Differential responses of osteoblasts and macrophages upon Staphylococcus aureus infection

Background Staphylococcus aureus (S. aureus) is one of the primary causes of bone infections which are often chronic and difficult to eradicate. Bacteria like S. aureus may survive upon internalization in cells and may be responsible for chronic and recurrent infections. In this study, we compared the responses of a phagocytic cell (i.e. macrophage) to a non-phagocytic cell (i.e. osteoblast) upon S. aureus internalization. Results We found that upon internalization, S. aureus could survive for up to 5 and 7 days within macrophages and osteoblasts, respectively. Significantly more S. aureus was internalized in macrophages compared to osteoblasts and a significantly higher (100 fold) level of live intracellular S. aureus was detected in macrophages compared to osteoblasts. However, the percentage of S. aureus survival after infection was significantly lower in macrophages compared to osteoblasts at post-infection days 1–6. Interestingly, macrophages had relatively lower viability in shorter infection time periods (i.e. 0.5-4 h; significant at 2 h) but higher viability in longer infection time periods (i.e. 6–8 h; significant at 8 h) compared to osteoblasts. In addition, S. aureusinfection led to significant changes in reactive oxygen species production in both macrophages and osteoblasts. Moreover, infected osteoblasts had significantly lower alkaline phosphatase activity at post-infection day 7 and infected macrophages had higher phagocytosis activity compared to non-infected cells. Conclusions S. aureus was found to internalize and survive within osteoblasts and macrophages and led to differential responses between osteoblasts and macrophages. These findings may assist in evaluation of the pathogenesis of chronic and recurrent infections which may be related to the intracellular persistence of bacteria within host cells

Long memory estimation for complex-valued time series

Long memory has been observed for time series across a multitude of fields and the accurate estimation of such dependence, e.g. via the Hurst exponent, is crucial for the modelling and prediction of many dynamic systems of interest. Many physical processes (such as wind data), are more naturally expressed as a complex-valued time series to represent magnitude and phase information (wind speed and direction). With data collection ubiquitously unreliable, irregular sampling or missingness is also commonplace and can cause bias in a range of analysis tasks, including Hurst estimation. This article proposes a new Hurst exponent estimation technique for complex-valued persistent data sampled with potential irregularity. Our approach is justified through establishing attractive theoretical properties of a new complex-valued wavelet lifting transform, also introduced in this paper. We demonstrate the accuracy of the proposed estimation method through simulations across a range of sampling scenarios and complex- and real-valued persistent processes. For wind data, our method highlights that inclusion of the intrinsic correlations between the real and imaginary data, inherent in our complex-valued approach, can produce different persistence estimates than when using real-valued analysis. Such analysis could then support alternative modelling or policy decisions compared with conclusions based on real-valued estimation

Treatment Targets in Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) imparts a higher mortality and morbidity than ischemic stroke. The therapeutic interventions that are currently available focus mainly on supportive care and secondary prevention. There is a paucity of evidence to support any one acute intervention that improves functional outcome. This chapter highlights current treatment targets for ICH based on the pathophysiology of the disease