Metabolic imaging in multiple time scales

Ramanujan, V. Krishnan

doi:10.1016/j.ymeth.2013.08.027

Cited by 8 publications

(3 citation statements)

References 44 publications

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“…In an attempt to improve metabolic imaging, alternative strategies have been developed, such as an introduction of the OMI index 25 or the time-correlated dynamics of a mitochondrial membrane potential reporter fluorescence. 44 Due to the complex variation and conformational heterogeneity of free and bound NADH, global analysis of spectral-and time-resolved data could resolve the system. Different global analysis algorithms have been developed.…”

Section: Discussionmentioning

confidence: 99%

Spectrally resolved fluorescence lifetime imaging to investigate cell metabolism in malignant and nonmalignant oral mucosa cells

et al. 2014

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Fluorescence-guided diagnosis of tumor tissue is in many cases insufficient, because false positive results interfere with the outcome. Improvement through observation of cell metabolism might offer the solution, but needs a detailed understanding of the origin of autofluorescence. With respect to this, spectrally resolved multiphoton fluorescence lifetime imaging was investigated to analyze cell metabolism in metabolic phenotypes of malignant and nonmalignant oral mucosa cells. The time-resolved fluorescence characteristics of NADH were measured in cells of different origins. The fluorescence lifetime of bound and free NADH was calculated from biexponential fitting of the fluorescence intensity decay within different spectral regions. The mean lifetime was increased from nonmalignant oral mucosa cells to different squamous carcinoma cells, where the most aggressive cells showed the longest lifetime. In correlation with reports in the literature, the total amount of NADH seemed to be less for the carcinoma cells and the ratio of free/bound NADH was decreased from nonmalignant to squamous carcinoma cells. Moreover for squamous carcinoma cells a high concentration of bound NADH was found in cytoplasmic organelles (mainly mitochondria). This all together indicates that oxidative phosphorylation and a high redox potential play an important role in the energy metabolism of these cells.

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Section: Discussionmentioning

confidence: 99%

Spectrally resolved fluorescence lifetime imaging to investigate cell metabolism in malignant and nonmalignant oral mucosa cells

et al. 2014

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“…Signals from certain luminescent systems require fractal/chaos based approaches for their analysis [ 42 , 43 ]. Several authors used the Fano factor [ 44 – 46 ], Hurst exponent [ 9 , 47 , 48 ] or further advanced methods such as description in terms of quantum squeezed states [ 49 – 51 ] to analyze photonic data and found correlations with biological parameters. However, most of these earlier works either did not use any detrending or used just a simple subtraction of the mean value of the signals so the interpretation of their results is ambiguous [ 52 ].…”

Section: Resultsmentioning

confidence: 99%

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

2017

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Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

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“…High resolution immunofluorescence images were obtained in a Leica confocal microscope platform (fixed tissues and cells) or in a Leica two-photon excitation microscope platform (3D live cell cultures) as described elsewhere. [13,14,11] All the data presented in this paper are mean ± S.E from at least three independent experiments unless otherwise mentioned. Statistical significance was estimated based on Student’s t-test (p < 0.05).…”

Section: Methodsmentioning

confidence: 99%

Targeting metabolic plasticity in breast cancer cells via mitochondrial complex I modulation

Biener-Ramanujan

Yang

et al. 2015

Breast Cancer Res Treat

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Purpose Heterogeneity commonly observed in clinical tumors stems both from the genetic diversity as well as from the differential metabolic adaptation of multiple cancer types during their struggle to maintain uncontrolled proliferation and invasion in vivo. This study aims to identify a potential metabolic window of such adaptation in aggressive human breast cancer cell lines. Methods With a multidisciplinary approach using high resolution imaging, cell metabolism assays, proteomic profiling and animal models of human tumor xenografts and via clinically-relevant, pharmacological approach for modulating mitochondrial complex I function in human breast cancer cell lines, we report a novel route to target metabolic plasticity in human breast cancer cells. Results By a systematic modulation of mitochondrial function and by mitigating metabolic switch phenotype in aggressive human breast cancer cells, we demonstrate that the resulting metabolic adaptation signatures can predictably decrease tumorigenic potential in vivo. Proteomic profiling of the metabolic adaptation in these cells further revealed novel protein-pathway interactograms highlighting the importance of antioxidant machinery in the observed metabolic adaptation. Conclusions Improved metabolic adaptation potential in aggressive human breast cancer cells contribute to improving mitochondrial function and reducing metabolic switch phenotype –which may be vital for targeting primary tumor growth in vivo.

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Metabolic imaging in multiple time scales

Cited by 8 publications

References 44 publications

Spectrally resolved fluorescence lifetime imaging to investigate cell metabolism in malignant and nonmalignant oral mucosa cells

Spectrally resolved fluorescence lifetime imaging to investigate cell metabolism in malignant and nonmalignant oral mucosa cells

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

Targeting metabolic plasticity in breast cancer cells via mitochondrial complex I modulation

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