Re-expression of IGF-II is important for beta cell regeneration in adult mice

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

Automated Image Analysis And Spatial Computational Modeling Of NF-kB In Cerebrovascular Endothelial Cells

Cerebrovascular endothelial cells play a key part in the inflammatory response of the blood-brain barrier in pathological conditions such as Alzheimer’s disease. Specifically, the NF-κB signaling pathway plays a central role. Better understanding of the factors in inflammatory disease progression can lead to more effective treatments for such devastating illnesses like Alzheimer’s, asthma, arthritis, cancer, diabetes and many more inflammatory diseases. The proposed approach analyzes spatial NF-κB distribution contained in multispectral stacked micrograph images of cerebrovascular endothelial cells indexed based on dose of the activating protein and the length of activation. Image analysis code identifies the location of nuclear boundaries and quantifies NF-κB in relation to the closest nuclear boundary. This information is used to develop a mathematical model that describes the time and concentration dependence of NF-κB in response to the activating proteins. The proposed method allows for analysis and modeling of previously unexplored spatial behavior of NF-κB

A system biology study of the molecular mechanism of Metformin on breast cancer

Breast cancer is a complicated, heterogeneous and diversified disease that comprises of a mixture of various subtypes. The emergence of high throughout technologies such as gene expression profiling and DNA copy number analysis has allowed a profound awareness of this complex disease. Breast cancer molecular classification began with ER, PR and HER2 based stratification of patients, and further classified into various intrinsic subtypes such as Luminal A, Luminal B, Her-2 enriched, Basal-like, and Claudin-low. These subtypes were proven to have significant divergences in amplified and mutated genes, survival rates, prognosis and response to therapy. The anti-diabetic drug Metformin has been prescribed to treat type 2 diabetes patients since 1957 with a well-established side effects and safety profile. Additionally, cancer researchers have studied the anti-tumour effects of this drug since 2005 and have determined Metformin benefit in the reduction of cancers incidence. Thus, Metformin has been suggested as an ideal candidate to treat and prevent diverse types of cancers, including breast carcinoma. The purpose of this study is to elucidate the biological and molecular effects of Metformin on breast cancer cell lines such as BT-474, MCF-7, MDA-MB-231, MDA-MB-468, and SkBr3. Interestingly, Metformin treatments reduced the viability and proliferation of examined breast cancer cell lines, while induced cells apoptosis. Basal-like (MDA-MB-468) was the most sensitive phenotype to Metformin treatments, whereas HER2 (SkBr3) was the least sensitive subtype. We performed Gene Expression Microarray and NanoString analysis of Metformin treated MDAMB- 468 and SkBr3 cells and found that the upregulated Protein Tyrosine Kinase 2 Beta (PTK2B) was predominantly involved in cell proliferation, cell survival, cell migration and cell invasion. We found that PTK2B promotes invasion and migration, while prevents the proliferation of breast cancer cells. It is also, playing a vital role in Autocrine Somatotropin signalling pathway in breast cancer. Additionally, Mass Spectrometry (MS) analyses and pathways enrichment analysis that has emphasised the role of PTK2B in breast cancer invasion and metastasis. Additionally, the combined action of both selected markers and Metformin treatment on fundamental biological functions in breast cancer were also assessed. These data showed that Metformin promotes Her-2 enriched breast cancer invasion through mechanisms involving PYK2, and that future treatments should consider potential complications resulting from metformin-based therapies

Molecular Imaging

The present book gives an exceptional overview of molecular imaging. Practical approach represents the red thread through the whole book, covering at the same time detailed background information that goes very deep into molecular as well as cellular level. Ideas how molecular imaging will develop in the near future present a special delicacy. This should be of special interest as the contributors are members of leading research groups from all over the world

Cognitive Foundations for Visual Analytics

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions

Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue

The challenging problem of computational bioimage analysis receives growing attention from life sciences. Fluorescence microscopy is capable of simultaneously visualizing multiple molecules by staining with different fluorescent dyes. In the analysis of the result multichannel images, segmentation of ROIs resembles only a first step which must be followed by a second step towards the analysis of the ROI's signals in the different channels. In this paper we present a system that combines image segmentation and information visualization principles for an integrated analysis of fluorescence micrographs of tissue samples. The analysis aims at the detection and annotation of cells of the Islets of Langerhans and the whole pancreas, which is of great importance in diabetes studies and in the search for new anti-diabetes treatments. The system operates with two modules. The automatic annotation module applies supervised machine learning for cell detection and segmentation. The second information visualization module can be used for an interactive classification and visualization of cell types following the link-and-brush principle for filtering. We can compare the results obtained with our system with results obtained manually by an expert, who evaluated a set of example images three times to account for his intra-observer variance. The comparison shows that using our system the images can be evaluated with high accuracy which allows a considerable speed up of the time-consuming evaluation process. (C) 2009 Elsevier Ltd. All rights reserved