Aerobiologia最新文献

Biological contaminants mainly consisting of living or dead microorganisms and compounds or fragments of plants and animal origin are gaining widespread research interest in recent years due to their ubiquitous presence along with their health effects on humans. Students spend a significant time of the day in educational institutions, which increases the cumulative health risk over the years. This review discusses the major biological contaminants, sampling strategies, health effects, and the factors affecting their prevalence in educational institutions. Fungi and bacteria were the most reported bio-contaminants followed by allergens and endotoxins. Exposure to bio-contaminants may result in acute and chronic respiratory diseases, infectious diseases, allergies, building-related illnesses, and even cancer. More research is needed to know the susceptibility of different age groups of students, formulation of guideline values, standard protocols for sampling, and proper diagnostic tests for diseases caused by bio-contaminants. Students should be made aware of the various aspects of indoor air quality such that they become inquisitive towards the same and become responsible for safety and hygiene.

Timely information on the beginning of the flowering of important plant species of pollen allergens is consequential for the entire population due to pollen allergy and its extensive clinical impact worldwide. This paper examines the prediction of the beginning of the flowering of the common hazel (Corylus avellana) based on the PhenoClim phenological model using long-term phenological observations (1991–2020) in the Czech Republic. Furthermore, temporal and spatial evaluations of the beginning of the flowering of C. avellana were examined in different climate zones in the Czech Republic within the same period. In total, 40 phenological stations at altitudes from 155 to 743 m asl located in warm, medium warm, and cold climate zones were evaluated using the Mann–Kendall test. The beginning of the flowering of C. avellana changed progressively in timing, and the difference in the rate of shifts was between −33 and + 15 days per the entire period. An extreme shift to an earlier date was detected at stations located in a warm region (W2). In contrast, the highest shift to a later date was found at stations located in the cold climate regions (C4, C6, C7). Using the PhenoClim, the base temperature and temperature sums were calculated for the beginning of the flowering of the common hazel. As the most accurate predictor for this phenological phase and species, the maximum air temperature was determined as the best predictor based on the combination of RMSE and R² values. The optimal start day for calculation was January 1st; the threshold (base temperature) was 2.7 °C with a temperature sum of 155.7 °C. The RMSE value was 5.46, and the MBE value was −0.93. The simulated data showed an excellent correlation with the observed data—the correlation coefficient was 0.932. The PhenoClim model results can be used in the forecast modelling of the beginning of the flowering of the common hazel in the Czech Republic.

Many methods have been devised to count pollen grains automatically; however, few combine speed, reliability, inexpensiveness and user friendliness. This study describes a combination of simple, glycerine-based extraction, digital imaging and free particle counting software configured to achieve semi-automated processing of a large volume of images. Pollen grains were extracted from anthers of 10 common perennial grass (Poaceae) species, all implicated in pollinosis in Europe, and samples, illuminated on slides and digitally imaged. ImageJ algorithms were designed to remove significant extraneous content and count just the pollen grains, then applied in batch mode on multiple images. Accuracy was assessed by comparing a sample of automated software counts to manual, visual counts of the same images and found to be high. Total pollen production per anther and per inflorescence was estimated by counting the number of pollen grains per anther and the number of florets per inflorescence. Methodological and natural variation in pollen counts is discussed. Results were compared to published pollen counts of the same species; new pollen production figures are published for Cynosurus cristatus. This method is portable to other plant species, and requires only readily available reagents, equipment and software, it is quick, reliable, inexpensive and user friendly.

Inhalation of olive pollen (Olea europaea L.) is one of the main causes of allergy in Mediterranean countries and some areas of North America. The response to allergens consists in the production of inflammatory cytokines which is mediated by the deregulation of Ca²⁺ signals. In this study, the biological activity of the material released in olive pollen hydration (PMR) was tested on Ca²⁺ cytosolic of PE/CA-PJ15 cells (PJ-15). Ca²⁺ cytosolic was determined by fluorometric assay with the cell line PE/CA-PJ15 (PJ-15) labeled with the fluorescent probe FURA 2 AM. The material released in olive pollen hydration (PMR) was analyzed by HPLC for the determination of phenolic acids. PMR was subjected to fractionation by gel filtration, and the fractions with Ca²⁺-chelating activity were tested with SDS-PAGE and the single bands characterized by proteomic analysis. PMR showed high Ca²⁺-chelating activity and is able of blocking the increase Ca²⁺-cytosolic produced by thapsigargin (TG). PMR then restored Ca²⁺ homeostasis in PJ-15 cells deregulated by the endoplasmic reticulum Ca²⁺-ATPases inhibitor. It is therefore possible that PMR can antagonize the effects of allergens on Ca²⁺ cytosolic. The analytical characterization of the material released by the pollen highlighted in the pollen allergen Ole e 3 and in the p-coumaric acid the possible culprits of the Ca²⁺-antagonist activity of PMR. Furthermore, the sequence of Ole e 3 could provide information for the possible construction of a synthetic peptide to be used in an allergy-targeted Ca²⁺-antagonist therapy.

The aim of this study was to identify and quantify the airborne fungal spore content in the Cathedral of Jaén (South Spain). The evaluation of the microclimatic conditions and their relationship with the presence of airborne fungal spores in different indoor areas was also tested. Airborne fungal spores were recorded during 2019 by using a volumetric sampler. The Choir was the study area with the maximum airborne fungal spore concentrations, representing 55% of the total compared to the minimum representation of 12% sampled in the Museum. Regarding the seasonality, winter records represented only 20% of the total the airborne spore monitoring. Peaks in the daily spore concentrations were mainly recorded in the first half of spring and during the middle of the summer. A total of 29 taxa were identified. Cladosporium and Aspergillus/Penicillium were the potentially biodeteriogen fungal spores that were more frequently recorded in all of the study areas. Of the total airborne fungal spores recorded in the indoor environment, 82.5% belong to biodeteriogen fungi that, under suitable conditions for their germination, could have a negative effect on the preservation of artistic-historical heritage. The installation and correct maintenance of air-conditioning systems and the aeromycological analysis in suspected places would be recommended.

Inhalation of grass pollen can result in acute exacerbation of asthma, prompting questions about how grass pollen reaches metropolitan areas. We establish typical atmospheric Poaceae (grass) pollen concentrations recorded at two pollen samplers within the Sydney basin in eastern Australia and analyse their correlation with each other and meteorological variables. We determine the effect of synoptic and regional airflow on Poaceae pollen transport during a period of extreme (≥ 100 grains m⁻³ air) concentration and characterise the meteorology. Finally, we tested the hypothesis that most Poaceae pollen captured by the pollen samplers originated from local sources. Fifteen months of daily pollen data, three days of hourly atmospheric Poaceae pollen concentrations and fifteen months of hourly meteorology from two locations within the Sydney basin were used. Weather Research Forecasting (WRF), Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) modelling and conditional bivariate probability functions (CBPF) were used to assess Poaceae pollen transport. Most Poaceae pollen collected was estimated to be from local sources under low wind speeds. Extreme daily Poaceae pollen concentrations were rare, and there was no strong evidence to support long-distance Poaceae pollen transport into the Sydney basin or across the greater Sydney metropolitan area. Daily average pollen concentrations mask sudden increases in atmospheric Poaceae pollen, which may put a significant and sudden strain on the healthcare system. Mapping of Poaceae pollen sources within Sydney and accurate prediction of pollen concentrations are the first steps to an advanced warning system necessary to pre-empt the healthcare resources needed during pollen season.

Exposure to wastewater treatment system (WWTS)-associated bioaerosols is not only linked with macro/field scale systems but also facilities which are operated in micro- and/or indoor environment such as university campus and research institutions. In this context, investigations on a laboratory-scale WWTS, adopting a sequential batch biofilm process and fed with synthetic municipal wastewater, were done in terms of its global treatment performance and characterization of emitted bioaerosols species. The microbial diversity of captured bioaerosols, collected through conventional particulate matter samplers, was identified on the basis of their metabolic properties using analytical profile index, biochemical tests, and other media specific growth patterns. Monitoring and analysis results of air quality in control and experimental period revealed that particulate emission from bioreactor increased the concentration of PM₁₀ and PM_2.5 up to 26.49 ± 4.18 µg/m³ and 12.84 ± 2.48 µg/m³ from an initial level of 17.26 ± 4.58 µg/m³ and 8.70 ± 1.84 µg/m³, respectively. Microscopic observations and staining characteristics revealed that cocci shape gram-negative and bacilli shape gram-positive bacteria dominated the bioaerosols with quantitative contribution as 70% and 9%, respectively. Based on the morphological and biochemical characterization, dominant isolated genera of opportunistic pathogenic bacteria in bioaerosols were identified as Escherichia coli, Bacillus cereus, Bacillus subtilis and Pseudomonas sp. with % dominance as 38.46, 13.46, 9.61 and 25, respectively. Overall, the findings of this study reiterate the concern of biological air pollution in research laboratories and represent an inevitable aspect for the validation of bioaerosol exposure in laboratory-scale WWTS workplaces.

Since research began in diatom ecology, scientists have focussed more on diatoms from aquatic habitats as opposed to aerial habitats. In this paper, we present the first dataset on diatoms from aerial habitats in the Indo-Burma hot spot. We have chosen the Blue Mountain region to collect tree mosses, an aerial habitat where diatoms thrive. We have addressed diatom composition and diversity in relation to altitude. Twenty-two moss samples were collected and 53 diatom taxa belonging to 21 genera were discovered and enumerated using light microscopy. The diatom flora of tree mosses is dominated by acidophilous genera Eunotia and Luticola, with both of the most abundant species Orthoseira roeseana and Luticola acidoclinata being euaerial and oligotraphentic diatoms. The samples from 1902-m altitude had the highest species diversity. Species richness was 8–22 diatom per sample, with an average of 14. The species accumulation curve shows that more diatom species will be discovered with additional sampling of aerial habitats in the Blue Mountain region.

This study investigates the use of pollen elastically scattered light images for species identification. The aim was to identify the best recognition algorithms for pollen classification based on the scattering images. A series of laboratory experiments with a Rapid-E device of Plair S.A. was conducted collecting scattering images and fluorescence spectra from pollen of 15 plant genera. The collected scattering data were supplied to 32 different setups of 8 computer vision models based on deep neural networks. The models were trained to classify the pollen types, and their performance was compared for the test sub-samples withheld from the training. Evaluation showed that most of the tested computer vision models convincingly outperform the basic convolutional neural network used in our previous studies: the accuracy gain was approaching 10% for best setups. The models of the Weakly Supervised Object Detection approach turned out to be the most accurate, but also slow. However, even the best setups still did not provide sufficient recognition accuracy barely reaching 65%–70% in the repeated tests. They also showed many false positives when applied to real-life time series collected by Rapid-E. Similar to the previous studies, fusion of the new scattering models with the fluorescence-based identification demonstrated almost 15% higher skills than either of the approaches alone reaching 77–83% of the overall classification accuracy.

From clinical point of view, knowledge of the pollen season and loads in the atmosphere of every community is important so as to guide on incidence and management of pollinosis. The aim of this work therefore is to evaluate the weekly constituents of the atmospheric pollen and fern spores of two communities in Lagos Nigeria and the relationship, if any, between the weekly aeroflora and hospital reported pollinosis cases. As part of efforts to contribute to the gathering of aerobiological data in Lagos State, a weekly gravimetric sampling of two locations (Ipaja and Ogba) in Lagos, Nigeria were undertaken from January 2018–December 2018 and the reported pollinosis cases (asthma and rhinitis) were collected from the surrounding hospitals. The samplers were placed on rigid platforms at 2 m above the ground level, the harvested residues were subjected to standard palynological procedure and twenty microlitres of each sample were studied microscopically. A total of 30 pollen taxa were identified with Amaranthaceae (544) dominating the palynomorphs at Ipaja and Elaeis guineensis (347) at Ogba. Using correlation (r = 0.1, p-value = 0.55 at Ipaja while r = 0.3, p-value = 0.33 at Ogba) and RDA test at p > 0.05, there is insignificant positive relationship between pollinosis cases and abundance of palynomorphs. However, at Ipaja, RDA indicated Poaceae and Elaeis guineensis as the possible drivers for asthma cases while Amaranthaceae and fungal spores were identified as weak drivers for catarrh. At Ogba, the loess curve and correlation test showed a significant positive relationship at p < 0.05 between the reported pollinosis cases and abundance of recovered palynomorph. Elaeis guineensis, Nephrolepis sp. and Dryopteris sp. seem to be the main drivers of asthma while Casuarina sp. and fungal spores perhaps drove catarrh. Dryopteris and Nephrolepis spores are firstly implicated as possible allergenic aeroconstituents in Nigeria in this work. The results from this work provide a background reference for the general public and hypersensitive individuals on the spatial distribution of pollen grains and fern spores in the study areas of Lagos as well as being a guide to the identification of culprit allergenic aeroconstituent.