Multifocal Raman Spectrophotometer for Examining Drug-Induced and Chemical-Induced Cellular Changes in 3D Cell Spheroids.

Cell spheroids offer alternative in vitro cell models to monolayer cultured cells because they express complexities similar to those of in vivo tissues, such as cellular responses to drugs and chemicals. Raman spectroscopy emerged as a powerful analytical tool for detecting chemical changes in living cells because it nondestructively provides vibrational information regarding a target. Although multiple iterations are required in drug screening to determine drugs to treat cell spheroids and assess the inter-spheroid heterogeneity, current Raman applications used in spheroids analysis allow the observation of only a few spheroids owing to the low throughput of Raman spectroscopy. In this study, we developed a multifocal Raman spectrophotometer that enables simultaneous analysis of multiple spheroids in separate wells of a regular 96-well plate. By utilizing 96 focal spots excitation and parallel signal collection, our system can improve the throughput by approximately 2 orders of magnitude compared to a conventional single-focus Raman microscope. The Raman spectra of HeLa cell spheroids treated with anticancer drugs and HepG2 cell spheroids treated with free fatty acids were measured simultaneously, and concentration-dependent cellular responses were observed in both studies. Using the multifocal Raman spectrophotometer, we rapidly observed chemical changes in spheroids, and thus, this system can facilitate the application of Raman spectroscopy in analyzing the cellular responses of spheroids.

Label-Free Monitoring of Drug-Induced Cytotoxicity and Its Molecular Fingerprint by Live-Cell Raman and Autofluorescence Imaging.

Simultaneous observation of drug distribution at the effector site and subsequent cell response are essential in the drug development process. However, few studies have visualized the drug itself and biomolecular interactions in living cells. Here, we used label-free Raman microscopy to investigate drug-induced cytotoxicity and visualize drug uptake and subcellular localization by its specific molecular fingerprint. A redox-sensitive Raman microscope detected the decrease of reduced cytochrome c (cyt c) after Actinomycin D (ActD) treatment in a time-dependent and dose-dependent format. Immunofluorescence staining of cyt c suggested that the release of cyt c was not the major cause. Combining Raman microscopy with conventional biological methods, we reported that the oxidization of cyt c is an early cytotoxicity marker prior to the release of cyt c. Moreover, as the spectral properties of ActD are sensitive to the surrounding environment, subcellular localization of ActD was visualized sensitively by the weak autofluorescence, and the intercalation of ActD into DNA was detected by shifted Raman peaks, allowing for parallel observation of drug uptake and the mechanism of action. In this research, we achieved simultaneous observation of cytotoxicity and cellular drug uptake by Raman microscopy, which could facilitate a precise understanding of pharmacological effects and predict potential drug toxicity in the future.

Improving VOCs control strategies based on source characteristics and chemical reactivity in a typical coastal city of South China through measurement and emission inventory.

In China, the corresponding control directives for volatile organic compounds (VOCs) have been based on primary emissions, rarely considering reactive speciation. To seek more effective VOCs control strategies, we investigated 107 VOC species in a typical coastal city (Beihai) of South China, from August to November 2018. Meanwhile, a high-resolution anthropogenic VOCs monthly emission inventory (EI) was established for 2018. For source apportionments (SAs) reliability, comparisons of source structures derived from positive matrix factorization (PMF) and EI were made mainly in terms of reaction losses, uncertainties and specific ratios. Finally, for the source-end control, a comprehensive reactivity control index (RCI) was established by combing SAs with reactive speciation profiles. Ambient measurements showed that the average concentration of VOCs was 26.38 ppbv, dominated by alkanes (36.7%) and oxygenated volatile organic compounds (OVOCs) (29.4%). VOC reactivity was estimated using ozone formation potential (52.35 ppbv) and propylene-equivalent concentration (4.22 ppbv). EI results displayed that the entire VOC, OFP, and propylene-equivalent emissions were 40.98 Gg, 67.98 Gg, and 105.93 Gg, respectively. Comparisons of source structures indicated that VOC SAs agreed within ±100% between two perspectives. Both PMF and EI results showed that petrochemical industry (24.0% and 33.0%), food processing and associated combustion (19.1% and 29.2%) were the significant contributors of anthropogenic VOCs, followed by other industrial processes (22.2% and 13.3%), transportation (18.9% and 12.0%), and solvent utilization (9.1% and10.5%). Aimed at VOCs abatement according to RCI: for terminal control, fifteen ambient highly reactive species (predominantly alkenes and alkanes) were targeted; for source control, the predominant anthropogenic sources (food industry, solvent usage, petrochemical industry and transportation) and their emitted highly reactive species were determined. Particularly, with low levels of ambient VOC and primary emissions, in this VOC and NOx double-controlled regime, crude disorganized emission from food industry contributed a high RCI.

Characteristics and health risk assessment of volatile organic compounds (VOCs) in restaurants in Shanghai.

Volatile organic compounds (VOCs) are important precursors of ozone and atmospheric particulates that have attracted extensive attention worldwide. Cooking emissions, the chemical characteristics of which vary dramatically due to different cooking styles, are a main source of ambient VOCs, especially in large cities. This research focused on the emission characteristics of VOCs from six types of restaurants in Shanghai: hot pot (HP), Sichuan cuisine (SC), Cantonese cuisine (CS), seafood (SF), Western fast food (WFF), and authentic Shanghai cuisine (ASC). It was found that HP, which discharged cooking fumes indoors, produced the highest mass concentration of VOCs (1900.2 ± 364.8 µg m-3), followed by SC (1403.7 ± 403.8 µg m-3), WFF (656.0 ± 156.9 µg m-3), SF (638.6 ± 145.1 µg m-3), CC (632.7 ± 127.7 µg m-3), and ASC (612.3 ± 51.3 µg m-3), the cooking fumes from which were collected by emission extraction stacks. Additionally, the VOC species from each cuisine were mainly low carbon substances. Alkanes were the major VOC pollutants from all six cuisines, accounting for 34.4-71.7%. The coefficient divergence values were 0.287-0.593, suggesting that there were differences between the cuisines in the present study. Ozone formation potential and secondary organic aerosol formation potential indicated that O-VOCs and aromatics were the largest contributors. Health risk assessment of VOCs via non-carcinogenic risk values (HQ) and carcinogenic risk values (RISK) indicated that frying, grilling, and stir-frying had relatively large impacts on human health. VOCs collected in emission extraction stacks were significantly higher risk compared with those in the indoor environment, but the RISK score of the HP restaurant was larger, second only to SC. The HQ and RISK values of 1,3-butadiene, acetaldehyde, and trichloroethylene in the HP restaurant all exceeded US EPA standards, indicating that long-term exposure in an HP restaurant would have a significant impact on human health and might carry a potential cancer risk.

Emission characteristics of fine particulate matter from ultra-low emission power plants.

As one of the highest energy consuming and polluting industries, the power generation industry is an important source of particulate matter emissions. Recently, implementation of ultra-low emission technology has changed the emission characteristic of fine particulate matter (PM2.5). In this study, PM2.5 emitted from four typical power plants in China was sampled using a dilution channel sampling system, and analyzed for elements, water-soluble ions and carbonaceous fractions. The results showed that PM2.5 concentrations emitted from the four power plants were 0.78 ±â€¯0.16, 0.63 ±â€¯0.09, 0.29 ±â€¯0.07 and 0.28 ±â€¯0.01 mg m-3, respectively. Emission factors were 0.004-0.005 g/kg coal, nearly 1-2 orders of magnitude lower than those reported in previous studies. The highest proportions of PM2.5 consisted of organic carbon (OC), SO42-, elemental carbon (EC), NH4+, Al and Cl-. Coefficients of divergence (CDs) were in the ranges 0.22-0.41 (for an individual plant), 0.43-0.69 (among different plants), and 0.60-0.99 (in previous studies). The results indicated that the source profiles of each tested power plant were relatively similar, but differed from those in previous studies. Enrichment factors showed elevated Se and Hg, in accordance with the source markers Se and As. Comparing source profiles with previous studies, the proportion of OC, EC and NH4+ were higher, while the proportion of Al in PM2.5 were relatively lower. The OC/EC ratio became concentrated at ∼5. Results from this study can be used for source apportionment and emission inventory calculations after implementation of ultra-low emission technologies.

Variation of wastewater contaminants in China and source identification using hierarchical clustering based on weighted factor scores.

Human activities have huge impact on the aquatic environment. Knowledge on sources of the contaminants provides guidelines to determine the ideal location and maintenance of monitoring stations, thus advancing environmental monitoring and pollution control. Factor analysis (FA) may be the most popular method for source identification, but the results should be affirmed. Following this logic, in this research, firstly the potential sources were determined, and secondly the contaminant concentrations in the source regions and the non-source regions were compared. To identify the potential sources, 75 meteorological, economic and social indicators were used to group the study regions. FA was used to reduce dimensionality and factor scores were calculated. The grouping was based on the weighted factor scores while the weight was variance explained by each factor respectively. Each group was supposed to correspond to a factor; that is, a potential source. The results indicated that the concentrations of chemical oxygen demand (COD), ammonia nitrogen, phosphorus and arsenic in wastewater were significantly different between groups. Animal husbandry, mining and/or energy industry were the main sources of COD, ammonia nitrogen and phosphorus; animal husbandry, mining, energy industry, and/or heavy and chemical industry were the main sources of phosphorus; humid climate and/or secondary industry were the main sources of arsenic.

Investigate the impact of local iron-steel industrial emission on atmospheric mercury concentration in Yangtze River Delta, China.

Mercury is a global neurotoxic pollutant, which can be globally transported and bioaccumulated in the food chain. Iron-steel production is one of the most significant sources of anthropogenic atmospheric mercury emission, while information on this source is scarce. Hourly gaseous elemental mercury (GEM) and particle bound mercury (PBM) were studied inside (IP) and at the boundary (BP) of a typical iron-steel plant in the Yangtze River Delta (YRD), China from September 2016 to August 2017. The GEM concentrations were 0.97-503.1 and 0.05-112.6 ng/m3 at the IP and BP sites, respectively, while PBM concentrations were one to four orders of magnitude higher than urban and suburban ambient levels. Several lines of evidences indicated that PBM was mainly originated from the iron-steel manufacturing process, especially from sintering and coke-making processes in this iron-steel plant. However, a combined emission effect contributed to GEM variation. The receptor model of positive matrix factorization (PMF) showed that local direct emissions (coal combustion, industrial activity, vehicle exhaust, and secondary evaporation from polluted soil) contributed 51.3% of the total GEM concentration variation. Potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models clearly showed that air masses moving from areas surrounding YRD had the highest concentrations of atmospheric mercury. These results provided evidence that iron-steel manufacturing emissions have a considerable effect on regional atmospheric mercury concentrations, especially PBM.