait data increased detection sensitivity for gait modification in two rat OA models. Analyzing the combined gait data provided a robust characterization of the pathologic gait produced by each model. Furthermore, this characterization revealed different patterns of gait compensations in two common rat models of knee OA.
Authors: W Zhang; G Nuki; R W Moskowitz; S Abramson; R D Altman; N K Arden; S Bierma-Zeinstra; K D Brandt; P Croft; M Doherty; M Dougados; M Hochberg; D J Hunter; K Kwoh; L S Lohmander; P Tugwell Journal: Osteoarthritis Cartilage Date: 2010-02-11 Impact factor: 6.576
Authors: Heidi E Kloefkorn; Travis R Pettengill; Sara M F Turner; Kristi A Streeter; Elisa J Gonzalez-Rothi; David D Fuller; Kyle D Allen Journal: Ann Biomed Eng Date: 2016-08-23 Impact factor: 3.934
Authors: W Zhang; R W Moskowitz; G Nuki; S Abramson; R D Altman; N Arden; S Bierma-Zeinstra; K D Brandt; P Croft; M Doherty; M Dougados; M Hochberg; D J Hunter; K Kwoh; L S Lohmander; P Tugwell Journal: Osteoarthritis Cartilage Date: 2008-02 Impact factor: 6.576
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Authors: Gustavo A Orozco; Kalle Karjalainen; Eng Kuan Moo; Lauri Stenroth; Petri Tanska; Jaqueline Lourdes Rios; Teemu V Tuomainen; Mikko J Nissi; Hanna Isaksson; Walter Herzog; Rami K Korhonen Journal: PLoS Comput Biol Date: 2022-06-03 Impact factor: 4.779
Authors: Brittany Y Jacobs; Emily H Lakes; Alex J Reiter; Spencer P Lake; Trevor R Ham; Nic D Leipzig; Stacy L Porvasnik; Christine E Schmidt; Rebecca A Wachs; Kyle D Allen Journal: Sci Rep Date: 2018-06-28 Impact factor: 4.379