Literature DB >> 9181304

Computer-based technique for cell aggregation analysis and cell aggregation in in vitro chondrogenesis.

I Martin1, B Dozin, R Quarto, R Cancedda, F Beltrame.   

Abstract

No quantitative methods are currently available to measure different aggregation parameters in cell cultures. In this paper we describe a computer-based technique for the automatic and reliable analysis of cellular aggregates, starting from optical microscopy images of living cells grown in suspension. The method allows determination, on the same sample at different time intervals, of quantitative parameters, including aggregation percentage, average number of cells in aggregates, and aggregate size statistical distribution. To determine the number of cells in an aggregate starting from its two-dimensional microscopic profile, a model has been proposed and verified, using sphere packing theory. Algorithms have been tested on chondrocyte suspension cultures, where cell aggregation is a very early and critical event leading to cell differentiation. Using this technique for the analysis of chick embryo chondrocyte cultures, we observed that aggregate size and development kinetics depend on the culture conditions used. The method, with minor adaptations, is of potential use also in other cell systems to evaluate aggregation indexes or to study aggregation kinetics.

Entities:  

Mesh:

Year:  1997        PMID: 9181304     DOI: 10.1002/(sici)1097-0320(19970601)28:2<141::aid-cyto7>3.0.co;2-i

Source DB:  PubMed          Journal:  Cytometry        ISSN: 0196-4763


  18 in total

1.  Three-dimensional Image-based Mechanical Modeling for Predicting the Response of Breast Cancer to Neoadjuvant Therapy.

Authors:  Jared A Weis; Michael I Miga; Thomas E Yankeelov
Journal:  Comput Methods Appl Mech Eng       Date:  2016-09-01       Impact factor: 6.756

2.  Predicting in vivo glioma growth with the reaction diffusion equation constrained by quantitative magnetic resonance imaging data.

Authors:  David A Hormuth; Jared A Weis; Stephanie L Barnes; Michael I Miga; Erin C Rericha; Vito Quaranta; Thomas E Yankeelov
Journal:  Phys Biol       Date:  2015-06-04       Impact factor: 2.583

3.  Enhanced production of human recombinant proteins from CHO cells grown to high densities in macroporous microcarriers.

Authors:  T Tharmalingam; K Sunley; M Spearman; M Butler
Journal:  Mol Biotechnol       Date:  2011-11       Impact factor: 2.695

4.  A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict in vivo glioma growth.

Authors:  David A Hormuth; Jared A Weis; Stephanie L Barnes; Michael I Miga; Erin C Rericha; Vito Quaranta; Thomas E Yankeelov
Journal:  J R Soc Interface       Date:  2017-03       Impact factor: 4.118

5.  Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer.

Authors:  David A Hormuth; Jared A Weis; Stephanie L Barnes; Michael I Miga; Vito Quaranta; Thomas E Yankeelov
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-12-13       Impact factor: 7.038

6.  Predicting the Response of Breast Cancer to Neoadjuvant Therapy Using a Mechanically Coupled Reaction-Diffusion Model.

Authors:  Jared A Weis; Michael I Miga; Lori R Arlinghaus; Xia Li; Vandana Abramson; A Bapsi Chakravarthy; Praveen Pendyala; Thomas E Yankeelov
Journal:  Cancer Res       Date:  2015-09-02       Impact factor: 12.701

7.  A mechanically coupled reaction-diffusion model for predicting the response of breast tumors to neoadjuvant chemotherapy.

Authors:  Jared A Weis; Michael I Miga; Lori R Arlinghaus; Xia Li; A Bapsi Chakravarthy; Vandana Abramson; Jaime Farley; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2013-08-06       Impact factor: 3.609

8.  Parameterizing the Logistic Model of Tumor Growth by DW-MRI and DCE-MRI Data to Predict Treatment Response and Changes in Breast Cancer Cellularity during Neoadjuvant Chemotherapy.

Authors:  Nkiruka C Atuegwu; Lori R Arlinghaus; Xia Li; A Bapsi Chakravarthy; Vandana G Abramson; Melinda E Sanders; Thomas E Yankeelov
Journal:  Transl Oncol       Date:  2013-06-01       Impact factor: 4.243

9.  Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results.

Authors:  Angela M Jarrett; David A Hormuth; Stephanie L Barnes; Xinzeng Feng; Wei Huang; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2018-05-17       Impact factor: 3.609

10.  Characterization and deposition of respirable large- and small-particle bioaerosols.

Authors:  Richard J Thomas; Daniel Webber; William Sellors; Aaron Collinge; Andrew Frost; Anthony J Stagg; Stephen C Bailey; Pramukh N Jayasekera; Rosa R Taylor; Steve Eley; Richard W Titball
Journal:  Appl Environ Microbiol       Date:  2008-08-22       Impact factor: 4.792

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