Risk factors for progression to blindness in high tension primary open angle glaucoma: Comparison of blind and nonblind subjects

Karanjit S Kooner1, Mohannad AlBdoor1, Byung J Cho3, Beverley Adams-Huet21Department of Ophthalmology, 2Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA; 3Konkuk University Hospital, Seoul, KoreaAims: To determine which risk factors for blindness were most critical in patients diagnosed with high tension primary open angle glaucoma (POAG) in a large ethnically diverse population managed with a uniform treatment strategy.Methods: A longitudinal observational study was designed to follow 487 patients (974 eyes) with POAG for an average of 5.5 ± 3.6 years. Detailed ocular and systemic information was collected on each patient and updated every six months. For this study, blindness was defined as visual acuity of 20/200 or worse and/or visual field less than 20° in either eye. Known risk factors were compared between patients with blindness in at least one eye versus nonblind patients.Results: The patients with blindness had on average: higher intraocular pressure (IOP, mmHg): (24.2 ± 11.2 vs. 22.1 ± 7.7, p = 0.03), wide variation of IOP in the follow-up period (5.9 vs. 4.1 mmHg, p = 0.031), late detection (p = 0.006), poor control of IOP (p < 0.0001), and noncompliance (p < 0.0003). Other known risk factors such as race, age, myopia, family history of glaucoma, history of ocular trauma, hypertension, diabetes, vascular disease, smoking, alcohol abuse, dysthyoidism, and steroid use were not significant.Conclusions: The most critical factors associated with the development of blindness among our patients were: elevated initial IOP, wide variations and poor control of IOP, late detection of glaucoma, and noncompliance with therapy.Keywords: primary open angle glaucoma, blindness, intraocular pressure, risk factors, and noncomplianc

Using DNA Metabarcoding to Identify the Floral Composition of Honey:A New Tool for Investigating Honey Bee Foraging Preferences

Identifying the floral composition of honey provides a method for investigating the plants that honey bees visit. We compared melissopalynology, where pollen grains retrieved from honey are identified morphologically, with a DNA metabarcoding approach using the rbcL DNA barcode marker and 454-pyrosequencing. We compared nine honeys supplied by beekeepers in the UK. DNA metabarcoding and melissopalynology were able to detect the most abundant floral components of honey. There was 92% correspondence for the plant taxa that had an abundance of over 20%. However, the level of similarity when all taxa were compared was lower, ranging from 22–45%, and there was little correspondence between the relative abundance of taxa found using the two techniques. DNA metabarcoding provided much greater repeatability, with a 64% taxa match compared to 28% with melissopalynology. DNA metabarcoding has the advantage over melissopalynology in that it does not require a high level of taxonomic expertise, a greater sample size can be screened and it provides greater resolution for some plant families. However, it does not provide a quantitative approach and pollen present in low levels are less likely to be detected. We investigated the plants that were frequently used by honey bees by examining the results obtained from both techniques. Plants with a broad taxonomic range were detected, covering 46 families and 25 orders, but a relatively small number of plants were consistently seen across multiple honey samples. Frequently found herbaceous species were Rubus fruticosus, Filipendula ulmaria, Taraxacum officinale, Trifolium spp., Brassica spp. and the non-native, invasive, Impatiens glandulifera. Tree pollen was frequently seen belonging to Castanea sativa, Crataegus monogyna and species of Malus, Salix and Quercus. We conclude that although honey bees are considered to be supergeneralists in their foraging choices, there are certain key species or plant groups that are particularly important in the honey bees environment. The reasons for this require further investigation in order to better understand honey bee nutritional requirements. DNA metabarcoding can be easily and widely used to investigate floral visitation in honey bees and can be adapted for use with other insects. It provides a starting point for investigating how we can better provide for the insects that we rely upon for pollination

Regional calendars and seasonal statistics for the United Kingdom's main pollen allergens

Pollen calendars are an effective way of bringing seasonal information to patients, healthcare professionals and pharmaceutical companies.1 Until now, there has only been one generalized pollen calendar available for the United Kingdom and very limited access to any recent seasonal statistics.3 Here, we present a set of regional pollen calendars and associated statistics to bring up-to-date information to patients and other users and to demonstrate spatial variation in the pollen seasons

Air mass trajectories and land cover map reveal cereal crops as major local sources of Alternaria spores in Worcester and Leicester, UK.

Alternaria is a plant pathogen and human allergen. Agricultural areas are known sources of Alternaria spores. Transport of Alternaria spores may occur between such geographical regions. This study examined Alternaria spore abundance and potential pathways for atmospheric transport of the spores between the cities of Worcester and Leicester in the UK, both surrounded by agricultural land. Alternaria spores were sampled using Burkard volumetric samplers for the period 2016-2018 at Worcester and Leicester, located ~90 km apart. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and UK’s land cover map for crops were used to examine the relationship between air mass trajectories and potential source areas of Alternaria spores at the two locations during an episode (27 Jul-07 Aug 2017) of high spore concentrations. During the 3 years of observation, 61 and 151 days of clinical relevance were recorded at Worcester and Leicester, respectively. Spore concentrations at Leicester were considerably higher than in Worcester. Analysis of the crop map showed higher amounts of winter barley and oilseed rape near to Leicester than Worcester. HYSPLIT calculations showed that during the episode, the air masses arrived at both stations from Ireland and the Atlantic Ocean. Long distance transport probably had a small and equal contribution to the observations at both sites. The hypothesis is therefore that the substantially higher concentrations of Alternaria spores at Leicester are caused by specific local sources with high emission potential: potentially winter barley and oilseed rape. Local sources of winter barley and oilseed rape likely contributed to Alternaria spore concentrations of clinical significance in the urban areas of Leicester and Worcester. The strength of the local sources likely resulted in higher emissions of spores at Leicester than at Worcester. Long distance transport probably had a small but equal contribution to the total spore load at the two stations

Coastal Ecosystems and Tsunami Protection after the December 2004 Indian Ocean Tsunami

An exploratory study was conducted on the role of coastal ecosystems in protecting communities from the December 2004 Indian Ocean tsunami, focusing on mangrove forests on the Andaman coast of Thailand and how well villages were undertaking environmental conservation. Remote sensing analysis identified predisaster mangrove change and postdisaster structural damage and landscape changes. Field data from five sites (20 villages), gathered via the VIEWS (TM) data collection system, validated and supplemented this analysis. Key informants at several of these villages were also interviewed. A preliminary comparison of villages that otherwise faced similar tsunami exposure suggests that the presence of healthy mangroves did afford substantial protection. Village performance in mangrove conservation and management efforts, and thus the presence of healthy forests, is influenced by both social capital and the design of external aid delivery programs

Variability in urinary oxalate measurements between six international laboratories

Background. Hyperoxaluria is a major risk factor for kidney stone formation. Although urinary oxalate measurement is part of all basic stone risk assessment, there is no standardized method for this measurement. Methods. Urine samples from 24-h urine collection covering a broad range of oxalate concentrations were aliquoted and sent, in duplicates, to six blinded international laboratories for oxalate, sodium and creatinine measurement. In a second set of experiments, ten pairs of native urine and urine spiked with 10 mg/L of oxalate were sent for oxalate measurement. Three laboratories used a commercially available oxalate oxidase kit, two laboratories used a high-performance liquid chromatography (HPLC)-based method and one laboratory used both methods. Results. Intra-laboratory reliability for oxalate measurement expressed as intraclass correlation coefficient (ICC) varied between 0.808 [95% confidence interval (CI): 0.427-0.948] and 0.998 (95% CI: 0.994-1.000), with lower values for HPLC-based methods. Acidification of urine samples prior to analysis led to significantly higher oxalate concentrations. ICC for inter-laboratory reliability varied between 0.745 (95% CI: 0.468-0.890) and 0.986 (95% CI: 0.967-0.995). Recovery of the 10 mg/L oxalate-spiked samples varied between 8.7 ± 2.3 and 10.7 ± 0.5 mg/L. Overall, HPLC-based methods showed more variability compared to the oxalate oxidase kit-based methods. Conclusions. Significant variability was noted in the quantification of urinary oxalate concentration by different laboratories, which may partially explain the differences of hyperoxaluria prevalence reported in the literature. Our data stress the need for a standardization of the method of oxalate measuremen

Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health

This is the final version. Available on open access from Elsevier via the DOI in this recordData and Code Availability Statement: Data collected using qPCR is archived and on NERC EIDC [https://doi.org/10.5285/28208be4-0163-45e6-912c-2db205126925]. Standard pollen monitoring ‘count’ data were sourced from the MEDMI database, with the exception of data from Bangor which were produced as part of the present study and are available on request. Prescribing datasets are publicly available, as are weather, air pollution, deprivation (IMD) and rural-urban category data. Hospital episode statistics (HES) datasets are sensitive, individual-level health data, which are subject to strict privacy regulations and are not publicly available. The study did not generate any unique codeGrass (Poaceae) pollen is the most important outdoor aeroallergen, exacerbating a range of respiratory conditions, including allergic asthma and rhinitis (‘hay fever’). Understanding the relationships between respiratory diseases and airborne grass pollen with view to improving forecasting has broad public health and socioeconomic relevance. It is estimated that there are over 400 million people with allergic rhinitis and over 300 million with asthma, globally, often comorbidly . In the UK, allergic asthma has an annual cost of around US$ 2.8 billion (2017). The relative contributions of the >11,000 (worldwide) grass species to respiratory health have been unresolved, as grass pollen cannot be readily discriminated using standard microscopy. Instead, here we used novel environmental DNA (eDNA) sampling and quantitative PCR (qPCR) , to measure the relative abundances of airborne pollen from common grass species, during two grass pollen seasons (2016 and 2017), across the UK. We quantitatively demonstrate discrete spatiotemporal patterns in airborne grass pollen assemblages. Using a series of generalised additive models (GAMs), we explore the relationship between the incidences of airborne pollen and severe asthma exacerbations (sub-weekly) and prescribing rates of drugs for respiratory allergies (monthly). Our results indicate that a subset of grass species may have disproportionate influence on these population-scale respiratory health responses during peak grass pollen concentrations. The work demonstrates the need for sensitive and detailed biomonitoring of harmful aeroallergens in order to investigate and mitigate their impacts on human health.Natural Environment Research Council (NERC)National Institute for Health Research (NIHR)Public Health EnglandUniversity of ExeterUniversity College LondonMet Offic

Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe

Allergic rhinitis is an inflammation in the nose caused by overreaction of the immune system to allergens in the air. Managing allergic rhinitis symptoms is challenging and requires timely intervention. The following are major questions often posed by those with allergic rhinitis: How should I prepare for the forthcoming season? How will the season's severity develop over the years? No country yet provides clear guidance addressing these questions. We propose two previously unexplored approaches for forecasting the severity of the grass pollen season on the basis of statistical and mechanistic models. The results suggest annual severity is largely governed by preseasonal meteorological conditions. The mechanistic model suggests climate change will increase the season severity by up to 60%, in line with experimental chamber studies. These models can be used as forecasting tools for advising individuals with hay fever and health care professionals how to prepare for the grass pollen season

Variability in urinary oxalate measurements between six international laboratories

Hyperoxaluria is a major risk factor for kidney stone formation. Although urinary oxalate measurement is part of all basic stone risk assessment, there is no standardized method for this measurement

Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields

We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities. Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper. We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data