5 results on '"Bearon R"'
Search Results
2. Multiparametric MRI based assessment of kidney injury in a mouse model of ischemia reperfusion injury.
- Author
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Mukherjee S, Bhaduri S, Harwood R, Murray P, Wilm B, Bearon R, and Poptani H
- Subjects
- Animals, Mice, Male, Glomerular Filtration Rate, Mice, Inbred C57BL, Diffusion Magnetic Resonance Imaging methods, Reperfusion Injury diagnostic imaging, Reperfusion Injury pathology, Disease Models, Animal, Acute Kidney Injury diagnostic imaging, Acute Kidney Injury etiology, Acute Kidney Injury pathology, Kidney diagnostic imaging, Kidney pathology, Multiparametric Magnetic Resonance Imaging methods
- Abstract
Kidney diseases pose a global healthcare burden, with millions requiring renal replacement therapy. Ischemia/reperfusion injury (IRI) is a common pathology of acute kidney injury, causing hypoxia and subsequent inflammation-induced kidney damage. Accurate detection of acute kidney injury due to IRI is crucial for timely intervention. We used longitudinal, multi-parametric magnetic resonance imaging (MRI) employing arterial spin labelling (ASL), diffusion weighted imaging (DWI), and dynamic contrast enhanced (DCE)-MRI to assess IRI induced changes in both the injured and healthy contralateral kidney, in a unilateral IRI mouse model (n = 9). Multi-parametric MRI demonstrated significant differences in kidney volume (p = 0.001), blood flow (p = 0.002), filtration coefficient (p = 0.038), glomerular filtration rate (p = 0.005) and apparent diffusion coefficient (p = 0.048) between the injured kidney and contralateral kidney on day 1 post-IRI surgery. Identification of the injured kidney using principal component analysis including most of the imaging parameters demonstrated an area under the curve (AUC) of 0.97. These results point to the utility of multi-parametric MRI in early detection of IRI-induced kidney damage suggesting that the combination of various MRI parameters may be suitable for monitoring the extent of injury in this model., (© 2024. The Author(s).)
- Published
- 2024
- Full Text
- View/download PDF
3. General Framework to Quantitatively Predict Pharmacokinetic Induction Drug-Drug Interactions Using In Vitro Data.
- Author
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Grañana-Castillo S, Williams A, Pham T, Khoo S, Hodge D, Akpan A, Bearon R, and Siccardi M
- Subjects
- Humans, Drug Interactions, Rifampin, Carbamazepine pharmacology, Models, Biological, Cytochrome P-450 CYP3A metabolism, Cytochrome P-450 Enzyme System metabolism
- Abstract
Introduction: Metabolic inducers can expose people with polypharmacy to adverse health outcomes. A limited fraction of potential drug-drug interactions (DDIs) have been or can ethically be studied in clinical trials, leaving the vast majority unexplored. In the present study, an algorithm has been developed to predict the induction DDI magnitude, integrating data related to drug-metabolising enzymes., Methods: The area under the curve ratio (AUC
ratio ) resulting from the DDI with a victim drug in the presence and absence of an inducer (rifampicin, rifabutin, efavirenz, or carbamazepine) was predicted from various in vitro parameters and then correlated with the clinical AUCratio (N = 319). In vitro data including fraction unbound in plasma, substrate specificity and induction potential for cytochrome P450s, phase II enzymes and uptake, and efflux transporters were integrated. To represent the interaction potential, the in vitro metabolic metric (IVMM) was generated by combining the fraction of substrate metabolised by each hepatic enzyme of interest with the corresponding in vitro fold increase in enzyme activity (E) value for the inducer., Results: Two independent variables were deemed significant and included in the algorithm: IVMM and fraction unbound in plasma. The observed and predicted magnitudes of the DDIs were categorised accordingly: no induction, mild, moderate, and strong induction. DDIs were assumed to be well classified if the predictions were in the same category as the observations, or if the ratio between these two was < 1.5-fold. This algorithm correctly classified 70.5% of the DDIs., Conclusion: This research presents a rapid screening tool to identify the magnitude of potential DDIs utilising in vitro data which can be highly advantageous in early drug development., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)- Published
- 2023
- Full Text
- View/download PDF
4. Actin filaments form a size-dependent diffusion barrier around centrosomes.
- Author
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Cheng H, Kao YL, Chen T, Sharma L, Yang WT, Chuang YC, Huang SH, Lin HR, Huang YS, Kao CL, Yang LW, Bearon R, Cheng HC, Hsia KC, and Lin YC
- Subjects
- Actins metabolism, Centrosome metabolism, Actin Cytoskeleton metabolism, Tubulin metabolism, Microtubules metabolism
- Abstract
The centrosome, a non-membranous organelle, constrains various soluble molecules locally to execute its functions. As the centrosome is surrounded by various dense components, we hypothesized that it may be bordered by a putative diffusion barrier. After quantitatively measuring the trapping kinetics of soluble proteins of varying size at centrosomes by a chemically inducible diffusion trapping assay, we find that centrosomes are highly accessible to soluble molecules with a Stokes radius of less than 5.8 nm, whereas larger molecules rarely reach centrosomes, indicating the existence of a size-dependent diffusion barrier at centrosomes. The permeability of this barrier is tightly regulated by branched actin filaments outside of centrosomes and it decreases during anaphase when branched actin temporally increases. The actin-based diffusion barrier gates microtubule nucleation by interfering with γ-tubulin ring complex recruitment. We propose that actin filaments spatiotemporally constrain protein complexes at centrosomes in a size-dependent manner., (© 2022 The Authors. Published under the terms of the CC BY NC ND 4.0 license.)
- Published
- 2023
- Full Text
- View/download PDF
5. Evaluation of drug-drug interaction between rilpivirine and rifapentine using PBPK modelling.
- Author
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Grañana-Castillo S, Montanha MC, Bearon R, Khoo S, and Siccardi M
- Abstract
Tuberculosis remains the leading cause of death among people living with HIV. Rifapentine is increasingly used to treat active disease or prevent reactivation, in both cases given either as weekly or daily therapy. However, rifapentine is an inducer of CYP3A4, potentially interacting with antiretrovirals like rilpivirine. This in silico study investigates the drug-drug interaction (DDI) magnitude between daily oral rilpivirine 25 mg with either daily 600 mg or weekly 900 mg rifapentine. A physiologically based pharmacokinetic (PBPK) model was built in Simbiology (Matlab R2018a) to simulate the drug-drug interaction. The simulated PK parameters from the PBPK model were verified against reported clinical data for rilpivirine and rifapentine separately, daily rifapentine with midazolam, and weekly rifapentine with doravirine. The simulations of concomitant administration of rifapentine with rilpivirine at steady-state lead to a maximum decrease on AUC
0-24 and Ctrough by 83% and 92% on day 5 for the daily rifapentine regimen and 68% and 92% for the weekly regimen on day 3. In the weekly regimen, prior to the following dose, AUC0-24 and Ctrough were still reduced by 47% and 53%. In both simulations, the induction effect ceased 2 weeks after the interruption of rifapentine's treatment. A daily double dose of rilpivirine after initiating rifapentine 900 mg weekly was simulated but failed to compensate the drug-drug interaction. The drug-drug interaction model suggested a significant decrease on rilpivirine exposure which is unlikely to be corrected by dose increment, thus coadministration should be avoided., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Grañana-Castillo, Montanha, Bearon, Khoo and Siccardi.)- Published
- 2022
- Full Text
- View/download PDF
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