scholarly journals Temperate grass allergy season defined by spatio-temporal shifts in airborne pollen communities

2018 ◽  
Author(s):  
Georgina L. Brennan ◽  
Caitlin Potter ◽  
Natasha de Vere ◽  
Gareth W. Griffith ◽  
Carsten A. Skjøth ◽  
...  
Keyword(s):  
Grass Pollen ◽  
High Throughput Sequencing ◽  
Airborne Pollen ◽  
High Mobility ◽  
Economic Benefits ◽  
Taxonomic Composition ◽  
Poaceae Pollen ◽  
Pollen Exposure ◽  
Spatio Temporal ◽  
Seasonal Pollen

AbstractGrass pollen is the world’s most harmful outdoor aeroallergen and sensitivity varies between species. Different species of grass flower at different times, but it is not known how airborne communities of grass pollen change in time and space. Persistence and high mobility of grass pollen could result in increasingly diverse seasonal pollen communities. Conversely, if grass pollen does not persist for an extended time in the air, shifting pollen communities would be predicted throughout the summer months. Here, using targeted high throughput sequencing, we tracked the seasonal progression of airborne Poaceae pollen biodiversity across Britain, throughout the grass allergy season. All grass genera displayed discrete, temporally restricted peaks of pollen incidence which varied with latitude, revealing that the taxonomic composition of grass pollen exposure changes substantially across the allergy season. By developing more refined aeroallergen profiling, we predict that our findings will facilitate the exploration of links between taxon-specific exposure of harmful grass pollen and disease, with concomitant socio-economic benefits.

scholarly journals Personalized Pollen Monitoring and Symptom Scores: A Feasibility Study in Grass Pollen Allergic Patients

2021 ◽  
Vol 2 ◽  
Author(s):  
Letty A. de Weger ◽  
Peter Th. W. van Hal ◽  
Bernadette Bos ◽  
Frank Molster ◽  
Marijke Mostert ◽  
...  
Keyword(s):  
Feasibility Study ◽  
Grass Pollen ◽  
Airborne Pollen ◽  
Mobile App ◽  
Pollen Monitoring ◽  
Pollen Counts ◽  
Pollen Concentrations ◽  
Symptom Scores ◽  
Pollen Exposure ◽  
Grass Pollen Counts

Background: Pollen is a major trigger for allergic symptoms in sensitized individuals. Airborne pollen is usually monitored by Hirst type pollen samplers located at rooftop level, providing a general overview of the pollen distribution in the larger surroundings. In this feasibility study, grass pollen-sensitized subjects monitored the pollen in their direct environment using a portable pollen sampler (Pollensniffer) and scored their symptoms, to study the relation between symptom severity and personal grass pollen exposure. For comparison the symptoms were also correlated with pollen collected by the rooftop sampler.Methods: After recruitment 18 participants were screened for grass pollen specific (GP-sIgE) of which 12 were eligible. Nine participants completed the study (May, 2018). They were asked to monitor personal pollen exposure using a Pollensniffer on their way to school, work or other destination, and to score their symptoms via a mobile app on a scale from 0 to 10. Daily pollen concentrations were collected by a Hirst type sampler at rooftop level. Pollen grains were analyzed using a microscope.Results: Three of the four participants with high GP-sIgE (≥9.6 kU/l) reported high symptom scores (>4) and an analysis showed a significant correlation (CC) between eye, nose, and lung symptoms and the grass pollen counts collected by the Pollensniffer, as well as the daily grass pollen concentrations monitored by the rooftop sampler (CC≥0.54). In contrast, the participants with low GP-sIgE levels (<9.6 kU/l) reported low symptom scores (≤4) and often other sensitizations were present. For these subjects, no significant positive correlations (CC<0.3) of symptoms with either grass pollen collected by the personal or the rooftop sampler were found.Conclusion: The results of this feasibility study suggest that correlations between the severity of clinical symptoms of grass pollen allergic patients, and grass pollen counts as determined by the Pollensniffer or a rooftop sampler, is restricted to patients with high GP-sIgE levels, high symptom scores, and no relevant other sensitizations. Based on the low numbers of subjects with severe symptoms included in this feasibility study, no conclusions can be drawn on the performance of the Pollensniffer in relating symptoms and pollen exposure in comparison with the rooftop sampler.Trial Registration: The study was approved by the Committee Medical Ethics of the LUMC (approval numbers: NL63953.058.17/ P17.304).

scholarly journals Personalized pollen monitoring and hay fever symptom scores: a feasibility study

2020 ◽  
Author(s):  
Letty de Weger ◽  
Peter TH.W van Hal ◽  
Bernadette Bos ◽  
Frank Molster ◽  
Marijke Mostert ◽  
...  
Keyword(s):  
Feasibility Study ◽  
Grass Pollen ◽  
Airborne Pollen ◽  
Mobile App ◽  
Pollen Monitoring ◽  
Pollen Counts ◽  
Pollen Concentrations ◽  
Symptom Scores ◽  
Pollen Exposure ◽  
Grass Pollen Counts

Abstract Background. Pollen is a major trigger for allergic symptoms in sensitized individuals. Airborne pollen is usually monitored by Hirst type pollen samplers located at rooftop level, providing a general overview of the pollen distribution in the larger surroundings. In this feasibility study, grass pollen-sensitized subjects monitored the pollen in their direct environment using a portable pollen sampler (Pollensniffer) and scored their symptoms, to study the relation between symptom severity and personal grass pollen exposure. For comparison the symptoms were also correlated with pollen collected by the rooftop sampler. Methods. Nine grass pollen-sensitized individuals were enrolled in this study (May 2018) and asked to monitor personal pollen exposure using a Pollensniffer on their way to school, work or other destination, and to score their symptoms via a mobile app on a scale from 0 to 10. Daily pollen concentrations were collected by a Hirst type sampler at rooftop level. Pollen grains were analysed using a microscope. Results. Three of the four participants with high grass pollen-specific (GPS) IgE (>9.6 kU/l) reported high symptom scores (>4) and an analysis showed a significant correlation (CC) between eye, nose and lung symptoms and the grass pollen counts collected by the Pollensniffer, as well as the daily grass pollen concentrations monitored by the rooftop sampler (CC>0.54). In contrast, the participants with low GPS IgE levels (<9.6 kU/l) reported low symptom scores (<4) and often other sensitizations were present. For these subjects, no significant positive correlations (CC<0.3) of symptoms with either grass pollen collected by the personal or the rooftop sampler were found. Conclusion. Our results show that correlations between the severity of clinical symptoms of grass pollen allergic patients, and airborne grass pollen counts as determined by a personal pollen sampler (Pollensniffer) or a rooftop sampler, is restricted to patients with high GPS IgE levels, high symptom scores and no relevant other sensitizations. Based on the number of subjects included in this feasibility study, no conclusions can be drawn on the performance of the personal pollen sampler in relating symptoms and pollen exposure in comparison with the rooftop sampler.Trial registrationThe study was approved by the Committee Medical Ethics of the LUMC (approval numbers: NL63953.058.17/ P17.304).

scholarly journals Main features of Poaceae pollen season in Madeira region (Portugal)

2015 ◽  
Vol 68 (4) ◽  
pp. 367-372
Author(s):  
Irene Câmara Camacho ◽  
Rita Câmara ◽  
Roberto Camacho
Keyword(s):  
Pollen Season ◽  
Airborne Pollen ◽  
Growing Season ◽  
Onset Date ◽  
Critical Levels ◽  
Pollen Monitoring ◽  
Madeira Island ◽  
Poaceae Pollen ◽  
The Mean ◽  
Low Levels

<p>The pollinic spectrum of the Madeira region is dominated by grass pollen, which also represents an important aeroallergen in Europe. The present work aims to analyze the main features of the Poaceae pollen season in the Madeira region to determine the allergic risk. The study took place in Funchal city, the capital of Madeira Island, over a period of 10 years (2003–2012). The airborne pollen monitoring was carried out with a Hirst type volumetric trap, following well-established guidelines.</p><p>In the atmosphere of Funchal, the mean annual Poaceae pollen index was 229. The mean Poaceae pollen season lasts 275 days, with an onset date in January/March and an end date in November/December. Poaceae counts showed a seasonal variation with 2 distinct peaks: a higher peak between March and June, and the second one in autumn. The peak values occurred mainly between April and June, and the highest peak was 93 grains/m<sup>3</sup>, detected on the 27th May of 2010. The Poaceae pollen remaining at low levels during the whole growing season, presenting a nil to low allergenic risk during most of the study period. Higher critical levels of allergens have been revealed after 2006. In general, the pollen risk from Poaceae lasted only a few days per year, despite the very long pollen season and the abundance of grasses in the landscape of Madeira Island.</p>

scholarly journals Biodiversity management of organic orchard enhances both ecological and economic profitability

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2137 ◽  
Author(s):  
Jie Meng ◽  
Lijun Li ◽  
Haitao Liu ◽  
Yong Li ◽  
Caihong Li ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Microbial Biomass Carbon ◽  
Organic Matter Content ◽  
Economic Benefits ◽  
Apple Orchard ◽  
Chemical Pollution ◽  
Native Plant ◽  
Biodiversity Management ◽  
Health Maintenance ◽  
Bacterial Phyla

Organic farming has been regarded as an alternative solution for both agricultural sustainability and human health maintenance. Few researches have concentrated on the differences of biodiversity and eco-economic benefits between organic and conventional orchards. Organic management (OM) of orchards mainly includes taking advantage of natural enemies and beneficial weeds as well as soil organisms and controlling harmful pests. Here we conducted a three-year experiment on the effects of managing biodiversity in an organic apple orchard, using cattle manure to enrich soil biota, propagating native plant to suppress weeds and applying ecological pest management to control pests. The effect was assessed against the conventional management (CM) model. We found that OM enhanced soil organic carbon, total nitrogen, microbial biomass carbon and nitrogen. The 16S rDNA high-throughput sequencing results indicated that the dominant bacterial phyla of the top soil wereProteobacteriaandActinobacteria, and OM had richer bacteria diversity with a 7% higher Shannon’s index than the CM. In particular, the relative abundance of rhizobium in the OM was higher than that of the CM. For OM,Duchesnea indicawas an ideal ground-cover plant to control weeds through winning the niche competition and thus decreased weeds’ Simpson, Shannon–Wiener and Pielou index by 38.2%, 53.8% and 16.9% separately. The phototactic pests’ weight and scarab beetle’s population were effectively decreased by 35% and 86% respectively through long time control and prevention. OM had an average of 20 times more earthworms than CM, and the maximum density had reached 369 m−2(0–20 cm soil). The dominant earthworm species of the OM were detritivores which preferring soil with high organic matter content. Due to no synthetic chemicals being used, the OM produced much safer apple fruits which were sold at high prices. Economically, up to a 103% increase of output–input ratio had been achieved in the OM. Our study clearly demonstrated that biodiversity management without chemical pollution increased the biodiversity of beneficial organisms, reduced antagonists of the fruit tree, and enhanced economic benefits of the apple orchard.

scholarly journals Geographical Imputation of Missing Poaceae Pollen Data via Convolutional Neural Networks

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 717
Author(s):  
Ricardo Navares ◽  
José Luis Aznarte
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Airborne Pollen ◽  
Missing At Random ◽  
Spatial Relations ◽  
Computational Time ◽  
Pollen Monitoring ◽  
Distance Weighting ◽  
Poaceae Pollen ◽  
Data Points

Airborne pollen monitoring datasets sometimes exhibit gaps, even very long, either because of maintenance or because of a lack of expert personnel. Despite the numerous imputation techniques available, not all of them effectively include the spatial relations of the data since the assumption of missing-at-random is made. However, there are several techniques in geostatistics that overcome this limitation such as the inverse distance weighting and Gaussian processes or kriging. In this paper, a new method is proposed that utilizes convolutional neural networks. This method not only shows a competitive advantage in terms of accuracy when compared to the aforementioned techniques by improving the error by 5% on average, but also reduces execution training times by 90% when compared to a Gaussian process. To show the advantages of the proposal, 10%, 20%, and 30% of the data points are removed in the time series of a Poaceae pollen observation station in the region of Madrid, and the airborne concentrations from the remaining available stations in the network are used to impute the data removed. Even though the improvements in terms of accuracy are not significantly large, even if consistent, the gain in computational time and the flexibility of the proposed convolutional neural network allow field experts to adapt and extend the solution, for instance including meteorological variables, with the potential decrease of the errors reported in this paper.

Temporal dynamics in the taxonomic and functional profile of the Sphagnum-associated fungi (mycobiomes) in a Sphagnum farming field site in Northwestern Germany

2020 ◽  
Vol 96 (11) ◽  
Author(s):  
Mathilde Borg Dahl ◽  
Matthias Krebs ◽  
Martin Unterseher ◽  
Tim Urich ◽  
Greta Gaudig
Keyword(s):  
Fungal Community ◽  
Plant Pathogens ◽  
High Throughput Sequencing ◽  
Temporal Dynamics ◽  
Environmental Parameters ◽  
Taxonomic Composition ◽  
Raw Material ◽  
Negative Consequences ◽  
Field Site ◽  
Community Profile

ABSTRACT The drainage of peatlands for their agricultural use leads to huge emissions of greenhouse gases. One sustainable alternative is the cultivation of peat mosses after rewetting (‘Sphagnum farming’). Environmental parameters of such artificial systems may differ from those of natural Sphagnum ecosystems which host a rich fungal community. We studied the fungal community at a 4 ha Sphagnum farming field site in Northwestern Germany and compared it with that of natural Sphagnum ecosystems. Additionally, we asked if any fungi occur with potentially negative consequences for the commercial production and/or use of Sphagnum biomass. Samples were collected every 3 months within 1 year. High-throughput sequencing of the fungal ITS2 barcode was used to obtain a comprehensive community profile of the fungi. The dominant taxa in the fungal community of the Sphagnum farming field site were all commonly reported from natural Sphagnum ecosystems. While the taxonomic composition showed clear differences between seasons, a stable functional community profile was identified across seasons. Additionally, nutrient supply seems to affect composition of fungal community. Despite a rather high abundance of bryophyte parasites, and the occurrence of both Sphagnum-species-specific and general plant pathogens, their impact on the productivity and usage of Sphagnum biomass as raw material for growing media was considered to be low.

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