Update and guidance on management of myopia. European Society of Ophthalmology in cooperation with International Myopia Institute

The prevalence of myopia is increasing extensively worldwide. The number of people with myopia in 2020 is predicted to be 2.6 billion globally, which is expected to rise up to 4.9 billion by 2050, unless preventive actions and interventions are taken. The number of individuals with high myopia is also increasing substantially and pathological myopia is predicted to become the most common cause of irreversible vision impairment and blindness worldwide and also in Europe. These prevalence estimates indicate the importance of reducing the burden of myopia by means of myopia control interventions to prevent myopia onset and to slow down myopia progression. Due to the urgency of the situation, the European Society of Ophthalmology decided to publish this update of the current information and guidance on management of myopia. The pathogenesis and genetics of myopia are also summarized and epidemiology, risk factors, preventive and treatment options are discussed in details

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications

This work was supported by a restricted research grant of Bayer AG

Rigolon_Nemeth_-_Appendix_online_supp – Supplemental material for What Shapes Uneven Access to Urban Amenities? Thick Injustice and the Legacy of Racial Discrimination in Denver’s Parks

<p>Supplemental material, Rigolon_Nemeth_-_Appendix_online_supp for What Shapes Uneven Access to Urban Amenities? Thick Injustice and the Legacy of Racial Discrimination in Denver’s Parks by Alessandro Rigolon and Jeremy Németh in Journal of Planning Education and Research</p

The neighborhood built environment and COVID-19 hospitalizations.

Research on the associations between the built environment and COVID-19 outcomes has mostly focused on incidence and mortality. Also, few studies on the built environment and COVID-19 have controlled for individual-level characteristics across large samples. In this study, we examine whether neighborhood built environment characteristics are associated with hospitalization in a cohort of 18,042 individuals who tested positive for SARS-CoV-2 between May and December 2020 in the Denver metropolitan area, USA. We use Poisson models with robust standard errors that control for spatial dependence and several individual-level demographic characteristics and comorbidity conditions. In multivariate models, we find that among individuals with SARS-CoV-2 infection, those living in multi-family housing units and/or in places with higher particulate matter (PM2.5) have a higher incident rate ratio (IRR) of hospitalization. We also find that higher walkability, higher bikeability, and lower public transit access are linked to a lower IRR of hospitalization. In multivariate models, we did not find associations between green space measures and the IRR of hospitalization. Results for non-Hispanic white and Latinx individuals highlight substantial differences: higher PM2.5 levels have stronger positive associations with the IRR of hospitalization for Latinx individuals, and density and overcrowding show stronger associations for non-Hispanic white individuals. Our results show that the neighborhood built environment might pose an independent risk for COVID-19 hospitalization. Our results may inform public health and urban planning initiatives to lower the risk of hospitalization linked to COVID-19 and other respiratory pathogens

Myopia management algorithm. Annexe to the article titled Update and guidance on management of myopia. European Society of Ophthalmology in cooperation with International Myopia Institute

Myopia is becoming increasingly common in young generations all over the world, and it is predicted to become the most common cause of blindness and visual impairment in later life in the near future. Because myopia can cause serious complications and vision loss, it is critical to create and prescribe effective myopia treatment solutions that can help prevent or delay the onset and progression of myopia. The scientific understanding of myopia's causes, genetic background, environmental conditions, and various management techniques, including therapies to prevent or postpone its development and slow its progression, is rapidly expanding. However, some significant information gaps exist on this subject, making it difficult to develop an effective intervention plan. As with the creation of this present algorithm, a compromise is to work on best practices and reach consensus among a wide number of specialists. The quick rise in information regarding myopia management may be difficult for the busy eye care provider, but it necessitates a continuing need to evaluate new research and implement it into daily practice. To assist eye care providers in developing these strategies, an algorithm has been proposed that covers all aspects of myopia mitigation and management. The algorithm aims to provide practical assistance in choosing and developing an effective myopia management strategy tailored to the individual child. It incorporates the latest research findings and covers a wide range of modalities, from primary, secondary, and tertiary myopia prevention to interventions that reduce the progression of myopia