Literatura académica sobre el tema "Heterogeneity and plasticity"
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Artículos de revistas sobre el tema "Heterogeneity and plasticity"
Margadant, Coert. "Endothelial heterogeneity and plasticity". Angiogenesis 24, n.º 2 (mayo de 2021): 197–98. http://dx.doi.org/10.1007/s10456-021-09794-6.
Texto completoFriedmann-Morvinski, Dinorah. "Glioblastoma Heterogeneity and Cancer Cell Plasticity". Critical Reviews in Oncogenesis 19, n.º 5 (2014): 327–36. http://dx.doi.org/10.1615/critrevoncog.2014011777.
Texto completoMeacham, Corbin E. y Sean J. Morrison. "Tumour heterogeneity and cancer cell plasticity". Nature 501, n.º 7467 (septiembre de 2013): 328–37. http://dx.doi.org/10.1038/nature12624.
Texto completoMorel, F. y N. Huyen. "Plasticity and damage heterogeneity in fatigue". Theoretical and Applied Fracture Mechanics 49, n.º 1 (febrero de 2008): 98–127. http://dx.doi.org/10.1016/j.tafmec.2007.10.006.
Texto completoPabst, Reinhard. "Plasticity and heterogeneity of lymphoid organs". Immunology Letters 112, n.º 1 (septiembre de 2007): 1–8. http://dx.doi.org/10.1016/j.imlet.2007.06.009.
Texto completoMarjanovic, Nemanja D., Robert A. Weinberg y Christine L. Chaffer. "Cell Plasticity and Heterogeneity in Cancer". Clinical Chemistry 59, n.º 1 (1 de enero de 2013): 168–79. http://dx.doi.org/10.1373/clinchem.2012.184655.
Texto completoKhan, Arshad, Vipul Kumar Singh, Robert L. Hunter y Chinnaswamy Jagannath. "Macrophage heterogeneity and plasticity in tuberculosis". Journal of Leukocyte Biology 106, n.º 2 (2 de abril de 2019): 275–82. http://dx.doi.org/10.1002/jlb.mr0318-095rr.
Texto completoLüönd, Fabiana, Stefanie Tiede y Gerhard Christofori. "Breast cancer as an example of tumour heterogeneity and tumour cell plasticity during malignant progression". British Journal of Cancer 125, n.º 2 (6 de abril de 2021): 164–75. http://dx.doi.org/10.1038/s41416-021-01328-7.
Texto completoSun, Wenfei, Salvatore Modica, Hua Dong y Christian Wolfrum. "Plasticity and heterogeneity of thermogenic adipose tissue". Nature Metabolism 3, n.º 6 (junio de 2021): 751–61. http://dx.doi.org/10.1038/s42255-021-00417-4.
Texto completoLee, Sunju, Inho Choi y Young-Kwon Hong. "Heterogeneity and Plasticity of Lymphatic Endothelial Cells". Seminars in Thrombosis and Hemostasis 36, n.º 03 (abril de 2010): 352–61. http://dx.doi.org/10.1055/s-0030-1253457.
Texto completoTesis sobre el tema "Heterogeneity and plasticity"
Chappell, Joel. "Vascular smooth muscle cell heterogeneity and plasticity in models of cardiovascular disease". Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/274543.
Texto completoFolguera, Blasco Núria. "Stochastic modelling of epigenetic regulation: analysis of its heterogeneity and its implications in cell plasticity". Doctoral thesis, Universitat Autònoma de Barcelona, 2018. http://hdl.handle.net/10803/666963.
Texto completoIn this thesis, we aim at understanding the importance of epigenetic regulation(ER) in cell fate decisions and transitions. In order to address this issue, we first formulate a stochastic model of epigenetic regulation. Within this model, we focus our discus- sion in cell reprogramming, i.e. the system moves from the differentiated epi-phenotype, characterised by differentiation(pluripotency) ER system open(closed), to the pluripotent epi-phenotype, where the ER system for differentiation(pluripotency) is closed(open). In particular, within the intrinsic heterogeneity existing in ER systems, we identify the appearance of two relevant scenarios: the resilient scenario, where reprogramming cannot occur, and the plastic one, which is the one allowing for the switch from the di erentiated epi-phenotype to the pluripotent epi-phenotype. The latter, which is characterised by ex- hibiting epigenetic plasticity, has been linked to ageing. In fact, when just ageing e ects are considered in the ER model, the system displays a `healthy' plasticity, where the stem-cell like properties can be acquired, but then, the ER system can go back to the dif- ferentiated epi-phenotype. This scenario may be related to regeneration and rejuvenation of tissues. Nevertheless, when ageing is considered along with epigenetic dis-regulations, which are likely to occur withing ageing cells/tissues, the plastic state leads to a patholog- ical plasticity, where stem cell features are acquired irreversibly. This scenario is the one which may predispose the system to cancer, as it implies the accumulation of undecided epi-phenotypes with the pluripotency ER system sustained in its on state. In order to further analyse this issue, we formulate a general framework for the study of a combined epigenetic regulation-gene regulatory network (ER-GRN)stochastic multi- scale model, which we later focus on our particular case of interest, i.e. a 2 gene regulatory network with one gene promoting differentiation and one gene promoting pluripotency. When analysing the ER-GRN model formulated, we show that the role played by ER is central since it allows the GRN to switch state, i.e. cell fate transitions from the differ- entiated phenotype to the pluripotent one (reprogramming) or vice versa (differentiation). The ER-GRN model allows to identify which ER systems are responsible for locking the cell in a stem cell like state and our formulation allows us to design epigenetic-based strategies able to obtain differentiation-primed cells from differentiation-resilient cells. Such strategies are of key relevance in the treatment of cancer and other age-associated diseases.
DI, FILIPPO MARZIA. "NEW CONSTRAINT-BASED APPROACHES TO TACKLE THE MULTIPLE SIDES OF CELL METABOLIC PLASTICITY AND HETEROGENEITY". Doctoral thesis, Università degli Studi di Milano-Bicocca, 2019. http://hdl.handle.net/10281/241163.
Texto completoPlasticity, heterogeneity and modelling approach constitute the three pillars on the top of which this thesis investigates the complexity of cell metabolism. The multiple sides of metabolic plasticity have been explored as cell adaptive response to varying conditions, demand and perturbations under both physiological and pathological conditions. By investigating cell populations as homogeneous and heterogeneous systems, new in silico predictive models and novel computational constraint-based methodologies have been defined. This work started from the investigation of cell populations as homogeneous systems, where the average behaviour is described and cell-to-cell differences are temporarily hidden. Reconstructing high-quality genome-scale metabolic models is crucial to computationally address cell metabolism and organize all the available metabolic knowledge of given cells or organisms. Although multiple tools for performing this task already exist, a pipeline for the semi-automatic reconstruction of genome-scale networks has been proposed to solve some current critical issues and generate higher quality models. The application of this approach for the genome-wide metabolic reconstruction of yeast Zygosaccharomyces parabailii showed adherence of in silico simulations to experimental data and literature findings. Moreover, metabolic plasticity in response to different metabolic regimes has been explored through constraint-based modelling. The potentialities of genome-scale reconstructions in mirroring the systemic perspective coexist with difficulty in their management. In this work, greater control is achieved by switching to smaller-scale core networks. In particular, core modelling has been exploited as an effective mean to investigate intertumoural heterogeneity, and plasticity of the implemented tumour metabolic programs as adaptation to different environmental scenarios. The effectiveness of homogeneous systems to lower overall system complexity level without compromising biological validity of in silico outcomes goes along with the need to address cell-to-cell variations of cell populations. In this regard, classic constraint-based modelling has been extended to deal with heterogeneous systems. A new strategy, called popFBA, has been developed to reconstruct and simulate cell populations metabolism, by putting emphasis on the relationships established among their components. Using as case study the ecosystemic view of cancer populations, popFBA highlighted that the achievement of optimal biomass is consistent with metabolic plasticity of population components under different scenarios together with a cooperative behaviour. At the same time, countless combinations of flux distributions for the individual population components prompted to develop a novel methodology called single-cell Flux Balance Analysis (scFBA). This metodology integrates single-cell transcriptomics data as further constraints on the individual components through the computation for each reaction of a Reaction Activity Score, which we implemented in a previous computational framework called MaREA. In this way, scFBA efficiently reduced the amount of allowable individual flux distributions, and captured complex networks of interactions between cells of a specific population. In view of the findings of this research, a deep characterization of metabolic plasticity within cell populations and of the intricate dialogue between cells and their environment can assist the formulation of more rational and personalized strategies. Their devising could enable to hamper disease progression, or to exploit metabolism of given microorganisms for producing relevant chemical compounds.
Konnully, Augustus Meera Bessy. "Characterization of cellular heterogeneity in Diffuse Low Grade Glioma". Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTT038.
Texto completoDiffuse Low-Grade Gliomas (DLGG) are WHO grade II glial tumors affecting younger adults. They are characterized as silent, slow growing tumors with fewer mitotic activities. However, they diffuse and invade the healthy brain via blood vessels and nerve fibers. These, over a period of years develop to malignant Glioblastoma, aggressive brain tumors where patients have an average medial survival of 12-15 months after diagnosis. Ill-defined phenotypic and cellular diversity of DLGG poses serious limitation to treatment and prevention at the early stage.In my PhD thesis, I aimed to address this limitation by characterizing the cellular heterogeneity in IDH1-mutated DLGG. By performing immunofluorescence analysis on grade II astrocytoma and oligodendroglioma, I have identified two largely non-overlapping cellular subpopulations expressing SOX9 and OLIG1 transcription factors, which represent astrocyte-like and oligodendrocyte-like cells, respectively. Upon further investigation, I have shown that these subpopulations express distinct molecular markers. Sox9 cells are associated with APOE, KCNN3, CRYAB and ID4, while Olig1 cells showed strong correlation with the expression of PDGFRA, SOX8, MASH1, and SOX4. In addition, the sox9 cells show a particular activation of signaling pathways including Notch, BMP and their downstream targets.To ascertain the role of Notch signaling in regulating the formation of these tumoral subpopulations, I used magnetic sorting of tumor cells from freshly resected glioma samples and overexpressed Notch Intracellular Domain (NICD), an active form of Notch. Increased Notch activation resulted in an upregulation of Sox9- and downregulation of Olig1-associated cell markers. I have then extended these analyses on one anaplastic IDH1 mutated patient derived cell line which reproduced similar gene expression profile confirming the robustness of the role of Notch signaling in regulating the plasticity of the cells. Parallel experiments performed by activation of Bone Morphogenetic Protein (BMP) signaling on IDH1 mutated cell line did not show a prominent effect on the plasticity. Nevertheless, BMP signal activation highly upregulated CRYAB, a SOX9 related marker and downregulated OLIG1 and OLIG2.In conclusion, I have identified two non-overlapping tumor subpopulations in diffuse low-grade gliomas and demonstrated the deterministic role of Notch signaling pathway in their formation. I believe that these findings would aid in better understanding tumoral heterogeneity in DLGG and be extended in designing new therapeutic strategies against these tumors
du, Plessis Darren Scott. "Temporal interactions with flamingo foraging plasticity: ecological effects on basal resources and benthic heterogeneity". Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29623.
Texto completoChi, Ma. "Improving the Plasticity of Metallic Glass through Heterogeneity Induced by Electropulsing-assisted Surface Severe Plastic Deformation". University of Akron / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1555595868348676.
Texto completoEinsmann, Juliet Caroline Jr. "Nutrient Foraging in Ten Southeast Coastal Plain Plant Species". Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36849.
Texto completoMaster of Science
Conlon, Kelly Timothy. "The effect of mesoscopic spatial heterogeneity on the plastic deformation of Al-Cu alloys". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0004/NQ42838.pdf.
Texto completoLi, Xiaoshuang. "Identification and Phenotypic Plasticity of Metastatic Cells in a Mouse Model of Melanoma". FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3472.
Texto completoMadrid, Canales Ignacio. "Model of Cellular Growth under Stress : Emergence of Heterogeneity and Impact of the Environment". Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAX008.
Texto completoThis thesis focuses on understanding individual-scale cell growth under stress. Starting from the analysis of the data collected by Sebastián Jaramillo and James Broughton under the supervision of Meriem El Karoui, we have developed various models to comprehend the impact of the heterogeneous response to genotoxic stress (SOS response) on the growth of a Escherichia coli populations. We employ measure-values stochastic processes to model the dynamics of these populations.Firstly, we construct a stochastic model based on the "adder" size-control model, extended to incorporate the dynamics of the SOS response and its effect on cell division. The chosen framework is parametric, and the model is fitted by maximum likelihood to individual lineage data obtained in mother machine. This allows us to quantitatively compare inferred parameters in different environments.Next, we explore the ergodic properties of a more general model than the "adder," addressing open questions about its long-time behaviour. We consider a general deterministic flow and a fragmentation kernel that is not necessarily self-similar. We demonstrate the existence of eigenelements. Then, a Doob dollar_h_dollar-transform with the found eigenfunction reduces the problem to the study of a conservative process. Finally, by proving a "petite set" property for the compact sets of the state space, we obtain the exponential convergence.Finally, we consider a bitype age-structured model capturing the phenotypic plasticity observed in the stress response. We study the survival probability of the population and the population growth rate in constant and periodic environments. We evince a trade-off for population establishment, as well as a sensitivity with respect to the model parameters that differs for survival probability and growth rate.We conclude with an independent section, collaborative work initiated during CEMRACS 2022. We investigate numerically the spatial propagation of size-structured populations modeling the collective movement of Myxobacteria clusters via a system of reaction-diffusion equations
Capítulos de libros sobre el tema "Heterogeneity and plasticity"
Sousa, Bárbara, Ana Sofia Ribeiro y Joana Paredes. "Heterogeneity and Plasticity of Breast Cancer Stem Cells". En Stem Cells Heterogeneity in Cancer, 83–103. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14366-4_5.
Texto completoBrasier, Allan R. "Innate Immunity, Epithelial Plasticity, and Remodeling in Asthma". En Precision Approaches to Heterogeneity in Asthma, 265–85. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32259-4_13.
Texto completoTripathi, Shubham, Jianhua Xing, Herbert Levine y Mohit Kumar Jolly. "Mathematical Modeling of Plasticity and Heterogeneity in EMT". En Methods in Molecular Biology, 385–413. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0779-4_28.
Texto completoSoumelis, Vassili, Yong-Jun Liu y Michel Gilliet. "Dendritic Cell Biology: Subset Heterogeneity and Functional Plasticity". En The Biology of Dendritic Cells and HIV Infection, 3–43. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/978-0-387-33785-2_1.
Texto completoKudo, Yoshihisa, Etsuro Ito y Akihiko Ogura. "Topographical Heterogeneity of Glutamate Agonist-Induced Calcium Increase in Hippocampus". En Excitatory Amino Acids and Neuronal Plasticity, 125–33. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-5769-8_15.
Texto completovan Diggelen, Fuda, Matteo de Carlo, Nicolas Cambier, Eliseo Ferrante y Guszti Eiben. "Emergence of Specialised Collective Behaviors in Evolving Heterogeneous Swarms". En Lecture Notes in Computer Science, 53–69. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70068-2_4.
Texto completoKoyama, Motomichi, Hiroshi Noguchi y Kaneaki Tsuzaki. "Microstructural Crack Tip Plasticity Controlling Small Fatigue Crack Growth". En The Plaston Concept, 213–34. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7715-1_10.
Texto completoKneppers, Jeroen, Andries M. Bergman y Wilbert Zwart. "Prostate Cancer Epigenetic Plasticity and Enhancer Heterogeneity: Molecular Causes, Consequences and Clinical Implications". En Advances in Experimental Medicine and Biology, 255–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11836-4_15.
Texto completoMazloom, Amin R., Kalyan Basu, Subhrangsu S. Mandal y Sajal K. Das. "Modeling a Complex Biological Network with Temporal Heterogeneity: Cardiac Myocyte Plasticity as a Case Study". En Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 467–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02466-5_46.
Texto completoDewitt, Thomas J. y R. Brian Langerhans. "Integrated Solutions to Environmental Heterogeneity: Theory of Multimoment Reaction Norms". En Phenotypic Plasticity, 98–111. Oxford University PressNew York, NY, 2004. http://dx.doi.org/10.1093/oso/9780195138962.003.0007.
Texto completoActas de conferencias sobre el tema "Heterogeneity and plasticity"
Durand, Simon, Valentina Boeva, Caroline Louis-Brennetot, Agathe Peltier, Cécile Pierre-Eugène, Sylvain Baulande, Olivier Delattre y Isabelle Janoueix-Lerosey. "Abstract B20: Deciphering heterogeneity and plasticity in neuroblastoma". En Abstracts: AACR Special Conference: Pediatric Cancer Research: From Basic Science to the Clinic; December 3-6, 2017; Atlanta, Georgia. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.pedca17-b20.
Texto completoMejias, J. F., H. J. Kappen, A. Longtin y J. J. Torres. "Short-term synaptic plasticity and heterogeneity in neural systems". En PHYSICS, COMPUTATION, AND THE MIND - ADVANCES AND CHALLENGES AT INTERFACES: Proceedings of the 12th Granada Seminar on Computational and Statistical Physics. AIP, 2013. http://dx.doi.org/10.1063/1.4776513.
Texto completoFrost, Miroslav, Petr Sedlák, Hanuš Seiner, Jan Valdman, Alexej Moskovka y Petr Šittner. "Constitutive Model for NiTi Polycrystalline Alloys Undergoing Transformation and Plastic Deformation Processes". En SMST 2024. ASM International, 2024. http://dx.doi.org/10.31399/asm.cp.smst2024p0082.
Texto completoNatsuizaka, Mitsuteru, Shinya Ohashi, Seiji Naganuma, Ross A. Kalman, Asami Ohyama, Ben Rhoades, Maria E. Vega et al. "Abstract 5194: Notch regulates squamous differentiation, cell plasticity and tumor heterogeneity in esophageal carcinoma". En Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/1538-7445.am2011-5194.
Texto completoTing, David T. "Abstract IA-02: Pancreatic cancer heterogeneity and plasticity: The mix of seed and soil". En Abstracts: AACR Virtual Special Conference on Pancreatic Cancer; September 29-30, 2020. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.panca20-ia-02.
Texto completoHANON, Guillaume. "Heterogeneity of strain and texture inside roll-bonded multilaminates". En Material Forming. Materials Research Forum LLC, 2024. http://dx.doi.org/10.21741/9781644903131-191.
Texto completoWinter, Peter S., Srivatsan Raghavan, Andrew Navia, Hannah Williams, Alan DenAdel, Radha Kalekar, Jennyfer Galvez-Reyes et al. "Abstract PR03: Subtype-specific microenvironmental crosstalk and tumor cell plasticity in metastatic pancreatic cancer". En Abstracts: AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; September 17-18, 2020. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.tumhet2020-pr03.
Texto completoZhang, Zeda, Chuanli Zhou, Xiaoling Li, Spencer Barnes, Su Deng, Elizabeth Hoover, Chi-Chao Chen et al. "Abstract NG06: CHD1-loss confers AR targeted therapy resistance via promoting cancer heterogeneity and lineage plasticity". En Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-ng06.
Texto completoClairambault, Jean. "Mathematical Modelling of Cancer Growth and Drug Treatments: Taking Into Account Cell Population Heterogeneity and Plasticity". En 2023 European Control Conference (ECC). IEEE, 2023. http://dx.doi.org/10.23919/ecc57647.2023.10178266.
Texto completoSedlak, Petr, Miroslav Frost, Hanus Seiner, Ludek Heller y Petr Sittner. "Thermodynamical Model of NiTi SMA Including Plastic Deformation Mechanisms". En SMST2022. ASM International, 2022. http://dx.doi.org/10.31399/asm.cp.smst2022p0065.
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