Learning by structural remodeling in a class of single cell models

2008 ◽  
Vol 25 (2) ◽  
pp. 282-295 ◽  
Author(s):  
K. J. Kelleher ◽  
V. Hajdik ◽  
C. M. Colbert ◽  
K. Josić
Keyword(s):  
Single Cell ◽  
Cell Models ◽  
Structural Remodeling

scholarly journals EPEN-21. IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION IN PEDIATRIC EPENDYMOMA REVEALED BY SINGLE-CELL RNA-SEQ

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii311-iii312
Author(s):  
Bernhard Englinger ◽  
Johannes Gojo ◽  
Li Jiang ◽  
Jens M Hübner ◽  
McKenzie L Shaw ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Regulatory Networks ◽  
Target Genes ◽  
Target Identification ◽  
Rna Seq ◽  
Cell Models ◽  
Pediatric Ependymoma ◽  
Glial Fate ◽  
Anatomic Locations

Abstract Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets including IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.

Computational Modelling of Optogenetics in Cardiac Cells

2012 ◽  
Author(s):  
Jonathan Wong ◽  
Oscar Abilez ◽  
Ellen Kuhl
Keyword(s):  
Finite Element ◽  
Ion Channel ◽  
Single Cell ◽  
Cardiac Myocytes ◽  
Cardiac Tissue ◽  
Channel Model ◽  
Computational Modelling ◽  
Cardiac Cells ◽  
Cardiac Cell ◽  
Cell Models

Channelrhodopsin-2 (ChR2) is a light-activated ion channel that can allow scientists to electrically activate cells via optical stimulation. Using a combination of existing computational electrophysiological and mechanical cardiac cell models with a novel ChR2 ion channel model, we created a model for ChR2-transduced cardiac myocytes. We implemented this model into a commonly available finite element platform and simulated both the single cell and the tissue electromechanical response. Our simulations show that it is possible to stimulate cardiac tissue optically with ChR2-transduced cells.

scholarly journals Global Sensitivity Analysis of Arrhythmic Risk Biomarkers in Cardiac Single Cell Models

2012 ◽  
Vol 102 (3) ◽  
pp. 596a
Author(s):  
Anna A. Sher ◽  
Paul Carter ◽  
Blair Bethwaite ◽  
Denis Noble ◽  
David Abramson ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Single Cell ◽  
Global Sensitivity Analysis ◽  
Cell Models ◽  
Global Sensitivity ◽  
Risk Biomarkers

Constructing 3D Model of Hardwood Structure

2016 ◽  
Vol 719 ◽  
pp. 9-13
Author(s):  
Zhuo Kai Qin ◽  
Jia Sheng Zhang ◽  
Yu Tian Yang ◽  
Jian Ju Luo ◽  
Wei Gao
Keyword(s):  
Single Cell ◽  
Wood Fiber ◽  
Wood Block ◽  
Cell Models ◽  
Fiber Cells ◽  
Modeling Technology ◽  
Vessel Elements ◽  
Ray Cells ◽  
Ficus Microcarpa ◽  
Tissue Models

Model constructing was conducted with 3D Studio Max modeling technology for hardwood minute structure in three steps. In the first step, the single-cell models were built according to the true form and shape of various kinds of cells, including vessel elements, wood-fiber cells, longitudinal parenchyma cells and ray cells. In the second step, the single-tissue models for all the four kinds of wood tissues (vessel, wood-fiber, longitudinal parenchyma and wood ray) were constructed by setting the same kind of single-cell models together according to the cell grouping ways inside true wood. In the third step, according to the distributing and arranging ways of the four kinds of wood tissues inside true wood, the whole model of wood block in minute structure was constructed by assembling the four kind of single-tissue models in a block. After that, the virtual model in computer was materialized by means of modern 3D printing technology, and finally the solid model in minute structure of Ficus microcarpa wood was constructed.

Single-cell models: promise and limitations

1999 ◽  
Vol 71 (1-3) ◽  
pp. 225-228 ◽  
Author(s):  
M.L Shuler
Keyword(s):  
Single Cell ◽  
Cell Models

scholarly journals On the origins and conceptual frameworks of natural plasticity—Lessons from single-cell models in C. elegans

2021 ◽  
Author(s):  
Julien Lambert ◽  
Carla Lloret-Fernández ◽  
Lucie Laplane ◽  
Richard J. Poole ◽  
Sophie Jarriault
Keyword(s):  
Single Cell ◽  
Cell Models ◽  
Conceptual Frameworks ◽  
C Elegans

scholarly journals Single cell analysis reveals molecular signatures of HIV latency in primary cell models

2019 ◽  
Vol 5 ◽  
pp. 4
Author(s):  
S. Telwatte ◽  
M. Montano ◽  
R. Resop ◽  
E. Battivelli ◽  
S. Morón-López ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Primary Cell ◽  
Hiv Latency ◽  
Molecular Signatures ◽  
Cell Analysis ◽  
Cell Models

scholarly journals Fitting single-cell models to voltage- and current-clamp data: Bayesian filtering

2010 ◽  
Vol 11 (S1) ◽  
Author(s):  
Sean G Carver ◽  
Michael L Hines
Keyword(s):  
Single Cell ◽  
Bayesian Filtering ◽  
Cell Models ◽  
Current Clamp

Guiding the modeller: organizing and selecting experimental data for single cell models using the CoCoDat database

2003 ◽  
Vol 52-54 ◽  
pp. 239-245
Author(s):  
Jonas-D. Johnsen ◽  
Klaas Stephan ◽  
Jürgen Maier ◽  
Heiko Luhmann ◽  
Rolf Kötter
Keyword(s):  
Experimental Data ◽  
Single Cell ◽  
Cell Models
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