Effect of diesel exhaust particles on RANK/RANKL expression in in vivo and in vitro models of middle ear inflammation.

OBJECTIVE: Increasing evidence suggests a link between middle ear inflammation and the development of diesel exhaust particles (DEPs). Chronic middle ear inflammation can lead to bone damage and remodeling. This study aimed to explore the impact of DEPs on the expression of interleukin (IL)-6 and RANKL under conditions of middle ear inflammation. METHODS: DEPs were collected by burning fuel in a diesel engine at the Gwangju Institute of Science and Technology. Human middle ear epithelial cells were cultured to 70-80% confluence in culture plates and then treated with DEPs at concentrations of 0, 5, 10, 20, 40, and 80 µg/mL for 24 h. Cell viability was assessed manually. B6.SJL mice, aged 9 weeks, were exposed to DEPs at a concentration of 200 µg/m3 for 1 h daily over a period of 28 days. The expression levels of IL-6, tumor necrosis factor α, RANKL, and RANK were evaluated using hematoxylin and eosin staining and western blot analysis of the harvested middle ear samples. RESULTS: The viability of human middle ear epithelial cells was found to decrease in a dose-dependent manner after 24 h. The mRNA expression level of IL-6 exhibited the most significant increase at the 48-h mark. In contrast, the mRNA expression levels of RANKL and RANK showed a marked increase as early as 6 h post-exposure, with both genes subsequently displaying a time-dependent decrease. Histological analysis revealed that the middle ear mucosa was thicker in the group exposed to DEPs compared to the control group. Additionally, the protein expression levels of IL-6 and RANKL were elevated in the DEP-exposed group relative to the normal control group. CONCLUSIONS: We confirmed the expression of osteoclast-related proteins in the mouse middle ear. These results imply that air pollutants might affect RANKL/RANK signaling, which is associated with bone remodeling.

Rational design of hybrid sensor arrays combined synergistically with machine learning for rapid response to a hazardous gas leak environment in chemical plants.

Combinations of semiconductor metal oxide (SMO) sensors, electrochemical (EC) sensors, and photoionization detection (PID) sensors were used to discriminate chemical hazards on the basis of machine learning. Sensing data inputs were exploited in the form of either numerical or image data formats, and the classification of chemical hazards with high accuracy was achieved in both cases. Even a small amount of gas sensing or purging data (input for ∼30 s) input can be exploited in machine-learning-based gas discrimination. SMO sensors exhibit high performance even in a single-sensor mode, presumably because of the intrinsic cross-sensitivity of metal oxides, which is otherwise considered a major disadvantage of SMO sensors. EC sensors were enhanced through synergistic integration of sensor combinations with machine learning. For precision detection of multiple target analytes, a minimum number of sensors can be proposed for gas detection/discrimination by combining sensors with dissimilar operating principles. The Type I hybrid sensor combines one SMO sensor, one EC sensor, and one PID sensor and is used to identify NH3 gas mixed with sulfur compounds in simulations of NH3 gas leak accidents in chemical plants. The portable remote sensing module made with a Type I hybrid sensor and LTE module can identify mixed NH3 gas with a detection time of 60 s, demonstrating the potential of the proposed system to quickly respond to hazardous gas leak accidents and prevent additional damage to the environment.

Morphological and chemical classification of fine particles over the Yellow Sea during spring, 2015-2018.

Airborne fine particles can affect climate change and human health; moreover, they can be transported over significant distances. However, studies on characteristics of individual particles and their morphology, elemental composition, aging processes, and spatial distribution after long-range transport over the Yellow Sea are limited. Therefore, in this study, we conducted shipborne measurements of fine particulate matter of less than 2.5 µm in diameter (PM2.5) over the Yellow Sea and classified the individual particles into seven types based on their morphology and composition. Overall, the percentage of organic-rich particles was the highest, followed by that of sea spray, sulfur-rich, dust, metals, fly ash, soot, and other particles. Near Shandong, China, the percentage of fly ash and sulfur-rich particles increased, while an increased percentage of only sulfur-rich particles was observed near the Korean Peninsula. In the open sea, the PM2.5 concentrations were the lowest, and sea spray particles predominated. During the cruises, three types (Types 1, 2, and 3) of events with substantially increased PM2.5 concentrations occurred, each with different dominant particles. Type 1 events frequently featured air masses from northern China and Mongolia with high wind speeds and increased dust particles. Type 2 events involved air masses from China with high wind speeds; fly ash, soot, organic-rich particles, and the sulfate percentage in PM2.5 increased. Type 3 events displayed stagnant conditions and local transport (from Korea); soot, dust particles, and the secondary sulfate and nitrate percentages in PM2.5 increased. Thus, different types of transport affected concentrations and dominant types of fine particles over the Yellow Sea during spring.

Application of laser-induced breakdown spectroscopy for detection of elements in flowback water samples from shale gas wells.

Laser-induced breakdown spectroscopy (LIBS) was applied to rapidly detect elements in flowback water samples from shale gas wells in Oklahoma. Two types of LIBS systems (aerosolization and collection on a substrate) were used. The LIBS with an aerosolization system provided rapid determination of elements in flowback water, but moisture present in the chamber and variation in the water droplet size could make quantification difficult. In the substrate collection system, a comparison among substrate types showed that a hydrophilic cellulose filter gave the most homogeneous sample distribution after drying and provided the best performance. The elements in flowback water samples were also determined by inductively coupled plasma-optical emission spectroscopy (ICP-OES). ICP-OES data showed spatial variations for the elements among the different wells. Among the elements, K showed the highest variation (relative standard ${\rm deviation} = {62.8}\% $deviation=62.8%) and Mg the lowest (relative standard ${\rm deviation} = {39.1}\% $deviation=39.1%). Good correlations (${ r} = {0.98 - 0.99}$r=0.98-0.99) were observed between Ca, K, Mg, and Na LIBS peak areas determined using the cellulose filter and their mass concentrations (ppm) measured by ICP-OES for aqueous solutions. The limits of detection for Ca, K, Mg, and Na by LIBS were 122 ppm, 68 ppm, 36 ppm, and 142 ppm, respectively. Both the LIBS and ICP-OES data showed that element concentrations in the flowback water samples were in the order of Na, Ca, Mg, and K from highest to lowest. Our data suggest that the LIBS technique could rapidly detect elements in flowback water samples on site. However, accurate quantification of elements present in low concentrations in water samples is limited.

Comparison of the in vitro toxicological activity of various particulate matter.

Ultrafine particles (UFPs, < 2.5 µm) in air pollutants have been identified as a major cause of respiratory diseases, since they can affect the lung alveoli through the bronchus. In particular, if toxicants such as heavy metals and polycyclic aromatic hydrocarbons (PAHs) are present in UFPs, they can cause diseases such as asthma, chronic obstructive pulmonary disease, and lung cancer. This study compared in vitro toxicity of various particulate matter including UFPs from combustion particles of diesel (diesel exhaust particles (DEP)), rice straw (RS), pine stem (PS) and coal (CC), and road dust particles from tunnel (TD) and roadside (RD). UFPs from combustion particles and road dust were collected with a glass fiber filter using burning systems and a solid aerosol generator. Cell viability was determined by neutral red uptake assay using Chinese hamster ovary strain K1 cells. Redox cycling activity and intracellular reactive oxygen species were measured using 1,4-dithiothreitol (DTT) and 2',7'-dichlorofluorescin diacetate (DCF-DA) assay, respectively. Our in vitro studies validated that combustion particles had high toxicological activity. PS demonstrated the highest activity in cytotoxicity but DEP had the highest activity in the DTT and DCF-DA assays. Overall, since the toxicological activity of particles generated by various means was different, risk assessment should be conducted through various toxicity evaluations rather than one toxicity evaluation.

Combined toxic effect of airborne heavy metals on human lung cell line A549.

Many studies have demonstrated that heavy metals existing as a mixture in the atmospheric environment cause adverse effects on human health and are important key factors of cytotoxicity; however, little investigation has been conducted on a toxicological study of a metal mixture from atmospheric fine particulate matter. The objective of this study was to predict the combined effects of heavy metals in aerosol by using in vitro human cells and obtain a suitable mixture toxicity model. Arsenic, nickel, and lead were selected for mixtures exposed to A549 human lung cancer cells. Cell proliferation (WST-1), glutathione (GSH), and interleukin (IL)-8 inhibition were observed and applied to the prediction models of mixture toxicity, concentration addition (CA) and independent action (IA). The total mixture concentrations were set by an IC10-fixed ratio of individual toxicity to be more realistic for mortality and enzyme inhibition tests. The results showed that the IA model was statistically closer to the observed results than the CA model in mortality, indicating dissimilar modes of action. For the GSH inhibition, the results predicted by the IA and CA models were highly overestimated relative to mortality. Meanwhile, the IL-8 results were stable with no significant change in immune reaction related to inflammation. In conclusion, the IA model is a rapid prediction model in heavy metals mixtures; mortality, as a total outcome of cell response, is a good tool for demonstrating the combined toxicity rather than other biochemical responses.

Detection of nutrient elements and contamination by pesticides in spinach and rice samples using laser-induced breakdown spectroscopy (LIBS).

The laser-induced breakdown spectroscopy (LIBS) technique was applied to quantify nutrients (Mg, Ca, Na, and K) in spinach and rice and to discriminate pesticide-contaminated products in a rapid manner. Standard reference materials (spinach leaves and unpolished rice flour) were used to establish a relationship between LIBS intensity and the concentration of each element (Mg, Ca, Na, and K) (i.e., calibration line). The limits of detection (LODs) for Mg, Ca, Na, and K were found to be 29.63, 102.65, 36.36, and 44.46 mg/kg in spinach and 7.54, 1.76, 4.19, and 6.70 mg/kg in unpolished rice, respectively. Concentrations of those nutrient elements present in spinach and unpolished rice from a local market were determined by using the calibration lines and compared with those measured with ICP-OES, showing good agreement. The data also suggested that the LIBS technique with the chemometric method (PLS-DA) could be a great tool to distinguish pesticide-contaminated samples from pesticide-free samples in a rapid manner even though they have similar elemental compositions. Misclassification rates were found to be 0 and 2% for clean spinach and pesticide-contaminated spinach, respectively, by applying the PLS-DA model established from the training set of data to predict the classes of test samples.

Increased intestinal macromolecular permeability and urine nitrite excretion associated with liver cirrhosis with ascites.

AIM: To determine intestinal permeability, the serum tumor necrosis factor (TNF)-alpha level and urine nitric oxide (NO) metabolites are altered in liver cirrhosis (LC) with or without ascites. METHODS: Fifty-three patients with LC and 26 healthy control subjects were enrolled in the study. The intestinal permeability value is expressed as the percentage of polyethylene glycol (PEG) 400 and 3350 retrieval in 8-h urine samples as determined by high performance liquid chromatography. Serum TNF-alpha concentrations and urine NO metabolites were determined using an enzyme-linked immunosorbent assay (ELISA) and Greiss reaction method, respectively. RESULTS: The intestinal permeability index was significantly higher in patients with LC with ascites than in healthy control subjects or patients with LC without ascites (0.88 +/- 0.12 vs 0.52 +/- 0.05 or 0.53 +/- 0.03, P < 0.05) and correlated with urine nitrite excretion (r = 0.98). Interestingly, the serum TNF-alpha concentration was significantly higher in LC without ascites than in control subjects or in LC with ascites (198.9 +/- 55.8 pg/mL vs 40.9 +/- 12.3 pg/mL or 32.1 +/- 13.3 pg/mL, P < 0.05). Urine nitrite excretion was significantly higher in LC with ascites than in the control subjects or in LC without ascites (1170.9 +/- 28.7 micromol/L vs 903.1 +/- 55.1 micromol/L or 956.7 +/- 47.7 micromol/L, P < 0.05). CONCLUSION: Increased intestinal macromolecular permeability and NO is probably of importance in the pathophysiology and progression of LC with ascites, but the serum TNF-alpha concentration was not related to LC with ascites.

Evaluation of 1047-nm photoacoustic instruments and photoelectric aerosol sensors in source-sampling of black carbon aerosol and particle-bound PAHs from gasoline and diesel powered vehicles.

A series of measurements have been performed at Hill Air Force Base to evaluate real-time instruments for measurements of black carbon aerosol and particle-bound PAHs emitted from spark and ignition compression vehicles. Vehicles were operated at idle or fast idle in one set of measurements and were placed under load on a dynamometer during the second series. Photoacoustic instruments were developed that operated at a wavelength of 1047 nm where gaseous interference is negligible, although sensitivity to black carbon is good. Compact, efficient, solid-state lasers with direct electronic modulation capabilities are used in these instruments. Black carbon measurements are compared with samples collected on quartz fiber filters that were evaluated using the thermal optical reflectance method. A measure of total particle-bound PAH was provided by photoelectric aerosol sensors (PAS) and is evaluated against a sum of PAH mass concentrations obtained with a filter-denuder combination. The PAS had to be operated with a dilution system held at approximately 150 degrees C for most of the source sampling to prevent spurious behavior, thus perhaps compromising detection of lighter PAHs. PA and PAS measurements were found to have a high degree of correlation, perhaps suggesting that the PAS can respond to the polycyclic nature of the black carbon aerosol. The PAS to PA ratio for ambient air in Fresno, CA is 3.7 times as large in winter than in summer months, suggesting that the PAS clearly does respond to compounds other than BC when the instrument is used without the heated inlet.