HDBuzz: empowering patients through accessible education

Research and patient communities are firmly interdependent. Engaged patient communities provide biological samples and data that drive discoveries which, in turn, fuel the development of novel therapies. Historically, Huntington's disease (HD) has benefited from trusting interactions between scientists and patients. However, even for HD, communication between the research and patient communities is suboptimal. The web platform HDBuzz was created to rectify this situation by providing accurate, accessible information on the latest HD research to patients and their supporters

Literacy development: evidence review

Literacy includes the word-level skills of word reading and spelling and the text-level skills of reading comprehension and writing composition. These skills are involved in virtually all everyday activities. As a result, poor literacy impacts on every aspect of life. Word reading, spelling, reading comprehension, and writing composition are supported by similar language and cognitive skills as well as affective and environment factors. Learning to be literate builds upon existing knowledge of the language from speech. Becoming literate then enables children to learn more about language. However, literacy is unlikely to be achieved without explicit and prolonged instruction. This review provides an evidence base for decision-making during literacy education. We identify key skills that must be in place to enable children to reach their optimum potential and highlight where weakness can suggest a need for extra support. We begin by discussing models of literacy development as these models provide a framework within which to present the evidence base for the rest of the review. We then consider the underlying skills in greater depth, beginning first with the proximal factors that underpin word-level and text-level reading and writing. Then we consider distal child-based and wider environmental factors that indirectly impact on literacy development

Adaptive optics imaging of inherited retinal diseases.

Adaptive optics (AO) ophthalmoscopy allows for non-invasive retinal phenotyping on a microscopic scale, thereby helping to improve our understanding of retinal diseases. An increasing number of natural history studies and ongoing/planned interventional clinical trials exploit AO ophthalmoscopy both for participant selection, stratification and monitoring treatment safety and efficacy. In this review, we briefly discuss the evolution of AO ophthalmoscopy, recent developments and its application to a broad range of inherited retinal diseases, including Stargardt disease, retinitis pigmentosa and achromatopsia. Finally, we describe the impact of this in vivo microscopic imaging on our understanding of disease pathogenesis, clinical trial design and outcome metrics, while recognising the limitation of the small cohorts reported to date

RAC-CNN: multimodal deep learning based automatic detection and classification of rod and cone photoreceptors in adaptive optics scanning light ophthalmoscope images

Quantification of the human rod and cone photoreceptor mosaic in adaptive optics scanning light ophthalmoscope (AOSLO) images is useful for the study of various retinal pathologies. Subjective and time-consuming manual grading has remained the gold standard for evaluating these images, with no well validated automatic methods for detecting individual rods having been developed. We present a novel deep learning based automatic method, called the rod and cone CNN (RAC-CNN), for detecting and classifying rods and cones in multimodal AOSLO images. We test our method on images from healthy subjects as well as subjects with achromatopsia over a range of retinal eccentricities. We show that our method is on par with human grading for detecting rods and cones

Probing Density Fluctuations using the FIRST Radio Survey

We use results of angular clustering measurements in 3000 sq. deg's of the FIRST radio survey to infer information on spatial clustering. Measurements are compared with CDM-model predictions. Clustering of FIRST sources with optical ID's in the APM catalog are also investigated. Finally, we outline a preliminary search for a weak lensing signal in the survey.Comment: 6 pages latex, 2 figures, to appear in Cosmology with the New Radio Surveys (Kluwer

Effects of color-enhancing glasses on color vision in congenital red-green color deficiencies

As commercially available glasses for color vision deficiency (CVD) are classified as low risk, they are not subject to stringent marketing regulations. We investigate how EnChroma and VINO glasses affect performance on the Colour Assessment and Diagnosis (CAD) test in individuals with CVD. Data were obtained from 51 individuals with red-green CVD. Blood or saliva samples were collected to examine the structure of the OPN1LW/OPN1MW array. Individuals completed the CAD test twice without glasses and once with each pair of glasses. Although there was a statistically significant effect of both glasses, only that of VINO could be considered functionally meaningful

Deep learning based detection of cone photoreceptors with multimodal adaptive optics scanning light ophthalmoscope images of achromatopsia

Fast and reliable quantification of cone photoreceptors is a bottleneck in the clinical utilization of adaptive optics scanning light ophthalmoscope (AOSLO) systems for the study, diagnosis, and prognosis of retinal diseases. To-date, manual grading has been the sole reliable source of AOSLO quantification, as no automatic method has been reliably utilized for cone detection in real-world low-quality images of diseased retina. We present a novel deep learning based approach that combines information from both the confocal and non-confocal split detector AOSLO modalities to detect cones in subjects with achromatopsia. Our dual-mode deep learning based approach outperforms the state-of-the-art automated techniques and is on a par with human grading

Water Challenges for Geologic Carbon Capture and Sequestration

Carbon capture and sequestration (CCS) has been proposed as a means to dramatically reduce greenhouse gas emissions with the continued use of fossil fuels. For geologic sequestration, the carbon dioxide is captured from large point sources (e.g., power plants or other industrial sources), transported to the injection site and injected into deep geological formations for storage. This will produce new water challenges, such as the amount of water used in energy resource development and utilization and the “capture penalty” for water use. At depth, brine displacement within formations, storage reservoir pressure increases resulting from injection, and leakage are potential concerns. Potential impacts range from increasing water demand for capture to contamination of groundwater through leakage or brine displacement. Understanding these potential impacts and the conditions under which they arise informs the design and implementation of appropriate monitoring and controls, important both for assurance of environmental safety and for accounting purposes. Potential benefits also exist, such as co-production and treatment of water to both offset reservoir pressure increase and to provide local water for beneficial use

Assessing the Interocular Symmetry of Foveal Outer Nuclear Layer Thickness in Achromatopsia

Purpose: We examine the interocular symmetry of foveal outer nuclear layer (ONL) thickness measurements in subjects with achromatopsia (ACHM). Methods: Images from 76 subjects with CNGA3- or CNGB3-associated ACHM and 42 control subjects were included in the study. Line or volume scans through the fovea of each eye were acquired using optical coherence tomography (OCT). Image quality was assessed for each image included in the analysis using a previously-described maximum tissue contrast index (mTCI) metric. Three foveal ONL thickness measurements were made by a single observer and interocular symmetry was assessed using the average of the three measurements for each eye. Results: Mean (± standard deviation) foveal ONL thickness for subjects with ACHM was 79.7 ± 18.3 μm (right eye) and 79.2 ± 18.7 μm (left eye) compared to 112.9 ± 15.2 (right eye) and 112.1 ± 13.9 μm (left eye) for controls. Foveal ONL thickness did not differ between eyes for ACHM (P = 0.636) or control subjects (P = 0.434). No significant relationship between mTCI and observer repeatability was observed for either control (P = 0.140) or ACHM (P = 0.351) images. Conclusions: While foveal ONL thickness is reduced in ACHM compared to controls, the high interocular symmetry indicates that contralateral ONL measurements could be used as a negative control in early-phase monocular treatment trials. Translational Relevance: Foveal ONL thickness can be measured using OCT images over a wide range of image quality. The interocular symmetry of foveal ONL thickness in ACHM and control populations supports the use of the non-study eye as a control for clinical trial purposes

Extracting spacing-derived estimates of rod density in healthy retinae

Quantification of the rod photoreceptor mosaic using adaptive optics scanning light ophthalmoscopy (AOSLO) remains challenging. Here we demonstrate a method for deriving estimates of rod density and rod:cone ratio based on measures of rod spacing, cone numerosity, and cone inner segment area. Twenty-two AOSLO images with complete rod visualization were used to validate this spacing-derived method for estimating density. The method was then used to estimate rod metrics in an additional 105 images without complete rod visualization. The spacing-derived rod mosaic metrics were comparable to published data from histology. This method could be leveraged to develop large normative databases of rod mosaic metrics, though limitations persist with intergrader variability in assessing cone area and numerosity