E type cyclins (E1 and E2) are believed to drive cell entry into the S phase. It is widely assumed that the two E type cyclins are critically required for proliferation of all cell types. Here, we demonstrate that E type cyclins are largely dispensable for mouse development. However, endoreplication of trophoblast giant cells and megakaryocytes is severely impaired in the absence of cyclin E. Cyclin E-deficient cells proliferate actively under conditions of continuous cell cycling but are unable to reenter the cell cycle from the quiescent G(0) state. Molecular analyses revealed that cells lacking cyclin E fail to normally incorporate MCM proteins into DNA replication origins during G(0)-->S progression. We also found that cyclin E-deficient cells are relatively resistant to oncogenic transformation. These findings define a molecular function for E type cyclins in cell cycle reentry and reveal a differential requirement for cyclin E in normal versus oncogenic proliferation.

No abstract

Background & AimsWith the increasing prevalence of liver disease worldwide, there is an urgent clinical need for reliable methods to diagnose and stage liver pathology. Liver biopsy, the current gold standard, is invasive and limited by sampling and observer dependent variability. In this study, we aimed to assess the diagnostic accuracy of a novel magnetic resonance protocol for liver tissue characterisation.MethodsWe conducted a prospective study comparing our magnetic resonance technique against liver biopsy. The individual components of the scanning protocol were T1 mapping, proton spectroscopy and T2⁎ mapping, which quantified liver fibrosis, steatosis and haemosiderosis, respectively. Unselected adult patients referred for liver biopsy as part of their routine care were recruited. Scans performed prior to liver biopsy were analysed by physicians blinded to the histology results. The associations between magnetic resonance and histology variables were assessed. Receiver-operating characteristic analyses were also carried out.ResultsPaired magnetic resonance and biopsy data were obtained in 79 patients. Magnetic resonance measures correlated strongly with histology (rs = 0.68 p <0.0001 for fibrosis; rs = 0.89 p <0.001 for steatosis; rs = −0.69 p <0.0001 for haemosiderosis). The area under the receiver operating characteristic curve was 0.94, 0.93, and 0.94 for the diagnosis of any degree of fibrosis, steatosis and haemosiderosis respectively.ConclusionThe novel scanning method described here provides high diagnostic accuracy for the assessment of liver fibrosis, steatosis and haemosiderosis and could potentially replace liver biopsy for many indications. This is the first demonstration of a non-invasive test to differentiate early stages of fibrosis from normal liver.

No abstract

Multiple sclerosis (MS) is a disease of the central nervous system that is associated with leukocyte recruitment and subsequent inflammation, demyelination and axonal loss. Endothelial vascular cell adhesion molecule-1 (VCAM-1) and its ligand, α 4 β 1 integrin, are key mediators of leukocyte recruitment and new selective inhibitors that bind to the α 4 subunit of α 4 β 1 substantially reduce clinical relapse in MS. Urgently needed is a molecular imaging technique to accelerate diagnosis, quantify disease activity and guide specific therapy.We report in vivo detection of VCAM-1 in acute brain inflammation, using MRI in a mouse model, at a time when pathology is otherwise undetectable. Antibody-conjugated microparticles carrying a high payload of iron oxide provided potent, quantifiable contrast effects that delineated the architecture of activated cerebral blood vessels. Rapid clearance from blood resulted in minimal background contrast. This technology is adaptable to monitor expression of endovascular molecules in vivo in a range of pathologies.Multiple sclerosis (MS) is a disease of the central nervous system characterized by multifocal white matter lesions 1 . Current diagnostic criteria for MS, incorporating both clinical and magnetic resonance imaging (MRI) characteristics, require the demonstration of lesion dissemination in both time and space 2 , 3 T2-weighted and gadolinium-enhanced T1-weighted MRI detect some, but not all, lesions while advanced MRI techniques such as diffusion imaging 4 , magnetization transfer 5 and MR spectroscopy 6 may provide additional insights. However, these approaches are limited in two key respects: (1) they image downstream injury, reflecting relatively advanced pathology and (2) while providing an indication of severity, current imaging techniques can not accurately assess disease activity 7 .

Objective-Microparticles of iron oxide (MPIO) distort magnetic field creating marked contrast effects far exceeding their physical size. We hypothesized that antibody-conjugated MPIO would enable magnetic resonance imaging (MRI) of endothelial cell adhesion molecules in mouse atherosclerosis. Methods and Results-MPIO (4.5 m) were conjugated to monoclonal antibodies against vascular cell adhesion molecule-1 (VCAM-MPIO) or P-selectin (P-selectin-MPIO). In vitro, VCAM-MPIO bound, in dose-dependent manner, to tumor necrosis factor (TNF)-␣ stimulated sEND-1 endothelial cells, as quantified by light microscopy (R 2 ϭ0.94, Pϭ0.03) and by MRI (R 2 ϭ0.98, Pϭ0.01). VCAM-MPIO binding was blocked by preincubation with soluble VCAM-1. To mimic leukocyte binding, MPIO targeting both VCAM-1 and P-selectin were administered in apolipoprotein E Ϫ/Ϫ mice. By light microscopy, dual-targeted MPIO binding to endothelium overlying aortic root atherosclerosis was 5-to 7-fold more than P-selectin-MPIO (PϽ0.05) or VCAM-MPIO (PϽ0.01) alone. Dual-targeted MPIO, injected intravenously in vivo bound aortic root endothelium and were quantifiable by MRI ex vivo (3.5-fold increase versus control; PϽ0.01). MPIO were well-tolerated in vivo, with sequestration in the spleen after 24 hours. Conclusions-Dual-ligand MPIO bound to endothelium over atherosclerosis in vivo, under flow conditions. MPIO may provide a functional MRI probe for detecting endothelial-specific markers in a range of vascular pathologies. Key Words: microparticles of iron oxide Ⅲ atherosclerosis Ⅲ magnetic resonance imaging Ⅲ molecular imaging M agnetic resonance imaging (MRI) has demonstrated substantial utility in phenotyping vascular disease. Using inherent physico-chemical properties that confer particular tissue relaxivities, it has been possible to characterize the vessel wall in atherosclerosis at a submillimeter level. 1,2 However, to capitalize fully on the diagnostic potential of MRI requires imaging at molecular and cellular levels. [3][4][5][6][7][8][9] To achieve this, purpose-built contrast agents are needed that can identify molecules of interest with high specificity, while conveying sufficient contrast to be easily distinguished from unenhanced tissue.Specificity can be achieved through conjugation of contrast agent with monoclonal antibodies or their immunospecific fragments F(ab), peptides, or peptide-mimetics. Previous approaches have included integrin-conjugated gadolinium-rich perfluorocarbon nanoparticles, 10 peptide-conjugated nanoparticles of iron oxide, 11 and fibrin-specific cyclic peptide labeled with gadolinium. 12 Gadolinium-based contrast agents shorten T1 providing positive contrast on T1-weighted images. However, for the quantities that can be delivered to an endothelial monolayer, the contrast effects are relatively modest. By comparison, iron oxide nanoparticles provide greater contrast effects, but require many particles to be delivered to a given voxel. Another potential drawback is that contrast effects are manifest in T 2 *-weighted images...

No abstract

Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges.