PubMed | Pathology Histotechnology Laboratory, Imperial College London, Urologic, Frederick National Laboratory for Cancer Research and 3 more.
Type: Journal Article | Journal: Human molecular genetics | Year: 2014
Cardiac hypertrophy, an adaptive process that responds to increased wall stress, is characterized by the enlargement of cardiomyocytes and structural remodeling. It is stimulated by various growth signals, of which the mTORC1 pathway is a well-recognized source. Here, we show that loss of Flcn, a novel AMPK-mTOR interacting molecule, causes severe cardiac hypertrophy with deregulated energy homeostasis leading to dilated cardiomyopathy in mice. We found that mTORC1 activity was upregulated in Flcn-deficient hearts, and that rapamycin treatment significantly reduced heart mass and ameliorated cardiac dysfunction. Phospho-AMP-activated protein kinase (AMPK)-alpha (T172) was reduced in Flcn-deficient hearts and nonresponsive to various stimulations including metformin and AICAR (5-amino-1--D-ribofuranosyl-imidazole-4-carboxamide). ATP levels were elevated and mitochondrial function was increased in Flcn-deficient hearts, suggesting that excess energy resulting from up-regulated mitochondrial metabolism under Flcn deficiency might attenuate AMPK activation. Expression of Ppargc1a, a central molecule for mitochondrial metabolism, was increased in Flcn-deficient hearts and indeed, inactivation of Ppargc1a in Flcn-deficient hearts significantly reduced heart mass and prolonged survival. Ppargc1a inactivation restored phospho-AMPK-alpha levels and suppressed mTORC1 activity in Flcn-deficient hearts, suggesting that up-regulated Ppargc1a confers increased mitochondrial metabolism and excess energy, leading to inactivation of AMPK and activation of mTORC1. Rapamycin treatment did not affect the heart size of Flcn/Ppargc1a doubly inactivated hearts, further supporting the idea that Ppargc1a is the critical element leading to deregulation of the AMPK-mTOR-axis and resulting in cardiac hypertrophy under Flcn deficiency. These data support an important role for Flcn in cardiac homeostasis in the murine model.
Torricelli R.,University of Perugia |
Silveri D.D.,Agenzia Regionale per i Servizi di Sviluppo Agricolo dAbruzzo ARSSA |
Ferradini N.,University of Perugia |
Venora G.,Image Analysis Laboratory |
And 2 more authors.
Genetic Resources and Crop Evolution | Year: 2012
In the world lentil is grown on more than 3 million hectares and is one of the most important, low-cost, food source of protein. In Italy lentil has been cultivated since ancient times, but in the last decades its cultivation has been confined to marginal areas, small islands and hilly, mountainous areas of central and southern Italy. Local varieties are still common and are often greatly appreciated for their taste and cooking qualities. Several accessions from the Santo Stefano di Sessanio area, Abruzzo Region, were collected and phenotypically and genotypically characterized in order to look for the existing variability within and between populations. Image analysis of seeds was also used. Populations grown in Santo Stefano di Sessanio and in the neighbouring area basically share most of their characteristics. However, some of the accessions anonymously gathered from the local market were shown to be different from those collected from farmers. The paper reports and discusses how this local product needs be characterized and promoted in order to avoid fraud that could negatively affect the local economy and put valuable, adapted, genetic resources at risk of erosion. © 2011 Springer Science+Business Media B.V.
Behzadfar N.,University of Tehran |
Behzadfar N.,Pooyandegan Rah Saadat Company |
Soltanian-Zadeh H.,University of Tehran |
Soltanian-Zadeh H.,Image Analysis Laboratory
Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012 | Year: 2012
Segmentation of tumors in magnetic resonance images (MRI) is an important task but is quite time consuming when performed manually by experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue in different patients, and in many cases, similarity between tumor and normal tissues. This paper presents an automatic method for segmentation of brain tumors in MRI. We use images of patients with glioblastoma multiform tumors. After pre-processing and removal of the regions that do not have useful information (e.g., eyes and scalp), we create a projection image for determining the primary location of the tumor. This image provides an overall view of the tumor. Then, we grow the primary region to segment the entire tumor. This method is automatic and independent of the operator. It segments low contrast tumors without requiring their exacta tissue boundaries. The segmentation results obtained by the proposed approach are compared with those of an expert radiologist showing excellent correlations among them (R 2=0.97). © 2012 IEEE.
Narang J.,Ford Motor Company |
Jain R.,Ford Motor Company |
Jain R.,Image Analysis Laboratory |
Arbab A.S.,Ford Motor Company |
And 5 more authors.
Neuro-Oncology | Year: 2011
Differentiating treatment-induced necrosis (TIN) from recurrent/progressive tumor (RPT) in brain tumor patients using conventional morphologic imaging features is a very challenging task. Functional imaging techniques also offer moderate success due to the complexity of the tissue microenvironment and the inherent limitation of the various modalities and techniques. The purpose of this retrospective study was to assess the utility of nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion (DCET1MRP) in differentiating TIN from RPT. Twenty-nine patients with previously treated brain tumors who showed recurrent or progressive enhancing lesion on follow-up MRI underwent DCET1MRP. Another 8 patients with treatment-naïve high-grade gliomas who also underwent DCET1MRP were included as the control group. Semiquantitative indices derived from DCET1MRP included maximum slope of enhancement in initial vascular phase (MSIVP), normalized MSIVP (nMSIVP), normalized slope of delayed equilibrium phase (nSDEP), and initial area under the time-intensity curve (IAUC) at 60 and 120 s (IAUC 60 and IAUC 120) obtained from the enhancement curve. There was a statistically significant difference between the 2 groups (P < .01), with the RPT group showing higher MSIVP (15.78 vs 8.06), nMSIVP (0.046 vs 0.028), nIAUC60 (33.07 vs 6.44), and nIAUC120 (80.14 vs 65.55) compared with the TIN group. nSDEP was significantly lower in the RPT group (7.20 × 10 -5 vs 15.35 × 10 -5) compared with the TIN group. Analysis of the receiver-operatingcharacteristic curve showed nMSIVP to be the best single predictor of RPT, with very high (95%) sensitivity and high (78%) specificity. Thus, nonmodel-based semiquantitative indices derived from DCET1MRP that are relatively easy to derive and do not require a complex model-based approach may aid in differentiating RPT from TIN and can be used as robust noninvasive imaging biomarkers. © 2011 The Author(s).