Automated monitoring of cell concentration and viability using an image analysis system

Maruhashi, Fumio; Murakami, S.; Baba, Kenji

doi:10.1007/978-94-011-0257-5_31

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Process information from on-line systems, such as mass spectrometers or probes can be used to calculate carbon dioxide evolution (Pelletier et al, 1994) and oxygen uptake rates (Kyung et al, 1994) to provide re-latively noisy estimates of the cell density. Direct process information of the cell density has been obtained by a microscopic imaging analysis system developed by Maruhashi et al (1994) to determine cell size and viability without sampling or staining. The dead cell concentrations, and corresponding viability, were correlated to the number of small, cell debris particles.…”

Section: Introductionmentioning

confidence: 99%

Untitled

et al. 2003

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Consistent perfusion culture production requires reliable cell retention and control of feed rates. An on-line cell probe based on capacitance was used to assay viable biomass concentrations. A constant cell specific perfusion rate controlled medium feed rates with a bioreactor cell concentration of approximately 5 x 10(6) cells mL(-1). Perfusion feeding was automatically adjusted based on the cell concentration signal from the on-line biomass sensor. Cell specific perfusion rates were varied over a range of 0.05 to 0.4 nL cell(-1) day(-1). Pseudo-steady-state bioreactor indices (concentrations, cellular rates and yields) were correlated to cell specific perfusion rates investigated to maximize recombinant protein production from a Chinese hamster ovary cell line. The tissue-type plasminogen activator concentration was maximized ( approximately 40 mg L(-1)) at 0.2 nL cell(-1) day(-1). The volumetric protein productivity ( approximately 60 mg L(-1) day(-1) was maximized above 0.3 nL cell(-1) day(-1). The use of cell specific perfusion rates provided a straightforward basis for controlling, modeling and optimizing perfusion cultures.

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Section: Introductionmentioning

confidence: 99%

Untitled

et al. 2003

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“…These systems involve circulation loops to bring the sample to the microscope. The major problem with online systems is the limited depth of focus, so the cells need to be kept close to the focus plane by forcing them through a capillary or flow cell (Maruhashi et al 1994;Yu et al 2005). Galindo et al (2005) described an image analysis technique for the in situ characterization of dispersions occurring in bioreactors.…”

Section: Operation Modementioning

confidence: 99%

Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review

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et al. 2013

Environ Sci Pollut Res

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Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.

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“…A first approach in order to analyze animal cell cultures by means of in situ microscopy and image analysis was proposed 1994 by Maruhashi et al Here, the amount of cell debris particles within low quality bright field micrographs was determined, allowing for an indirect estimation of the culture's viability (Maruhashi et al, 1994). More recently, a novel system for online biomass determination of mammalian cell cultures was introduced.…”

Section: Introductionmentioning

confidence: 99%