• 제목/요약/키워드: Toxicity prediction

검색결과 84건 처리시간 0.028초

ROLE OF COMPUTER SIMULATION MODELING IN PESTICIDE ENVIRONMENTAL RISK ASSESSMENT

  • Wauchope, R.Don;Linders, Jan B.H.J.
    • 한국환경독성학회:학술대회논문집
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    • 한국환경독성학회 2003년도 추계국제학술대회
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    • pp.91-93
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    • 2003
  • It has been estimated that the equivalent of approximately $US 50 billion has been spent on research on the behavior and fate of pesticides in the environment since Rachel Carson published “Silent Spring” in 1962. Much of the resulting knowledge has been summarized explicitly in computer algorithms in a variety of empirical, deterministic, and probabilistic simulation models. These models describe and predict the transport, degradation and resultant concentrations of pesticides in various compartments of the environment during and after application. In many cases the known errors of model predictions are large. For this reason they are typically designed to be “conservative”, i.e., err on the side of over-prediction of concentrations in order to err on the side of safety. These predictions are then compared with toxicity data, from tests of the pesticide on a series of standard representative biota, including terrestrial and aquatic indicator species and higher animals (e.g., wildlife and humans). The models' predictions are good enough in some cases to provide screening of those compounds which are very unlikely to do harm, and to indicate those compounds which must be investigated further. If further investigation is indicated a more detailed (and therefore more complicated) model may be employed to give a better estimate, or field experiments may be required. A model may be used to explore “what if” questions leading to possible alternative pesticide usage patterns which give lower potential environmental concentrations and allowable exposures. We are currently at a maturing stage in this research where the knowledge base of pesticide behavior in the environmental is growing more slowly than in the past. However, innovative uses are being made of the explosion in available computer technology to use models to take ever more advantage of the knowledge we have. In this presentation, current developments in the state of the art as practiced in North America and Europe will be presented. Specifically, we will look at the efforts of the ‘Focus’ consortium in the European Union, and the ‘EMWG’ consortium in North America. These groups have been innovative in developing a process and mechanisms for discussion amongst academic, agriculture, industry and regulatory scientists, for consensus adoption of research advances into risk management methodology.

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Dendropanax morbifera and Rubus coreanus Miq. Extracts Inhibits the Formation of Uric Acid Crystal by Reducing Xanthine Oxidase Activity

  • Hurh, Joon;Simu, Shakina Yesmin;Han, Yaxi;Ahn, Jong-Chan;Yang, Deok-Chun
    • 한국자원식물학회:학술대회논문집
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    • 한국자원식물학회 2018년도 춘계학술발표회
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    • pp.95-95
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    • 2018
  • Uric acid is the end product of purine metabolism in human body, originating from hypoxanthine after enzyme catalysis by Xanthine oxidase (XOD). Hyperuricemia results as a result of either over-generation of uric acid or a reduction in its excretion. In silico modelling methods such as Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) prediction, Autodock 4.2.6 program were used to study the potential inhibitory compounds of XOD. Also we investigated the inhibition of XOD activity by using the extracts of Dendropanax morbifera and Rubus coreanus Miq spectrophotometrically. According to ADMET data, several compounds from D. morbifera and R. coreanus plants, were found to be more potent in inhibiting the XOD activity than allopurinol. XOD inhibitory activity is evaluated by quantifying the formation of uric acid by measuring the absorbance at 290 m ($A_{290}$).D. morbifera extract inhibited XOD activity at $250{\mu}g/ml$, however the extracts from R. coreanus has inhibited XOD activity at $25{\mu}g/ml$. The major compound of R. coreanus, ellagic acid significantly increased the inhibition rate from $9{\mu}g/ml$ and showed a 71% suppression rate at $15{\mu}g/ml$. Finally, these results suggested a potential inhibitory activities of the extracts from D. morbifera and R. coreanus Miq, but further research is needed to validate to ensure their safe usage as drug.

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Novel Biomarkers for Prediction of Response to Preoperative Systemic Therapies in Gastric Cancer

  • Cavaliere, Alessandro;Merz, Valeria;Casalino, Simona;Zecchetto, Camilla;Simionato, Francesca;Salt, Hayley Louise;Contarelli, Serena;Santoro, Raffaela;Melisi, Davide
    • Journal of Gastric Cancer
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    • 제19권4호
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    • pp.375-392
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    • 2019
  • Preoperative chemo- and radiotherapeutic strategies followed by surgery are currently a standard approach for treating locally advanced gastric and esophagogastric junction cancer in Western countries. However, in a large number of cases, the tumor is extremely resistant to these treatments and the patients are exposed to unnecessary toxicity and delayed surgical therapy. The current clinical trials evaluating the combination of preoperative systemic therapies with modern targeted and immunotherapeutic agents represent a unique opportunity for identifying predictive biomarkers of response to select patients that would benefit the most from these treatments. However, it is of utmost importance that these potential biomarkers are corroborated by extensive preclinical and translational research. The aim of this review article is to present the most promising biomarkers of response to classic chemotherapeutic, anti-HER2, antiangiogenic, and immunotherapeutic agents that can be potentially useful for personalized preoperative systemic therapies in gastric cancer patients.

Anti-Inflammatory Activity of Antimicrobial Peptide Periplanetasin-5 Derived from the Cockroach Periplaneta americana

  • Kim, In-Woo;Lee, Joon Ha;Seo, Minchul;Lee, Hwa Jeong;Baek, Minhee;Kim, Mi-Ae;Shin, Yong Pyo;Kim, Sung Hyun;Kim, Iksoo;Hwang, Jae Sam
    • Journal of Microbiology and Biotechnology
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    • 제30권9호
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    • pp.1282-1289
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    • 2020
  • Previously, we performed an in silico analysis of the Periplaneta americana transcriptome. Antimicrobial peptide candidates were selected using an in silico antimicrobial peptide prediction method. It was found that periplanetasin-5 had antimicrobial activity against yeast and gram-positive and gram-negative bacteria. In the present study, we demonstrated the anti-inflammatory activities of periplanetasin-5 in mouse macrophage Raw264.7 cells. No cytotoxicity was observed at 60 ㎍/ml periplanetasin-5, and treatment decreased nitric oxide production in Raw264.7 cells exposed to lipopolysaccharide (LPS). In addition, quantitative RT-PCR and enzyme-linked immunosorbent assay revealed that periplanetasin-5 reduced cytokine (tumor necrosis factor-α, interleukin-6) expression levels in the Raw264.7 cells. Periplanetasin-5 controlled inflammation by inhibiting phosphorylation of MAPKs, an inflammatory signaling element, and reducing the degradation of IκB. Through LAL assay, LPS toxicity was found to decrease in a periplanetasin-5 dose-dependent manner. Collectively, these data showed that periplanetasin-5 had anti-inflammatory activities, exemplified in LPS-exposed Raw264.7 cells. Thus, we have provided a potentially useful antibacterial peptide candidate with anti-inflammatory activities.

Molecular docking of bioactive compounds derived from Moringa oleifera with p53 protein in the apoptosis pathway of oral squamous cell carcinoma

  • Rath, Sonali;Jagadeb, Manaswini;Bhuyan, Ruchi
    • Genomics & Informatics
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    • 제19권4호
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    • pp.46.1-46.11
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    • 2021
  • Moringa oleifera is nowadays raising as the most preferred medicinal plant, as every part of the moringa plant has potential bioactive compounds which can be used as herbal medicines. Some bioactive compounds of M. oleifera possess potential anti-cancer properties which interact with the apoptosis protein p53 in cancer cell lines of oral squamous cell carcinoma. This research work focuses on the interaction among the selected bioactive compounds derived from M. oleifera with targeted apoptosis protein p53 from the apoptosis pathway to check whether the bioactive compound will induce apoptosis after the mutation in p53. To check the toxicity and drug-likeness of the selected bioactive compound derived from M. oleifera based on Lipinski's Rule of Five. Detailed analysis of the 3D structure of apoptosis protein p53. To analyze protein's active site by CASTp 3.0 server. Molecular docking and binding affinity were analyzed between protein p53 with selected bioactive compounds in order to find the most potential inhibitor against the target. This study shows the docking between the potential bioactive compounds with targeted apoptosis protein p53. Quercetin was the most potential bioactive compound whereas kaempferol shows poor affinity towards the targeted p53 protein in the apoptosis pathway. Thus, the objective of this research can provide an insight prediction towards M. oleifera derived bioactive compounds and target apoptosis protein p53 in the structural analysis for compound isolation and in-vivo experiments on the cancer cell line.

약물 정보 문서 임베딩을 이용한 딥러닝 기반 약물 간 상호작용 예측 (Prediction of Drug-Drug Interaction Based on Deep Learning Using Drug Information Document Embedding)

  • 정선우;유선용
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2022년도 춘계학술대회
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    • pp.276-278
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    • 2022
  • 모든 약물은 신체 내에서 특정한 작용을 하며, 많은 경우 합병증 또는 기존 약물치료 중 새롭게 발생하는 증상에 의해 약물이 혼용되는 경우가 발생한다. 이런 경우 신체 내에서 예상치 못한 상호작용이 발생할 수 있다. 따라서 약물 간 상호작용을 예측하는 것은 안전한 약물 사용을 위해 매우 중요한 과제이다. 본 연구에서는 다중 약물 사용 시 발생 가능한 약물 간 상호작용 예측을 위해 약물 정보 문서를 이용해 학습시키는 딥러닝 기반의 예측 모델을 제안한다. 약물 정보 문서는 DrugBank 데이터를 이용해 약물의 작용 기전, 독성, 표적 등 여러 속성을 결합해 생성되었으며, 두 약물 문서가 한 쌍으로 묶여 딥러닝 기반 예측 모델에 입력으로 사용되고 해당 모델은 두 약물 간 상호작용을 출력한다. 해당 연구는 임베딩 방법이나 데이터 전처리 방법 등 다양한 조건의 변화에 따른 실험 결과의 차이를 분석하여 차후 새로운 약물쌍 간 상호작용을 예측하는 데에 활용이 가능하다.

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In silico 기법을 이용한 신경독성 예측 (In Silico Approach for Predicting Neurotoxicity)

  • 이소연;유선용
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2022년도 춘계학술대회
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    • pp.270-272
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    • 2022
  • 임상을 거친 약물이 시중에 유통되지 못하는 요인 중 하나는 안전성이다. 약물 부작용으로 인해 발생하는 안전성 문제의 주된 원인인 신경독성의 경우, 사전에 약물이나 화합물에 대한 위험 평가가 필요하다. 현재 약물의 안전성 검사를 위한 실험들은 동물 실험을 기반으로 하고 있으며, 이는 시간과 비용이 많이 든다는 단점을 갖는다. 따라서 위 문제를 해결하기 위해 in silico 실험을 통한 신경독성 예측모델을 제안하고자 한다. 본 연구에서는 의학 언어 시스템 (Unified Medical Language System)을 이용해 신경독성의 범주를 확대하고, 통합 데이터베이스를 기반으로 다양한 관련 화합물 데이터를 얻었다. 얻은 화합물들의 SMILES (Simplified Molecular Input Line Entry System)를 fingerprint로 변환시키고 이를 사용한 기계학습 기반의 모델을 만들었다. 모델은 최종적으로 신경독성의 유무를 예측한다. 해당 연구에서 제안된 실험은 in vivo 실험에 소요되는 시간 및 비용을 줄일 수 있다. 더 나아가 신약 개발 연구 기간을 단축하고 개발 중지 등의 부담을 줄일 수 있을 것으로 기대된다.

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임상시험에서 인공지능의 활용에 대한 분석 및 고찰: ClinicalTrials.gov 분석 (Trends in Artificial Intelligence Applications in Clinical Trials: An analysis of ClinicalTrials.gov)

  • 고정민;이지연;송윤경;김재현
    • 한국임상약학회지
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    • 제34권2호
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    • pp.134-139
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    • 2024
  • Background: Increasing numbers of studies and research about artificial intelligence (AI) and machine learning (ML) have led to their application in clinical trials. The purpose of this study is to analyze computer-based new technologies (AI/ML) applied on clinical trials registered on ClinicalTrials.gov to elucidate current usage of these technologies. Methods: As of March 1st, 2023, protocols listed on ClinicalTrials.gov that claimed to use AI/ML and included at least one of the following interventions-Drug, Biological, Dietary Supplement, or Combination Product-were selected. The selected protocols were classified according to their context of use: 1) drug discovery; 2) toxicity prediction; 3) enrichment; 4) risk stratification/management; 5) dose selection/optimization; 6) adherence; 7) synthetic control; 8) endpoint assessment; 9) postmarketing surveillance; and 10) drug selection. Results: The applications of AI/ML were explored in 131 clinical trial protocols. The areas where AI/ML was most frequently utilized in clinical trials included endpoint assessment (n=80), followed by dose selection/optimization (n=15), risk stratification/management (n=13), drug discovery (n=4), adherence (n=4), drug selection (n=1) and enrichment (n=1). Conclusion: The most frequent application of AI/ML in clinical trials is in the fields of endpoint assessment, where the utilization is primarily focuses on the diagnosis of disease by imaging or video analyses. The number of clinical trials using artificial intelligence will increase as the technology continues to develop rapidly, making it necessary for regulatory associates to establish proper regulations for these clinical trials.

Manganese and Iron Interaction: a Mechanism of Manganese-Induced Parkinsonism

  • Zheng, Wei
    • 한국환경성돌연변이발암원학회:학술대회논문집
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    • 한국환경성돌연변이발암원학회 2003년도 추계학술대회
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    • pp.34-63
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    • 2003
  • Occupational and environmental exposure to manganese continue to represent a realistic public health problem in both developed and developing countries. Increased utility of MMT as a replacement for lead in gasoline creates a new source of environmental exposure to manganese. It is, therefore, imperative that further attention be directed at molecular neurotoxicology of manganese. A Need for a more complete understanding of manganese functions both in health and disease, and for a better defined role of manganese in iron metabolism is well substantiated. The in-depth studies in this area should provide novel information on the potential public health risk associated with manganese exposure. It will also explore novel mechanism(s) of manganese-induced neurotoxicity from the angle of Mn-Fe interaction at both systemic and cellular levels. More importantly, the result of these studies will offer clues to the etiology of IPD and its associated abnormal iron and energy metabolism. To achieve these goals, however, a number of outstanding questions remain to be resolved. First, one must understand what species of manganese in the biological matrices plays critical role in the induction of neurotoxicity, Mn(II) or Mn(III)? In our own studies with aconitase, Cpx-I, and Cpx-II, manganese was added to the buffers as the divalent salt, i.e., $MnCl_2$. While it is quite reasonable to suggest that the effect on aconitase and/or Cpx-I activites was associated with the divalent species of manganese, the experimental design does not preclude the possibility that a manganese species of higher oxidation state, such as Mn(III), is required for the induction of these effects. The ionic radius of Mn(III) is 65 ppm, which is similar to the ionic size to Fe(III) (65 ppm at the high spin state) in aconitase (Nieboer and Fletcher, 1996; Sneed et al., 1953). Thus it is plausible that the higher oxidation state of manganese optimally fits into the geometric space of aconitase, serving as the active species in this enzymatic reaction. In the current literature, most of the studies on manganese toxicity have used Mn(II) as $MnCl_2$ rather than Mn(III). The obvious advantage of Mn(II) is its good water solubility, which allows effortless preparation in either in vivo or in vitro investigation, whereas almost all of the Mn(III) salt products on the comparison between two valent manganese species nearly infeasible. Thus a more intimate collaboration with physiochemists to develop a better way to study Mn(III) species in biological matrices is pressingly needed. Second, In spite of the special affinity of manganese for mitochondria and its similar chemical properties to iron, there is a sound reason to postulate that manganese may act as an iron surrogate in certain iron-requiring enzymes. It is, therefore, imperative to design the physiochemical studies to determine whether manganese can indeed exchange with iron in proteins, and to understand how manganese interacts with tertiary structure of proteins. The studies on binding properties (such as affinity constant, dissociation parameter, etc.) of manganese and iron to key enzymes associated with iron and energy regulation would add additional information to our knowledge of Mn-Fe neurotoxicity. Third, manganese exposure, either in vivo or in vitro, promotes cellular overload of iron. It is still unclear, however, how exactly manganese interacts with cellular iron regulatory processes and what is the mechanism underlying this cellular iron overload. As discussed above, the binding of IRP-I to TfR mRNA leads to the expression of TfR, thereby increasing cellular iron uptake. The sequence encoding TfR mRNA, in particular IRE fragments, has been well-documented in literature. It is therefore possible to use molecular technique to elaborate whether manganese cytotoxicity influences the mRNA expression of iron regulatory proteins and how manganese exposure alters the binding activity of IPRs to TfR mRNA. Finally, the current manganese investigation has largely focused on the issues ranging from disposition/toxicity study to the characterization of clinical symptoms. Much less has been done regarding the risk assessment of environmenta/occupational exposure. One of the unsolved, pressing puzzles is the lack of reliable biomarker(s) for manganese-induced neurologic lesions in long-term, low-level exposure situation. Lack of such a diagnostic means renders it impossible to assess the human health risk and long-term social impact associated with potentially elevated manganese in environment. The biochemical interaction between manganese and iron, particularly the ensuing subtle changes of certain relevant proteins, provides the opportunity to identify and develop such a specific biomarker for manganese-induced neuronal damage. By learning the molecular mechanism of cytotoxicity, one will be able to find a better way for prediction and treatment of manganese-initiated neurodegenerative diseases.

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유해폐기물 생애 전주기 흐름 기반 정보 관리 전략 (An Information Management Strategy Over Entire Life Cycles of Hazardous Waste Streams)

  • 이상훈;김정은
    • 청정기술
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    • 제26권3호
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    • pp.228-236
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    • 2020
  • 우리나라는 제조업 중심의 경제구조상 각종 유해폐기물이 발생하고 있으나 매립후보지가 적고 소각처리의 경우 미세먼지의 발생에 대한 우려가 커서 전통적인 폐기물 처리가 쉽지 않다. 더구나 최근에는 개발도상국의 유해폐기물 수입규제, 배달문화의 보편화와 보건위기사태까지 겹쳐 폐기물 수거 및 적체 문제가 심화되고 있다. 본 연구에서는 특히 최근 폐기물 국제 규제 관련 추세에 맞춘 국내 폐기물 정보관리 전략을 제시하려 하였다. 그 내용은 (1) 국내 유해폐기물 분류 코드와 바젤협약 등 국제적 코드와의 정합성을 제고하려는 노력을 지속해야 하며 (2) 폐전자제품내 희토류 등 저함량 성분의 혼합 유해성을 고려해야 하고 (3) 유해폐기물 전주기 위해성을 기반으로 하는 관리가 수행되어야 한다. 또한 (4) 올바로시스템, 화학물질배출·이동량 정보공개시스템 및 폐기물 수출입 자료 등을 서로 연동하여 폐기물 상세 흐름 정보를 구축하고 (5) 센서와 지리정보 시스템 등을 활용하여 폐기물 흐름의 감시와 불법오염지역의 예측이 필요하다. 마지막으로 (6) 청정기술과 전과정평가 등으로 처리/재활용의 최적대안을 선정/수행하는 것이 바람직하다.