Plos One
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This was an in vitro and in vivo study to develop a novel artificial cervical vertebra and intervertebral complex (ACVC) joint in a goat model to provide a new method for treating degenerative disc disease in the cervical spine. The objectives of this study were to test the safety, validity, and effectiveness of ACVC by goat model and to provide preclinical data for a clinical trial in humans in future. We designed the ACVC based on the radiological and anatomical data on goat and human cervical spines, established an animal model by implanting the ACVC into goat cervical spines in vitro prior to in vivo implantation through the anterior approach, and evaluated clinical, radiological, biomechanical parameters after implantation. ⋯ The ROM and NZ of the ACVC group were greater than those of the control group for rotation. In conclusion, the goat provides an excellent animal model for the biomechanical study of the cervical spine. The ACVC is able to provide instant stability after surgery and to preserve normal motion in the cervical spine.
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The current investigations on social stress primarily point to the negative health consequences of being in a stressful social hierarchy. The repetitive nature of such stressors seems to affect behavioral response to pain both in rodents and humans. Moreover, a large discrepancy in the possibility of social stresses affecting pain perception in the two genders exists. ⋯ Finally, despite chronic pain perception in control and unstable male subjects was larger than females; the decrease of chronic pain perception in male stressed animals (poverty and inequality experienced subjects) was much more than stressed females. These results revealed that although food deprivation and social inequality can induce hypoalgesia, some socioeconomic situations like social instability don't affect pain sensation, whereas there were similar increases of proinflammatory cytokines level in all socially stressed subjects. In addition, males display larger hypoalgesic responses to inequality as compared with females.
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In vitro hypoxic preconditioning (HP) of mesenchymal stem cells (MSCs) could ameliorate their viability and tissue repair capabilities after transplantation into the injured tissue through yet undefined mechanisms. There is also experimental evidence that HP enhances the expression of both stromal-derived factor-1 (SDF-1) receptors, CXCR4 and CXCR7, which are involved in migration and survival of MSCs in vitro, but little is known about their role in the in vivo therapeutic effectiveness of MSCs in renal ischemia/reperfusion (I/R) injury. Here, we evaluated the role of SDF-1-CXCR4/CXCR7 pathway in regulating chemotaxis, viability and paracrine actions of HP-MSCs in vitro and in vivo. ⋯ Furthermore, the increased recruitment of HP-MSCs was associated with enhanced functional recovery, accelerated mitogenic response, and reduced apoptotic cell death. In addition, neutralization of either CXCR4 or CXCR7 impaired the improved therapeutic potential of HP-MSCs. These results advance our knowledge about SDF-1-CXCR4/CXCR7 axis as an attractive target pathway for improving the beneficial effects of MSC-based therapies for renal I/R.
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The aim of this study was to investigate the role of TLR2, TLR4 and MyD88 in sepsis-induced AKI. C57BL/6 TLR2(-/-), TLR4(-/-) and MyD88(-/-) male mice were subjected to sepsis by cecal ligation and puncture (CLP). Twenty four hours later, kidney tissue and blood samples were collected for analysis. ⋯ The TLR2(-/-), TLR4(-/-), and MyD88(-/-) mice had lower neutrophil infiltration in the kidneys. Depletion of neutrophils in the WT mice led to protection of renal function and less inflammation in the kidneys of these mice. Innate immunity participates in polymicrobial sepsis-induced AKI, mainly through the MyD88 pathway, by leading to an increased migration of neutrophils to the kidney, increased production of proinflammatory cytokines, vascular permeability, hypoxia and apoptosis of tubular cells.
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Electronic health records are invaluable for medical research, but much of the information is recorded as unstructured free text which is time-consuming to review manually. ⋯ Our novel S3CM machine learning algorithm effectively detected free texts in primary care records associated with angiogram results and ovarian cancer diagnoses, after training on pre-classified test sets. It should be easy to adapt to other disease areas as it does not rely on linguistic rules, but needs further testing in other electronic health record datasets.