| 1. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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| 2. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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| 3. |
- Gathercole, L. L., et al.
(author)
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AKR1D1 knockout mice develop a sex-dependent metabolic phenotype
- 2022
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In: Journal of Endocrinology. - : Bioscientifica. - 0022-0795 .- 1479-6805. ; 253:3, s. 97-113
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Journal article (peer-reviewed)abstract
- Steroid 5 beta-reductase (AKR1D1) plays important role in hepatic bile acid synthesis and glucocorticoid clearance. Bile acids and glucocorticoids are potent metabolic regulators, but whether AKR1D1 controls metabolic phenotype in vivo is unknown. Akr1d1(-/-) mice were generated on a C57BL/6 background. Liquid chromatography/mass spectrometry, metabolomic and transcriptomic approaches were used to determine effects on glucocorticoid and bile add homeostasis. Metabolic phenotypes including body weight and composition, lipid homeostasis, glucose tolerance and insulin tolerance were evaluated. Molecular changes were assessed by RNA-Seq and Western blotting. Male Akr1d1(-/-) mice were challenged with a high fat diet (60% kcal from fat) for 20 weeks. Akr1d1(-/-) mice had a sex-specific metabolic phenotype. At 30 weeks of age, male, but not female, Akr1d1(-/-) mice were more insulin tolerant and had reduced lipid accumulation in the liver and adipose tissue yet had hypertriglyceridemia and increased intramuscular triacylglycerol. This phenotype was associated with sexually dimorphic changes in bile acid metabolism and composition but without overt effects on circulating glucocorticoid levels or glucocorticoid-regulated gene expression in the liver. Male Akr1d1(-/-) mice were not protected against diet-induced obesity and insulin resistance. In conclusion, this study shows that AKR1D1 controls bile acid homeostasis in vivo and that altering its activity can affect insulin tolerance and lipid homeostasis in a sex-dependent manner.
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| 4. |
- Lucien, Fabrice, et al.
(author)
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MIBlood-EV: Minimal information to enhance the quality and reproducibility of blood extracellular vesicle research
- 2023
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In: Journal of Extracellular Vesicles. - 2001-3078. ; 12:12
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Journal article (peer-reviewed)abstract
- Blood is the most commonly used body fluid for extracellular vesicle (EV) research. The composition of a blood sample and its derivatives (i.e., plasma and serum) are not only donor-dependent but also influenced by collection and preparation protocols. Since there are hundreds of pre-analytical protocols and over forty variables, the development of standard operating procedures for EV research is very challenging. To improve the reproducibility of blood EV research, the International Society for Extracellular Vesicles (ISEV) Blood EV Task Force proposes standardized reporting of (i) the applied blood collection and preparation protocol and (ii) the quality of the prepared plasma and serum samples. Gathering detailed information will provide insight into the performance of the protocols and more effectively identify potential confounders in the prepared plasma and serum samples. To collect this information, the ISEV Blood EV Task Force created the Minimal Information for Blood EV research (MIBlood-EV), a tool to record and report information about pre-analytical protocols used for plasma and serum preparation as well as assays used to assess the quality of these preparations. This tool does not require modifications of established local pre-analytical protocols and can be easily implemented to enhance existing databases thereby enabling evidence-based optimization of pre-analytical protocols through meta-analysis. Taken together, insight into the quality of prepared plasma and serum samples will (i) improve the quality of biobanks for EV research, (ii) guide the exchange of plasma and serum samples between biobanks and laboratories, (iii) facilitate inter-laboratory comparative EV studies, and (iv) improve the peer review process.
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| 5. |
- Pink, Demi L., et al.
(author)
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Interplay of lipid and surfactant : Impact on nanoparticle structure
- 2021
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In: Journal of Colloid and Interface Science. - : Elsevier BV. - 0021-9797. ; 597, s. 278-288
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Journal article (peer-reviewed)abstract
- Liquid lipid nanoparticles (LLN) are oil-in-water nanoemulsions of great interest in the delivery of hydrophobic drug molecules. They consist of a surfactant shell and a liquid lipid core. The small size of LLNs makes them difficult to study, yet a detailed understanding of their internal structure is vital in developing stable drug delivery vehicles (DDVs). Here, we implement machine learning techniques alongside small angle neutron scattering experiments and molecular dynamics simulations to provide critical insight into the conformations and distributions of the lipid and surfactant throughout the LLN. We simulate the assembly of a single LLN composed of the lipid, triolein (GTO), and the surfactant, Brij O10. Our work shows that the addition of surfactant is pivotal in the formation of a disordered lipid core; the even coverage of Brij O10 across the LLN shields the GTO from water and so the lipids adopt conformations that reduce crystallisation. We demonstrate the superior ability of unsupervised artificial neural networks in characterising the internal structure of DDVs, when compared to more conventional geometric methods. We have identified, clustered, classified and averaged the dominant conformations of lipid and surfactant molecules within the LLN, providing a multi-scale picture of the internal structure of LLNs.
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| 6. |
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