Application of Surface Roughness Analysis on Micro–Computed Tomographic Images of Bone Erosion: Examples Using a Rodent Model of Rheumatoid Arthritis

Quantifying the bone erosion in preclinical models of rheumatoid arthritis is valuable for the evaluation of drug treatments. This study introduces a three-dimensional method for bone surface roughness measurement from micro–computed tomographic data obtained from rats subjected to collagen-induced arthritis (CIA), in which the degree of bone erosion is related to the severity and the duration of the disease. In two studies of rat CIA, the surface roughness of the talus bone following 21 days of disease increased 559% and 486% from the control group. At 41 days following disease induction, the roughness of the bone surface increased 857% above baseline. The roughness of the control samples was similar from each study (less than 4% different), demonstrating the robustness of the algorithm. Treatment with methotrexate at 0.1 mg/kg daily demonstrated significant protection from bone erosion, whereas the 0.05 mg/kg daily dose was not efficacious (98% versus 22% inhibition of roughness-measured bone erosion). The main advantage of such an algorithm is demonstrated in the preclinical drug study of rat CIA with methotrexate treatment, indicating the immediate utility of this approach in drug development studies

Metabolomic and proteomic analysis of serum from preterm infants with necrotising entercolitis and late-onset sepsis

Background: Necrotising enterocolitis (NEC) and late-onset sepsis (LOS) are the leading causes of death among preterm infants in the developed world. This study aimed to explore the serum proteome and metabolome longitudinally in preterm infants with NEC or LOS, matched to controls. Methods: Nineteen patients (10 cases, 9 controls) were included. A sample 14 d prior to and following, as well as at disease diagnosis, was included for cases. Controls had serum matched at diagnosis for corresponding case. All samples (n = 39) underwent shotgun proteomic analysis, and 37 samples also underwent metabolomics analysis using ultra performance liquid chromatography–tandem mass spectrometry. Results: The proteomic and metabolomic profiles of serum were comparable between all infants. Eight proteins were associated with NEC and four proteins were associated with LOS. C-reactive protein was increased in all NEC patients at diagnosis. Conclusion: No single protein or metabolite was detected in all NEC or LOS cases which was absent from controls; however, several proteins were identified which were associated with disease status. The differing expression of these proteins between diseased infants potentially relates to differing pathophysiology of disease. Thus, it is unlikely a single biomarker exists for NEC and/or LOS