RESUMEN
Objective: To investigate the effects of vibration therapy on fracture healing in diabetic and non-diabetic rats. Methods: 148 rats underwent fracture surgery and were assigned to four groups: (1) SHAM: weight-matched non-diabetic rats, (2) SHAM+VT: non-diabetic rats treated with vibration therapy (VT), (3) DM: diabetic rats, and (4) DM+VT: diabetic rats treated with VT. Thirty days after diabetes induction with streptozotocin, animals underwent bone fracture, followed by surgical stabilization. Three days after bone fracture, rats began VT. Bone healing was assessed on days 14 and 28 post-fracture by serum bone marker analysis, and femurs collected for dual-energy X-ray absorptiometry, micro-computed tomography, histology, and gene expression. Results: Our results are based on 88 animals. Diabetes led to a dramatic impairment of bone healing as demonstrated by a 17% reduction in bone mineral density and decreases in formation-related microstructural parameters compared to non-diabetic control rats (81% reduction in bone callus volume, 69% reduction in woven bone fraction, 39% reduction in trabecular thickness, and 45% in trabecular number). These changes were accompanied by a significant decrease in the expression of osteoblast-related genes (Runx2, Col1a1, Osx), as well as a 92% reduction in serum insulin-like growth factor I (IGF-1) levels. On the other hand, resorption-related parameters were increased in diabetic rats, including a 20% increase in the callus porosity, a 33% increase in trabecular separation, and a 318% increase in serum C terminal telopeptide of type 1 collagen levels. VT augmented osteogenic and chondrogenic cell proliferation at the fracture callus in diabetic rats; increased circulating IGF-1 by 668%, callus volume by 52%, callus bone mineral content by 90%, and callus area by 72%; and was associated with a 19% reduction in circulating receptor activator of nuclear factor kappa beta ligand (RANK-L). Conclusions: Diabetes had detrimental effects on bone healing. Vibration therapy was effective at counteracting the significant disruption in bone repair induced by diabetes, but did not improve fracture healing in non-diabetic control rats. The mechanical stimulus not only improved bone callus quality and quantity, but also partially restored the serum levels of IGF-1 and RANK-L, inducing bone formation and mineralization, thus creating conditions for adequate fracture repair in diabetic rats.
Asunto(s)
Diabetes Mellitus , Fracturas Óseas , Animales , Callo Óseo/metabolismo , Callo Óseo/patología , Diabetes Mellitus/patología , Curación de Fractura , Fracturas Óseas/metabolismo , Factor I del Crecimiento Similar a la Insulina/metabolismo , Ratas , Vibración/uso terapéutico , Microtomografía por Rayos XRESUMEN
Osteoporosis and its consequence of fragility fracture represent a major public health problem. Human exposure to heavy metals has received considerable attention over the last decades. However, little is known about the influence of co-exposure to multiple heavy metals on bone density. The present study aimed to examine the association between exposure to metals and bone mineral density (BMD) loss. Blood and urine concentrations of 20 chemical elements were selected from 3 cycles (2005-2010) NHANES (National Health and Nutrition Examination Survey), in which we included white women over 50 years of age and previously selected for BMD testing (N = 1892). The bone loss group was defined as participants having T-score < - 1.0, and the normal group was defined as participants having T-score ≥ - 1.0. We developed classification models based on support vector machines capable of determining which factors could best predict BMD loss. The model which included the five-best features-selected from the random forest were age, body mass index, urinary concentration of arsenic (As), cadmium (Cd), and tungsten (W), which have achieved high scores for accuracy (92.18%), sensitivity (90.50%), and specificity (93.35%). These data demonstrate the importance of these factors and metals to the classification since they alone were capable of generating a classification model with a high prediction of accuracy without requiring the other variables. In summary, our findings provide insight into the important, yet overlooked impact that arsenic, cadmium, and tungsten have on overall bone health.