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Kostromina, Elena
Publications (3 of 3) Show all publications
Parween, S., Eriksson, M., Nord, C., Kostromina, E. & Ahlgren, U. (2017). Spatial and quantitative datasets of the pancreatic beta-cell mass distribution in lean and obese mice. Scientific Data, 4, Article ID 170031.
Open this publication in new window or tab >>Spatial and quantitative datasets of the pancreatic beta-cell mass distribution in lean and obese mice
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2017 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 4, article id 170031Article in journal (Refereed) Published
Abstract [en]

A detailed understanding of pancreatic β-cell mass distribution is a key element to fully appreciate the pathophysiology of models of diabetes and metabolic stress. Commonly, such assessments have been performed by stereological approaches that rely on the extrapolation of two-dimensional data and provide very limited topological information. We present ex vivo optical tomographic data sets of the full β-cell mass distribution in cohorts of obese ob/ob mice and their lean controls, together with information about individual islet β-cell volumes, their three-dimensional coordinates and shape throughout the volume of the pancreas between 4 and 52 weeks of age. These data sets offer the currently most comprehensive public record of the β-cell mass distribution in the mouse. As such, they may serve as a quantitative and topological reference for the planning of a variety of in vivo or ex vivo experiments including computational modelling and statistical analyses. By shedding light on intra- and inter-lobular variations in β-cell mass distribution, they further provide a powerful tool for the planning of stereological sampling assessments.

National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:umu:diva-133764 (URN)10.1038/sdata.2017.31 (DOI)000396109500001 ()
Available from: 2017-05-03 Created: 2017-05-03 Last updated: 2018-06-09Bibliographically approved
Parween, S., Kostromina, E., Nord, C., Eriksson, M., Lindström, P. & Ahlgren, U. (2016). Intra-islet lesions and lobular variations in β-cell mass expansion in ob/ob mice revealed by 3D imaging of intact pancreas. Scientific Reports, 6, Article ID 34885.
Open this publication in new window or tab >>Intra-islet lesions and lobular variations in β-cell mass expansion in ob/ob mice revealed by 3D imaging of intact pancreas
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2016 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, article id 34885Article in journal (Refereed) Published
Abstract [en]

The leptin deficient ob/ob mouse is a widely used model for studies on initial aspects of metabolic disturbances leading to type 2 diabetes, including insulin resistance and obesity. Although it is generally accepted that ob/ob mice display a dramatic increase in β-cell mass to compensate for increased insulin demand, the spatial and quantitative dynamics of β-cell mass distribution in this model has not been assessed by modern optical 3D imaging techniques. We applied optical projection tomography and ultramicroscopy imaging to extract information about individual islet β-cell volumes throughout the volume of ob/ob pancreas between 4 and 52 weeks of age. Our data show that cystic lesions constitute a significant volume of the hyperplastic ob/ob islets. We propose that these lesions are formed by a mechanism involving extravasation of red blood cells/plasma due to increased islet vessel blood flow and vessel instability. Further, our data indicate that the primary lobular compartments of the ob/ob pancreas have different potentials for expanding their β-cell population. Unawareness of the characteristics of β-cell expansion in ob/ob mice presented in this report may significantly influence ex vivo and in vivo assessments of this model in studies of β-cell adaptation and function.

Place, publisher, year, edition, pages
Nature Publishing Group, 2016
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-127539 (URN)10.1038/srep34885 (DOI)000392007800001 ()27713548 (PubMedID)2-s2.0-84990210699 (Scopus ID)
Funder
EU, FP7, Seventh Framework Programme, 289932Swedish Research Council
Available from: 2016-11-15 Created: 2016-11-15 Last updated: 2018-06-09Bibliographically approved
Eriksson, A. U., Svensson, C., Hörnblad, A., Cheddad, A., Kostromina, E., Eriksson, M., . . . Ahlgren, U. (2013). Near infrared optical projection tomography for assessments of beta-cell mass distribution in diabetes research. Journal of Visualized Experiments, 71, Article ID e50238.
Open this publication in new window or tab >>Near infrared optical projection tomography for assessments of beta-cell mass distribution in diabetes research
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2013 (English)In: Journal of Visualized Experiments, ISSN 1940-087X, E-ISSN 1940-087X, Vol. 71, article id e50238Article in journal (Refereed) Published
Abstract [en]

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.

National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:umu:diva-64029 (URN)10.3791/50238 (DOI)000209226200052 ()23353681 (PubMedID)
Available from: 2013-01-14 Created: 2013-01-14 Last updated: 2018-06-08Bibliographically approved
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