993 resultados para Cell mechanics


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Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

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Tissue mechanics and cellular interactions influence every single cell in our bodies to drive morphogenesis. However, little is known about mechanisms by which cells sense physical forces and transduce them from the cytoskeleton to the nucleus to control gene expression and stem cell fate. We have identified a novel nuclear-mechanosensor complex, consisting of the nuclear membrane protein emerin (Emd), actin and non-muscle myosin IIA (NMIIA), that regulates transcription, chromatin remodeling and lineage commitment. Force-induced enrichment of Emd at the outer nuclear membrane leads to a compensation between H3K9me2,3 and H3K27me3 on constitutive heterochromatin. This strain-induced epigenetic switch is accompanied by the global rearrangement of chromatin. In parallel, forces promote local F-actin polymerization at the outer nuclear membrane, which limits the availability of nuclear G-actin. Subsequently, the reduction of nuclear G-actin results in attenuated global transcription and therefore increased H3K27me3 occupancy to reinforce gene silencing. Restoring nuclear actin levels in the presence of mechanical strain counteracts PRC2-mediated silencing of transcribed genes. This mechanosensory circuit is also observed in vivo. Depletion of NMIIA in mouse epidermis leads to decreased H3K27me3 levels and precocious lineage commitment, thus abrogating organ growth and patterning. Our results reveal how mechanical signals regulate nuclear architecture, chromatin organization and transcription to control cell fate decisions.

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This research work analyses techniques for implementing a cell-centred finite-volume time-domain (ccFV-TD) computational methodology for the purpose of studying microwave heating. Various state-of-the-art spatial and temporal discretisation methods employed to solve Maxwell's equations on multidimensional structured grid networks are investigated, and the dispersive and dissipative errors inherent in those techniques examined. Both staggered and unstaggered grid approaches are considered. Upwind schemes using a Riemann solver and intensity vector splitting are studied and evaluated. Staggered and unstaggered Leapfrog and Runge-Kutta time integration methods are analysed in terms of phase and amplitude error to identify which method is the most accurate and efficient for simulating microwave heating processes. The implementation and migration of typical electromagnetic boundary conditions. from staggered in space to cell-centred approaches also is deliberated. In particular, an existing perfectly matched layer absorbing boundary methodology is adapted to formulate a new cell-centred boundary implementation for the ccFV-TD solvers. Finally for microwave heating purposes, a comparison of analytical and numerical results for standard case studies in rectangular waveguides allows the accuracy of the developed methods to be assessed.

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The anatomy and microstructure of the spine and in particular the intervertebral disc are intimately linked to how they operate in vivo and how they distribute loads to the adjacent musculature and bony anatomy. The degeneration of the intervertebral discs may be characterised by a loss of hydration, loss of disc height, a granular texture and the presence of annular lesions. As such, degeneration of the intervertebral discs compromises the mechanical integrity of their components and results in adaption and modification in the mechanical means by which loads are distributed between adjacent spinal motion segments.

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PURPOSE: To introduce techniques for deriving a map that relates visual field locations to optic nerve head (ONH) sectors and to use the techniques to derive a map relating Medmont perimetric data to data from the Heidelberg Retinal Tomograph. METHODS: Spearman correlation coefficients were calculated relating each visual field location (Medmont M700) to rim area and volume measures for 10 degrees ONH sectors (HRT III software) for 57 participants: 34 with glaucoma, 18 with suspected glaucoma, and 5 with ocular hypertension. Correlations were constrained to be anatomically plausible with a computational model of the axon growth of retinal ganglion cells (Algorithm GROW). GROW generated a map relating field locations to sectors of the ONH. The sector with the maximum statistically significant (P < 0.05) correlation coefficient within 40 degrees of the angle predicted by GROW for each location was computed. Before correlation, both functional and structural data were normalized by either normative data or the fellow eye in each participant. RESULTS: The model of axon growth produced a 24-2 map that is qualitatively similar to existing maps derived from empiric data. When GROW was used in conjunction with normative data, 31% of field locations exhibited a statistically significant relationship. This significance increased to 67% (z-test, z = 4.84; P < 0.001) when both field and rim area data were normalized with the fellow eye. CONCLUSIONS: A computational model of axon growth and normalizing data by the fellow eye can assist in constructing an anatomically plausible map connecting visual field data and sectoral ONH data.

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Australia is currently well placed to contribute to the global growth of human stem cell research. However, as the science has progressed, authorities have had to deal with the ongoing challenges of regulating such a fast moving field of scientific endeavour. Australia’s past and current approach to regulating the use of embryos in human embryonic stem cell research provides an insight into how Australia may continue to adapt to future regulatory challenges presented by human stem cell research. In the broader context, a number of issues have been identified that may impact upon the success of future human stem cell research in Australia.

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Human embryonic stem cell research promises to deliver in the future a whole range of therapeutic treatments, but currently governments in different jurisdictions must try to regulate this burgeoning area. Part of the problem has been, and continues to be, polarised community opinion on the use of human embryonic stem cells for research. This article compares the approaches of the Australian, United Kingdom and United States governments in regulating human embryonic stem cell research. To date, these governments have approached the issue through implementing legislation or policy to control research. Similarly, the three jurisdictions have viewed the patentability of human embryonic stem cell technologies in their own ways with different policies being adopted by the three patent offices. This article examines these different approaches and discusses the inevitable concerns that have been raised due to the lack of a universal approach in relation to the regulation of research; the patenting of stem cell technologies; and the effects patents granted are having on further human embryonic stem cell research.