fluorescence-recovery-after-merging-droplet-to-measure-two

Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer

We introduce a new method to measure the lateral diffusivity of a surfactant monolayer at the fluid-fluid interface, called fluorescence recovery after ...

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In this paper, an entropy based method for quantifying the depth of anesthesia from rat EEG is presented. The proposed index for the depth of anesthesia called modified Shannon entropy (MShEn) is based on Shannon entropy (ShEn) and spectral entropy (SpEn) which are widely used for analyzing non-stationary signals. Discrimination power (DP), as a performance indicator for indexes, is defined and used to derive the final index for the depth of anesthesia. For experiment, EEG from anesthetized rats are measured and analyzed by using MShEn. MShEn shows both high stability and high correlation with other indexes for depth of anesthesia.

Monitoring the depth of anesthesia from rat EEG using modified Shannon entropy analysis.

In this paper, a cepstral analysis based approach to measuring the depth of anesthesia (DoA) is presented. Cepstral analysis is a signal processing technique widely used especially for speech recognition in order to extract speech information regardless of vocal cord characteristics. The resulting index for the DoA is called index based on cepstral analysis (ICep). The Fisher criterion is engaged to evaluate the performance of indices. All analyses are based on a single-channel electroencephalogram (EEG) of 10 human subjects. To validate the proposed technique, ICep is compared with bispectral index (BIS), which is the most commonly used method to estimate the level of consciousness via EEG during general anesthesia. The results show that ICep has high correlation with BIS, and is outstanding in terms of the Fisher criterion and offers faster tracking than BIS in the transition from consciousness to unconsciousness.

A cepstral analysis based method for quantifying the depth of anesthesia from human EEG.

We present a novel technique to measure diffusion coefficients of insoluble surfactant monolayers. We merge a surfactant-coated droplet with a fluorescently labeled planar monolayer. During the merging process, a monolayer on a droplet displaces the existing planar monolayer, leaving a dark area when viewed under a fluorescence microscope. We measure fractional intensities as the dyes recover, which allows diffusion coefficients to be computed. We validate this technique with the two most common phospholipid monolayers (DPPC and DOPC) and study the diffusion of their mixtures. The proposed technique has several advantages over the FRAP technique and is potentially capable of measuring the diffusion of any soluble/insoluble surfactant monolayers.

Fluorescence recovery after merging a surfactant-covered droplet: a novel technique to measure the diffusion of phospholipid monolayers at fluid/fluid interfaces.

Article	Year
Monitoring the depth of anesthesia from rat EEG using modified Shannon entropy analysis. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference\| PubMed ID: 22255311	2011
A cepstral analysis based method for quantifying the depth of anesthesia from human EEG. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference\| PubMed ID: 24111105	2013
Fluorescence recovery after merging a surfactant-covered droplet: a novel technique to measure the diffusion of phospholipid monolayers at fluid/fluid interfaces. Langmuir : the ACS journal of surfaces and colloids\| PubMed ID: 25422050	2014

Dae-Woong Jeong

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