873 research outputs found
A framework for image-based, automated, multilevel analysis of the cytoskeletal morphology
Get PDFAim: The aim of this thesis is to create an integrated bioinformatic framework for the quantitative assessment of cytoskeleton (CSK) morphology. In this research, we demonstrated the validity of this approach by applying computational biology in two cases: Cytospace images and neurite images. I used these 2 dataset of images as reference dataset to build the computational biology framework and to verify its functionality. To accomplish this, I have analyzed Cytospace optical and confocal microscope images by Image J and MATLAB programming.
I have analyzed the neurite number and length of PC 12 cells by using the following software and tools: (a) custom made tool MATLAB, (b) Cell profiler, (c) Image J, and (d) Filopodyan. Outside this goal of CSK analysis I have also analysed the microcalcification and parenchyma images through my framework to verify the capability of the framework to operate on a different scenario.
Methods: We have developed various algorithms and protocols for the analysis of nuclei, tubulin and microtubules. Each component of the cytoskeleton plays a very essential role in understanding the behaviour of the cell. Moreover, the confocal images were processed properly to extract the information regarding the cytoskelton.
Finally, we also studied PC 12 cells and selected / designed useful algorithms to analyze changes in the number and length of neurites.
Results: In the first part of this thesis we presented an in-silico model constructed by using measurable parameters obtained from microscope images of cells. We use image analysis software Image J to identify cell shape parameters – including surface area, roundness, fractal dimension, such as entropy and coherency.
In the second part of thesis, we also analysed area, perimeter, major and minor axis, circularity, the solidity of the nuclei and tubulin by MATLAB programming. In the third part of the thesis, we anlayzed the dynamics of neurites by developing MATLAB scripts, using also other analysis tools such as Image J, Neuron J.
Conclusion: I have build a computational framework to analyse in quantitative manner images from optical and confocal microscopy.
During the first two years of PhD course I select, develop and integrated bioinformatics protocols and algorithms to define optimized operational pipelines. I used two datasets of image as reference to tuning the computational pipeline.
In the last period of phd course I can apply my optimised framework on microscopy images for detection and analysis of neurites. By means of the application of the framework was possible reduce considerable time of biologist to analyse the images
Author response: India and China in Africa: a comparative perspective of the oil industry by Raj Verma
Get PDFEarlier this month Ian Taylor reviewed India and China in Africa, a new book about Asian engagement in the West African oil industry. Here, the book’s author Raj Verma responds to Taylor’s comments, outlining the rationale and evidence for the framework used in the study. India and China in Africa: A comparative perspective of the oil industry. Raj Verma. London: Routledge. 2017
Systems biology-driven hypotheses tested in vivo: the need to advancing molecular imaging tools
No full textProcessing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties
Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer: a diagnostic perspective
No full textIntroduction
Herein, we propose a Systems Biology approach aimed at identifying quantitative morphological parameters useful in discriminating benign from malignant breast microcalcifications at digital mammography.
Materials and Methods
The study includes 31 patients in which microcalcifications had been detected during XR mammography and were further confirmed by stereotactic (XR-guided) biopsies. Patients were classified according to the BIRADS (Breast Imaging-Reporting and Data System), along with their parenchyma fractal dimension and biopsy size. A geometrical-topological characterization of microcalcifications was obtained as well.
Results
The ‘size of biopsy’ was the parameter endowed with the highest discriminant power between malignant and benign lesions thus confirming the reliability of surgeon judgment. The quantitative shape evaluation of both lesions and parenchyma allowed for a promising prediction of the BIRADS score. The area of lesions and parenchyma fractal dimension show a complex distribution for malignant breast calcifications that are consistent with their qualitative morphological pattern. Fractal dimension analysis enables the user to obtain reliable results as proved by its efficiency in the prediction of the morphology of breast cancer.
Conclusion
By reconstructing a phase-space distribution of biophysical parameters, different patterns of aggregation are recognized corresponding to different calcium deposition patterns, while the combination of tissue and microcalcification morphological descriptors provide a statistically significant prediction of tumour grade.
Clinical Relevance
The development of an automated morphology evaluation system can help during clinical evaluation while also sketching mechanistic hypotheses of microcalcification generation
Sweeping has no effect on renormalized turbulent viscosity
No full textWe perform renormalization group analysis (RG) of the Navier-Stokes equation in the presence of constant mean velocity field , and show that the renormalized viscosity is unaffected by , thus negating the ``sweeping effect", proposed by Kraichnan [Phys. Fluids {\bf 7}, 1723 (1964)] using random Galilean invariance. Using direct numerical simulation, we show that the correlation functions for and differ from each other, but the renormalized viscosity for the two cases are the same. Our numerical results are consistent with the RG calculations
A Unified Shell model for Buoyancy-Driven Turbulence
No full textWe construct a unified shell model for stably stratified and convective turbulence. Shell model simulation of stably stratified flow in turbulent regime exhibit Bolgiano-Obukhbov (BO) scaling in which the kinetic energy spectrum varies as . However, simulation of convective turbulence shows Kolmogorov's spectrum. These results are consistent with the direct numerical simulations of Kumar {\em et al.} [Phys. Rev. E {\bf 90}, 023016 (2014)]. We also observe a dual scaling ( and ) for a limited range of parameters in stably stratified flow
Energy transfers in small-scale and large-scale dynamos
No full textWe study energy transfers during magnetic energy growth in small-scale and large-scale dynamos. We perform direct numerical simulations for magnetic Prandtl number Pm =20 and 0.2 in a periodic box on 1024^3 grid. Energy fluxes and shell-to-shell energy transfers indicate that in small-scale dynamo for Pm =20, the magnetic energy growth takes place due to a non-local energy transfer from large-scale velocity field to small-scale magnetic field. On the other hand, in large-scale dynamo for Pm =0.2, local energy transfers from large-scale velocity field to large-scale magnetic field takes place
Role of the strain-rate tensor in turbulent scalar-transport modeling
No full textWe examine the geometric orientation of the subfilter-scale scalar-flux vector in homogeneous isotropic turbulence. Vector orientation is determined using the eigenframe of the resolved strain-rate tensor. The Schmidt number is kept sufficiently large so as to leave the velocity field, and hence, the strain-rate tensor, unaltered by filtering in the viscous-convective subrange. Strong preferential alignment is observed for the case of Gaussian and box filters, whereas the sharp-spectral filter leads to close to a random orientation. The orientation angle obtained with the Gaussian and box filters is largely independent of the filter-width and the Schmidt number. It is shown that the alignment direction observed numerically using these two filters is predicted very well by the tensor-diffusivity model. Further a-priori tests indicate poor alignment of the Smagorinsky and stretched vortex model predictions with the exact subfilter flux
Systems of Differential Operators and Generalized Verma Modules
Get PDFIn this paper we close the cases that were left open in our earlier works on the study of conformally invariant systems of second-order differential operators for degenerate principal series. More precisely, for these cases, we find the special values of the systems of differential operators, and determine the standardness of the homomorphisms between the generalized Verma modules, that come from the conformally invariant systems.The author was supported by the Global COE program at the Graduate School of Mathematical
Sciences, the University of Tokyo, Japan. He would like to be thankful for the referees for their
careful reading and invaluable comments
Inflammation-induced Id2 promotes plasticity in regulatory T cells
Get PDFT(H)17 cells originating from regulatory T (T-reg) cells upon loss of the T-reg-specific transcription factor Foxp3 accumulate in sites of inflammation and aggravate autoimmune diseases. Whether an active mechanism drives the generation of these pathogenic 'ex-Foxp3 T(H)17' cells, remains unclear. Here we show that pro-inflammatory cytokines enhance the expression of transcription regulator Id2, which mediates cellular plasticity of T-reg into 'ex-Foxp3' T(H)17 cells. Expression of Id2 in in vitro differentiated iT(reg) cells reduces the expression of Foxp3 by sequestration of the transcription activator E2A, leading to the induction of T(H)17-related cytokines. T-reg-specific ectopic expression of Id2 in mice significantly reduces the T-reg compartment and causes immune dysregulation. Cellular fate-mapping experiments reveal enhanced T-reg plasticity compared to wild-type, resulting in exacerbated experimental autoimmune encephalomyelitis pathogenesis or enhanced anti-tumor immunity. Our findings suggest that controlling Id2 expression may provide a novel approach for effective T-reg cell immunotherapies for both autoimmunity and cancer.11sciescopu
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