Aims. CRP is an acute-phase protein that is used as a biomarker to follow severity and progression in infectious and inflammatory diseases. Its pathophysiological mechanisms of action are still poorly defined. CRP in its pentameric form exhibits weak anti-inflammatory activity. The monomeric isoform (mCRP) exerts potent proinflammatory properties in chondrocytes, endothelial cells, and leucocytes. No data exist regarding mCRP effects in human
Introduction. Multiple studies have identified Cutibacterium acnes (C.acnes) and other microbes in
Aims. This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of
Purpose of study and background. Clinical researchers use Pfirrmann classification for grading
Aims. In this investigation, we administered oxidative stress to nucleus pulposus cells (NPCs), recognized DNA-damage-inducible transcript 4 (DDIT4) as a component in
Purpose and Background. The
Objectives. Low back pain is strongly associated with degeneration of the
Background. Chronic low back pain is strongly linked to degeneration of the
Introduction. Vertebral compression fractures are the most common type of osteoporotic fracture. Though 89% of clinical fractures occur anteriorly, it is challenging to replicate these ex vivo with the underlying
Background. The association between lumbar
Background. Magnetic resonance imaging (MRI) algorithm identifies end stage severely degenerated disc as ‘black’, and a moderately degenerate to non-degenerated disc as ‘white’. MRI is based on signal intensity changes that identifies loss of proteoglycans, water, and general radial bulging but lacks association with microscopic features such as fissure, endplate damage, persistent inflammatory catabolism that facilitates proteoglycan loss leading to ultimate collapse of annulus with neo-innervation and vascularization, as an indicator of pain. Thus, we propose a novel machine learning based imaging tool that combines quantifiable microscopic histopathological features with macroscopic signal intensities changes for hybrid assessment of disc degeneration. Methods. 100-disc tissue were collected from patients undergoing surgeries and cadaveric controls, age range of 35–75 years. MRI Pfirrmann grades were collected in each case, and each disc specimen were processed to identify the 1) region of interest 2) analytical imaging vector 3) data assimilation, grading and scoring pattern 4) identification of machine learning algorithm 5) predictive learning parameters to form an interface between hardware and software operating system. Results. Kernel algorithm defines non-linear data in xy histogram. X,Y values are scored histological spatial variables that signifies loss of proteoglycans, blood vessels ingrowth, and occurrence of tears or fissures in the inner and outer annulus regions mapped with the dampening and graded series of signal intensity changes. Conclusion. To our knowledge this study is the first to propose a machine learning method between microscopic spatial tissue changes and macroscopic signal intensity grades in the
Antibiotics are often administrated prophylactically in spinal procedures to reduce the risk of infection of the disc space. It is still not known which antibiotics are able to penetrate the
Background.
To develop and internally validate a preoperative clinical prediction model for acute adjacent vertebral fracture (AVF) after vertebral augmentation to support preoperative decision-making, named the after vertebral augmentation (AVA) score. In this prognostic study, a multicentre, retrospective single-level vertebral augmentation cohort of 377 patients from six Japanese hospitals was used to derive an AVF prediction model. Backward stepwise selection (p < 0.05) was used to select preoperative clinical and imaging predictors for acute AVF after vertebral augmentation for up to one month, from 14 predictors. We assigned a score to each selected variable based on the regression coefficient and developed the AVA scoring system. We evaluated sensitivity and specificity for each cut-off, area under the curve (AUC), and calibration as diagnostic performance. Internal validation was conducted using bootstrapping to correct the optimism.Aims
Methods
Introduction. Injectable hydrogels via minimally invasive surgery offer benefits to the healthcare system, reduced risk of infection, scar formation and the cost of treatment. Development of new treatments with the use of novel biomaterials requires significant pre-clinical testing and must comply with regulations before they can reach the bedside. In the European economic area (EEA) one of the first hurdles of this process is attaining the CE marking which protects the health, safety and environmental aspects of a product. Implanted materials fall under the class III medical device EU745 regulation standards. To attain the CE marking for a product parties must provide evidence of the materials safety with an investigational medicinal product dossier (IMPD). Methods and Results. We have been working to develop a new thermoresponsive injectable biomaterial hydrogel (NPgel) for the treatment of
Purpose of study and background. Low back pain affects 80% of the population at some point in their lives with 40% of cases attributed to
Introduction. Injectable hydrogels via minimally invasive surgery reduce the risk of infection, scar formation and the cost of treatment. Degradation of the
Background. Endplate defect is an MRI trait, found to be associated with
Introduction. The
Purpose of study and background. Mechanical overloading initiates