• Korean Journal of Hydrosciences
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• v.2
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• pp.61-68
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• 1991

This study assessed the contribution of heavy metals to total toxicity as well as the presence other toxic compounds before and after adding the chemical P to concurrently conducted bioassay tests of Daphnia magna and P. Phosphoreum. The following conclusions were drawn from this study : With excessive EDTA dosage, a toxicity reduction in Microtox would occur due to a metal-comples being formed. Microtox was far less sensitive than D. magna to heavy metal toxicity, but extended exposure time and reagent could increase the sensitivity.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.11a
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• pp.11-15
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• 2007

Metabolomics is an emerging technology which makes it possible to evaluate change of biological system in response to the physiological, environmental alterations. It has advantages in the simplicity and sensitivity to analyze metabolites since the researcher can use cutting edge instrument, such as mass spectrometry and simple sample preparation method compared to genomics or proteomics. Nowadays this technology has been tried in pharmaceutical area to investigate toxicity and efficacy of drug candidates and drugs in preclinical test. The metabolomic applications on the pharmaceutics for early prediction on toxicity and efficacy are described in this presentation. The multivariate analysis to get metabolic fingerprinting and its relations with the physiological changes are investigated with several drugs. Feasibility of metabolomic application for pharmaceutical area would be suggested from those researches.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

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.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2001.11a
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• pp.91-91
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• 2001

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2005.05a
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• pp.166-166
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• 2005

• Bulletin of the Korean Chemical Society
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• v.35 no.12
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• pp.3637-3641
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• 2014

In this study, we analyzed the toxicity of mixtures of dimethylformamide (DMF) and methyl ethyl ketone (MEK) or DMF and toluene (TOL) and predicted their toxicity using quantitative structure-activity relationships (QSAR). A QSAR model for single substances and mixtures was analyzed using multiple linear regression (MLR) by taking into account the statistical parameters between the observed and predicted $EC_{50}$. After preprocessing, the best subsets of descriptors in the learning methods were determined using a 5-fold cross-validation method. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP), flash point (FP), low explosion limit (LEL), and octanol/water partition coefficient (Pow) were observed between the single substances and the mixtures. The $EC_{50}$ of the mixture of DMF and TOL was significantly lower than that of DMF. The mixture toxicity was directly related to the mixing ratio of TOL and MEK (MLR $EC_{50}$ equation = $1.76997-1.12249{\times}TOL+1.21045{\times}MEK$), as well as to SG, VP, and LEL (MLR equation $EC_{50}=15.44388-19.84549{\times}SG+0.05091{\times}VP+1.85846{\times}LEL$). These results show that QSAR-based models can be used to quantitatively predict the toxicity of mixtures used in manufacturing industries.

• Environmental Mutagens and Carcinogens
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• v.21 no.2
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• pp.113-117
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• 2001

The screening of various molecular descriptors for predicting carcinogenic, mutagenic and teratogenic activities of chlorinated aliphatic compounds as drinking water disinfection byproducts (DBPs) has been investigated for the application of quantitative structure-activity relationships (QSAR). The present work embodies the study of relationship between molecular descriptors and toxicity parameters of the genotoxicity endpoints for the screening of relevant molecular descriptors. The toxicity Indices for 29 compounds constituting the testing set were computed by the PASS program and active values were chosen. We investigate feasibility of screening descriptors and of their applications among different genotoxic endpoints. The correlation to teratogenicity of all 29 compounds was significantly improved when the same analysis was done with 20 alkanes only without alkene compounds. The HOMO (highest occupied molecular orbital) energy and number of Cl parameters were dominantly contributed.

• Environmental Mutagens and Carcinogens
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• v.20 no.1
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• pp.21-25
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• 2000

Recently there is increasing interest in the use of structure activity relationships for predicting the biological activity of chemicals. The reasons for the interest include the decrease cost and time per chemical as compared with animal or cell system for identifying toxicological effects of chemicals and the reduction in the use of animals for toxicological testing. This study is to test the validity of the mutagenicity data generated from QSAR (Quantitative Structure Activity Relationship) program. Thirty chemicals, which had been evaluated by Ames test during 1997-1999, were assessed with TOPKAT QSAR mutagenicity prediction module. Among 30chemicals experimented, 28 were negative and 2 were positive for Ames test. On the contrary, 23 chemicals showed the high confidence level indicating high prediction rate in mutagenicity evaluation, and 7 chemicals showed the lsow to moderate confidence level indicating low prediction in mutagenicity evaluation. Overall mutagenicity prediction rate was 77% (23/30). The prediction rates for non-mutagenic chemicals were 79% (22/28) and mutagenic chemicals were 50% (1/2). QSAR could be a useful tool in providing toxicological data for newly introduced chemicals or in furnishing data for MSDS or in determining the dose in toxicity testing for chemicals with no known toxicological data.

• Journal of the Korean Society of Safety
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• v.38 no.6
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• pp.60-71
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• 2023

The purpose of this study is to propose a quantitative toxicity endpoint distance suitable for the initial response of firefighters by comparing and analyzing the commonly applied toxic level of concern (T-LOC), specifically emergency response planning guidelines (ERPG), acute exposure guideline levels (AEGL), and immediately dangerous to life or health (IDLH). This is to protect the fire brigade, which responds to toxic chemical accidents first during the golden time. Using areal locations of hazardous atmospheres, a damage prediction program, the amount of leakage for both acidic and basic substances, along with the endpoint distance, were analyzed for alternative accident and worst-case accident scenarios. The results showed that the toxicity endpoint distance, serving as a compromise between Level-3 and Level-2 of T-LOC, was longer than ERPG-3 and shorter than ERPG-2 with IDLH, while its values were analyzed in the order of ERPG-2, AEGL-2, IDLH, AEGL-3, and ERPG-3. It is suggested that the application of IDLH in an emergency (red card) and ERPG-2 endpoint distance in a non-emergency (non-red card) can be utilized for the initial response of the fire brigade.

• Journal of Korean Society on Water Environment
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• v.29 no.2
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• pp.176-183
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• 2013

The variation of the stable region of arsenic compounds in aqueous environment with temperature has been investigated by constructing the Pourbaix diagram of arsenic at different temperatures. The standard potential corresponding to the boundary between arsenic compounds with different charge valence was estimated to be decreased with temperature, which means the stability of arsenic compound with +5 charge valence increases. The distribution diagram of the most highly oxidized arsenic compound showed that arsenic acid is formed at higher pH and arsenate is generated at lower pH as temperature rises. The aquatic toxicity due to arsenic compounds was considered to be decreased with temperature in the neutral pH condition based on the $LD_T$ value defined in this study.