Pollen forecasting and its relevance in pollen allergen avoidance

A review of botany, phytochemistry, pharmacology, and applications of the herb with the homology of medicine and food: Ligustrum lucidum W.T. Aiton

Ligustrum lucidum W.T. Aiton is an outstanding herb with the homology of medicine and food. Its ripe fruits are traditionally used as an important tonic for kidneys and liver in China. Ligustrum lucidum W.T. Aiton is rich in nutritional components and a variety of bioactive ingredients. A total of 206 compounds have been isolated and identified, they mainly include flavonoids, phenylpropanoids, iridoid glycosides, and triterpenoids. These compounds exert anti-osteoporosis, anti-tumor, liver protective, antioxidant, anti-inflammatory, and immunomodulatory effects. Ligustrum lucidum W.T. Aiton has been traditionally used to treat many complex diseases, including osteoporotic bone pain, rheumatic bone, cancer, related aging symptoms, and so on. In the 2020 Edition of Chinese Pharmacopoeia, there are more than 100 prescriptions containing L. lucidum W.T. Aiton. Among them, some classical preparations including Er Zhi Wan and Zhenqi fuzheng formula, are used in the treatment of various cancers with good therapeutic effects. Additionally, L. lucidum W.T. Aiton has also many excellent applications for functional food, ornamental plants, bioindicator of air pollution, algicidal agents, and feed additives. Ligustrum lucidum W.T. Aiton has rich plant resources. However, the application potential of it has not been fully exploited. We hope that this paper provides a theoretical basis for the high-value and high-connotation development of L. lucidum W.T. Aiton in the future.

Pollen identification through convolutional neural networks: First application on a full fossil pollen sequence

The automation of pollen identification has seen vast improvements in the past years, with Convolutional Neural Networks coming out as the preferred tool to train models. Still, only a small portion of works published on the matter address the identification of fossil pollen. Fossil pollen is commonly extracted from organic sediment cores and are used by paleoecologists to reconstruct past environments, flora, vegetation, and their evolution through time. The automation of fossil pollen identification would allow paleoecologists to save both time and money while reducing bias and uncertainty. However, Convolutional Neural Networks require a large amount of data for training and databases of fossilized pollen are rare and often incomplete. Since machine learning models are usually trained using labelled fresh pollen associated with many different species, there exists a gap between the training data and target data. We propose a method for a large-scale fossil pollen identification workflow. Our proposed method employs an accelerated fossil pollen extraction protocol and Convolutional Neural Networks trained on the labelled fresh pollen of the species most commonly found in Northeastern American organic sediments. We first test our model on fresh pollen and then on a full fossil pollen sequence totalling 196,526 images. Our model achieved an average per class accuracy of 91.2% when tested against fresh pollen. However, we find that our model does not perform as well when tested on fossil data. While our model is overconfident in its predictions, the general abundance patterns remain consistent with the traditional palynologist IDs. Although not yet capable of accurately classifying a whole fossil pollen sequence, our model serves as a proof of concept towards creating a full large-scale identification workflow.

Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis

Background

Allergic rhinitis (AR) is a widespread allergic airway disease that results from a complex interplay between genetic and environmental factors and affects approximately 10%-40% of the global population. Pollen is a common allergen, and exposure to pollen can cause epigenetic changes. However, the mechanism underlying pollen-induced DNA methylation changes and their potential effects on the allergic march are still unclear. The purpose of this study was to explore the methylation-driven mechanisms of AR during the pollen and non-pollen seasons using bioinformatics analysis and to investigate their relationship with asthma.

Methods

We downloaded DNA methylation and gene expression data from the GEO database (GSE50387: GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) during the pollen and non-pollen seasons using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis to annotate their functions. We incorporated external data on AR combined with asthma (GSE101720) for analysis to identify key CpGs that promote the transformation of AR to asthma. We also utilized external data on olive pollen allergy (GSE54522) for analysis to validate the methylation-driven genes. Weighted correlation network analysis (WGCNA) was employed to identify gene modules significantly correlated with pollen allergy. We extracted genes related to the key methylation-driven gene ZNF667-AS1 from the significant module and performed pathway intelligent clustering using KOBAS-i. We also utilized gene set enrichment analysis to explore the potential function of ZNF667-AS1.

Results

We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating external data from GSE101720, we found that ZNF667-AS1 is a key gene that may facilitate the transformation of AR into asthma during the pollen season. This finding was further validated in another external dataset, GSE54522, which is associated with pollen allergy. WGCNA identified 17 modules, among which the blue module showed significant correlation with allergies. ZNF667-AS1 was located in the blue module. We performed pathway analysis on the genes correlated with ZNF667-AS1 extracted from the blue module and identified a prominent cluster of pathways in the KOBAS-i results, including Toll-like receptor (TLR) family, MyD88, MAPK, and oxidative stress. Gene set enrichment analysis around cg05508084 (paired with ZNF667-AS1) also indicated its potential involvement in initiating and modulating allergic inflammation from the perspective of TLR and MAPK signaling.

Conclusion

We identified methylation-driven genes and their related pathways during the pollen and non-pollen seasons in patients with AR and identified key CpGs that promote the transformation of AR into asthma due to pollen exposure. This study provides new insights into the underlying molecular mechanisms of the transformation of AR to asthma.

Prediction Model for Annual Variation in Total Pollen by Allergenic Trees in Korean Cities

PURPOSE

Pollen forecasting systems can provide information for coping with respiratory allergies. They estimate daily pollen production, dispersal, deposition, and removal based on daily weather conditions to predict daily pollen concentrations and provide allergy warnings. As of 2023, the Korea Meteorological Administration (KMA) provides 2-day forecast of allergenic pollens. However, unlike these models, long-term analysis of annual observations of tree pollen reveal annual variations. Therefore, in this study, we aimed to develop annual prediction models for allergenic tree pollens based on long-term multi-site pollen and meteorological data.

METHODS

Daily pollen concentrations were observed using Hirst-type volumetric spore traps at nine sites in Korea from 1998 to 2021, and daily weather data from the closest KMA stations were utilized. Models were developed to predict the seasonal pollen integral of seven tree species based on monthly mean temperature, wind speed, and total precipitation using three variable selection methods: 1) the t-test based key variable screening followed by linear regression with stepwise procedure (TM), 2) direct linear regression with stepwise procedure from the full variable model (FM), and 3) LASSO regression from the full variable model (LM).

RESULTS

Data obtained during 1998-2017 and 2018=2021 were utilized for model development and validation, respectively. The root mean squared error, mean absolute error, mean error, and coefficient of determination (R²) revealed that the TM models were best suited for actual forecasting, even though R² in the TM model was lower than those of the FM and LM models.

CONCLUSIONS

The annual variation model in this study can be integrated with the daily pollen forecast model by controlling the annual pollen potential, and the accuracy of the daily forecast can be improved accordingly.

Effects of pollen concentration on allergic rhinitis in children: A retrospective study from Beijing, a Chinese megacity

With global climate change and rapid urbanization, the prevalence of allergic diseases caused by pollen is rising dramatically worldwide with unprecedented complexity and severity, especially for children in mega-cities. However, because of the lack of long time-series pollen concentrations data, the accurate evaluation of the impact of pollen on allergic rhinitis (AR) was scarce in the Chinese metropolis. A generalized additive model was used to assess the effect of pollen concentration on pediatric AR outpatient visits in Beijing from 2014 to 2019. A stratified analysis of 10 pollen species and age-gender-specific groups was also conducted during the spring and summer-autumn peak pollen periods separately. Positive associations between pollen concentration and pediatric AR varied with the season and pollen species were detected. Although the average daily pollen concentration is higher during the spring tree pollen peak, the influence was stronger at the summer-autumn weed pollen peak with the maximum relative risk 1.010 (95% CI 1.009, 1.011), which was higher than the greatest relative risk, 1.003 (95% CI 1.002, 1.004) in the spring peak. The significant adverse effects can be sustained to lag10 during the study period, and longer in the summer-autumn peak (lag13) than in the spring peak (lag8). There are thresholds for the health effects and they varied between seasons. The significant effect appeared when the pollen concentration was higher than 3.74 × 105 grain·m-2·d-1 during the spring tree pollen peaks and 4.70 × 104 grain·m-2·d-1 during the summer-autumn weed pollen peaks. The stratified results suggested that the species-specific effects were heterogeneous. It further highlights that enough attention should be paid to the problem of pollen allergy in children, especially school-aged children aged 7-18 years and weed pollen in the summer-autumn peak pollen period. These findings provide a more accurate reference for the rational coordination of medical resources and improvement of public health.

Microscale pollen release and dispersal patterns in flowering grass populations

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites (<300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index (α-diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales.

Isolating the species element in grass pollen allergy: A review

Grass pollen is a leading cause of allergy in many countries, particularly Europe. Although many elements of grass pollen production and dispersal are quite well researched, gaps still remain around the grass species that are predominant in the air and which of those are most likely to trigger allergy. In this comprehensive review we isolate the species aspect in grass pollen allergy by exploring the interdisciplinary interdependencies between plant ecology, public health, aerobiology, reproductive phenology and molecular ecology. We further identify current research gaps and provide open ended questions and recommendations for future research in an effort to focus the research community to develop novel strategies to combat grass pollen allergy. We emphasise the role of separating temperate and subtropical grasses, identified through divergence in evolutionary history, climate adaptations and flowering times. However, allergen cross-reactivity and the degree of IgE connectivity in sufferers between the two groups remains an area of active research. The importance of future research to identify allergen homology through biomolecular similarity and the connection to species taxonomy and practical implications of this to allergenicity is further emphasised. We also discuss the relevance of eDNA and molecular ecological techniques (DNA metabarcoding, qPCR and ELISA) as important tools in quantifying the connection between the biosphere with the atmosphere. By gaining more understanding of the connection between species-specific atmospheric eDNA and flowering phenology we will further elucidate the importance of species in releasing grass pollen and allergens to the atmosphere and their individual role in grass pollen allergy.

How to select the optimal monitoring locations for an aerobiological network: A case of study in central northwest of Spain

Airborne pollen concentration varies depending on several factors, such as local plant biodiversity, geography and climatology. These particles are involved in triggering pollinosis in a share of worldwide human population, and adequate monitoring is, therefore, important. However, the pollen traps in aerobiological monitoring networks are usually installed in cities, and the features of the whole territory are not taken into account. The aim of this study was to analyze what environmental parameters are more suitable as regards setting up monitoring stations throughout a territory in order to obtain an aerobiological network that can represent environmental diversity. The analysis was carried out in 13 locations in Castilla y León over an 8 year period. This is a favorable territory in which to conduct this type of study owing to its climatic features, orography and biodiversity. The ten most abundant pollen types in the region were analyzed, and a clustering analysis was calculated with different distances so as to obtain homogeneous groups of stations. Moreover, the clusters obtained were analyzed in combination with altitudinal and different bioclimatic parameters, which derived from temperature and precipitation. The result here shows that the Castilla y León aerobiological network RACYL represents most of the environmental variability of the territory. Furthermore, it can be divided into two clusters and five sub-clusters for which the start of the main pollen season is different. This corresponds with the division of the territory as regards bioclimatic conditions. The most important bioclimatic parameters were the seasonality of the precipitation and the maximum temperature of the warmest month, although orography must also be taken into account. All of these help discover the optimal places in which to install traps and could reduce the number of monitoring stations. This study additionally provides data for unmonitored areas with similar bioclimatic conditions to those monitored.

Allergen Management in Children with Type 2-High Asthma

Children exposed to various indoor and outdoor allergens are placed at an increased risk of developing asthma in later life, with sensitization in these individuals being a strong predictor of disease morbidity. In addition, aeroallergen exposure influences asthma outcomes through an interplay with adverse determinants of health. The goal of this review is to provide an introductory overview of factors related to aeroallergen exposure in type 2-high childhood asthma. These include the relevance of exposure in asthma exacerbations and severity, and the evidence-base for avoidance and treatment for sensitization to these allergens. This review will focus on both indoor aeroallergens (house dust mite, pet, cockroach, mold, and rodent) and outdoor aeroallergens (pollens and molds). Treatment of aeroallergen sensitization in children with asthma includes avoidance and removal measures, although there is limited evidence of clinical benefit especially with single-strategy approaches. We will also address the interplay of aeroallergens and climate change, adverse social determinants, and the current COVID-19 pandemic, when we have seen a dramatic reduction in asthma exacerbations and emergency department visits among children. While there are many factors that are hypothesized to contribute to this reduction, among them is a reduced exposure to outdoor seasonal aeroallergens.

Allergenic risk assessment of urban parks: Towards a standard index

Allergenicity indices are a powerful tool to assess the health hazard posed by urban parks to pollen allergic subjects. Nonetheless, only few indices have been developed and applied to urban vegetation in the last decade, and they were never compared nor standardised over the same dataset. To address this issue, in this paper the two best-known allergenicity indices, the Urban Green Zones Allergenicity Index (I_UGZA) and the Specific Allergenicity Index (SAI), have been calculated for the same park (the Botanical Garden of Bologna), collecting vegetation data through both systematic sampling and arboreal census. The results obtained with the two data collection methods were comparable for both indices, indicating systematic sampling as a reliable approximation of the total census. Besides, the allergenic risk resulted moderate to high according to SAI, and very low according to I_UGZA. Since SAI does not consider the total volume of the vegetation, it was deemed less reliable than I_UGZA in evaluating the allergenicity of an enclosed green space.