Screening, Diagnosis, and Management of Open Angle Glaucoma: An Evidence-Based Guideline for Canadian Optometrists

Glaucoma is the most common form of irreversible blindness in the world, and second only to cataract among all causes of blindness. There is still no universally agreed-upon definition of glaucoma, and as such, it remains a condition for which there are differing views on the classification of individuals within the continuum of suspicion through diagnosis. Regardless, there appears to be consensus that glaucoma refers to a group of diseases that manifest as a characteristic progressive optic neuropathy and retinal ganglion cell loss that eventually leads to a permanent loss of visual field. Glaucoma is a major public health issue because individuals are typically asymptomatic until end stages of the disease when the associated vision loss is significant and irreversible. Studies have shown that the prevalence of undetected glaucoma is as high as 50% even in high income areas including North America and Australia, increasing to 90% in middle and low income areas such as Asia and Africa. This is at least in part a result of inadequate screening tools and strategies to detect this asymptomatic disease: without more individuals accessing routine eye examinations, glaucoma will continue to go undetected. Vision loss from glaucoma imposes significant societal and economic burdens that increase with disease severity: the direct costs of vision loss from glaucoma exceed $300 million annually in Canada, and approach$2 billion across North America

Do Complexity Measures of Frontal EEG Distinguish Loss of Consciousness in Geriatric Patients Under Anesthesia?

While geriatric patients have a high likelihood of requiring anesthesia, they carry an increased risk for adverse cognitive outcomes from its use. Previous work suggests this could be mitigated by better intraoperative monitoring using indexes defined by several processed electroencephalogram (EEG) measures. Unfortunately, inconsistencies between patients and anesthetic agents in current analysis techniques have limited the adoption of EEG as standard of care. In attempts to identify new analyses that discriminate clinically-relevant anesthesia timepoints, we tested 1/f frequency scaling as well as measures of complexity from nonlinear dynamics. Specifically, we tested whether analyses that characterize time-delayed embeddings, correlation dimension (CD), phase-space geometric analysis, and multiscale entropy (MSE) capture loss-of-consciousness changes in EEG activity. We performed these analyses on EEG activity collected from a traditionally hard-to-monitor patient population: geriatric patients on beta-adrenergic blockade who were anesthetized using a combination of fentanyl and propofol. We compared these analyses to traditional frequency-derived measures to test how well they discriminated EEG states before and after loss of response to verbal stimuli. We found spectral changes similar to those reported previously during loss of response. We also found significant changes in 1/f frequency scaling. Additionally, we found that our phase-space geometric characterization of time-delayed embeddings showed significant differences before and after loss of response, as did measures of MSE. Our results suggest that our new spectral and complexity measures are capable of capturing subtle differences in EEG activity with anesthesia administration-differences which future work may reveal to improve geriatric patient monitoring

Optioneering analysis for connecting Dogger Bank offshore wind farms to the GB electricity network

This paper outlines possibilities for connecting 2.4 GW of power from two separate wind farms at Dogger Bank in the North Sea to the GB transmission system in Great Britain. Three options based on HVDC with Voltage Source Converters (VSC HVDC) are investigated: two separate point-to-point connections, a four-terminal multi-terminal network and a four-terminal network with the addition of an AC auxiliary cable between the two wind farms. Each option is investigated in terms of investment cost, controllability and reliability against expected fault scenarios. The paper concludes that a VSC-HVDC point-to-point connection is the cheapest option in terms of capital cost and has the additional advantage that it uses technology that is commercially available. However, while multi-terminal connections are more expensive to build it is found that they can offer significant advantages over point to point systems in terms of security of supply and so could offer better value for money overall. A multi-terminal option with an auxiliary AC connection between wind farms is found to be lower cost than a full multi-terminal DC grid option although the latter network would offer ability to operate at greater connection distances between substations

Adenosine-mono-phosphate-activated protein kinase-independent effects of metformin in T cells

The anti-diabetic drug metformin regulates T-cell responses to immune activation and is proposed to function by regulating the energy-stress-sensing adenosine-monophosphate-activated protein kinase (AMPK). However, the molecular details of how metformin controls T cell immune responses have not been studied nor is there any direct evidence that metformin acts on T cells via AMPK. Here, we report that metformin regulates cell growth and proliferation of antigen-activated T cells by modulating the metabolic reprogramming that is required for effector T cell differentiation. Metformin thus inhibits the mammalian target of rapamycin complex I signalling pathway and prevents the expression of the transcription factors c-Myc and hypoxia-inducible factor 1 alpha. However, the inhibitory effects of metformin on T cells did not depend on the expression of AMPK in T cells. Accordingly, experiments with metformin inform about the importance of metabolic reprogramming for T cell immune responses but do not inform about the importance of AMPK

Filtration‐histogram based magnetic resonance texture analysis (Mrta) for the distinction of primary central nervous system lymphoma and glioblastoma

Primary central nervous system lymphoma (PCNSL) has variable imaging appearances, which overlap with those of glioblastoma (GBM), thereby necessitating invasive tissue diagnosis. We aimed to investigate whether a rapid filtration histogram analysis of clinical MRI data supports the distinction of PCNSL from GBM. Ninety tumours (PCNSL n = 48, GBM n = 42) were analysed using pre‐treatment MRI sequences (T1‐weighted contrast‐enhanced (T1CE), T2‐weighted (T2), and apparent diffusion coefficient maps (ADC)). The segmentations were completed with proprietary texture analysis software (TexRAD version 3.3). Filtered (five filter sizes SSF = 2–6 mm) and unfil-tered (SSF = 0) histogram parameters were compared using Mann‐Whitney U non‐parametric test-ing, with receiver operating characteristic (ROC) derived area under the curve (AUC) analysis for significant results. Across all (n = 90) tumours, the optimal algorithm performance was achieved using an unfiltered ADC mean and the mean of positive pixels (MPP), with a sensitivity of 83.8%, specificity of 8.9%, and AUC of 0.88. For subgroup analysis with >1/3 necrosis masses, ADC permit-ted the identification of PCNSL with a sensitivity of 96.9% and specificity of 100%. For T1CE‐derived regions, the distinction was less accurate, with a sensitivity of 71.4%, specificity of 77.1%, and AUC of 0.779. A role may exist for cross‐sectional texture analysis without complex machine learning models to differentiate PCNSL from GBM. ADC appears the most suitable sequence, especially for necrotic lesion distinction

Multidataset Incremental Training for Optic Disc Segmentation

When convolutional neural networks are applied to image segmentation results depend greatly on the data sets used to train the networks. Cloud providers support multi GPU and TPU virtual machines making the idea of cloud-based segmentation as service attractive. In this paper we study the problem of building a segmentation service, where images would come from different acquisition instruments, by training a generalized U-Net with images from a single or several datasets. We also study the possibility of training with a single instrument and perform quick retrains when more data is available. As our example we perform segmentation of Optic Disc in fundus images which is useful for glau coma diagnosis. We use two publicly available data sets (RIM-One V3, DRISHTI) for individual, mixed or incremental training. We show that multidataset or incremental training can produce results that are simi lar to those published by researchers who use the same dataset for both training and validation

Large scale three-dimensional modelling for wave and tidal energy resource and environmental impact : methodologies for quantifying acceptable thresholds for sustainable exploitation

We describe a modelling project to estimate the potential effects of wave & tidal stream renewables on the marine environment. • Realistic generic devices to be used by those without access to the technical details available to developers are described. • Results show largely local sea bed effects at the level of the currently proposed renewables developments in our study area. • Large scale 3D modelling is critical to quantify the direct, indirect and cumulative effects of renewable energy extraction. • This is critical to comply with planning & environmental impact assessment regulations and achieve Good Environmental Status

Global longitudinal active strain energy density (GLASED): age and sex differences between young and veteran athletes

Background Global longitudinal active strain energy density (GLASED) is an innovative method for assessing myocardial function and quantifies the work performed per unit volume of the left ventricular myocardium. The GLASED, measured using MRI, is the best prognostic marker currently available. This study aimed to evaluate the feasibility of measuring the GLASED using echocardiography and to investigate potential differences in the GLASED among athletes based on age and sex. Methods An echocardiographic study was conducted with male controls, male and female young athletes, and male and female veteran athletes. GLASED was calculated from the myocardial stress and strain. Results The mean age (in years) of the young athletes was 21.6 for males and 21.4 for females, while the mean age of the veteran athletes was 53.5 for males and 54.2 for females. GLASED was found to be highest in young male athletes (2.40 kJ/m3) and lowest in female veterans (1.96 kJ/m3). Veteran males exhibited lower values (1.96 kJ/m3) than young male athletes did (P < 0.001). Young females demonstrated greater GLASED (2.28 kJ/m3) than did veteran females (P < 0.01). However, no significant difference in the GLASED was observed between male and female veterans. Conclusion Our findings demonstrated the feasibility of measuring GLASED using echocardiography. GLASED values were greater in young male athletes than in female athletes and decreased with age, suggesting possible physiological differences in their myocardium. The sex-related differences observed in GLASED values among young athletes were no longer present in veteran athletes. We postulate that measuring the GLASED may serve as a useful additional screening tool for cardiac diseases in athletes, particularly for those with borderline phenotypes of hypertrophic and dilated cardiomyopathies