Semi-Automated Image Analysis Methodology to Investigate Intracellular Heterogeneity in Immunohistochemical Stained Sections

The discovery of tissue heterogeneity revolutionized the existing knowledge regarding the cellular, molecular, and pathophysiological mechanisms in biomedicine. Therefore, basic science investigations were redirected to encompass observation at the classical and quantum biology levels. Various approaches have been developed to investigate and capture tissue heterogeneity; however, these approaches are costly and incompatible with all types of samples. In this paper, we propose an approach to quantify heterogeneous cellular populations through combining histology and images processing techniques. In this approach, images of immunohistochemically stained sections are processed through color binning of DAB-stained cells (in brown) and non-stained cells (in blue) to select cellular clusters expressing biomarkers of interest. Subsequently, the images were converted to a binary format through threshold modification (threshold 60%) in the grey scale. The cell count was extrapolated from the binary images using the particle analysis tool in ImageJ. This approach was applied to quantify the level of progesterone receptor expression levels in a breast cancer cell line sample. The results of the proposed approach were found to closely reflect those of manual counting. Through this approach, quantitative measures can be added to qualitative observation of subcellular targets expression

"Precious Metals-Exchange Rate Volatility Transmissions and Hedging Strategies"

This study examines the conditional volatility and correlation dependency and interdependency for the four major precious metals (that is, gold, silver, platinum and palladium), while accounting for geopolitics within a multivariate system. The implications of the estimated results for portfolio designs and hedging strategies are also analyzed. The results for the four metals system show significant short-run and long-run dependencies and interdependencies to news and past volatility. These results have become more pervasive when the exchange rate and FFR are included. Monetary policy also has a differential impact on the precious metals and the exchange rate volatilities. Finally, the applications of the results show the optimal weights in a two-asset portfolio and the hedging ratios for long positions.

Precious Metals-Exchange Rate Volatility Transmissions and Hedging Strategies

This study examines the conditional volatility and correlation dependency and interdependency for the four major precious metals (that is, gold, silver, platinum and palladium), while accounting for geopolitics within a multivariate system. The implications of the estimated results for portfolio designs and hedging strategies are also analyzed. The results for the four metals system show significant short-run and long-run dependencies and interdependencies to news and past volatility. These results have become more pervasive when the exchange rate and FFR are included. Monetary policy also has a differential impact on the precious metals and the exchange rate volatilities. Finally, the applications of the results show the optimal weights in a two-asset portfolio and the hedging ratios for long positions.

One year prognosis of young Middle Eastern patients undergoing percutaneous coronary interventions

Background: There is scarcity of data about the outcome in young Middle Eastern patients who undergo percutaneous coronary intervention (PCI). We sought to assess clinical and coronary angiographic features and one year outcome of young compared with older patients following PCI.Methods: Baseline clinical and coronary angiographic features and major cardiovascular events from hospital admission to one year were assessed in young patients (45 years of age).Results: Of 2426 patients; 308 (12.7%) were young. Young and older patients were predominantly males (76.3% vs. 79.8%; p=0.18) and had similar prevalence of hypertension, diabetes, dyslipidemia, and cigarette smoking. There were no differences between young and older patients in the rates of acute coronary syndrome as an indication for PCI (75.6% vs. 76.1%; p=0.90). The two groups had similar prevalence of one-vessel coronary artery disease (55.2% vs. 58.1%; p=0.37) and intervention for one vessel (74.0% vs. 72.1%; p=0.53). No significant differences were observed in the incidence of in-hospital adverse events in young compared with older patients. Incidence of adverse events in young patients at one year were not different from those in older patients, including cardiac death (3.63% vs. 2.11%), stent thrombosis (3.63% vs. 2.08%), major bleeding (1.30% vs. 1.18%), and coronary revascularization (3.65% vs. 3.24%); all p=NS.Conclusions: Among Middle Eastern patients undergoing coronary intervention; 13% were 45 years of age or younger. No favourable risk profile, coronary angiographic features or cardiovascular outcome were observed in young compared with older patients

Network traffic analysis for threats detection in the Internet of Things

As the prevalence of the Internet of Things (IoT) continues to increase, cyber criminals are quick to exploit the security gaps that many devices are inherently designed with. Users cannot be expected to tackle this threat alone, and many current solutions available for network monitoring are simply not accessible or can be difficult to implement for the average user, which is a gap that needs to be addressed. This article presents an effective signature-based solution to monitor, analyze, and detect potentially malicious traffic for IoT ecosystems in the typical home network environment by utilizing passive network sniffing techniques and a cloud application to monitor anomalous activity. The proposed solution focuses on two attack and propagation vectors leveraged by the infamous Mirai botnet, namely DNS and Telnet. Experimental evaluation demonstrates the proposed solution can detect 98.35 percent of malicious DNS traffic and 99.33 percent of Telnet traffic for an overall detection accuracy of 98.84 percent

Millimetric wavelength mobile radio characterisation and frequency diversity propagation measurements

SIGLEAvailable from British Library Document Supply Centre- DSC:DX92447 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

A Systematic Review of the Availability and Efficacy of Countermeasures to Internal Threats in Healthcare Critical Infrastructure

Insider attacks are becoming increasingly detrimental and frequent, affecting critical infrastructure at a massive scale. Recent attacks such as the UK National Health Service (NHS) WannaCry ransomware attack which partly depends on internal users for initial infection highlight the increasing role of the malicious insiders in cyber attack campaigns . The objective of this research is to ascertain the existing technological capability to mitigate insider threats within computer security systems by way of a mixed-method systematic review. Evidence was acquired from major sources of mainstream and grey literature by analysing about 300, 000 papers. Crude aggregated results were analysed across the literature, the results were TPR 0.75, FPR 0.32, σ 0.24 and 0.36 respectively, σ 2 0.06 and 0.13 respectively. In totality, the literature evidence suggests that there is high heterogeneity across crude data indicating that the effectiveness of security measures varies significantly. No solution is able to totally mitigate an insider threat. Themes when set against that data suggest that most, if not all, security measures require breaches to occur before an analysis of malicious activity can prevent it in future through recall. Such a reactive approach is not effective to protect our critical infrastructure including our healthcare systems. Consequently, there is a major theoretical shortfall in current cyber defence architecture

Behaviour Profiling in Healthcare Applications Using the Internet of Things Technology

This position paper advocates applying the monitoring pogwer of IoT to build profiles of user behaviour using the large volumes of collected data. The desired system exploits sensor data mining approaches to profile user behaviour patterns in smart environments. Sensor data is mined to extract relationships of interest between environmental variables (context) and the user, building in this way behaviour profiles. The capability of applying knowledge to manipulate user’s environment is expected take monitoring beyond the simple alert-mode of operation to long term profiling of user’s behaviour. After a brief literature review to prove the suitability of IoT as a low-cost unsupervised profiling platform, we give the details of our proposal and the objectives that needs to be met before user behaviour profiling across inter-spaces is possible