Hyponatremic hypertensive syndrome (HHS) in an 18-month old-child presenting as malignant hypertension: a case report

BACKGROUND: The combination of hyponatremia and renovascular hypertension is called hyponatremic hypertensive syndrome (HHS). Malignant hypertension as a presentation has been reported in adults with HHS but is rare in children. CASE PRESENTATION: An eighteen month-old male presented with drowsiness, sudden onset status epilepticus and blood pressure of 210/160. The electrolytes on admission revealed sodium of 120 mEq/L and potassium of 2.1 mEq/L. The peripheral renin activity (PRA) was 172 ng/ml/min (normal 3–11 ng/ml/min) and serum aldosterone level was 91 ng/dl (normal 4 to 16 ng/dl). Patient underwent angioplasty with no success, followed by surgical correction. Two years since the diagnosis, the blood pressure is controlled with labetolol and amlodipine (at less than sixth of the pre-operative dosages). The PRA is 2.4 ng/ml/min and aldosterone 15.5 ng/dl. The child not only had three renal arteries on left but all of them were stenosed which to best of our knowledge has not been described. CONCLUSION: As uncommon as HHS with malignant hypertension may be in adults it is under-reported in children and purpose of the case report is to raise its awareness

Context-dependent combination of sensor information in Dempster–Shafer theory for BDI

© 2016, The Author(s). There has been much interest in the belief–desire–intention (BDI) agent-based model for developing scalable intelligent systems, e.g. using the AgentSpeak framework. However, reasoning from sensor information in these large-scale systems remains a significant challenge. For example, agents may be faced with information from heterogeneous sources which is uncertain and incomplete, while the sources themselves may be unreliable or conflicting. In order to derive meaningful conclusions, it is important that such information be correctly modelled and combined. In this paper, we choose to model uncertain sensor information in Dempster–Shafer (DS) theory. Unfortunately, as in other uncertainty theories, simple combination strategies in DS theory are often too restrictive (losing valuable information) or too permissive (resulting in ignorance). For this reason, we investigate how a context-dependent strategy originally defined for possibility theory can be adapted to DS theory. In particular, we use the notion of largely partially maximal consistent subsets (LPMCSes) to characterise the context for when to use Dempster’s original rule of combination and for when to resort to an alternative. To guide this process, we identify existing measures of similarity and conflict for finding LPMCSes along with quality of information heuristics to ensure that LPMCSes are formed around high-quality information. We then propose an intelligent sensor model for integrating this information into the AgentSpeak framework which is responsible for applying evidence propagation to construct compatible information, for performing context-dependent combination and for deriving beliefs for revising an agent’s belief base. Finally, we present a power grid scenario inspired by a real-world case study to demonstrate our work

Characterisation of a CZT detector for dosimetry of molecular radiotherapy

A pixelated cadmium zinc telluride (CZT) detector has been characterised for the purpose of developing a quantitative single photon emission computed tomography (SPECT) system for dosimetry of molecular radiotherapy (MRT). This is the aim of the Dosimetric Imaging with CZT (DEPICT) project, which is a collaboration between the University of Liverpool, The Royal Marsden Hospital, The Royal Liverpool and Broadgreen University Hospital, and the commercial partner Kromek. CZT is a direct band gap semiconductor with superior energy resolution and stopping power compared to scintillator detectors used in current SPECT systems. The inherent detector properties have been investigated and operational parameters such as bias voltage and peaking time have been selected to optimise the performance of the system. Good energy resolution is required to discriminate γ-rays that are scattered as they are emitted from the body and within the collimator, and high photon throughput is essential due to the high activities of isotopes administered in MRT. The system has an average measured electronic noise of 3.31 keV full width at half maximum (FWHM), determined through the use of an internal pulser. The energy response of the system was measured across the energy region of interest 59.5 keV to 364.5 keV and found to be linear. The reverse bias voltage and peaking time producing the optimum FWHM and maximum photon throughput were 600 V and 0.5 μs respectively. The average dead time of the system was measured as 4.84 μs and charge sharing was quantified to be 0.71 % at 59.5 keV . A pixel sensitivity calibration map was created and planar images of the medical imaging isotopes 99mTc and 123I were acquired by coupling the device to a prototype collimator, thereby demonstrating the suitability of the detector for the DEPICT project