| 1. |
- Hellberg, Magnus, et al.
(författare)
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In situ scanning probe microscopy studies of morphology and growth kinetics in amyloid-peptide fibrillogenesis with custom designed tapping mode and pulsed force mode systems
- 2004
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Ingår i: Proceedings of 5th Nordic-Baltic Scanning Probe Microscopy Workshop. ; , s. 93-95
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Konferensbidrag (refereegranskat)abstract
- We have used a commercial Nanoscope II atomic force microscope (AFM) with a custom designedtapping mode (TM) system to in situ monitor amyloid β-peptide aggregation related to Alzheimer’sdisease (AD). The custom tapping mode setup was successfully used to image the real timeaggregation behaviour of the arctic mutation amyloid β-peptide, Aβ(1-40), in vitro in aphysiologically relevant buffer and compare with the behaviour of the normal wild type of theAlzheimer’s amyloid peptide Aβ(1-40) at the same conditions. The investigation revealed distinctdifferences in fibrillogenesis behaviour for the two peptides. Our results demonstrate a previouslysuggested alternative fibrillogenesis pathway, of highly distinct aggregates with orderedmorphology as on-pathway. Moreover, additional investigations using a pulsed force mode (PFM)are under way.
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| 2. |
- Norlin, Nils, et al.
(författare)
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Aggregation and fibril morphology of the Arctic mutation of Alzheimer's Aβ peptide by CD, TEM, STEM and in situ AFM
- 2012
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Ingår i: Journal of Structural Biology. - San Diego, CA, USA : Academic Press. - 1047-8477 .- 1095-8657. ; 180:1, s. 174-189
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Tidskriftsartikel (refereegranskat)abstract
- Morphology of aggregation intermediates, polymorphism of amyloid fibrils and aggregation kinetics of the "Arctic" mutant of the Alzheimer's amyloid β-peptide, Aβ((1-40))(E22G), in a physiologically relevant Tris buffer (pH 7.4) were thoroughly explored in comparison with the human wild type Alzheimer's amyloid peptide, wt-Aβ((1-40)), using both in situ atomic force and electron microscopy, circular dichroism and thioflavin T fluorescence assays. For arc-Aβ((1-40)) at the end of the 'lag'-period of fibrillization an abrupt appearance of ∼3nm size 'spherical aggregates' with a homogeneous morphology, was identified. Then, the aggregation proceeds with a rapid growth of amyloid fibrils with a variety of morphologies, while the spherical aggregates eventually disappeared during in situ measurements. Arc-Aβ((1-40)) was also shown to form fibrils at much lower concentrations than wt-Aβ((1-40)): ⩽2.5μM and 12.5μM, respectively. Moreover, at the same concentration, 50μM, the aggregation process proceeds more rapidly for arc-Aβ((1-40)): the first amyloid fibrils were observed after c.a. 72h from the onset of incubation as compared to approximately 7days for wt-Aβ((1-40)). Amyloid fibrils of arc-Aβ((1-40)) exhibit a large variety of polymorphs, at least five, both coiled and non-coiled distinct fibril structures were recognized by AFM, while at least four types of arc-Aβ((1-40)) fibrils were identified by TEM and STEM and their mass-per-length statistics were collected suggesting supramolecular structures with two, four and six β-sheet laminae. Our results suggest a pathway of fibrillogenesis for full-length Alzheimer's peptides with small and structurally ordered transient spherical aggregates as on-pathway immediate precursors of amyloid fibrils.
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| 3. |
- Wagner, Nils, et al.
(författare)
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Deep learning-enhanced light-field imaging with continuous validation
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Light field microscopy (LFM) has emerged as a powerful tool for fast volumetric image acquisition in biology, but its effective throughput and widespread use has been hampered by a computationally demanding and artefact-prone image reconstruction process. Here, we present a novel framework consisting of a hybrid light-field light-sheet microscope and deep learning-based volume reconstruction, where single light-sheet acquisitions continuously serve as training data and validation for the convolutional neural network reconstructing the LFM volume. Our network delivers high-quality reconstructions at video-rate throughput and we demonstrate the capabilities of our approach by imaging medaka heart dynamics and zebrafish neural activity.
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| 4. |
- Wagner, Nils, et al.
(författare)
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Deep learning-enhanced light-field imaging with continuous validation
- 2021
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Ingår i: Nature Methods. - : Springer Science and Business Media LLC. - 1548-7105 .- 1548-7091. ; 18:5, s. 557-563
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Tidskriftsartikel (refereegranskat)abstract
- Visualizing dynamic processes over large, three-dimensional fields of view at high speed is essential for many applications in the life sciences. Light-field microscopy (LFM) has emerged as a tool for fast volumetric image acquisition, but its effective throughput and widespread use in biology has been hampered by a computationally demanding and artifact-prone image reconstruction process. Here, we present a framework for artificial intelligence-enhanced microscopy, integrating a hybrid light-field light-sheet microscope and deep learning-based volume reconstruction. In our approach, concomitantly acquired, high-resolution two-dimensional light-sheet images continuously serve as training data and validation for the convolutional neural network reconstructing the raw LFM data during extended volumetric time-lapse imaging experiments. Our network delivers high-quality three-dimensional reconstructions at video-rate throughput, which can be further refined based on the high-resolution light-sheet images. We demonstrate the capabilities of our approach by imaging medaka heart dynamics and zebrafish neural activity with volumetric imaging rates up to 100 Hz.
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| 5. |
- André, Oscar, et al.
(författare)
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Data-driven microscopy allows for automated context-specific acquisition of high-fidelity image data
- 2023
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Ingår i: Cell reports methods. - : Elsevier BV. - 2667-2375. ; 3:3
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Tidskriftsartikel (refereegranskat)abstract
- Light microscopy is a powerful single-cell technique that allows for quantitative spatial information at subcellular resolution. However, unlike flow cytometry and single-cell sequencing techniques, microscopy has issues achieving high-quality population-wide sample characterization while maintaining high resolution. Here, we present a general framework, data-driven microscopy (DDM) that uses real-time population-wide object characterization to enable data-driven high-fidelity imaging of relevant phenotypes based on the population context. DDM combines data-independent and data-dependent steps to synergistically enhance data acquired using different imaging modalities. As a proof of concept, we develop and apply DDM with plugins for improved high-content screening and live adaptive microscopy for cell migration and infection studies that capture events of interest, rare or common, with high precision and resolution. We propose that DDM can reduce human bias, increase reproducibility, and place single-cell characteristics in the context of the sample population when interpreting microscopy data, leading to an increase in overall data fidelity.
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| 6. |
- André, Oscar, et al.
(författare)
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Data-driven microscopy allows for automated targeted acquisition of relevant data with higher fidelity
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Light microscopy is a powerful single-cell technique that allows for quantitative spatial information at subcellular resolution. However, unlike flow cytometry and single-cell sequencing techniques, microscopy has issues achieving high-quality population-wide sample characterization while maintaining high resolution. Here, we present a general framework, data-driven microscopy (DDM), that uses population-wide cell characterization to enable data-driven high-fidelity imaging of relevant phenotypes. DDM combines data-independent and data-dependent steps to synergistically enhance data acquired using different imaging modalities. As proof-of-concept, we apply DDM with plugins for improved high-content screening and live adaptive microscopy. DDM also allows for easy correlative imaging in other systems with a plugin that uses the spatial relationship of the sample population for automated registration. We believe DDM will be a valuable approach for reducing human bias, increasing reproducibility, and placing singlecell characteristics in the context of the sample population when interpreting microscopy data, leading to an overall increase in data fidelity.
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| 7. |
- Antzutkin, Oleg, et al.
(författare)
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Binding of Aluminium(III)-Citrate Complexes, [Al3(H-1Cit)3(OH)]-4 and [Al3(H-1Cit)3(OH)4]-7, to Alzheimer's A-beta(1-40) Peptides : In situ Atomic Force, Electron Microscopy and Solid State 13C and 27Al NMR Studies
- 2005
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Ingår i: Sixth Keele Meeting on Aluminium. - : Centro de Estudos do Ambiente e Mar, Universidade de Aveiro. ; , s. 16-
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- It is believed that Alzheimer's disease (AD) amyloid-β-peptide (Aβ) deposits contribute directly to the disease's progressive neurodegeneration. Aggregation cascade for Aβ peptides, its relevance to neurotoxicity in the course of AD, various factors modulating Aβ aggregation kinetics and experimental methods useful for these studies were recently discussed [1]. Al(III), Zn(II), Cu(II) and Fe(III) ions are often colocalized at the center of the core of Alzheimer's amyloid plaques [2] and are suggested to promote aggregation of physiological concentrations of Aβ [3]. It has also been suggested that Al can block calcium permeable putative Aβ-peptide channels in bilayer membranes [4]. Therefore studies of complexation of metal ions with Aβ-oligomers and fibrils are important in the search for the causes of and potential treatments for AD.We studied effects of highly soluble and biologically relevant aluminium(III)-citrate compounds, [Al3(H-1Cit)3(OH)]-4 and [Al3(H-1Cit)3(OH)4]-7, on the fibrillogenesis of Aβ(1-40). All resonances in 156.37 MHz 27Al and 90.52 MHz 13C MAS NMR spectra of powder Al(III)-citrate complexes were assigned. 27Al MAS NMR of dialysed samples of Aβ(1-40) co-incubated with the Al(III)-citrate complexes at different concentrations in TRIS buffer solutions, pH 7.4, shows that Al(III)-citrates bind to Aβ(1-40) as [Al3(H-1Cit)3(OH)]-4 and either accelerate ([Al3(H-1Cit)3(OH)]-4 complex) or retard ([Al3(H-1Cit)3(OH)4]-7 compound) aggregation of Aβ(1-40) as revealed by AFM. [1] ON Antzutkin, Magn. Reson. Chem. 42 (2004) 231; [2] MA Lovell et al., J. Neurol. Sci. 158 (1998) 47; Ch Exley et al., Al and Alzheimer's disease, Ch Exley (Ed)1998) 47; Ch Exley , Ch Exley (Ed) Elsevier Science, 2001, 421; [3] PW Mantyh et al., J. Neurochem. 61 (1993) 1171; [4] N Arispe et al, PNAS 90 (1993) 567.
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| 8. |
- Eriksson, Anna U., et al.
(författare)
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Near infrared optical projection tomography for assessments of beta-cell mass distribution in diabetes research
- 2013
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Ingår i: Journal of Visualized Experiments. - : MyJove Corporation. - 1940-087X. ; 71
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Tidskriftsartikel (refereegranskat)abstract
- By adapting OPT to include the capability of imaging in the near infrared (NIR) spectrum, we here illustrate the possibility to image larger bodies of pancreatic tissue, such as the rat pancreas, and to increase the number of channels (cell types) that may be studied in a single specimen. We further describe the implementation of a number of computational tools that provide: 1/ accurate positioning of a specimen's (in our case the pancreas) centre of mass (COM) at the axis of rotation (AR)2; 2/ improved algorithms for post-alignment tuning which prevents geometric distortions during the tomographic reconstruction2 and 3/ a protocol for intensity equalization to increase signal to noise ratios in OPT-based BCM determinations3. In addition, we describe a sample holder that minimizes the risk for unintentional movements of the specimen during image acquisition. Together, these protocols enable assessments of BCM distribution and other features, to be performed throughout the volume of intact pancreata or other organs (e.g. in studies of islet transplantation), with a resolution down to the level of individual islets of Langerhans.
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| 9. |
- Isaksson, Mikael, et al.
(författare)
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On the quantitative molecular analysis of electronic energy transfer within donor–acceptor pairs
- 2007
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Ingår i: Physical Chemistry, Chemical Physics - PCCP. - : Royal Society of Chemistry (RSC). - 1463-9076 .- 1463-9084. ; 9, s. 1941-51
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Tidskriftsartikel (refereegranskat)abstract
- An extended Förster theory (EFT) on electronic energy transfer is presented for the quantitative analysis of time-resolved fluorescence lifetime and depolarisation experiments. The EFT, which was derived from the stochastic Liouville equation, yields microscopic information concerning the reorientation correlation times, the order parameters, as well as inter chromophoric distances. Weakly interacting donor and acceptor groups, which reorient and interact in a pair wise fashion, are considered, under isotropic and anisotropic conditions. For the analysis of experiments it is shown that not only do we need to consider the orientational distributions of the transition dipoles, but the internal reorienting molecular dynamics within the pair which is of even greater importance. The latter determines the shape as well as the rate of the observed donor fluorescence and depolarisation decays, which are most often not mono-exponential functions. It is shown that the commonly used Förster theory is a special case of the EFT. Strategies are presented for applying the EFT, which makes use of Brownian dynamics simulation.
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| 10. |
- Moore, Josh, et al.
(författare)
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OME-Zarr : A cloud-optimized bioimaging file format with international community support
- 2023
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Ingår i: Histochemistry and Cell Biology. - : Springer Nature. - 1432-119X .- 0948-6143. ; 160:3, s. 223-251
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Tidskriftsartikel (refereegranskat)abstract
- A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.
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