| 1. |
- Zhang, Y. S., et al.
(författare)
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Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors
- 2017
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 114:12, s. E2293-E2302
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Tidskriftsartikel (refereegranskat)abstract
- Organ-on-a-chip systems areminiaturizedmicrofluidic 3D human tissue and organ models designed to recapitulate the important biological and physiological parameters of their in vivo counterparts. They have recently emerged as a viable platform for personalized medicine and drug screening. These in vitro models, featuring biomimetic compositions, architectures, and functions, are expected to replace the conventional planar, static cell cultures and bridge the gap between the currently used preclinical animal models and the human body. Multiple organoid models may be further connected together through the microfluidics in a similar manner in which they are arranged in vivo, providing the capability to analyze multiorgan interactions. Although a wide variety of human organ-on-a-chip models have been created, there are limited efforts on the integration of multisensor systems. However, in situ continual measuring is critical in precise assessment of the microenvironment parameters and the dynamic responses of the organs to pharmaceutical compounds over extended periods of time. In addition, automated and noninvasive capability is strongly desired for long-term monitoring. Here, we report a fully integrated modular physical, biochemical, and optical sensing platform through a fluidics-routing breadboard, which operates organ-on-a-chip units in a continual, dynamic, and automated manner.We believe that this platform technology has paved a potential avenue to promote the performance of current organ-on-a-chip models in drug screening by integrating a multitude of real-time sensors to achieve automated in situ monitoring of biophysical and biochemical parameters.
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| 2. |
- Pagano, G., et al.
(författare)
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Fanconi anaemia proteins : Major roles in cell protection against oxidative damage
- 2003
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Ingår i: Bioessays. - : Wiley. - 0265-9247 .- 1521-1878. ; 25:6, s. 589-595
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Forskningsöversikt (refereegranskat)abstract
- Fanconi anaemia (FA) is a cancer-prone genetic disorder that is characterised by cytogenetic instability and redox abnormalities. Although rare subtypes of FA (B, D1 and D2) have been implicated in DNA repair through links with BRCA1 and BRCA2, such a role has yet to be demonstrated for gene products of the common subtypes. Instead, these products have been strongly implicated in xenobiotic metabolism and redox homeostasis through interactions of FANCC with cytochrome P-450 reductase and with glutathione S-transferase, and of FANCG with cytochrome P-450 2E1, as well as redox-dependent signalling through an interaction between FANCA and Akt kinase. We hypothesise that FA proteins act directly (via FANCC and FANCG) and indirectly (via FANCA, BRCA2 and FANCD2) with the machinery of cellular defence to modulate oxidative stress. The latter interactions may co-ordinate the link between the response to DNA damage and oxidative stress parameters (3, 6-12). © 2003 Wiley Periodicals, Inc.
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| 3. |
- Ostaszewski, Marek, et al.
(författare)
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COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
- 2021
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Ingår i: Molecular Systems Biology. - : John Wiley & Sons. - 1744-4292 .- 1744-4292. ; 17:10
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Tidskriftsartikel (refereegranskat)abstract
- We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
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