Aerobiologia最新文献

Indoor air pollution directly affects mortality and also morbidity; it is also a vital issue of concern for the majority of nations that are in their developing phase. Coal and biomass (crop waste, wood, dung, and charcoal) are the main household energy sources for approximately around three billion people worldwide. Additionally, as most persons spend nearly 80–90% of their time in an indoor environment regularly, indoor air quality has a vital and direct effect on both general health and productivity of them. Although outdated, air pollution monitoring is nevertheless a very important idea in daily life. The monitoring of air quality has been done using both conventional methods and the most advanced computing techniques. However, as everyone needs access to clean air, many advanced wireless technologies have been used and some of them are quite helpful in giving information related to real-time data on air quality. The main purpose of this study is to describe some advanced techniques and devices used to monitor indoor air pollution and some of the significant advancements which have been done in this research field.

Smog is a form of pollution composed of smoke and fog. It is one of the major environmental and public health problems in many urban areas around the world. Intriguingly, recent evidences have unveiled the potential link between smog and antimicrobial resistance (AMR). Smog can contribute to AMR through a complex and multifaceted set of mechanisms, including particulate matter (PM) which is found in smog, mediated transport of AMR microorganisms and genes, disruption of the respiratory microbiome, and modulation of host immune responses. Since the PM can lodge deeper in the lungs and harbors antibiotic resistance genes (ARGs), it should be considered that PM contributes to AMR toward the respiratory tract infections and other infections. PM can create conditions conducive to bacterial survival and growth in the respiratory system due to inflammation and immune suppression. PM2. 5 and PM10 have been associated with several respiratory system ailments due to their capability to penetrate inner areas. Moreover, PM can serve as a carrier for ARGs and other microbial components, aiding in their spread. This interaction may accelerate the development and spread of AMR. It is imperative to further unleash the mechanisms adopted by microbial extracellular DNA associated with the PM to envisage the potential health and environmental hazards. eDNA, for example, has been shown to contribute to the diversity and composition of microbiota associated with PM, such as bacteria, fungi, and viruses. This review focuses on PM, ARGs, and microbial eDNA as emerging environmental contaminants. A comprehensive analysis is conducted of the mechanisms and circumstances that contribute to its spread in diverse settings. Considering the current explosive increase in microbial resistance to the antibiotics, this also necessitates uncovering the underpinnings of the smog’s effect on AMR and developing effective strategies for mitigating these deleterious smog effects on health and environment.

In the last decade, a great deal of research has focused on the determination of potential toxic elements by total concentration and identification the microorganisms in dust. However, determining bio-relevant (e.g., inhalable) forms of elements instead of total contents in acids is necessary for human health. Moreover, examination of the behavior of microorganism under these bio-relevant conditions and revealing the interaction between elements and pathogens is vital and necessary for deeper understanding. However, previous studies have ignored these topics. Therefore, the present study aimed to (i) investigate elements in household dusts extracted in simulated lung fluids, (ii) examine the total concentration of culturable bacteria and their biochemical responses with exposure to bio-fractions of household dusts, and (iii) assess their relations and risks using the model approaches by inhalation. Here, settled dusts were collected in 25 houses, and extracted in four simulated body fluids to determine bio-fractions of elements. Moreover, total count of potentially pathogenic and heterotrophic bacteria, and four clinically important culturable pathogens were incubated in the presence of household-dusts extracted in simulated body fluids. The activity, biofilm, biochemical and oxidative responses of pathogens were measured following household-dust exposures. Afterward, the relationship between elements and pathogen responses were evaluated, and model and derived approaches were used for risk assessments of elements and pathogens. The higher daily intake of elements obtained in artificial lysosomal fluid fraction of household dust mimicking the inflammatory condition compared to other body fluids. Moreover, bacterial responses were mainly influenced from bio-fractions of household dusts and their elemental contents.

Airborne fungal spores of the genus Alternaria pose challenges for accurate airborne spore identification by automatic bioaerosol monitors, because of their significant implications for public health and agriculture due to their role as airborne allergen and plant pathogen. These systems require high-quality reference data for training algorithms by machine learning. Alternaria alternata was cultured on three different media, including exposure to UV light to favor sporulation. Spore morphology was evaluated both macroscopically and microscopically, and chemical analysis was conducted using micro-Raman spectroscopy to assess spore composition. Significant differences were observed in colony morphology and spore characteristics among culture media. While typical spores predominated, atypical forms were also identified, which may represent a potential bias for identification. Comparative analysis with air samples by the Hirst method also revealed overall differences in spore morphology pattern. Standardizing culture conditions and accounting for variability in spore properties are essential for improving the reliability of bioaerosol monitoring systems. Further research is needed to refine detection methods for A. alternata and other airborne fungal spores.

Accurate identification and quantification of pollens (e.g., pollen of a flower, airborne pollens) is essential to understand plant pollination and reproductive biology, pollen aerobiology, and plant–insect interactions. Currently, a couple of methods are available for pollen counting, such as manual counting, flow cytometry-based and image software-based counting. However, due to inconsistent results and experimental repeatability, a more accurate, consistent, and high-throughput quantification approach is required. This study evaluated and compared the performance between a proposed Swin-transformer-YOLOv5 (S-T-YOLOv5) and common YOLO models in pollen detection and quantification. The present study demonstrated that the S-T-YOLOv5 outperformed other YOLO models, including YOLOv3, YOLOv4, YOLOR, and YOLOv5 for alfalfa (Medicago sativa L.) pollen detection and quantification, with excellent precision (99.6%), recall (99.4%), F₁-score (0.995), mAP50 (99.4%), and mAP50-95 (76.2%) values. The mAP50-95 (mAP at an IoU of 0.5–0.95) of S-T-YOLOv5 was 9.9, 58.7, 25.3 and 8.2% higher than those of YOLOv3, YOLOv4, YOLOR, and YOLOv5, respectively. Additionally, the S-T-YOLOv5 showed a good transferability in quantifying pollen with varied sizes and shapes in different plant species, including annual fleabane, camelina, Canadian goldenrod, Indian lettuce, mustard, and oilseed rape. In summary, our results showed that the S-T-YOLOv5 is an accurate, robust, and widely adaptable pollen quantification approach, with minimizing errors and labor expense. We would like to highlight the potential application of S-T-YOLOv5 in quantifying samples of airborne pollens from a known pollen source or insect-dispersed pollens (e.g., alfalfa) in supporting the environmental risk assessment of genetically engineered (GE) plants.

Bioaerosols are useful indicators of plant phenology and can demonstrate the impacts of climate change on both local and regional scales (e.g. pollen monitoring/flowering phenology). Analysing bioaerosols with eDNA approaches are becoming more popular to quantify the diversity of airborne plant environmental DNA (eDNA) and flowering season of plants and trees. Leaf abscission from broadleaved trees and other perennial species can also indicate the status of plant health in response to climate. This happens primarily during autumn in response to seasonal growth conditions and environmental factors, such as changing photoperiod and reduced temperatures. During this period biological material is released in larger quantities to the environment. Here, rural bioaerosol composition during late summer and autumn was captured by MiSEQ sequencing of the rRNA internal transcribed spacer 2 (ITS2) region, a common marker for taxonomic variation. Meteorological parameters were recorded from a proximal weather station. The composition of atmospheric taxa demonstrated that deciduous tree DNA forms part of the bioaerosol community during autumn and, for several common broadleaved tree species, atmospheric DNA abundance correlated to high wind events. This suggests that both flowering and autumn storms cause bioaerosols from deciduous trees that can be detected with eDNA approaches. This is an aspect that must be considered when eDNA methods are used to analyse either pollen or other fragments from trees.