Drug-induced liver injury

Suh, Jeong Ill

doi:10.12701/yujm.2019.00297

Cited by 24 publications

(22 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Usually, the drug-induced hepatocyte injury mechanism is divided into three stages: initial hepatocyte injury (cell stress and mitochondrial inhibition), mitochondrial permeability transition, and hepatocyte death (apoptosis and necrosis) ( Russmann et al, 2009 ; Suh, 2020 ). Similarly, in this study, the mechanism of PF-induced hepatotoxicity had also been categorized into the following three stages: ROS accumulation, MMP repression, and hepatocyte apoptosis and steatosis.…”

Section: Discussionmentioning

confidence: 99%

Five Constituents Contributed to the Psoraleae Fructus-Induced Hepatotoxicity via Mitochondrial Dysfunction and Apoptosis

et al. 2021

View full text Add to dashboard Cite

Backgrounds: Psoraleae Fructus (PF)-induced hepatotoxicity has been reported in clinical and animal experiments. However, the hepatotoxic constituents and mechanisms underlying PF-induced toxicity have remained unclear. Therefore, this study explored the potentially toxic PF components and revealed their relative mechanisms.Methods: The hepatotoxicity of PF water (PFW) and ethanol (PFE) extracts was compared using Kunming mice. The different compositions between PFW and PFE, which were considered toxic compositions, were identified using the UHPLC-Q-Exactive MS method. Then, L02 and HepG2 cell lines were used to evaluate the toxicity of these compositions. Cell viability and apoptosis were determined through the Cell Counting Kit-8 (CCK-8) assay and flow cytometry, respectively. An automatic biochemical analyzer detected the aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP). Lastly, we used high-content screening (HCS) to determine the levels of reactive oxygen species (ROS), lipid, and mitochondrial membrane potential (MMP).Results: The ethanol extraction process aggravated the hepatotoxicity of PF, causing more severe injuries. The content of psoralen, isopsoralen, bavachin, psoralidin, bavachinin, neobavaisoflavone, and bakuchiol was higher in the PFE than PFW. Bavachin, psoralidin, bavachinin, neobavaisoflavone, and bakuchiol induced cell apoptosis and the AST, ALT, and ALP leakages. Furthermore, these five constituents increased intracellular lipid accumulation and ROS levels but decreased the MMP level.Conclusion: The ethanol extraction process could induce severe PF hepatotoxicity. Bavachin, psoralidin, bavachinin, neobavaisoflavone, and bakuchiol are the main hepatotoxic ingredients. This mechanism could be associated with oxidative stress and mitochondrial damage-mediated apoptosis. Taken together, this study provides a basis for the clinical application of PF that formulates and improves its herbal standards.

show abstract

Section: Discussionmentioning

confidence: 99%

Five Constituents Contributed to the Psoraleae Fructus-Induced Hepatotoxicity via Mitochondrial Dysfunction and Apoptosis

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Animal studies for predicting DILI concerns in the preclinical assessment are not reliable, as it provides a low correlation results in clinical trials and also in post-marketing treatment [ 11 , 12 ]. In vitro and in vivo experiments for detecting DILI of large number of substances are time-consuming and expensive.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets

Jaganathan

Tayara

Chong

2021

IJMS

View full text Add to dashboard Cite

Drug-induced liver toxicity is one of the significant safety challenges for the patient’s health and the pharmaceutical industry. It causes termination of drug candidates in clinical trials and also the retractions of approved drugs from the market. Thus, it is essential to identify hepatotoxic compounds in the initial stages of drug development process. The purpose of this study is to construct quantitative structure activity relationship models using machine learning algorithms and systematical feature selection methods for molecular descriptor sets. The models were built from a large and diverse set of 1253 drug compounds and were validated internally with 10-fold cross-validation. In this study, we applied a variety of feature selection techniques to extract the optimal subset of descriptors as modeling features to improve the prediction performance. Experimental results suggested that the support vector machine-based classifier had achieved a better classification accuracy with reduced molecular descriptors. The final optimal model provides an accuracy of 0.811, a sensitivity of 0.840, a specificity of 0.783 and Mathew’s correlation coefficient of 0.623 with an internal validation set. Furthermore, this model outperformed the prior studies while evaluated in both the internal and external test sets. The utilization of distinct optimal molecular descriptors as modeling features produce an in silico model with a superior performance.

show abstract

“…Drug-induced liver injury (DILI) is one of the most common etiologies of acute liver failure (ALF) in the United States. Patients may present with a range of clinical manifestations from an asymptomatic transaminase elevation to ALF [1][2][3]. Clinically, DILI has been described as the rise of alanine aminotransferase (ALT) or aspartate aminotransferase (AST) greater than five times the upper limit of normal (ULN), alkaline phosphatase (ALP) greater than two times the ULN, or bilirubin greater than two times the ULN with an associated rise of AST and ALT [4][5].…”

Section: Introductionmentioning

confidence: 99%