Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life.

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

Water-soluble organic compounds (WSOC) from atmospheric aerosols in Bou-Ismail (Algeria).

In this contribution, we report the study of nuclear resonance magnetic spectroscopy techniques (1H-NMR, 13C-NMR, and 2D-NMR) efficiency in the characterisation of the functional composition of water-soluble organic compounds (WSOC) from atmospheric aerosols. The chosen site was our scientific and technical center of research (CRAPC) situated in Algerian Bou-Ismail city. where the concentrations of PM10 were found to be between 15.66 and 142.19 µg.m-3. As results, 1H-NMR analysis showed the coexistence of biological material and emissions from urban and biomass burning. The dominant source was identified by quantitative integration of each 1H NMR spectral region. By using the HSQC technique, many peaks are revealed in biogenic samples including biomass burning. On the other hand, the identification of the source of various organic compounds and their functional composition is possible through specific NMR spectra, which can also be used to adjust the surrounding organic aerosol sources.

Air quality in a revitalized special economic zone at the center of an urban monocentric agglomeration.

In this study, we have examined the air quality within a revitalized, post-industrial urban area in Lódz, Poland. The use of Dron technology with mobile measurement equipment allowed for accurate assessment of air quality (particulate matter and gaseous pollutants) and factors influencing air quality (wind speed and direction) on a local scale in an area of 0.18 km2 and altitudes from 2 to 50 m. The results show that the revitalization carried out in the Lodz special economic zone area contributed to eliminate internal air pollution emitters through the use of ecological and effective heat sources. The exceedances permissible concentration values were local, and concerned mainly the higher measurement zones of the troposphere (more than 30 m above ground level). In the case of gaseous pollutants, higher wind speeds were associated with a decrease in the concentration of SO2 and an increase in H2S concentration. In both cases, the wind contributed to the occurrence of local areas of accumulation of these gaseous pollutants in the spaces between buildings or wooded areas.

Evaluation of dust and endotoxin exposure among rice mill workers in northeast India.

Exposure to particulate matter and endotoxin can lead to acute and chronic respiratory problems in workers. A study was conducted to quantify particulate matter with an aerodynamic diameter of ≤10 µm (PM10) and endotoxin levels in rice mills in northeast India. Sixty-four PM10 dust samples were collected from eight rice mills at two locations: the feeding and polishing sections for two varieties of paddy: Ranjit and Hali. Endotoxin exposures were analyzed using the Limulus Amoebocyte Lysate (LAL) gel clot test. The results showed that the geometric mean of the 8-h time-weighted average (TWA) PM10 dust concentration and endotoxin level in the rice mills were 10.69 mg/m³ and 2.2 EU/m³, respectively. Dust and endotoxin exposure were higher in the feeding section than in the polishing section. Endotoxin exposure in the feeding section during the milling of the Hali variety of paddy was 56.0 % higher than the milling of the Ranjit variety. Additionally, endotoxin exposure during the milling of the Hali variety was 24.2 % higher than that of the milling of the Ranjit variety in the polishing section. The dust exposure in the rice mills was 194.5 % higher than the standards set up by the United States Environmental Protection Agency. However, the exposure to endotoxin in rice mills was approximately 40.10 times below the recommended limit of 90 EU/m3.

Long-term effects of air quality on hospital readmission for heart failure in patients with acute myocardial infarction.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization. METHODS: We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups. RESULTS: After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 µg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 µg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064). CONCLUSION: NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 µg/m3 and PM10 exceeds 55 µg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Sources of PM10 ionic species in the South-West Mediterranean (Algeria).

The contents of water-soluble major's ions (MSA, Cl-, NO3-, SO42-, Na+, NH4+, K+, Mg2+, and Ca2+) in the PM10 particle fraction were investigated thanks to detailed measurements of the main chemical constituents of PM10 in remote coastal areas in Bou-Ismail; in the South-West of the Mediterranean Sea (Algeria), during a 2-year period; from July 2011 to August 2013, under the framework of the ChArMEx project (Chemistry-Aerosol Mediterranean Experiment, http://charmex.lsce.ipsl.fr ). The total water-soluble ion concentrations in PM10 at the Bou-Ismail measurement station varied from 3.3 µg/m3 (July 2011) to 49.6 µg/m3 (March 2012). The annual mean mass concentrations of ions in the PM10 particulate fraction were Cl- > Na+ > SO42- > Mg2+ > NO3- > Ca2+ > K+ > NH4+ > Oxalate. The change in potassium nss-K + concentrations in PM10 over the course of a year reveals that biomass burning (BB) has an effect on three separate seasons: the beginning of winter (February and March), the end of summer (August), and the autumn (September and October). The origin periods of biomass burning BB identified employing the mapping of hotspots and fires during periods of August and September 2011, 2012, and 2013 underlined the important fires in the surrounding areas of the Mediterranean Sea (Sardinia Islands from Italy, Corsica from France).

Multi-source observations on the effect of atmospheric blocking on air quality in Istanbul: a study case.

Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in Istanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in Istanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in Istanbul was determined as "poor" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the Istanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m.

PM10 exposure induces bronchial hyperresponsiveness by upreguating acetylcholine muscarinic 3 receptor.

Exposure to particulate matter (PM10) can induce respiratory diseases that are closely related to bronchial hyperresponsiveness. However, the involved mechanism remains to be fully elucidated. This study aimed to demonstrate the effects of PM10 on the acetylcholine muscarinic 3 receptor (CHRM3) expression and the role of the ERK1/2 pathway in rat bronchial smooth muscle. A whole-body PM10 exposure system was used to stimulate bronchial hyperresponsiveness in rats for 2 and 4 months, accompanied by MEK1/2 inhibitor U0126 injection. The whole-body plethysmography system and myography were used to detect the pulmonary and bronchoconstrictor function, respectively. The mRNA and protein levels were determined by Western blotting, qPCR, and immunofluorescence. Enzyme-linked immunosorbent assay was used to detect the inflammatory cytokines. Compared with the filtered air group, 4 months of PM10 exposure significantly increased CHRM3-mediated pulmonary function and bronchial constriction, elevated CHRM3 mRNA and protein expression levels on bronchial smooth muscle, then induced bronchial hyperreactivity. Additionally, 4 months of PM10 exposure caused an increase in ERK1/2 phosphorylation and increased the secretion of inflammatory factors in bronchoalveolar lavage fluid. Treatment with the MEK1/2 inhibitor, U0126 inhibited the PM10 exposure-induced phosphorylation of the ERK1/2 pathway, thereby reducing the PM10 exposure-induced upregulation of CHRM3 in bronchial smooth muscle and CHRM3-mediated bronchoconstriction. U0126 could rescue PM10 exposure-induced pathological changes in the bronchus. In conclusion, PM10 exposure can induce bronchial hyperresponsiveness in rats by upregulating CHRM3, and the ERK1/2 pathway may be involved in this process. These findings could reveal a potential therapeutic target for air pollution induced respiratory diseases.

Morphology, aspect ratio, and surface elemental composition of primary aerosol particles at urban region of India.

The PM2.5 and PM10 particles were characterized in terms of morphology (size and shape) and surface elemental composition at two different (traffic and industrial) locations in urban region of India and further linked to different morphological defining parameters. The overall PM2.5 and PM10 showed significant daily variability indicating higher PM10 as compared to PM2.5. PM2.5/PM10 ratio was found to be 0.58 ± 0.10 indicating the abundance of PM2.5. Soot aggregates, aluminosilicates, and brochosomes particles were classified based on morphology, aspect ratio (AR), and surface elemental composition of single particles. The linear regression analysis indicates the significant correlation between area equivalent (Daeq) and feret diameter (Dfd) (R2 0.86-0.98). Higher aspect ratio (1.48 ± 0.87-1.43 ± 0.50) was noted at traffic site as compared to industrial site (1.33 ± 0.58-1.29 ± 0.30), while circularity showed the opposite trend. Fractal dimension (Df) of soot aggregates estimated by the soot parameters method (SPM) were found to be 1.70, 1.72, and 1.88, mainly attributed to vehicular emissions, biomass, and industrial emission/coal burning, respectively. This further inferred that freshly emitted soot particles exhibited lacey in nature with spherical shape (Df 1.70) at traffic site, while at industrial location, they were different with compact shapes (Df 1.88) due to particle aging processes. This study inferred the synoptic changes in mass, chemical characteristics, and morphology of aerosol particles which provide the new insights into individual atmospheric particle and their dynamic nature.

Chemical composition of PM10 at a rural site in the western Mediterranean and its relationship with the oxidative potential.

A comprehensive chemical characterization (water-soluble ions, organic and elemental carbon, water- and methanol-soluble organic carbon, levoglucosan, and major and trace metals) of PM10 samples collected in a rural area located in the southeast of the Iberian Peninsula was performed. Additionally, the oxidative potential of the samples, used as an indicator of aerosol toxicity, was determined by the ascorbic acid (OPAA) and dithiothreitol (OPDTT) assays. The average concentration of PM10 during the study period, spanning from late winter to early spring, was 20.2 ± 10.8 µg m-3. Nitrate, carbonate and calcium (accounting for 20% of the average PM10 mass concentration) and organic matter (with a contribution of 28%) were the main chemical components of PM10. Average concentrations of traffic tracers such as elemental carbon, copper and zinc (0.31 µg m-3, 3 ng m-3, and 9 ng m-3, respectively) were low compared with those obtained at an urban site in the same region, due to the almost total absence of traffic in the surrounding of the sampling site. Regarding levoglucosan and K+, which can be considered as tracers of biomass burning, their concentrations (0.12 µg m-3 and 55 ng m-3, respectively) were in the lower range of values reported for other rural areas in Europe, suggesting a moderate contribution form this source to PM10 levels. The results of the Pearson's correlation analysis showed that volume-normalised OPAA and OPDTT levels (average values of 0.11 and 0.32 nmol min-1 m-3, respectively) were sensitive to different PM10 chemical components. Whereas OPAA was not strongly correlated with any of the species measured, good correlation coefficients of OPDTT with water-soluble organic carbon (r = 0.81) and K+ (r = 0.73) were obtained, which points to biomass burning as an important driver of the DTT activity.

River dust-induced air pollution in a changing climate: A study of Taiwan's Choshui and Kaoping Rivers.

This study investigates river dust episodes along the Choshui and Kaoping Rivers in Taiwan, focusing on their spatiotemporal distribution and correlation with hydrometeorological factors (temperature, precipitation, relative humidity, and wind speed). Using the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm and time-dependent intrinsic correlation (TDIC) analysis, we identified significant annual and diurnal correlations between PM10 concentrations and these factors. The analysis revealed that wind speed at Lunbei station had a positive annual correlation with PM10, while other factors exhibited significant negative correlations. Seasonal variations in PM10 correlations with temperature, relative humidity, and wind speed were observed, aligning with the prevailing seasons of river dust episodes. Wind motion analysis highlighted diurnal associations with land-sea breezes and annual correlations with the winter monsoon. Specifically, the Choshui River's dust events coincided with the northeast monsoon, whereas the Kaoping River's events occurred during the northwest and southwest monsoons. The study also uncovered that downstream stations (Lunbei and Daliao) were more prone to severe dust events than upstream stations (Douliu and Pingtung). These findings enhance our understanding of the dynamics and environmental impacts of river dust episodes, providing valuable insights for air quality management and health risk mitigation.

Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy).

Two low-cost (LC) monitoring networks, PurpleAir (instrumented by Plantower PMS5003 sensors) and AirQino (Novasense SDS011), were assessed in monitoring PM2.5 and PM10 daily concentrations in the Padana Plain (Northern Italy). A total of 19 LC stations for PM2.5 and 20 for PM10 concentrations were compared vs. regulatory-grade stations during a full "heating season" (15 October 2022-15 April 2023). Both LC sensor networks showed higher accuracy in fitting the magnitude of PM10 than PM2.5 reference observations, while lower accuracy was shown in terms of RMSE, MAE and R2. AirQino stations under-estimated both PM2.5 and PM10 reference concentrations (MB = -4.8 and -2.9 µg/m3, respectively), while PurpleAir stations over-estimated PM2.5 concentrations (MB = +5.4 µg/m3) and slightly under-estimated PM10 concentrations (MB = -0.4 µg/m3). PurpleAir stations were finer than AirQino at capturing the time variation of both PM2.5 and PM10 daily concentrations (R2 = 0.68-0.75 vs. 0.59-0.61). LC sensors from both monitoring networks failed to capture the magnitude and dynamics of the PM2.5/PM10 ratio, confirming their well-known issues in correctly discriminating the size of individual particles. These findings suggest the need for further efforts in the implementation of mass conversion algorithms within LC units to improve the tuning of PM2.5 vs. PM10 outputs.

The association between indoor air quality and respiratory health symptoms among preschool children in Penang, Malaysia.

A cross-sectional study was conducted among 126 preschool children aged 4-6 years in traffic, industrial, and suburban areas of Penang, Malaysia, to determine their exposure to indoor air pollutants and their associations with respiratory symptoms. A standardised and validated questionnaire was used to collect data on respiratory health symptoms among respondents. An indoor air quality assessment was conducted in selected preschools that included temperature, relative humidity, air velocity, volatile organic compounds (VOCs), and particulate matter (PM2.5, and PM10). There were significant differences in median concentrations of PM2.5, PM10 and relative humidity among study groups. Statistical analysis showed significant associations between air pollutants in preschool with respiratory symptoms. Factors that influenced the increased likelihood of cough and phlegm were linked to the increase in PM2.5 exposure. This study suggests regular classroom cleaning and routine maintenance of air conditioners to be done inside the preschools.

Impact of Airborne Exposure to PM10 Increases Susceptibility to P. aeruginosa Infection.

The effects of exposure to airborne particulate matter with a size of 10 µm or less (PM10) on C57BL/6 mouse corneas, their response to Pseudomonas aeruginosa (PA) infection, and the protective effects of SKQ1 were determined. C57BL/6 mouse corneas receiving PBS or SKQ1 were exposed to control (air) or PM10 for 2 weeks, infected, and the disease was documented by clinical score, PMN quantitation, bacterial plate count, RT-PCR and Western blot. PBS-treated, PM10-exposed corneas did not differ at 1 day postinfection (dpi), but exhibited earlier (3 dpi) corneal thinning compared to controls. By 3 dpi, PM10 significantly increased corneal mRNA levels of several pro-inflammatory cytokines, but decreased IL-10, NQO1, GR1, GPX4, and Nrf2 over control. SKQ1 reversed these effects and Western blot selectively confirmed the RT-PCR results. PM10 resulted in higher viable bacterial plate counts at 1 and 3 dpi, but SKQ1 reduced them at 3 dpi. PM10 significantly increased MPO in the cornea at 3 dpi and was reduced by SKQ1. SKQ1, used as an adjunctive treatment to moxifloxacin, was not significantly different from moxifloxacin alone. Exposure to PM10 increased the susceptibility of C57BL/6 to PA infection; SKQ1 significantly reversed these effects, but was not effective as an adjunctive treatment.

Does Exposure to Ambient Air Pollution Affect Gestational Age and Newborn Weight?-A Systematic Review.

Current evidence suggests that airborne pollutants have a detrimental effect on fetal growth through the emergence of small for gestational age (SGA) or term low birth weight (TLBW). The study's objective was to critically evaluate the available literature on the association between environmental pollution and the incidence of SGA or TLBW occurrence. A comprehensive literature search was conducted across Pubmed/MEDLINE, Web of Science, Cochrane Library, EMBASE, and Google Scholar using predefined inclusion and exclusion criteria. The methodology adhered to the PRISMA guidelines. The systematic review protocol was registered in PROSPERO with ID number: CRD42022329624. As a result, 69 selected papers described the influence of environmental pollutants on SGA and TLBW occurrence with an Odds Ratios (ORs) of 1.138 for particulate matter ≤ 10 µm (PM10), 1.338 for particulate matter ≤ 2.5 µm (PM2.5), 1.173 for ozone (O3), 1.287 for sulfur dioxide (SO2), and 1.226 for carbon monoxide (CO). All eight studies analyzed validated that exposure to volatile organic compounds (VOCs) is a risk factor for SGA or TLBW. Pregnant women in the high-risk group of SGA occurrence, i.e., those living in urban areas or close to sources of pollution, are at an increased risk of complications. Understanding the exact exposure time of pregnant women could help improve prenatal care and timely intervention for fetuses with SGA. Nevertheless, the pervasive air pollution underscored in our findings suggests a pressing need for adaptive measures in everyday life to mitigate worldwide environmental pollution.

Investigation of the relationship between air pollution and gestational diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes. METHODS: The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 µm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant. RESULTS: None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05). CONCLUSIONS: This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.

The health of pregnant women and their children can be impacted by gestational diabetes mellitus (GDM), one of the prevalent pregnancy complications. Some of studies showed that the incidence of gestational diabetes can be influenced by genetic or environmental factors. Air pollution is an environmental stimulus that may predispose pregnant women to GDM. This research explored whether air pollution could increase the risk of developing gestational diabetes. Over 6000 pregnant women in five cities of Iran participated in the study and were screened for gestational diabetes. Their exposure to the various air pollutants during the three months preceding pregnancy and total pregnancy period was measured. In this study, we found no clear association between air pollution and gestational diabetes. However, this finding needs to be interpreted cautiously since all the influential factors were not assessed.

Residues of atrazine and diuron in rice straw, soils, and air post herbicide-contaminated straw biomass burning.

This study investigates the environmental impact of burning herbicide-contaminated biomass, focusing on atrazine (ATZ) and diuron (DIU) sprayed on rice straw prior to burning. Samples of soil, biomass residues, total suspended particulate (TSP), particulate matter with an aerodynamic diameter ≤ 10 µm (PM10), and aerosols were collected and analyzed. Soil analysis before and after burning contaminated biomass showed significant changes, with 2,4-dichlorophenoxyacetic acid (2,4-D) initially constituting 79.2% and decreasing by 3.3 times post-burning. Atrazine-desethyl, sebuthylazine, and terbuthylazine were detected post-burning. In raw rice straw biomass, terbuthylazine dominated at 80.0%, but burning ATZ-contaminated biomass led to the detection of atrazine-desethyl and notable increases in sebuthylazine and terbuthylazine. Conversely, burning DIU-contaminated biomass resulted in a shift to 2,4-D dominance. Analysis of atmospheric components showed changes in TSP, PM10, and aerosol samples. Linuron in ambient TSP decreased by 1.6 times after burning ATZ-contaminated biomass, while atrazine increased by 2.9 times. Carcinogenic polycyclic aromatic hydrocarbons (PAHs), including benzo[a]anthracene (BaA), benzo[a]pyrene (BaP), and benzo[b]fluoranthene (BbF), increased by approximately 9.9 to 13.9 times after burning ATZ-contaminated biomass. In PM10, BaA and BaP concentrations increased by approximately 11.4 and 19.0 times, respectively, after burning ATZ-contaminated biomass. This study sheds light on the environmental risks posed by burning herbicide-contaminated biomass, emphasizing the need for sustainable agricultural practices and effective waste management. The findings underscore the importance of regulatory measures to mitigate environmental contamination and protect human health.

Airborne Aluminum as an Underestimated Source of Human Exposure: Quantification of Aluminum in 24 Human Tissue Types Reveals High Aluminum Concentrations in Lung and Hilar Lymph Node Tissues.

Aluminum (Al) is the most abundant metal in the earth's crust, and humans are exposed to Al through sources like food, cosmetics, and medication. So far, no comprehensive data on the Al distribution between and within human tissues were reported. We measured Al concentrations in 24 different tissue types of 8 autopsied patients using ICP-MS/MS (inductively coupled plasma-tandem mass spectrometry) under cleanroom conditions and found surprisingly high concentrations in both the upper and inferior lobes of the lung and hilar lymph nodes. Al/Si ratios in lung and hilar lymph node samples of 12 additional patients were similar to the ratios reported in urban fine dust. Histological analyses using lumogallion staining showed Al in lung erythrocytes and macrophages, indicating the uptake of airborne Al in the bloodstream. Furthermore, Al was continuously found in PM2.5 and PM10 fine dust particles over 7 years in Upper Austria, Austria. According to our findings, air pollution needs to be reconsidered as a major Al source for humans and the environment.

Coarse particulate matter (PM10) induce an inflammatory response through the NLRP3 activation.

INTRODUCTION: PM exposure can induce inflammatory and oxidative responses; however, differences in these adverse effects have been reported depending on the chemical composition and size. Moreover, inflammatory mechanisms such as NLRP3 activation by PM10 have yet to be explored. OBJECTIVE: To assess the impact of PM10 on cell cytotoxicity and the inflammatory response through in vitro and in vivo models. METHODOLOGY: Peripheral blood mononuclear cells (PBMCs) from healthy donors were exposed to PM10. Cytotoxicity was determined using the LDH assay; the expression of inflammasome components and the production of pro-inflammatory cytokines were quantified through qPCR and ELISA, respectively; and the formation of ASC complexes was examined using confocal microscopy. For in vivo analysis, male C57BL6 mice were intranasally challenged with PM10 and bronchoalveolar lavage fluid was collected to determine cell counts and quantification of pro-inflammatory cytokines by ELISA. RNA was extracted from lung tissue, and the gene expression of inflammatory mediators was quantified. RESULTS: PM10 exposure induced significant cytotoxicity at concentrations over 100 µg/mL. Moreover, PM10 enhances the gene expression and release of pro-inflammatory cytokines in PBMCs, particularly IL-1ß; and induces the formation of ASC complexes in a dose-dependent manner. In vivo, PM10 exposure led to cell recruitment to the lungs, which was characterized by a significant increase in polymorphonuclear cells compared to control animals. Furthermore, PM10 induces the expression of several inflammatory response-related genes, such as NLRP3, IL-1ß and IL-18, within lung tissue. CONCLUSION: Briefly, PM10 exposure reduced the viability of primary cells and triggered an inflammatory response, involving NLRP3 inflammasome activation and the subsequent production of IL-1ß. Moreover, PM10 induces the recruitment of cells to the lung and the expression of multiple cytokines; this phenomenon could contribute to epithelial damage and, thus to the development and exacerbation of respiratory diseases such as viral infections.

Local spatiotemporal dynamics of particulate matter and oak pollen measured by machine learning aided optical particle counters.

Conventional techniques for monitoring pollen currently have significant limitations in terms of labour, cost and the spatiotemporal resolution that can be achieved. Pollen monitoring networks across the world are generally sparse and are not able to fully represent the detailed characteristics of airborne pollen. There are few studies that observe concentrations on a local scale, and even fewer that do so in ecologically rich rural areas and close to emitting sources. Better understanding of these would be relevant to occupational risk assessments for public health, as well as ecology, biodiversity, and climate. We present a study using low-cost optical particle counters (OPCs) and the application of machine learning models to monitor particulate matter and pollen within a mature oak forest in the UK. We characterise the observed oak pollen concentrations, first during an OPC colocation period (6 days) for calibration purposes, then for a period (36 days) when the OPCs were distributed on an observational tower at different heights through the canopy. We assess the efficacy and usefulness of this method and discuss directions for future development, including the requirements for training data. The results show promise, with the derived pollen concentrations following the expected diurnal trends and interactions with meteorological variables. Quercus pollen concentrations appeared greatest when measured at the canopy height of the forest (20-30 m). Quercus pollen concentrations were lowest at the greatest measurement height that is above the canopy (40 m), which is congruent with previous studies of background pollen in urban environments. The attenuation of pollen concentrations as sources are depleted is also observed across the season and at different heights, with some evidence that the pollen concentrations persist later at the lowest level beneath the canopy (10 m) where catkins mature latest in the season compared to higher catkins.