Hip osteoarthritis: A novel network analysis of subchondral trabecular bone structures.

Hip osteoarthritis (HOA) is a degenerative joint disease that leads to the progressive destruction of subchondral bone and cartilage at the hip joint. Development of effective treatments for HOA remains an open problem, primarily due to the lack of knowledge of its pathogenesis and a typically late-stage diagnosis. We describe a novel network analysis methodology for microcomputed tomography (micro-CT) images of human trabecular bone. We explored differences between the trabecular bone microstructure of femoral heads with and without HOA. Large-scale automated extraction of the network formed by trabecular bone revealed significant network properties not previously reported for bone. Profound differences were discovered, particularly in the proximal third of the femoral head, where HOA networks demonstrated elevated numbers of edges, vertices, and graph components. When further differentiating healthy joint and HOA networks, the latter showed fewer small-world network properties, due to decreased clustering coefficient and increased characteristic path length. Furthermore, we found that HOA networks had reduced length of edges, indicating the formation of compressed trabecular structures. In order to assess our network approach, we developed a deep learning model for classifying HOA and control cases, and we fed it with two separate inputs: (i) micro-CT images of the trabecular bone, and (ii) the network extracted from them. The model with plain micro-CT images achieves 74.6% overall accuracy while the trained model with extracted networks attains 96.5% accuracy. We anticipate our findings to be a starting point for a novel description of bone microstructure in HOA, by considering the phenomenon from a graph theory viewpoint.

The development of tumour vascular networks.

The growth of solid tumours relies on an ever-increasing supply of oxygen and nutrients that are delivered via vascular networks. Tumour vasculature includes endothelial cell lined angiogenesis and the less common cancer cell lined vasculogenic mimicry (VM). To study and compare the development of vascular networks formed during angiogenesis and VM (represented here by breast cancer and pancreatic cancer cell lines) a number of in vitro assays were utilised. From live cell imaging, we performed a large-scale automated extraction of network parameters and identified properties not previously reported. We show that for both angiogenesis and VM, the characteristic network path length reduces over time; however, only endothelial cells increase network clustering coefficients thus maintaining small-world network properties as they develop. When compared to angiogenesis, the VM network efficiency is improved by decreasing the number of edges and vertices, and also by increasing edge length. Furthermore, our results demonstrate that angiogenic and VM networks appear to display similar properties to road traffic networks and are also subject to the well-known Braess paradox. This quantitative measurement framework opens up new avenues to potentially evaluate the impact of anti-cancer drugs and anti-vascular therapies.

On detection of periodicity in C-reactive protein (CRP) levels.

C-reactive protein (CRP) is an acute-phase plasma protein that can be used as a biomarker for activation of the immune system. A spectral analysis of CRP level over time for patients with gynaecological tumours has been reported by Madondo et al., using a periodogram method, suggesting that there is no significant periodicity in the data. In our study, we investigate the impact of low sample number on periodogram analysis, for non-uniform sampling intervals-we conclude that data of Madondo et al. cannot rule out periodic behaviour. The search for patterns (periodic or otherwise) in the CRP time-series is of interest for providing a cue for the optimal times at which cancer therapies are best administered. In this paper we show (i) there is no evidence to rule out periodicity in CRP levels, and (ii) we provide a prescription for the minimum data sample rate required in future experiments for improved testing of a periodic CRP signal hypothesis. The analysis we provide may be used for establishing periodicity in any short time-series signal that is observed without a priori information.

Role of l-arginine/SNAP/NO/cGMP/KATP channel signalling pathway in antinociceptive effect of α-terpineol in mice.

OBJECTIVES: The main purpose of this study was to assess the role of l-arginine/SNAP/NO/cGMP/KATP channel pathway in analgesic effects of α-terpineol in mice. METHODS: Male NMRI mice were pretreated intraperitoneally with NO precursor (l-arginine, 100 mg/kg), NO synthase inhibitor (l-NAME, 30 mg/kg), NO donor (SNAP, 1 mg/kg), guanylyl cyclase inhibitor (methylene blue, 20 mg/kg), PDE inhibitor (sildenafil, 0.5 mg/kg), KATP channel blocker (glibenclamide, 10 mg/kg) and naloxone (2 mg/kg) 20 min before the administration of α-terpineol. The formalin test was performed 20 min after the administration of α-terpineol, and nociceptive responses of mice were recorded during 30 min. KEY FINDINGS: A significant and dose-dependent antinociception was produced by α-terpineol (40 and 80 mg/kg) in both the phases of formalin test. The antinociceptive effect of α-terpineol was significantly potentiated by l-arginine in the second phase while significantly antagonized by l-NAME in both phases of formalin test. Also, SNAP and sildenafil non-significantly enhanced-while methylene blue significantly diminished-the antinociceptive effect of α-terpineol in both phases of formalin test. Glibenclamide significantly reversed the α-terpineol-induced antinociception, indicating the involvement of KATP channels in antinociceptive effect of α-terpineol. CONCLUSIONS: These results indicate that the antinociceptive effect of α-terpineol is mediated through l-arginine/SNAP/NO/cGMP/KATP channel pathway.