| 1. |
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- 2019
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Journal article (peer-reviewed)
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| 2. |
- Klionsky, Daniel J., et al.
(author)
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Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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In: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
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Research review (peer-reviewed)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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| 3. |
- Anderson, Cynthia M., et al.
(author)
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Permanent Genetic Resources added to Molecular Ecology Resources Database 1 December 2009-31 January 2010
- 2010
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In: Molecular Ecology Resources. - : Wiley. - 1755-098X .- 1755-0998. ; 10:3, s. 576-579
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Journal article (peer-reviewed)abstract
- This article documents the addition of 220 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Allanblackia floribunda, Amblyraja radiata, Bactrocera cucurbitae, Brachycaudus helichrysi, Calopogonium mucunoides, Dissodactylus primitivus, Elodea canadensis, Ephydatia fluviatilis, Galapaganus howdenae howdenae, Hoplostethus atlanticus, Ischnura elegans, Larimichthys polyactis, Opheodrys vernalis, Pelteobagrus fulvidraco, Phragmidium violaceum, Pistacia vera, and Thunnus thynnus. These loci were cross-tested on the following species: Allanblackia gabonensis, Allanblackia stanerana, Neoceratitis cyanescens, Dacus ciliatus, Dacus demmerezi, Bactrocera zonata, Ceratitis capitata, Ceratitis rosa, Ceratits catoirii, Dacus punctatifrons, Ephydatia mulleri, Spongilla lacustris, Geodia cydonium, Axinella sp., Ischnura graellsii, Ischnura ramburii, Ischnura pumilio, Pistacia integerrima and Pistacia terebinthus.
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| 4. |
- Grossmann, Igor, et al.
(author)
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Insights into the accuracy of social scientists' forecasts of societal change
- 2023
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In: Nature Human Behaviour. - : Springer Nature. - 2397-3374. ; 7, s. 484-501
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Journal article (peer-reviewed)abstract
- How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models.
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| 5. |
- Svensson, Ulrika S H, et al.
(author)
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Artemisinin induces omeprazole metabolism in human beings
- 1998
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In: Clinical Pharmacology and Therapeutics. - 0009-9236 .- 1532-6535. ; 64, s. 160-
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Journal article (peer-reviewed)abstract
- Objective: This study investigated whether time-dependent artemisinin pharmacokinetics correlated to CYP3A4 or CYP2C19 activity in vivo. Methods: Artemisinin (two oral doses per day of 250 mg) was given to nine healthy Vietnamese subjects for 7 days (day 1 to day 7), Single 20 mg doses of omeprazole were given orally on day -7, day 1, and day 7, Single doses of artemisinin and omeprazole were given in combination on day 14 after a 6-day washout period. The pharmacokinetics of artemisinin, omeprazole, hydroxyomeprazole, and omeprazole sulfone were evaluated on days -7, 1, 7, and 14, On the same days urine was collected for the determination of 6 beta-hydroxycortisol and cortisol excretion. Results: Areas under plasma concentration-time curves (AUC) for artemisinin and omeprazole decreased on day 7 to 20% (95% confidence intervals, 13%, 28%) and 35% (25%, 46%), respectively, compared with values on day 1, AUC ratios for hydroxyomeprazole/omeprazole increased 2.2-fold (1,7, 2.7) on day 7 compared with values on day 1, Al values were normalized at day 14, There were no significant changes in the omeprazole sulfone/omeprazole ratio or in the 6 beta-hydroxycortisol/cortisol ratio between the study days. In one subject found to have poor CYP2C19 metabolization, the elimination of omeprazole increased after artemisinin exposure, with no change in the hydroxyomeprazole/omeprazole AUC ratio. Conclusion: Artemisinin did not alter CYP3A4 activity, whereas an increase in CYP2C19 activity was observed. The increased elimination of omeprazole in both poor and extensive CYP2C19 metabolizers suggests artemisinin induces both CYP2C19 and another enzyme.
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| 6. |
- Chen, H., et al.
(author)
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Unprecedented non-hysteretic superelasticity of [001]-oriented NiCoFeGa single crystals
- 2020
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In: Nature Materials. - : Nature Research. - 1476-1122 .- 1476-4660.
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Journal article (peer-reviewed)abstract
- Superelasticity associated with the martensitic transformation has found a broad range of engineering applications1,2. However, the intrinsic hysteresis3 and temperature sensitivity4 of the first-order phase transformation significantly hinder the usage of smart metallic components in many critical areas. Here, we report a large superelasticity up to 15.2% strain in [001]-oriented NiCoFeGa single crystals, exhibiting non-hysteretic mechanical responses, a small temperature dependence and high-energy-storage capability and cyclic stability over a wide temperature and composition range. In situ synchrotron X-ray diffraction measurements show that the superelasticity is correlated with a stress-induced continuous variation of lattice parameter accompanied by structural fluctuation. Neutron diffraction and electron microscopy observations reveal an unprecedented microstructure consisting of atomic-level entanglement of ordered and disordered crystal structures, which can be manipulated to tune the superelasticity. The discovery of the large elasticity related to the entangled structure paves the way for exploiting elastic strain engineering and development of related functional materials.
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| 7. |
- Cong, D. Y., et al.
(author)
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Neutron diffraction study on crystal structure and phase transformation in Ni-Mn-Ga ferromagnetic shape memory alloys
- 2007
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In: Powder Diffraction. - : Cambridge University Press (CUP). - 0885-7156 .- 1945-7413. ; 22:4, s. 307-311
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Journal article (peer-reviewed)abstract
- Crystal structure and phase transformation behaviors in two Ni-Mn-Ga ferromagnetic shape memory alloys (FSMAs) with compositions of Ni48Mn30Ga22 and Ni53Mn25Ga22 (at. %) as a function of temperature were investigated by in situ neutron diffraction experiments. Neutron diffraction technique proves to be highly efficient in characterizing structural transformation in Ni-Mn-Ga FSMAs, which consist of nearby elements in the periodic table. Our neutron results show that Ni48Mn30Ga22 has a cubic, L-21 Heusler structure from 373 to 293 K. Its crystal structure changes into a seven-layered orthorhombic martensitic structure when cooled to 243 K, and no further transformation is observed upon cooling to 19 K. Neutron diffraction results also show that Ni53Mn25Ga22 has a tetragonal 14/mmm martensitic structure from 20 to 403 K. A pre-transformation around room temperature is observed from an abrupt jump in unit-cell volume of Ni53Mn25Ga22, which corresponds with an endothermic peak detected in a heated DSC curve.
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| 8. |
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| 9. |
- Peng, Ru, 1960-, et al.
(author)
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Crystal structure and phase transformation in Ni53Mn 25Ga22 shape memory alloy from 20 K to 473 K
- 2005
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In: Applied Physics Letters. - : AIP Publishing. - 0003-6951 .- 1077-3118. ; 87:11
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Journal article (peer-reviewed)abstract
- The crystal structures, magnetic structures, and phase transformation of the off-stoichiometric Ni53 Mn25 Ga22 were studied by neutron powder diffraction at different temperatures. It is shown that Ni53 Mn25 Ga22 has a tetragonal I4/mmm structure from 20 K to 403 K. An abrupt jump in unit-cell volume around room temperature, corresponding to an endothermic peak in the differential scanning calorimetry curve, was observed. This indicates a pretransformation in the martensitic phase of Ni53 Mn25 Ga22, which is completely different from the phase transformation in the stoichiometric Ni2 MnGa. The sequence of structural transformation in Ni53 Mn25 Ga22 is closely related to its intrinsic temperature-dependent magnetic structure. © 2005 American Institute of Physics.
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| 10. |
- Petrov, Dmitry, et al.
(author)
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Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
- 2017
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In: Machine learning in medical imaging. MLMI (Workshop). - Cham : Springer International Publishing. ; 10541, s. 371-378
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Journal article (peer-reviewed)abstract
- As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability.
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