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Institute
Pancreatic cancer is a common malignant tumor with a high incidence and mortality rate. The prognosis of patients with pancreatic cancer is considerably poor due to the lack of effective treatment in clinically. Despite numerous studies have revealed that baicalein, a natural product, is responsible for suppressing multiple cancer cells proliferation, motility and invasion. The mechanism by which baicalein restraining pancreatic cancer progression remains unclear. In this study, we firstly verified that baicalein plays a critical role in inhibiting pancreatic tumorigenesis in vitro and in vivo. Then we analyzed the alteration of microRNAs (miRNAs) expression levels in Panc-1 cells incubated with DMSO, 50 and 100 μM baicalein by High-Throughput sequencing. Intriguingly, we observed that 20 and 39 miRNAs were accordingly up- and down-regulated through comparing Panc-1 cells exposed to 100 μM baicalein with the control group. Quantitative PCR analysis confirmed that miR-139-3p was the most up-regulated miRNA after baicalein treatment, while miR-196b-5p was the most down-regulated miRNA. Further studies showed that miR-139-3p induced, miR-196b-5p inhibited the apoptosis of Panc-1 cells via targeting NOB1 and ING5 respectively. In conclusion, we demonstrated that baicalein is a potent inhibitor against pancreatic cancer by modulating the expression of miR-139-3p or miR-196b-5p.
The present paper deals with two new species, Yaginumaella pulchella sp. nov. and Yaginumaella hubeiensis sp. nov. Distributional data, as well as illustrations of body and copulatory organs, are provided. Descriptions of their morphology are given. The differences between the new species and their related taxa are discussed.
Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014–Feb 2015). In a companion part 1 paper, we presented an in-depth CCN characterization based on annually as well as seasonally averaged time intervals and discuss different parametrization strategies to represent the Amazonian CCN cycling in modelling studies (M. Pöhlker et al., 2016b). The present part 2 study analyzes the aerosol and CCN variability in original time resolution and, thus, resolves aerosol advection and transformation for the following case studies, which represent the most characteristic states of the Amazonian atmosphere:
1. Near-pristine (NP) conditions, defined as the absence of detectable black carbon (< 0.01 µg m−3), showed their highest occurrence (up to 30 %) in the wet season (i.e., Mar–May). On average, the NP episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode: DAit = 70 nm, NAit = ~ 200 cm−3 vs. weaker accumulation mode: Dacc = 170 nm, Nacc = ~ 60 cm−3), a mostly organic particle composition, and relatively low hygroscopicity levels (κAit = 0.12 vs. κacc = 0.18). The NP CCN efficiency spectrum shows that the CCN population is sensitive to changes in supersaturation (S) over a wide S range.
2. Long-range transport (LRT) conditions frequently mix Saharan dust, African combustion smoke, and sea spray aerosols into the Amazonian wet season atmosphere. The LRT episodes (i.e., Feb–Apr) are characterized by an accumulation mode dominated size distribution (DAit = 80 nm, NAit = 120 cm−3 vs. Dacc = 180 nm, Nacc = 300 cm−3), a clearly increased abundance of dust and salt compounds, and relatively high hygroscopicity levels (κAit = 0.18, κacc = 0.34). The LRT CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
3. Biomass burning (BB) conditions dominate the Amazonian dry season. A selected characteristic BB episode shows a very strong accumulation mode (DAit = 70 nm, NAit = ~ 140 cm−3 vs. Dacc = 170 nm, Nacc = ~ 3400 cm−3), particles with very high organic fractions (> 90 %), and correspondingly low hygroscopicity levels (κAit = 0.14, κacc = 0.17). The BB CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
4. Mixed pollution conditions show the superposition of African (i.e., volcanic) and Amazonian (i.e., biomass burning) aerosol emissions during the dry season. The African aerosols showed a broad monomodal distribution (D = 130 nm, N = ~ 1300 cm−3), with very high sulfate fractions (20 %), and correspondingly high hygroscopicity (κAit = 0.14, κacc = 0.22). This was superimposed by fresh smoke from nearby fires with one strong mode (D = 113 nm, Nacc = ~ 2800 cm−3), an organic-dominated aerosol, and sharply decreased hygroscopicity (κAit = 0.10, κacc = 0.20). These conditions underline the rapidly changing pollution regimes with clear impacts on the aerosol and CCN properties.
Overall, this study provides detailed insights into the CCN cycling in relation to aerosol-cloud interaction in the vulnerable and climate-relevant Amazon region. The detailed analysis of aerosol and CCN key properties and particularly the extracted CCN efficiency spectra with the associated fit parameters provide a basis for an in-depth analysis of aerosol-cloud interaction in the Amazon and beyond.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations as well as hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a one-year period and full seasonal cycle (March 2014 - February 2015). The presented measurements provide a climatology of CCN properties for a characteristic central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The observed mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), elevated values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter κ exhibits remarkably little temporal variability: no pronounced diurnal cycles, weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modelling purposes, we compare different approaches of predicting CCN number concentration and present a novel parameterization, which allows accurate CCN predictions based on a small set of input data.
Measurement of iodine species and sulfuric acid using bromide chemical ionization mass spectrometers
(2021)
Iodine species are important in the marine atmosphere for oxidation and new-particle formation. Understanding iodine chemistry and iodine new-particle formation requires high time resolution, high sensitivity, and simultaneous measurements of many iodine species. Here, we describe the application of a bromide chemical ionization mass spectrometer (Br-CIMS) to this task. During the iodine oxidation experiments in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber, we have measured gas-phase iodine species and sulfuric acid using two Br-CIMS, one coupled to a Multi-scheme chemical IONization inlet (Br-MION-CIMS) and the other to a Filter Inlet for Gasses and AEROsols inlet (Br-FIGAERO-CIMS). From offline calibrations and intercomparisons with other instruments, we have quantified the sensitivities of the Br-MION-CIMS to HOI, I2, and H2SO4 and obtained detection limits of 5.8 × 106, 3.8 × 105, and 2.0 × 105 molec. cm−3, respectively, for a 2 min integration time. From binding energy calculations, we estimate the detection limit for HIO3 to be 1.2 × 105 molec. cm−3, based on an assumption of maximum sensitivity. Detection limits in the Br-FIGAERO-CIMS are around 1 order of magnitude higher than those in the Br-MION-CIMS; for example, the detection limits for HOI and HIO3 are 3.3 × 107 and 5.1 × 106 molec. cm−3, respectively. Our comparisons of the performance of the MION inlet and the FIGAERO inlet show that bromide chemical ionization mass spectrometers using either atmospheric pressure or reduced pressure interfaces are well-matched to measuring iodine species and sulfuric acid in marine environments.