Human Health Risk Assessment of Soils Contaminated with Metal(loid)s by Using DGT Uptake: A Case Study of a Former Korean Metal Refinery Site

The human health risk of soils contaminated with As, Pb, Cu, and Zn was evaluated based on pseudo-total concentrations of metal(loid)s, the physiologically based extraction test (PBET), and diffusive gradients in thin films (DGT). Non-carcinogenic (NCR) and carcinogenic (CR) risks exceeded the U.S. Environmental Protection Agency criteria under both the residential and non-residential scenarios. Human bioavailable concentrations (PBET) were much lower than pseudo-total concentrations. The Hazardous Index of NCR (HI (NCR)) for the PBET in the studied soils was 67% and 94% less than that for pseudo-total concentration, respectively, under the non-residential and residential scenarios. Similarly, CR for the PBET was also 65% and 93% less for the two soils. The concentration of metal(loid)s accumulated in the DGT resin was highly correlated with the PBET-extractable concentration (R² > 0.649). Therefore, for both the CR and HI (NCR), the DGT-calculated risk was linearly related to the PBET-calculated risk for the studied soils under both scenarios. The results suggest that DGT uptake and PBET-extracted concentrations are good surrogates for risk estimation and that both J1 and J2 soils require remediation before their use for residential or non-residential purposes.     

Translational Validation of Personalized Treatment Strategy Based on Genetic Characteristics of Glioblastoma

Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient''s surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMT-unmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtype-specific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated.     

Expression and characterization of Ca2+-independent lipase from Bacillus pumilus B26

A lipase-producing Bacillus pumilus strain (B26) was isolated from a soil sample collected in Korea. The cloned gene showed that the lipase B26 composed of a 34-amino-acid signal sequence and a 181-amino-acid mature part corresponding to a molecular mass (M_r) of 19,225. Based on the M_r and the protein sequence, the lipase B26 belongs to the lipase family I.4. The optimum temperature and pH of the purified enzyme were 35 °C and 8.5, respectively. The lipase B26 showed a ‘Ca²⁺-independent thermostability and catalytic activity’. These are novel properties observed for the first time in lipase B26 among all bacterial lipases and correspond with the suggestion that this enzyme had no Ca²⁺-binding motif around the catalytic His156 residue. This enzyme seems to be a true lipase based on the experimental results that it could hydrolyze various long-chain triglycerides (C₁₄–C₁₈) and triolein (C_18:1) and that it showed a typical interfacial activation mechanism toward both tripropionin and p-nitrophenyl butyrate.     

Phosphorylation and activation of phospholipase D1 by protein kinase C in vivo: determination of multiple phosphorylation sites.

Protein kinase C (PKC) is an important regulator of phospholipase D1 (PLD1). Currently there is some controversy about a phosphorylation-dependent or -independent mechanism of the activation of PLD1 by PKC. To solve this problem, we examined whether PLD1 is phosphorylated by PKC in vivo. For the first time, we have now identified multiple basal phophopeptides and multiple phorbol myristate acetate (PMA) induced phosphopeptides of endogenous PLD1 in 3Y1 cells as well as of transiently expressed PLD1 in COS-7 cells. Down regulation or inhibition of PKC greatly attenuated the PMA-induced phosphorylation as well as the activation of PLD1. In the presence of PMA, purified PLD1 from rat brain was also found to be phosphorylated by PKCalpha in vitro at multiple sites generating seven distinct tryptic phosphopeptides. Four phosphopeptides generated in vivo and in vitro correlated well with each other, suggesting direct phosphorylation of PLD1 by PKCalpha in the cells. Serine 2, threonine 147, and serine 561 were identified as phosphorylation sites, and by mutation of these residues to alanine these residues were proven to be specific phosphorylation sites in vivo. Interestingly, threonine 147 is located in the PX domain and serine 561 is in the negative regulatory "loop" region of PLD1. Mutation of serine 2, threonine 147, or serine 561 significantly reduced PMA-induced PLD1 activity. These results strongly suggest that phosphorylation plays a pivotal role in PLD1 regulation in vivo.     

Crystalline structure analysis of cellulose treated with sodium hydroxide and carbon dioxide by means of X-ray diffraction and FTIR spectroscopy

Crystalline structures of cellulose (named as Cell 1), NaOH-treated cellulose (Cell 2), and subsequent CO2-treated cellulose (Cell 2-C) were analyzed by wide-angle X-ray diffraction and FTIR spectroscopy. Transformation from cellulose I to cellulose II was observed by X-ray diffraction for Cell 2 treated with 15-20 wt% NaOH. Subsequent treatment with CO2 also transformed the Cell 2-C treated with 5-10 wt% NaOH. Many of the FTIR bands including 2901, 1431, 1282, 1236, 1202, 1165, 1032, and 897 cm(-1) were shifted to higher wave number (by 2-13 cm(-1)). However, the bands at 3352, 1373, and 983 cm(-1) were shifted to lower wave number (by 3-95 cm(-1)). In contrast to the bands at 1337, 1114, and 1058 cm(-1), the absorbances measured at 1263, 993, 897, and 668 cm(-1) were increased. The FTIR spectra of hydrogen-bonded OH stretching vibrations at around 3352 cm(-1) were resolved into three bands for cellulose I and four bands for cellulose II, assuming that all the vibration modes follow Gaussian distribution. The bands of 1 (3518 cm(-1)), 2 (3349 cm(-1)), and 3 (3195 cm(-1)) were related to the sum of valence vibration of an H-bonded OH group and an intramolecular hydrogen bond of 2-OH ...O-6, intramolecular hydrogen bond of 3-OH...O-5 and the intermolecular hydrogen bond of 6-O...HO-3', respectively. Compared with the bands of cellulose I, a new band of 4 (3115 cm(-1)) related to intermolecular hydrogen bond of 2-OH...O-2' and/or intermolecular hydrogen bond of 6-OH...O-2' in cellulose II appeared. The crystallinity index (CI) was obtained by X-ray diffraction [CI(XD)] and FTIR spectroscopy [CI(IR)]. Including absorbance ratios such as A1431,1419/A897,894 and A1263/A1202,1200, the CI(IR) was evaluated by the absorbance ratios using all the characteristic absorbances of cellulose. The CI(XD) was calculated by the method of Jayme and Knolle. In addition, X-ray diffraction curves, with and without amorphous halo correction, were resolved into portions of cellulose I and cellulose II lattice. From the ratio of the peak area, that is, peak area of cellulose I (or cellulose II)/total peak area, CI(XD) were divided into CI(XD-CI) for cellulose I and CI(XD-CII) for cellulose II. The correlation between CI(XD-CI) (or CI(XD-CII)) and CI(IR) was evaluated, and the bands at 2901 (2802), 1373 (1376), 897 (894), 1263, 668 cm(-1) were good for the internal standard (or denominator) of CI(IR), which increased the correlation coefficient. Both fraction of the absorbances showing peak shift were assigned as the alternate components of CI(IR). The crystallite size was decreased to constant value for Cell 2 treated at >or= 15 wt% NaOH. The crystallite size of Cell 2-C (cellulose II) was smaller than that of Cell 2 (cellulose I) treated at 5-10 wt% NaOH. But the crystallite size of Cell 2-C (cellulose II) was larger than that of Cell 2 (cellulose II) treated at 15-20 wt% NaOH.     

Inhibition of tyrosinase by gastrodin: An integrated kinetic-computational simulation analysis

We studied the inhibitory effect of gastrodin on tyrosinase using inhibition kinetics and computational simulation. Gastrodin reversibly inhibited tyrosinase in a mixed-type manner with K_i = 123.8 ± 20.2 mM. Time-interval kinetics revealed the inhibition to be a first-order process with mono- and bi-phasic components. Using AutoDock Vina, we calculated a binding energy of ?6.3 kcal/mol for gastrodin and tyrosinase, and we performed a molecular dynamics simulation of the tyrosinase–gastrodin interaction. The simulation results suggested that gastrodin interacts primarily with histidine residues in the active site. A 10-ns molecular dynamics simulation showed that one copper ion in the tyrosinase active site was responsible for the interaction with gastrodin. Our study provides insight into the inhibition of tyrosinase by the hydroxyl groups of gastrodin. A combination of inhibition kinetics and computational calculations may help to confirm the inhibitory action of gastrodin on tyrosinase and define the mechanisms of inhibition.