Evaluation of time-temperature integrator for indicating the ripeness of kiwifruit in plastic container at home

Enzyme-based time-temperature integrators (TTIs) were applied to indicate the ripeness of plastic-container-packaged kiwifruit. The hypothesis was that the ethylene gas production, an indication of kiwifruit ripeness, depends on the time-temperature history. The market-purchased, unripe kiwifruit was assumed to be stored in a plastic container to ripen at home, as common practice in Korea. The kinetics of ethylene gas production and TTI color change was found to be suitable for the indication. The Arrhenius activation energy (E_a ) of the ethylene gas production and color changes of lipase-, amylase-, and laccase-based TTIs were 41.60 ± 10.87 kJ/mol, and 42.76 ± 9.57, 100.28 ± 6.84, and 30.49 ± 4.41 kJ/mol, respectively. Kiwifruit firmness was also tested as a practical, major quality factor. The E_a of the firmness changes was 39.66 ± 4.64 kJ/mol. In scenarios tests, the firmness could be most accurately predicted from the lipase-based TTI color. Overall, the lipase-based TTI was found to be the best in terms of the similarity of the E_a and the prediction accuracy. PRACTICAL APPLICATION: Currently, there is no commercially available indicator that can determine the ripeness of packaged kiwifruit. Although an ethylene gas indicator is possible, it has been difficult to commercialize because the gas may leak in the package. An indicator on plastic containers with kiwifruit, as is common in Korea, has been developed using a conventional time-temperature integrator (TTI). The hypothesis was that the production of ethylene gas, indicating kiwi ripening, is also dependent on the time-temperature history. It was found that the TTI color change over time was suitable for judging suitable kiwifruit hardness, a major kiwifruit ripeness index.

Extended Blind End-member and Abundance Extraction for Biomedical Imaging Applications

In some applications of biomedical imaging, a linear mixture model can represent the constitutive elements (end-members) and their contributions (abundances) per pixel of the image. In this work, the extended blind end-member and abundance extraction (EBEAE) methodology is mathematically formulated to address the blind linear unmixing (BLU) problem subject to positivity constraints in optical measurements. The EBEAE algorithm is based on a constrained quadratic optimization and an alternated least-squares strategy to jointly estimate end-members and their abundances. In our proposal, a local approach is used to estimate the abundances of each end-member by maximizing their entropy, and a global technique is adopted to iteratively identify the end-members by reducing the similarity among them. All the cost functions are normalized, and four initialization approaches are suggested for the end-members matrix. Synthetic datasets are used first for the EBEAE validation at different noise types and levels, and its performance is compared to state-of-the-art algorithms in BLU. In a second stage, three experimental biomedical imaging applications are addressed with EBEAE: m-FLIM for chemometric analysis in oral cavity samples, OCT for macrophages identification in post-mortem artery samples, and hyper-spectral images for in-vivo brain tissue classification and tumor identification. In our evaluations, EBEAE was able to provide a quantitative analysis of the samples with none or minimal a priori information.

Analysis of Fluorescence Lifetime Imaging Microscopy (FLIM) data. Based on a fully automated Laguerre deconvolution method

OBJECTIVES

A novel Fluorescence Lifetime Imaging Microscopy (FLIM) deconvolution method based on the linear expansion of fluorescence decays on a set of orthonormal Laguerre functions was recently proposed. The Laguerre deconvolution method applies linear least-square estimation to estimate the expansion coefficients of all pixel decays simultaneously, performing at least two orders of magnitude faster than the other algorithms. In the original Laguerre FLIM deconvolution implementation, however, the Laguerre parameter α is selected using a heuristic approach, making it unsuitable for online applications.

METHODS

In this study, we present a fully automated implementation of the Laguerre FLIM deconvolution, whereby the Laguerre parameter α is treated as a free parameter within a nonlinear least-squares optimization scheme.

RESULTS

The performance of this method has been successfully validated on simulated data, and experimental FLIM images of standard fluorescent dyes and endogenous tissue fluorescence.

CONCLUSIONS

The main advantage of the proposed method is that it does not require any user intervention for tuning up the deconvolution process. Thus, we believe this method will facilitate the translation of FLIM to online applications, including real-time clinical diagnosis.

Application of the laguerre deconvolution method for time-resolved fluorescence spectroscopy to the characterization of atherosclerotic plaques

This study investigates the ability of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) to detect inflammation in atherosclerotic lesion, a key feature of plaque vulnerability. A total of 348 TR-LIFS measurements were taken from carotid plaques of 30 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as Early, Fibrotic/Calcified or Inflamed lesions. A stepwise linear discriminant analysis algorithm was developed using spectral and TR features (normalized intensity values and Laguerre expansion coefficients at discrete emission wavelengths, respectively). Features from only three emission wavelengths (390, 450 and 500 nm) were used in the classifier. The Inflamed lesions were discriminated with sensitivity > 80% and specificity > 90 %, when the Laguerre expansion coefficients were included in the feature space. These results indicate that TR-LIFS information derived from the Laguerre expansion coefficients at few selected emission wavelengths can discriminate inflammation in atherosclerotic plaques. We believe that TR-LIFS derived Laguerre expansion coefficients can provide a valuable additional dimension for the detection of vulnerable plaques.

Spatially resolved fluorescence lifetime mapping of enzyme kinetics in living cells

Traditional cuvette-based enzyme studies lack spatial information and do not allow real-time monitoring of the effects of modulating enzyme functions in vivo. In order to probe the realistic timescales of steric modifications in enzyme-substrate complexes and functional binding-unbinding kinetics in living cells without losing spatial information, it is imperative to develop sensitive imaging strategies that can report enzyme kinetics in real time over a wide dynamic range of timescales. Here we present a multi-photon excitation-based, ultra-fast photon detection using a streak camera and Laguerre expansion-based fast deconvolution approach for achieving high spatio-temporal resolution in monitoring real-time enzyme kinetics in single cells. In particular, we report spatially resolved, nanosecond-scale fluorescence dynamics associated with binding-unbinding kinetics of endogenous metabolic co-factor nicotinamide adenine dinucleotide with enzymes in intact living cells. By monitoring real-time kinetics of NAD(P)H-enzyme kinetics in primary hepatocytes isolated from young and aged mouse models, we observed that the mechanism of inhibition of mitochondrial respiration at complex I site is mediated by redistribution of free and protein-bound nicotinamide adenine dinucleotide pools and that this equilibrium redistribution is affected by age-related modifications in mitochondrial function. We describe unique advantages of Laguerre deconvolution algorithm in comparison with conventional lifetime analysis approaches. Non-invasive monitoring of metabolic dysfunctions in intact animal models is an attractive strategy for gaining insight into the dynamics of tissue metabolism in health and in various metabolic syndromes such as cancer, diabetes and aging-induced metabolic dysfunctions. Besides the example demonstrated above, we envisage that the proposed method can find applications in a variety of other situations where intensity-based approaches fall short owing to spectroscopic artefacts.

Novel methods of time-resolved fluorescence data analysis for in-vivo tissue characterization: application to atherosclerosis

This study investigates the ability of new analytical methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data to characterize tissue in-vivo, such as the composition of atherosclerotic vulnerable plaques. A total of 73 TR-LIFS measurements were taken in-vivo from the aorta of 8 rabbits, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as normal aorta, thin or thick lesions, and lesions rich in either collagen or macrophages/foam-cells. Different linear and nonlinear classification algorithms (linear discriminant analysis, stepwise linear discriminant analysis, principal component analysis, and feedforward neural networks) were developed using spectral and TR features (ratios of intensity values and Laguerre expansion coefficients, respectively). Normal intima and thin lesions were discriminated from thick lesions (sensitivity >90%, specificity 100%) using only spectral features. However, both spectral and time-resolved features were necessary to discriminate thick lesions rich in collagen from thick lesions rich in foam cells (sensitivity >85%, specificity >93%), and thin lesions rich in foam cells from normal aorta and thin lesions rich in collagen (sensitivity >85%, specificity >94%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for in-vivo tissue characterization.

Novel ultra-fast deconvolution method for fluorescence lifetime imaging microscopy based on the Laguerre expansion technique

A new deconvolution method for fluorescence lifetime imaging microscopy (FLIM) based on the Laguerre expansion technique is presented. The performance of this method was tested on synthetic FLIM images derived from a multiexponential model and from fluorescence lifetime standards, and then compared to standard algorithms of FLIM analysis. Our results demonstrated significant advantages of the Laguerre method over standard algorithms. First, the fluorescence intensity decays of arbitrary form can be estimated at every pixel, without a priori assumption of its functional form. Second, the number of delayed images required to perform deconvolution is relatively low (as low as 5), reducing the acquisition time. Third, ultra-fast light sources are not longer required, making less expensive to perform lifetime imaging. Finally and most important, deconvolution at every pixel is performed in parallel using a common Laguerre basis, thus allowing reducing significantly the computation time (i.e. synthetic 600x600 pixel images can be deconvolved with high accuracy in less than 20 s). Based on these findings, we believe that the Laguerre deconvolution technique represents a more robust and extremely fast analytical method that will allow exploring FLIM in practical real-time applications, such as clinical diagnosis.

Miniaturized side-viewing imaging probe for fluorescence lifetime imaging (FLIM): validation with fluorescence dyes, tissue structural proteins and tissue specimens

We report a side viewing fibre-based endoscope that is compatible with intravascular imaging and fluorescence lifetime imaging microscopy (FLIM). The instrument has been validated through testing with fluorescent dyes and collagen and elastin powders using the Laguerre expansion deconvolution technique to calculate the fluorescence lifetimes. The instrument has also been tested on freshly excised unstained animal vascular tissues.

New methods for time-resolved fluorescence spectroscopy data analysis based on the Laguerre expansion technique--applications in tissue diagnosis

OBJECTIVES

A new deconvolution method for the analysis of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data is introduced and applied for tissue diagnosis.

METHOD

The intrinsic TR-LIFS decays are expanded on a Laguerre basis, and the computed Laguerre expansion coefficients (LEC) are used to characterize the sample fluorescence emission. The method was applied for the diagnosis of atherosclerotic vulnerable plaques.

RESULTS

At a first stage, using a rabbit atherosclerotic model, 73 TR-LIFS in-vivo measurements from the normal and atherosclerotic aorta segments of eight rabbits were taken. The Laguerre deconvolution technique was able to accurately deconvolve the TR-LIFS measurements. More interesting, the LEC reflected the changes in the arterial biochemical composition and provided discrimination of lesions rich in macrophages/foam-cells with high sensitivity (> 85%) and specificity (> 95%). At a second stage, 348 TR-LIFS measurements were obtained from the explanted carotid arteries of 30 patients. Lesions with significant inflammatory cells (macrophages/foam-cells and lymphocytes) were detected with high sensitivity (> 80%) and specificity (> 90%), using LEC-based classifiers.

CONCLUSION

This study has demonstrated the potential of using TR-LIFS information by means of LEC for in vivo tissue diagnosis, and specifically for detecting inflammation in atherosclerotic lesions, a key marker of plaque vulnerability.

Diagnosis of vulnerable atherosclerotic plaques by time-resolved fluorescence spectroscopy and ultrasound imaging

In this study, time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and ultrasonography were applied to detect vulnerable (high-risk) atherosclerotic plaque. A total of 813 TR-LIFS measurements were taken from carotid plaques of 65 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified by histopathology as thin, fibrotic, calcified, low-inflamed, inflamed and necrotic lesions. Spectral and time-resolved parameters (normalized intensity values and Laguerre expansion coefficients) were extracted from the TR-LIFS data. Feature selection for classification was performed by either analysis of variance (ANOVA) or principal component analysis (PCA). A stepwise linear discriminant analysis algorithm was developed for detecting inflamed and necrotic lesion, representing the most vulnerable plaques. These vulnerable plaques were detected with high sensitivity (>80%) and specificity (>90%). Ultrasound (US) imaging was obtained in 4 carotid plaques in addition to TR-LIFS examination. Preliminary results indicate that US provides important structural information of the plaques that could be combined with the compositional information obtained by TR-LIFS, to obtain a more accurate diagnosis of vulnerable atherosclerotic plaque.

Determinants of heart rate variability in obstructive sleep apnea syndrome during wakefulness and sleep

Heart rate variability (HRV) is mediated by at least three primary mechanisms: 1) vagal feedback from pulmonary stretch receptors (PSR), 2) central medullary coupling between respiratory and cardiovagal neurons (RCC), and 3) arterial baroreflex (ABR)-induced fluctuations. We employed a noninvasive experimental protocol in conjunction with a minimal model to determine how these sources of HRV are altered in obstructive sleep apnea syndrome (OSAS). Respiration, heart rate, and blood pressure were monitored in eight normal subjects and nine untreated OSAS patients in relaxed wakefulness and stage 2 and rapid eye movement sleep. A computer-controlled ventilator delivered inspiratory pressures that varied randomly from breath to breath. Application of the model to the corresponding subject responses allowed the delineation of the three components of HRV. In all states, RCC gain was lower in OSAS patients than in normal subjects (P < 0.04). ABR gain was also reduced in OSAS patients (P < 0.03). RCC and ABR gains increased from wakefulness to sleep (P < 0.04). However, there was no difference in PSR gain between subject groups or across states. The findings of this study suggest that the adverse autonomic effects of OSAS include impairment of baroreflex gain and central respiratory-cardiovascular coupling, but the component of respiratory sinus arrhythmia that is mediated by lung vagal feedback remains intact.

Nonparametric Analysis Of Time-Resolved Fluorescence Data Based On The Laguerre Expansion Technique

To estimate the intrinsic fluorescence intensity decay of a compound, the excitation light pulse must be deconvolved from the measured fluorescence pulse trace. The most commonly used deconvolution method is the multiexponential least-square iterative reconvolution (LSIR) technique. A variant of LSIR in which the intrinsic fluorescence intensity decay is expressed as an expansion on the discrete time Laguerre basis, was recently introduced. In this study, the performance of the Laguerre deconvolution technique was successfully tested with simulated and fluorescence standard data. It was also demonstrated that the Laguerre deconvolution presents a number of advantages over the classical multiexponential LSIR, including less expensive computational resolution, and the property to generate a unique set of expansion coefficients highly correlated with the intrinsic lifetimes. A novel method for concentration estimation based on the analysis of the Laguerre expansion coefficients was also proposed and successfully applied to different fluorescence standard mixtures, performing even better (error<2%) than more traditional methods of spectral analysis, such as PCR (error<7%) and PLS (error<10%). These findings suggest that the use of Laguerre expansion coefficients represents an alternative nonparametric approach to characterize and discriminate biological systems, in terms of their spectral and lifetime characteristics.