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1.  Re-Expression of IGF-II Is Important for Beta Cell Regeneration in Adult Mice 
PLoS ONE  2012;7(9):e43623.
Background
The key factors which support re-expansion of beta cell numbers after injury are largely unknown. Insulin-like growth factor II (IGF-II) plays a critical role in supporting cell division and differentiation during ontogeny but its role in the adult is not known. In this study we investigated the effect of IGF-II on beta cell regeneration.
Methodology/Principal Findings
We employed an in vivo model of ‘switchable’ c-Myc-induced beta cell ablation, pIns-c-MycERTAM, in which 90% of beta cells are lost following 11 days of c-Myc (Myc) activation in vivo. Importantly, such ablation is normally followed by beta cell regeneration once Myc is deactivated, enabling functional studies of beta cell regeneration in vivo. IGF-II was shown to be re-expressed in the adult pancreas of pIns-c-MycERTAM/IGF-II+/+ (MIG) mice, following beta cell injury. As expected in the presence of IGF-II beta cell mass and numbers recover rapidly after ablation. In contrast, in pIns-c-MycERTAM/IGF-II+/− (MIGKO) mice, which express no IGF-II, recovery of beta cell mass and numbers were delayed and impaired. Despite failure of beta cell number increase, MIGKO mice recovered from hyperglycaemia, although this was delayed.
Conclusions/Significance
Our results demonstrate that beta cell regeneration in adult mice depends on re-expression of IGF-II, and supports the utility of using such ablation-recovery models for identifying other potential factors critical for underpinning successful beta cell regeneration in vivo. The potential therapeutic benefits of manipulating the IGF-II signaling systems merit further exploration.
doi:10.1371/journal.pone.0043623
PMCID: PMC3436856  PMID: 22970135
2.  WHIDE—a web tool for visual data mining colocation patterns in multivariate bioimages 
Bioinformatics  2012;28(8):1143-1150.
Motivation: Bioimaging techniques rapidly develop toward higher resolution and dimension. The increase in dimension is achieved by different techniques such as multitag fluorescence imaging, Matrix Assisted Laser Desorption / Ionization (MALDI) imaging or Raman imaging, which record for each pixel an N-dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBIs) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this article, we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application.
Results: We applied WHIDE to a set of MBI recorded using the multitag fluorescence imaging Toponome Imaging System. The MBI show field of view in tissue sections from a colon cancer study and we compare tissue from normal/healthy colon with tissue classified as tumor. Our results show, that WHIDE efficiently reduces the complexity of the data by mapping each of the pixels to a cluster, referred to as Molecular Co-Expression Phenotypes and provides a structural basis for a sophisticated multimodal visualization, which combines topology preserving pseudocoloring with information visualization. The wide range of WHIDE's applicability is demonstrated with examples from toponome imaging, high content screens and MALDI imaging (shown in the Supplementary Material).
Availability and implementation: The WHIDE tool can be accessed via the BioIMAX website http://ani.cebitec.uni-bielefeld.de/BioIMAX/; Login: whidetestuser; Password: whidetest.
Supplementary information: Supplementary data are available at Bioinformatics online.
Contact: tim.nattkemper@uni-bielefeld.de
doi:10.1093/bioinformatics/bts104
PMCID: PMC3324520  PMID: 22390938
3.  RAMTaB: Robust Alignment of Multi-Tag Bioimages 
PLoS ONE  2012;7(2):e30894.
Background
In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.
Methodology/Principal Findings
We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.
Conclusions
For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.
doi:10.1371/journal.pone.0030894
PMCID: PMC3280195  PMID: 22363510
4.  Non-β-cell progenitors of β-cells in pregnant mice 
Organogenesis  2010;6(2):125-133.
Pregnancy is a normal physiological condition in which the maternal β-cell mass increases rapidly about two-fold to adapt to new metabolic challenges. We have used a lineage tracing of β-cells to analyse the origin of new β-cells during this rapid expansion in pregnancy. Double transgenic mice bearing a tamoxifen-dependent Cre-recombinase construct under the control of a rat insulin promoter, together with a reporter Z/AP gene, were generated. Then, in response to a pulse of tamoxifen before pregnancy, β-cells in these animals were marked irreversibly and heritably with the human placental alkaline phosphatase (HP AP). First, we conclude that the lineage tracing system was highly specific for β-cells. Secondly, we scored the proportion of the β-cells marked with HP AP during a subsequent chase period in pregnant and non-pregnant females. We observed a dilution in this labeling index in pregnant animal pancreata, compared to nonpregnant controls, during a single pregnancy in the chase period. To extend these observations we also analysed the labeling index in pancreata of animals during the second of two pregnancies in the chase period. The combined data revealed statistically-significant dilution during pregnancy, indicating a contribution to new beta cells from a non-β-cell source. Thus for the first time in a normal physiological condition, we have demonstrated not only β-cell duplication, but also the activation of a non-β-cell progenitor population. Further, there was no transdifferentiation of β-cells to other cell types in a two and half month period following labeling, including the period of pregnancy.
PMCID: PMC2901816  PMID: 20885859
β-cells; pancreas; β-cell duplication; non-β-cell progenitor; pregnancy
5.  Brief inactivation of c-Myc is not sufficient for sustained regression of c-Myc-induced tumours of pancreatic islets and skin epidermis 
BMC Biology  2004;2:26.
Background
Tumour regression observed in many conditional mouse models following oncogene inactivation provides the impetus to develop, and a platform to preclinically evaluate, novel therapeutics to inactivate specific oncogenes. Inactivating single oncogenes, such as c-Myc, can reverse even advanced tumours. Intriguingly, transient c-Myc inactivation proved sufficient for sustained osteosarcoma regression; the resulting osteocyte differentiation potentially explaining loss of c-Myc's oncogenic properties. But would this apply to other tumours?
Results
We show that brief inactivation of c-Myc does not sustain tumour regression in two distinct tissue types; tumour cells in pancreatic islets and skin epidermis continue to avoid apoptosis after c-Myc reactivation, by virtue of Bcl-xL over-expression or a favourable microenvironment, respectively. Moreover, tumours progress despite reacquiring a differentiated phenotype and partial loss of vasculature during c-Myc inactivation. Interestingly, reactivating c-Myc in β-cell tumours appears to result not only in further growth of the tumour, but also re-expansion of the accompanying angiogenesis and more pronounced β-cell invasion (adenocarcinoma).
Conclusions
Given that transient c-Myc inactivation could under some circumstances produce sustained tumour regression, the possible application of this potentially less toxic strategy in treating other tumours has been suggested. We show that brief inactivation of c-Myc fails to sustain tumour regression in two distinct models of tumourigenesis: pancreatic islets and skin epidermis. These findings challenge the potential for cancer therapies aimed at transient oncogene inactivation, at least under those circumstances where tumour cell differentiation and alteration of epigenetic context fail to reinstate apoptosis. Together, these results suggest that treatment schedules will need to be informed by knowledge of the molecular basis and environmental context of any given cancer.
doi:10.1186/1741-7007-2-26
PMCID: PMC544575  PMID: 15613240

Results 1-5 (5)