Dataset Information

Mechanical Communication Acts as a Noise Filter.

ABSTRACT: Cells can communicate mechanically by responding to mechanical deformations generated by their neighbors. Here, we describe a new role for mechanical communication by demonstrating that mechanical coupling between cells acts as a signaling cue that reduces intrinsic noise in the interacting cells. We measure mechanical interaction between beating cardiac cells cultured on a patterned flexible substrate and find that beat-to-beat variability decays exponentially with coupling strength. To demonstrate that such noise reduction is indeed a direct consequence of mechanical coupling, we reproduce the exponential decay in an assay where a beating cell interacts mechanically with an artificial stochastic 'mechanical cell'. The mechanical cell consists of a probe that mimics the deformations generated by a stochastically beating neighboring cardiac cell. We show that noise reduction through mechanical coupling persists long after stimulation stops and identify microtubule integrity, NOX2, and CaMKII as mediators of noise reduction.

SUBMITTER: Viner H

PROVIDER: S-EPMC6441679 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Mechanical Communication Acts as a Noise Filter.

Viner Hen H Nitsan Ido I Sapir Liel L Drori Stavit S Tzlil Shelly S

iScience 20190302

Cells can communicate mechanically by responding to mechanical deformations generated by their neighbors. Here, we describe a new role for mechanical communication by demonstrating that mechanical coupling between cells acts as a signaling cue that reduces intrinsic noise in the interacting cells. We measure mechanical interaction between beating cardiac cells cultured on a patterned flexible substrate and find that beat-to-beat variability decays exponentially with coupling strength. To demonst ...[more]

PMID: 30927696

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Project description:BACKGROUND:In this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise from dynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. We furthermore show how preprocessing images with this filter improves parametric images created from such dynamic sequence.We use zero-mean unit variance normalization, prior to performing a Hotelling filter on the slices of a dynamic time-series. The Scree-plot technique was used to determine which principal components to be rejected in the filter process. This filter was applied to [11C]-acetate on heart and head-neck tumors, [18F]-FDG on liver tumors and brain, and [11C]-Raclopride on brain. Simulations of blood and tissue regions with noise properties matched to real PET data, was used to analyze how quantitation and resolution is affected by the Hotelling filter. Summing varying parts of a 90-frame [18F]-FDG brain scan, we created 9-frame dynamic scans with image statistics comparable to 20 MBq, 60 MBq and 200 MBq injected activity. Hotelling filter performed on slices (2D) and on volumes (3D) were compared. RESULTS:The 2D Hotelling filter reduces noise in the tissue uptake drastically, so that it becomes simple to manually pick out regions-of-interest from noisy data. 2D Hotelling filter introduces less bias than 3D Hotelling filter in focal Raclopride uptake. Simulations show that the Hotelling filter is sensitive to typical blood peak in PET prior to tissue uptake have commenced, introducing a negative bias in early tissue uptake. Quantitation on real dynamic data is reliable. Two examples clearly show that pre-filtering the dynamic sequence with the Hotelling filter prior to Patlak-slope calculations gives clearly improved parametric image quality. We also show that a dramatic dose reduction can be achieved for Patlak slope images without changing image quality or quantitation. CONCLUSIONS:The 2D Hotelling-filtering of dynamic PET data is a computer-efficient method that gives visually improved differentiation of different tissues, which we have observed improve manual or automated region-of-interest delineation of dynamic data. Parametric Patlak images on Hotelling-filtered data display improved clarity, compared to non-filtered Patlak slope images without measurable loss of quantitation, and allow a dramatic decrease in patient injected dose.

Dataset Information

Mechanical Communication Acts as a Noise Filter.

Publications

Mechanical Communication Acts as a Noise Filter.

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