scholarly journals Vascular endothelial ERp72 is involved in the inflammatory response in a rat model of skeletal muscle injury

2021 ◽  
Vol 23 (3) ◽  
Author(s):  
Noureddine Khalaf ◽  
Dalal Al‑Μehatab ◽  
Dahmani Fathallah
2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Bruno Paun ◽  
Daniel García Leon ◽  
Alex Claveria Cabello ◽  
Roso Mares Pages ◽  
Elena de la Calle Vargas ◽  
...  

Abstract Background Skeletal muscle injury characterisation during healing supports trauma prognosis. Given the potential interest of computed tomography (CT) in muscle diseases and lack of in vivo CT methodology to image skeletal muscle wound healing, we tracked skeletal muscle injury recovery using in vivo micro-CT in a rat model to obtain a predictive model. Methods Skeletal muscle injury was performed in 23 rats. Twenty animals were sorted into five groups to image lesion recovery at 2, 4, 7, 10, or 14 days after injury using contrast-enhanced micro-CT. Injury volumes were quantified using a semiautomatic image processing, and these values were used to build a prediction model. The remaining 3 rats were imaged at all monitoring time points as validation. Predictions were compared with Bland-Altman analysis. Results Optimal contrast agent dose was found to be 20 mL/kg injected at 400 μL/min. Injury volumes showed a decreasing tendency from day 0 (32.3 ± 12.0mm3, mean ± standard deviation) to day 2, 4, 7, 10, and 14 after injury (19.6 ± 12.6, 11.0 ± 6.7, 8.2 ± 7.7, 5.7 ± 3.9, and 4.5 ± 4.8 mm3, respectively). Groups with single monitoring time point did not yield significant differences with the validation group lesions. Further exponential model training with single follow-up data (R2 = 0.968) to predict injury recovery in the validation cohort gave a predictions root mean squared error of 6.8 ± 5.4 mm3. Further prediction analysis yielded a bias of 2.327. Conclusion Contrast-enhanced CT allowed in vivo tracking of skeletal muscle injury recovery in rat.


2013 ◽  
Vol 115 (6) ◽  
pp. 920-928 ◽  
Author(s):  
Maria L. Urso

Exercise, eccentric contractions, acute trauma, and disease are all causal mechanisms of skeletal muscle injury. After skeletal muscle is injured, it undergoes sequential phases of degeneration, inflammation, regeneration, and fibrosis. Events that occur in response to inflammation trigger regenerative processes. However, since inflammation causes pain, decreases skeletal muscle function, has a negative effect on performance, and contributes to fibrosis, which is one of the leading causes of delayed regeneration, the general practice has been to reduce inflammation. The problem with this approach is that preventing inflammation may hinder recovery. Current treatment options for inflammation are not necessarily effective and, in some cases, they may be unsafe. This review focuses on the question of whether the most beneficial course of treatment should be to block inflammation or if it is sensible to allow inflammatory processes to progress naturally. If blocking inflammation is perceived as a beneficial approach, it is not yet known at what time point during the inflammatory response it is most sensible to interfere. To address these issues, this review evaluates the effects of various anti-inflammatory agents on recovery processes in response to exercise-induced, traumatic, and disease-associated models of skeletal muscle injury. A collective analysis such as this should lay the foundation for future work that systematically manipulates the inflammatory response to most effectively promote regeneration and functional recovery in injured skeletal muscle, while reducing the negative effects of inflammatory processes such as pain and fibrosis.


2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Bruno Paun ◽  
Daniel García Leon ◽  
Alex Claveria Cabello ◽  
Roso Mares Pages ◽  
Elena de la Calle Vargas ◽  
...  

An amendment to this paper has been published and can be accessed via the original article.


Phytomedicine ◽  
2021 ◽  
pp. 153791
Author(s):  
Maria Sikorska ◽  
Małgorzata Dutkiewicz ◽  
Oliwia Zegrocka – Stendel ◽  
Magdalena Kowalewska ◽  
Iwona Grabowska ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e62687 ◽  
Author(s):  
Sarah M. Senf ◽  
Travis M. Howard ◽  
Bumsoo Ahn ◽  
Leonardo F. Ferreira ◽  
Andrew R. Judge

2022 ◽  
pp. 104477
Author(s):  
Jing Wei ◽  
Yuhang Huan ◽  
Ziqi Heng ◽  
Chenyang Zhao ◽  
Lulu Jia ◽  
...  

2008 ◽  
Vol 38 (11) ◽  
pp. 947-969 ◽  
Author(s):  
Carine Smith ◽  
Maritza J. Kruger ◽  
Robert M. Smith ◽  
Kathryn H. Myburgh

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