6 resultados para Breast Model

em Indian Institute of Science - Bangalore - Índia


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The analytical solutions for the coupled diffusion equations that are encountered in diffuse fluorescence spectroscopy/ imaging for regular geometries were compared with the well-established numerical models, which are based on the finite element method. Comparison among the analytical solutions obtained using zero boundary conditions and extrapolated boundary conditions (EBCs) was also performed. The results reveal that the analytical solutions are in close agreement with the numerical solutions, and solutions obtained using EBCs are more accurate in obtaining the mean time of flight data compared to their counterpart. The analytical solutions were also shown to be capable of providing bulk optical properties through a numerical experiment using a realistic breast model. (C) 2013 Optical Society of America

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Metastasis is clinically the most challenging and lethal aspect of breast cancer. While animal-based xenograft models are expensive and time-consuming, conventional two-dimensional (2D) cell culture systems fail to mimic in vivo signaling. In this study we have developed a three-dimensional (3D) scaffold system that better mimics the topography and mechanical properties of the breast tumor, thus recreating the tumor microenvironment in vitro to study breast cancer metastasis. Porous poly(e-caprolactone) (PCL) scaffolds of modulus 7.0 +/- 0.5 kPa, comparable to that of breast tumor tissue were fabricated, on which MDA-MB-231 cells proliferated forming tumoroids. A comparative gene expression analysis revealed that cells growing in the scaffolds expressed increased levels of genes implicated in the three major events of metastasis, viz., initiation, progression, and the site-specific colonization compared to cells grown in conventional 2D tissue culture polystyrene (TCPS) dishes. The cells cultured in scaffolds showed increased invasiveness and sphere efficiency in vitro and increased lung metastasis in vivo. A global gene expression analysis revealed a significant increase in the expression of genes involved in cell cell and cell matrix interactions and tissue remodeling, cancer inflammation, and the PI3K/Akt, Wnt, NF-kappaB, and HIFI signaling pathways all of which are implicated in metastasis. Thus, culturing breast cancer cells in 3D scaffolds that mimic the in vivo tumor-like microenvironment enhances their metastatic potential. This system could serve as a comprehensive in vitro model to investigate the manifold mechanisms of breast cancer metastasis.

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Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

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Emerging evidence suggests that cancers arise in stem/progenitor cells. Yet, the requirements for transformation of these primitive cells remains poorly understood. In this study, we have exploited the `mammosphere' system that selects for primitive mammary stem/progenitor cells to explore their potential and requirements for transformation. Introduction of Simian Virus 40 Early Region and hTERT into mammosphere-derived cells led to the generation of NBLE, an immortalized mammary epithelial cell line. The NBLEs largely comprised of bi-potent progenitors with long-term self-renewal and multi-lineage differentiation potential. Clonal and karyotype analyses revealed the existence of heterogeneous population within NBLEs with varied proliferation, differentiation and sphere-forming potential. Significantly, injection of NBLEs into immunocompromised mice resulted in the generation of invasive ductal adenocarcinomas. Further, these cells harbored a sub-population of CD44(+)/CD24(-) fraction that alone had sphere- and tumor-initiating potential and resembled the breast cancer stem cell gene signature. Interestingly, prolonged in vitro culturing led to their further enrichment. The NBLE cells also showed increased expression of stemness and epithelial to mesenchymal transition markers, deregulated self-renewal pathways, activated DNA-damage response and cancer-associated chromosomal aberrations-all of which are likely to have contributed to their tumorigenic transformation. Thus, unlike previous in vitro transformation studies that used adherent, more differentiated human mammary epithelial cells our study demonstrates that the mammosphere-derived, less-differentiated cells undergo tumorigenic conversion with only two genetic elements, without requiring oncogenic Ras. Moreover, the striking phenotypic and molecular resemblance of the NBLE-generated tumors with naturally arising breast adenocarcinomas supports the notion of a primitive breast cell as the origin for this subtype of breast cancer. Finally, the NBLEs represent a heterogeneous population of cells with striking plasticity, capable of differentiation, self-renewal and tumorigenicity, thus offering a unique model system to study the molecular mechanisms involved with these processes. Oncogene (2012) 31, 1896-1909; doi:10.1038/onc.2011.378; published online 29 August 2011

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A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Delta phi) becomes very close to zero. The phase of the individual photon is randomly distributed over 2 pi when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l(s) is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than l(s), and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.

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Owing to the reduced co-relationship between conventional flat Petri dish culture (two-dimensional) and the tumour microenvironment, there has been a shift towards three-dimensional culture systems that show an improved analogy to the same. In this work, an extracellular matrix (ECM)-mimicking three-dimensional scaffold based on chitosan and gelatin was fabricated and explored for its potential as a tumour model for lung cancer. It was demonstrated that the chitosan-gelatin (CG) scaffolds supported the formation of tumoroids that were similar to tumours grown in vivo for factors involved in tumour-cell-ECM interaction, invasion and metastasis, and response to anti-cancer drugs. On the other hand, the two-dimensional Petri dish surfaces did not demonstrate gene-expression profiles similar to tumours grown in vivo. Further, the three-dimensional CG scaffolds supported the formation of tumoroids, using other types of cancer cells such as breast, cervix and bone, indicating a possible wider potential for in vitro tumoroid generation. Overall, the results demonstrated that CG scaffolds can be an improved in vitro tool to study cancer progression and drug screening for solid tumours.