Welcome to MitoTOX, your ultimate resource for managing mitochondrial toxicity-related small molecules and their mitochondrial targets!
Our comprehensive database is meticulously curated from a wide array of trusted sources, such as electronic databases, scientific journals, and textbooks, ensuring accuracy and reliability. Stay ahead of the latest findings as we continuously update the content of the MitoTox database to offer you the most up-to-date information available. Our user-friendly interface allows for effortless searches, and each entry comes with convenient links to the relevant references and other databases, enabling you to delve even deeper into the world of mitochondrial toxicity research.
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https://doi.org/10.1186/s12859-021-04285-3Mitochondria are organelles that undergo frequent changes in morphology through processes like fission, fusion, and mitophagy to adapt to varying energy requirements. Consequently, understanding mitochondrial morphology is essential for evaluating cellular metabolism. Imaging-based analysis is commonly applied but relies on the use of fluorescent dyes, which may cause permanent damage to cells. Additionally, long-term observation may be hindered by signal decay and photobleaching issues. Therefore, our lab has developed label-free deep learning methods for generating mitochondrial images from bright-field images with high accuracy.
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https://doi.org/10.1117/12.2591089This mitochondria-predicting model was also applied to enhance the performance of other label-free models, including the cell cycle predictor. The improved performance resulting from the inclusion of predicted mitochondrial images as an input highlights the significance and potential of incorporating mitochondrial morphology into label-free deep-learning imaging techniques.
https://doi.org/10.1109/BIBE55377.2022.00050In addition to developing a model for predicting mitochondrial fluorescence images, our lab has summarized and compared various post-processing tools for mitochondrial analysis in the previous review article, which aims to assist in the selection of appropriate methods for analyzing mitochondrial morphology.
https://doi.org/10.3389/fphy.2022.855775Our passionate team is dedicated to unraveling the intricate metabolic networks that govern the behavior of organisms. We developed a powerful, sophisticated tool, pipeGEM, that integrates omics data with genome-scale metabolic models (GEMs). This Python package combines well-known algorithms, such as FASTCORE, mCADRE, and tINIT, to integrate omics data with GEMs. Through this integration, we aim to uncover novel insights into cellular metabolism, shedding light on the underlying mechanisms that govern cellular function. This research has immense potential for diverse applications, ranging from understanding diseases at the molecular level to optimizing biotechnological processes. Focusing on precision medicine and the development of targeted therapies, our work paves the way for innovative strategies in drug target discovery and personalized treatment approaches.
In addition to GEMs, we developed ordinary differential equation (ODE) models to investigate mitochondrial pathways. Previous research simulated the signal propagation to the nucleus following mitochondrial damage in yeast using a Boolean model. The study discovered bistable retrograde signaling with localized steady states, which has potential for aiding drug development targeting yeast and fungi.
https://doi.org/10.1016/j.isci.2022.105502Photobiomodulation (PBM) involves the application of low-energy light, specifically red or near-infrared light, for the purpose of promoting positive effects on biological tissues. Previous research has pointed out the significance of mitochondria in the cellular effects induced by PBM, and our lab aims to investigate the interaction between light and mitochondria.
In previous research, we investigated the 3-day effects of an 810 nm LED on IMR-32 human neuroblastoma and identified two distinct mechanisms of action, which were observed using two power densities that were slightly different: 1.40 mW/cm2 mainly promotes cell division, while 1.95 mW/cm2 mostly enhances mitochondrial functions. Our study reveals the intricate nature of the PBM dose-dependent mechanism and provides evidence for the potential therapeutic application of PBM in addressing toxicity associated with mitochondria.
https://doi.org/10.1117/12.2646682https://doi.org/10.1109/JSTQE.2023.3240480In addition to studying the effects of PBM, we developed an ordinary differential equation (ODE) model to examine the hypothesis that the initiation of PBM effects is associated with the removal of nitric oxide. Our computational analysis indicates that the utilization of green and blue light strongly supports the hypothesis; however, there may be other pathways that account to red and near-infrared light.
https://doi.org/10.1109/BIBE55377.2022.00048Our team is currently developing a PBM-based method to enhance the efficiency and quality of cardiomyocyte differentiation, a process involving mitochondrial and metabolic transitions. (unpublished data)
