In this study, an ultrasound-assisted micellar extraction process was developed to efficiently purify the anticancer substance paclitaxel from the plant cell Taxus chinensis. The problem of many extraction steps and long phase separation time in the traditional micellar process could be dramatically improved. The highest paclitaxel yield (~96%, extracted twice) was obtained at 180 W of ultrasonic power and 1.5 h of ultrasonic irradiation time, which was 24.7% higher than that of the traditional method. In addition, the partition coefficient (K) showed a maximum value (24.0) at 180 W of ultrasonic power and 1.5 h of irradiation time. There was no significant difference in the purity of paclitaxel, and the purity of initial paclitaxel (6.81%) increased to 22.0% after purification. Compared to the traditional method, the phase separation time of the back extraction decreased by 40.7-56.2% (ultrasonic power 80 W), 46.3-67.6% (ultrasonic power 180 W), and 51.9-67.6% (ultrasonic power 250 W), respectively. The phase separation time decreased as the ultrasonic power (80-250 W) and irradiation time (0.5-2.5 h) increased.
Objectives : Oryeong-san was composed of Alismatis Rhizoma, Atractylodis Rhizoma Alba, Poria Sclerotium, Polyporus, Cinnamomi Cortex, and known to have hundreds of chemical compounds. The aim of this study was to screen chemical compounds constituting Oryeong-san with the drug-likeness and oral bioavailability from the analysis of their physicochemical properties. Methods : A list of chemical compounds of Oryeong-san was obtained from TM-MC(database of medicinal materials and chemical compounds in Northeast Asian traditional medicine). To remove redundant compounds, the SMILES (Simplified Molecular Input Line Entry System) strings of each compound were identified. All of the physicochemical properties for the compounds were calculated using the DruLiTo(Drug Likeness Tool). Drug-likeness was estimated by QED(Quantitative Estimate of Druglikeness) and OB(Oral bioavailability) was checked based on the Veber's rules. Results : A total of 475 compounds were obtained by eliminating duplication among 544 compounds of 5 medicinal materials. Analysis of the physicochemical properties revealed that the most common values were MW(molecular weight) 200~300 g/mol, ALOGP(octanol-water partition coefficient) 1~2, HBA(number of hydrogen bond acceptors) 0~1, HBD(number of hydrogen bond donors) 0, PSA(polar surface area) 0~50 angstrom, ROTB(number of rotatable bonds) 1, AROM(number of aromatic rings) 0, and ALERT(number of structural alerts) 1. QED had 93% of the values between 0.2 and 0.7, and OB had 90% of the value of TRUE. Conclusions : We in this paper screened the candidate active compounds of Oryeong-san using the QED and Veber's rules. In the future, we will use the screening results to analyze the mechanism of Oryeong-san based on systems pharmacology.
Jonathan Emanuel Valerio-Hernandez;Agustin Ruiz-Flores;Mohammad Ali Nilforooshan;Paulino Perez-Rodriguez
Animal Bioscience
/
v.36
no.7
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pp.1003-1009
/
2023
Objective: The objective was to compare (pedigree-based) best linear unbiased prediction (BLUP), genomic BLUP (GBLUP), and single-step GBLUP (ssGBLUP) methods for genomic evaluation of growth traits in a Mexican Braunvieh cattle population. Methods: Birth (BW), weaning (WW), and yearling weight (YW) data of a Mexican Braunvieh cattle population were analyzed with BLUP, GBLUP, and ssGBLUP methods. These methods are differentiated by the additive genetic relationship matrix included in the model and the animals under evaluation. The predictive ability of the model was evaluated using random partitions of the data in training and testing sets, consistently predicting about 20% of genotyped animals on all occasions. For each partition, the Pearson correlation coefficient between adjusted phenotypes for fixed effects and non-genetic random effects and the estimated breeding values (EBV) were computed. Results: The random contemporary group (CG) effect explained about 50%, 45%, and 35% of the phenotypic variance in BW, WW, and YW, respectively. For the three methods, the CG effect explained the highest proportion of the phenotypic variances (except for YW-GBLUP). The heritability estimate obtained with GBLUP was the lowest for BW, while the highest heritability was obtained with BLUP. For WW, the highest heritability estimate was obtained with BLUP, the estimates obtained with GBLUP and ssGBLUP were similar. For YW, the heritability estimates obtained with GBLUP and BLUP were similar, and the lowest heritability was obtained with ssGBLUP. Pearson correlation coefficients between adjusted phenotypes for non-genetic effects and EBVs were the highest for BLUP, followed by ssBLUP and GBLUP. Conclusion: The successful implementation of genetic evaluations that include genotyped and non-genotyped animals in our study indicate a promising method for use in genetic improvement programs of Braunvieh cattle. Our findings showed that simultaneous evaluation of genotyped and non-genotyped animals improved prediction accuracy for growth traits even with a limited number of genotyped animals.
Research trends in the measurement of foliar uptake of pesticides and the recently proposed action mechanism of the surfactant-induced uptake of pesticides were reviewed with the related reports and studies. Major techniques used in those fields are bioassay, radiotracer techniques with leaves or cuticular membrane. Recently, a new method using Congo Red as a tracer was proposed. The limiting factor in the pesticides uptake into leaves is the waxy layer which consists of the epicuticular and cuticular wax. Physico-chemical parameters such as molar volume, water solubility and partition coefficient of pesticides have limited influences on the pesticide uptake into leaves. Polydisperse ethoxylated fatty alcohol surfactants are well known as the good activator for many pesticides. It is now generally agreed that uptake activation is not related to the intrinsic surface active properties of surfactants such as surface activity, solvent property, humectancy and critical micelle concentration. Recent studies using ESR-spectroscopy revealed that the surfactants have an unspecific plasticising effect on the molecular structure of the wax and cuticular matrix, leading to increased mobilities of pesticides. Penetration of surfactants into waxy layer altered the pesticide mobility in wax and the partition coefficient of pesticide, and then the pesticides penetration into leaves was enhanced temporally. The enhancing effect of surfactant could be significantly different depending on the carbon number of aliphatic moiety and the number of ethoxy group in polyoxyethylene chain of surfactants. It is suggested that the rate of penetration of surfactants should have a significant relationship with the rate of penetration of pesticides.
Freundlich isothermal adsorption parameters, applicable to such biofilter-model as process-lumping model(Lim's model), for sterilized granular activated carbon(GAC), sterilized compost and sterilized equal volume mixture of GAC and compost were obtained and were compared each other, assuming that adsorbents are enclosed by water layer, in order to construct robust process-lumping biofilter model effective for wide-range of hydrophilic volatile organic compounds(VOC). In this investigation 0.04, 0.08, 0.12, 0.16, 0.2, 0.4, 0.8 and 1.0ml of ethanol were added to three kinds of adsorbent-media and were placed at $30^{\circ}{\cdots}$ under the wet condition of the media, which was the same as biofilter operating condition, until the adsorption reached the condition of equilibrium before each adsorbed amount of ethanol was obtained. Then adsorption capacity parameters(K) and adsorption exponents of Freundlich adsorption isotherm equation, which simulates the adsorbed amount of ethanol equilibrated with the ethanol concentration of the condensed water in the pore of the media, were constructed for sterilized granular activated carbon(GAC), sterilized compost and sterilized equal volume mixture of GAC and compost as (0.7566 and $5.070{\times}10^{-7}mg-ethanol/mgmedia/(mg-ethanol/m^3)^{0.7566}$), (0.8827 and $1.000{\times}10^{-8}mg-ethanol/mgmedia/(mg-ethanol/m^3)^{0.8827}$) and (0.5688 and $5.243{\times}10^{-6}mg-ethanol/mgmedia/(mg-ethanol/m^3)^{0.5688}$), respectively. These Freundlich isothermal adsorption parameters were applicable to the adsorption characteristics of biofilter media enclosed with bio-layer. The order of magnitude of the ratio of ethanol-air/water partition coefficient and toluene-air/water partition coefficient was almost consistent to that of ethanol-adsorbed amounts in this experiment with compost and in the investigation of Delhomenie et al. on toluene-adsorption to wet compost.
A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO2, (nano-TiO2) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO2 to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO2 was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO2 removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO2 particles in a WWTP.
As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.
In the laboratory experiment, concentration and rate of runoff of 7 pesticides were measured under the simulated rainfall. Total runoff rate of metolachlor, alachlor, chlorothalonil, chlorpyrifos, EPN, phorate and captafol were 57.0, 14.2, 13.2, 7.9, 7.2, 7.1 and 2.8%, respectively, and the average runoff concentrations were 940, 399, 55, 7.0, 9.3, 151 and 7.0 ppb, respectively. Significant relationship was observed between the runoff rate and water solubility in the laboratory experiment(r=0.923). Even though not very high, relatively significant results were obtained in other experimental conditions. Based on the results, runoff rate prediction$[Y=0.2812{\times}10exp(0.261logWS-0.366)+0.3594{\times}10exp(-0.545logKoc+1.747)+0.3594{\times}10exp(-0.362log\;Kow+1.105]$ and conversion equations were calculated to investigate the possibility of estimating runoff rate in the field by natural rain. Calculated runoff rate by conversion equation was similar to experimental result with captafol in the field while 6 times higher result was obtained by the prediction equation. Therefore, those prediction and conversion equations derived from the laboratory experiment data and physicochemical properties of the pesticides could be used for the prediction of field runoff rate of pesticides by natural rainfall.
Ha, Rim;Nam, Gibeom;Park, Sanghyun;Kang, Taegu;Shin, Hyunjoo;Kim, Kyunghyun;Rhew, Doughee;Lee, Hyuk
Korean Journal of Remote Sensing
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v.33
no.2
/
pp.111-123
/
2017
The phycocyanin pigment (PC) is a marker for cyanobacterial presence in eutrophic inland water. Accurate estimation of low PC concentration in turbid inland water is challenging due to the optical complexity and criticalforissuing an early warning of potentialrisks of cyanobacterial bloom to the public. To monitor cyanobacterial bloom in eutrophic inland waters, an approach is proposed to partition non-water absorption coefficient from measured reflectance and to retrieve absorption coefficient of PC with the aim of improving the accuracy in remotely estimated PC, in particular for low concentrations. The proposed inversion model retrieves absorption spectra of PC ($a_{pc}({\lambda})$) with $R^2{\geq}0.8$ for $a_{pc}(620)$. The algorithm achieved more accurate Chl-a and PC estimation with $0.71{\leq}R^2{\leq}0.85$, relative root mean square error (rRMSE) ${\leq}39.4%$ and mean relative error(RE) ${\leq}78.0%$ than the widely used semi-empirical algorithm for the same dataset. In particular, low PC ($PC{\leq}50mg/m^3$) and low PC: Chl-a ratio values of for all datasets used in this study were well predicted by the proposed algorithm.
Journal of Korean Society of Environmental Engineers
/
v.32
no.8
/
pp.747-753
/
2010
This study was performed to investigate the removal characteristics of volatile organic compounds (VOCs) in the gasphase biofilters, and to propose a stoichiometric analysis approach to characterize biological reaction through carbon mass balance. The VOCs studied were toluene, styrene, methyl ethyl ketone (MEK), and methyl isobutyl ketone (MIBK) as a single substrate for each biofilter. The critical loading rate was determined to be $46.9\;g/m^3{\cdot}hr$, $25.8\;g/m^3{\cdot}hr$, $96.3\;g/m^3{\cdot}hr$, and $66.5\;g/m^3{\cdot}hr$ for toluene, styrene, MEK, and MIBK, respectively. The obtained results indicated that the critical loading rate was well correlated the octanol-water partition coefficient. In the analysis of carbon mass balance, carbon recovery to $CO_2$ became relatively lower as substrate loadings increased, but higher for carbon recovery to biomass. Stoichiometric analysis revealed that biomass yield increased as substrate loadings increased, and its coefficient (g biomass/g substrate) varied from 0.31 to 0.57 for toluene, 0.29 to 0.57 for styrene, 0.08 to 0.56 for MEK, and 0.14 to 0.53 for MIBK.
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