Background: Our understanding of low back disorder causality is limited in that how biomechanical loading acting on various spinal tissues initiates the pain pathway is not clear. Previous studies suggest that cytokines may be important in mediating the inflammatory responses in patients with back pain. This study quantified the acute biochemical responses to physical work stressing the low back and assessed the relationships between these systemic responses and specific lumbar spine tissue loads.
Methods: Twelve healthy males were tested under control and two weight-lifting conditions (light and heavy). Venous blood was sampled at various time points before and after the physical work and analyzed for cytokine, granulocyte, and creatine kinase levels. Biomechanical data were collected during the tasks and a biologically-assisted lumbar spine model was used to calculate spinal loads at various lumbar spine levels and trunk muscle forces.
Findings: Levels of interleukin-6, granulocytes, and creatine kinase all increased after both weight-lifting tasks, with the greatest changes observed with the heavier lifting task. Similarly, plasma levels of interleukin-1β and tumor necrosis factor-α both increased following the heavier lifting task. These inflammatory responses were significantly correlated with specific spinal tissue loads.
Interpretation: This study suggests that it may be possible to use inflammatory cytokines as biomarkers to monitor the physiological responses of the human body to biomechanical loading. Identifying the possible sources of cytokine up-regulation using an advanced biomechanical model may help a more effective understanding of the causal pathways that lead to low back disorders.
Serum protein profiling of systemic lupus erythematosus and systemic sclerosis using recombinant antibody microarrays
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组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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