Lifetime Information Research Articles

Bayesian reliability acceptance sampling plan with optional warranty under hybrid censoring

AbstractThis work considers the design of a Bayesian reliability acceptance sampling plan (RASP) under a hybrid censored life test for the products sold under an optional warranty. The consumer and manufacturer agree on a common lifetime distribution of the product. However, they differ in the assessment of the prior distributions because of the adversarial nature of the consumer and manufacturer. The consumer takes a decision based on his/her utility and prior belief without a warranty offer by the manufacturer. If the decision is rejection, the manufacturer provides warranty offer to the consumer. If the consumer rejects the lot with a warranty, the manufacturer conducts a life test under the hybrid censoring scheme (HCS) and provides lifetime information to the consumer. The consumer updates his/her belief based on lifetime information provided by the manufacturer. The consumer then takes a decision of acceptance or rejection of the lot based on updated beliefs. The task of the manufacturer is to determine the optimal life testing plan.

Reliability inference for dual constant-stress accelerated life test with exponential distribution and progressively Type-II censoring

Accelerated life test provides a feasible and effective way to rapidly derive lifetime information by exposing products to higher-than-normal operating conditions. However, most of the previous research on accelerated life test has focused on the application of a single stress factor and a traditional censoring scheme. This article considers the reliability inference for a dual constant-stress accelerated life test model with exponential distribution and progressively Type-II censoring. Point estimates for model parameters are provided using maximum likelihood estimation and the weighted least squares method based on random variable transformation. In addition, we construct asymptotic confidence intervals, approximate confidence intervals, and bootstrap confidence intervals for the parameters of interest. Finally, extensive simulation studies and an illustrative example are presented to investigate the performance of the proposed methods.

Fluorescence Lifetime Multiplexing (FLEX) for simultaneous high dimensional spatial biology in 3D

Immunohistochemistry is a crucial method for detecting specific proteins within tissue samples, yet constrained to one biomarker per tissue section. Multiplexed immunofluorescence, while allowing simultaneous visualization of multiple proteins, faces limitations in the number of simultaneous fluorescent labels due to spectral overlap. Although cyclic immunofluorescence techniques have successfully broadened antibody staining capacities in a single tissue sample, they are plagued by time-consuming and labor-intensive procedures, sample degradation risks, and inability to scale beyond thin sections. In this study, we introduce the use of 3D confocal Fluorescence Lifetime Imaging Microscopy as a high-throughput, multiplexed immunofluorescence platform that can differentiate 11 or more biomarkers in 3D tissue volumes. Leveraging both spectral and lifetime information, this approach allows for practical spatial biology in thin sections that can readily scale to larger volumes of tissue. We believe that this highly multiplexed and versatile biomarker imaging platform will significantly expedite cancer research and enable new translational approaches in the future.

Deep learning-based virtual H& E staining from label-free autofluorescence lifetime images

Label-free autofluorescence lifetime is a unique feature of the inherent fluorescence signals emitted by natural fluorophores in biological samples. Fluorescence lifetime imaging microscopy (FLIM) can capture these signals enabling comprehensive analyses of biological samples. Despite the fundamental importance and wide application of FLIM in biomedical and clinical sciences, existing methods for analysing FLIM images often struggle to provide rapid and precise interpretations without reliable references, such as histology images, which are usually unavailable alongside FLIM images. To address this issue, we propose a deep learning (DL)-based approach for generating virtual Hematoxylin and Eosin (H&E) staining. By combining an advanced DL model with a contemporary image quality metric, we can generate clinical-grade virtual H&E-stained images from label-free FLIM images acquired on unstained tissue samples. Our experiments also show that the inclusion of lifetime information, an extra dimension beyond intensity, results in more accurate reconstructions of virtual staining when compared to using intensity-only images. This advancement allows for the instant and accurate interpretation of FLIM images at the cellular level without the complexities associated with co-registering FLIM and histology images. Consequently, we are able to identify distinct lifetime signatures of seven different cell types commonly found in the tumour microenvironment, opening up new opportunities towards biomarker-free tissue histology using FLIM across multiple cancer types.

Pulsed-Interleaved-Excitation Two-Dimensional Fluorescence Lifetime Correlation Spectroscopy.

We report on pulsed-interleaved-excitation two-dimensional fluorescence lifetime correlation spectroscopy (PIE 2D FLCS) to study biomolecular structural dynamics with high sensitivity and high time resolution using Förster resonance energy transfer (FRET). PIE 2D FLCS is an extension of 2D FLCS, which is a unique single-molecule fluorescence method that uses fluorescence lifetime information to distinguish different fluorescence species in equilibrium and resolves their interconversion dynamics with a submicrosecond time resolution. Because 2D FLCS has used only a single-color excitation so far, it was difficult to distinguish a very low-FRET (or zero-FRET) species from only donor-labeled species. We overcome this difficulty by implementing the PIE scheme (i.e., alternate excitation of the donor and acceptor dyes using two temporally interleaved excitations with different colors) to 2D FLCS, realizing two-color excitation and two-color fluorescence detection in 2D FLCS. After proof-of-principle PIE 2D FLCS analysis on the photon data synthesized with Monte Carlo simulation, we apply PIE 2D FLCS to a DNA-hairpin sample and show that this method readily distinguishes four fluorescent species, i.e., high-FRET, low-FRET, and two single-dye-labeled species. In addition, we show that PIE 2D FLCS can also quantitatively evaluate the contributions of the donor-acceptor spectral crosstalk, which often appears as artifacts in FRET studies and degrades the information obtained.

Construction of piezoelectric photocatalyst Au/BiVO4 for efficient degradation of tetracycline and studied at single-particle level

Piezopotential-assisted catalysis has been proven to be a low-cost and high-efficiency environmental purification process. Herein, Au/bismuth vanadate (BiVO4) piezoelectric photocatalysts are prepared by modifying highly dispersed Au nanoparticles (AuNPs) on piezoelectric BiVO4 microcrystal by a deposition-precipitation approach. Under visible light irradiation and assisted ultrasound excitation, the removal rate of tetracycline was 95% within 60 min, demonstrating the optimum photocatalytic performance over 3Au/BiVO4. The significantly enhanced photocatalytic performance is due to the synergistic coupling of plasmonic and piezotronic effect based on facet engineering. Single-particle spectroscopy technology can provide photoluminescence (PL) lifetime and PL spectra information in the micro-/nano regions, thereby exploring the charge transfer behavior of heterostructures. Single-particle PL images revealed a significant attenuation of PL emission and shortened PL lifetime of 3Au/BiVO4, compared with BiVO4, indicating that high-density dispersed AuNPs promote charge transfer. In situ monitoring of individual BiVO4 and 3Au/BiVO4 particles before and after polarization treatment confirms that the piezoelectric field of the BiVO4 decahedron further promotes separation of photogenerated carriers induced by plasmonic effect. Driven by the piezoelectric potential induced by ultrasonic vibration near the heterostructures, high-energy hot electrons excited on plasmonic AuNPs can be effectively extracted to BiVO4. This work provides new choices for designing high-performance pollutant treatment catalysts.

Three species multiplexing of fluorescent dyes and gold nanoclusters recovered with fluorescence lifetime correlation spectroscopy

Biosensor applications often require the simultaneous detection of multiple analytes, with a clear need to go beyond the traditional multiplexing relying on distinct fluorescent dyes across the visible spectrum. Fluorescence lifetime correlation spectroscopy (FLCS) is a powerful approach taking advantage of the fluorescence lifetime information to separate the contributions of different fluorescent species with overlapping emission spectra. However, so far FLCS detection has been demonstrated only on binary mixtures of two fluorescent dyes, limiting its multiplexing capabilities. Here, we report the first quantitative FLCS measurements within a ternary mixture composed of three different fluorescent emitters with near-identical emission spectra. Two organic fluorescent dyes, Alexa Fluor 647 and CF640R, are combined with water-soluble Au18(SG)14 gold nanoclusters. Our experimental data establish that FLCS allows to accurately determine individual concentrations within intricate ternary mixtures. Another major aspect of interest concerns the assessment of the suitability of gold nanoclusters for FLCS multiplexing applications. With their microsecond lifetime and stable emission characteristics, gold nanoclusters add a valuable new aspect to the array of FLCS probes. Extending FLCS multiplexing beyond binary mixtures paves the way for further progress in the simultaneous highly parallel biosensing of multiple species.

Log‐location‐scale increment degradation model: A Bayesian perspective

AbstractDegradation modeling serves as a valuable tool for assessing the lifetime information of highly reliable products. One frequently employed approach for describing the degradation phenomenon involves the use of a degradation model that relies on stochastic processes. In a stochastic‐process‐based degradation model, it is assumed that the increments follow a distribution with the additivity property. This property makes the further inferences mathematically and statistically tractable. However, it limits the choices of the distributions. This paper aims to use those distributions without the additivity property to model the increments and explores distributions from the log‐location‐scale family. Under the frame of Bayesian analysis, Markov Chain Monte Carlo algorithms are developed for executing the necessary computations. Given that the proposed degradation models do not adhere to the additivity property, this paper tackles the challenges involved in predicting the lifetime of both on‐line and off‐line products. Two illustrative examples are subsequently analyzed to demonstrate the procedural steps outlined. The suitability of the proposed model is finally validated through a simulation study.

Diffusion of Multiple Species Resolved by Fluorescence Lifetime Recovery after Photobleaching (FLRAP).

Fluorescence recovery after photobleaching (FRAP) is now an indispensable tool to analyze the diffusion of molecules in vivo and in vitro. However, a conventional fluorescence intensity-based approach has difficulty in analyzing the diffusion of multiple species simultaneously. Here, we report fluorescence lifetime recovery after photobleaching (FLRAP) that incorporates fluorescence lifetime information into FRAP. By using FLRAP, the fluorescence intensity-recovery curves of each species can be successfully extracted from the ensemble photon data by utilizing their species-specific fluorescence decay curves, which are verified by applying FLRAP to two heterogeneous systems. Thus, FLRAP can be a powerful tool to quantitatively elucidate the molecular diffusion of multiple species in complex systems such as in living cells.

Fast Bayesian Inference of Reparameterized Gamma Process With Random Effects

In the field of reliability engineering, the gamma process plays an important role in modeling degradation processes. However, extracting lifetime information from product degradation observations has long been suffering from both ineffective modeling techniques and inefficient statistical inference methods. To overcome these challenges, we propose a reparameterized gamma process with random effects in this article. Compared with the classical gamma process, the proposed model has a more intuitive physical interpretation. In addition, statistical inference for the model can be readily done through the variational Bayesian algorithm. Combining with the Gauss–Hermite quadrature and the Laplace approximation, the algorithm yields closed-form variational posteriors for the proposed model. Its superiority over two other inference methods (expectation maximization and Monte Carlo Markov Chain) in terms of computational efficiency and estimation accuracy is demonstrated by simulation.

Prevalent occupational exposures and risk of lung cancer among women: Results from the application of the Canadian Job-Exposure Matrix (CANJEM) to a combined set of ten case-control studies.

Worldwide, lung cancer is the second leading cause of cancer death in women. The present study explored associations between occupational exposures that are prevalent among women, and lung cancer. Data from 10 case-control studies of lung cancer from Europe, Canada, and New Zealand conducted between 1988 and 2008 were combined. Lifetime occupational history and information on nonoccupational factors including smoking were available for 3040 incident lung cancer cases and 4187 controls. We linked each reported job to the Canadian Job-Exposure Matrix (CANJEM), which provided estimates of probability, intensity, and frequency of exposure to each selected agent in each job. For this analysis, we selected 15 agents (cleaning agents, biocides, cotton dust, synthetic fibers, formaldehyde, cooking fumes, organic solvents, cellulose, polycyclic aromatic hydrocarbons from petroleum, ammonia, metallic dust, alkanes C18+, iron compounds, isopropanol, and calcium carbonate) that had lifetime exposure prevalence of at least 5% in the combined study population. For each agent, we estimated lung cancer risk in each study center for ever-exposure, by duration of exposure, and by cumulative exposure, using separate logistic regression models adjusted for smoking and other covariates. We then estimated the meta-odds ratios using random-effects meta-analysis. None of the agents assessed showed consistent and compelling associations with lung cancer among women. The following agents showed elevated odds ratio in some analyses: metallic dust, iron compounds, isopropanol, and organic solvents. Future research into occupational lung cancer risk factors among women should prioritize these agents.

TauSTED super-resolution imaging of labile iron in primary hippocampal neurons.

Iron dyshomeostasis is involved in many neurological disorders, particularly neurodegenerative diseases where iron accumulates in various brain regions. Identifying mechanisms of iron transport in the brain is crucial for understanding the role of iron in healthy and pathological states. In neurons, it has been suggested that iron can be transported by the axon to different brain regions in the form of labile iron; a pool of reactive and exchangeable intracellular iron. Here we report a novel approach to imaging labile ferrous iron, Fe(II), in live primary hippocampal neurons using confocal and TauSTED (stimulated emission depletion) microscopy. TauSTED is based on super-resolution STED nanoscopy, which combines high spatial resolution imaging (<40nm) with fluorescence lifetime information, thus reducing background noise and improving image quality. We applied TauSTED imaging utilizing biotracker FerroFarRed Fe(II) and found that labile iron was present as submicrometric puncta in dendrites and axons. Some of these iron-rich structures are mobile and move along neuritic pathways, arguing for a labile iron transport mechanism in neurons. This super-resolution imaging approach offers a new perspective for studying the dynamic mechanisms of axonal and dendritic transport of iron at high spatial resolution in living neurons. In addition, this methodology could be transposed to the imaging of other fluorescent metal sensors.

Statistical inference for the step-stress model with competing risks from the Kumaraswamy distribution under progressive type-II censoring

In reliability and life analysis, the accelerated life test is frequently used because it can reduce cost and obtain additional reliability and lifetime information. In addition, when a unit fails in a life test, there are often two or more risk factors related to the cause of the failure. In this article, we consider the inference from a step-stress-accelerated life test with competing risks using progressive type-II censored data. Based on the assumption that the parameters affected by stress follow a log-linear model with the stress level, the proportional hazard model with the Kumaraswamy distribution is established. The point estimation of the unknown parameters is derived using maximum likelihood and Bayesian methods. Accordingly, the logarithmic asymptotic confidence and the highest posterior density credible intervals are derived and constructed. Moreover, the algorithm for multi-parameter sampling and simulation technology based on this model is given. Simulation results show that the proposed methods have good performance. In light of the estimates of the parameters, the estimated reliability function under normal conditions can be expressed, and its images under different methods are drawn. Last, a real dataset and a set of simulated data are presented for illustrative purposes.

A Bayesian nonparametric system reliability model which integrates multiple sources of lifetime information

We present a Bayesian nonparametric system reliability model which scales well and provides a great deal of flexibility in modeling. The Bayesian approach naturally handles the disparate amounts of component and subsystem data that may exist. However, traditional Bayesian reliability models are quite computationally complex, relying on MCMC techniques. Our approach utilizes the conjugate properties of the beta-Stacy process, which is the fundamental building block of our model. These individual models are linked together using a method of moments estimation approach. This model is computationally fast, allows for right-censored data, and is used for estimating and predicting system reliability.

Fluorescence lifetime Hong-Ou-Mandel sensing

Fluorescence Lifetime Imaging Microscopy in the time domain is typically performed by recording the arrival time of photons either by using electronic time tagging or a gated detector. As such the temporal resolution is limited by the performance of the electronics to 100’s of picoseconds. Here, we demonstrate a fluorescence lifetime measurement technique based on photon-bunching statistics with a resolution that is only dependent on the duration of the reference photon or laser pulse, which can readily reach the 1–0.1 picosecond timescale. A range of fluorescent dyes having lifetimes spanning from 1.6 to 7 picoseconds have been here measured with only ~1 s measurement duration. We corroborate the effectiveness of the technique by measuring the Newtonian viscosity of glycerol/water mixtures by means of a molecular rotor having over an order of magnitude variability in lifetime, thus introducing a new method for contact-free nanorheology. Accessing fluorescence lifetime information at such high temporal resolution opens a doorway for a wide range of fluorescent markers to be adopted for studying yet unexplored fast biological processes, as well as fundamental interactions such as lifetime shortening in resonant plasmonic devices.

Acceleration invariance principle for Hougaard processes in degradation analysis

AbstractAccelerated degradation tests (ADTs) are widely used to assess lifetime information under normal use conditions for highly reliable products. For the accelerated tests, two basic assumptions are that changing stress levels does not affect the underlying distribution family and that there is stochastic ordering for the life distributions at different stress levels. The acceleration invariance (AI) principle for ADTs is proposed to study these fundamental assumptions. Using the AI principle, a theoretical connection between the model parameters and the accelerating variables is developed for Hougaard processes. This concept can be extended to heterogeneous gamma and inverse Gaussian processes. Simulation studies are presented to support the applicability and flexibility of the Hougaard process using the AI principle for ADTs. A real data analysis using the derived relationship is used to validate the AI principle for accelerated degradation analysis. All technical details, simulation results for nonlinear cases and model mis‐specification analysis are available online as Supporting Information.

Simultaneous Spectral Temporal Modelling for a Time-Resolved Fluorescence Emission Spectrum

Innovations in complementary metal-oxide semiconductor (CMOS) single-photon avalanche diode (SPAD) technology has featured in the development of next-generation instruments for point-based time-resolved fluorescence spectroscopy (TRFS). These instruments provide hundreds of spectral channels, allowing the collection of fluorescence intensity and fluorescence lifetime information over a broad spectral range at a high spectral and temporal resolution. We present Multichannel Fluorescence Lifetime Estimation, MuFLE, an efficient computational approach to exploit the unique multi-channel spectroscopy data with an emphasis on simultaneous estimation of the emission spectra, and the respective spectral fluorescence lifetimes. In addition, we show that this approach can estimate the individual spectral characteristics of fluorophores from a mixed sample.

Super-Resolved FRET Imaging by Confocal Fluorescence-Lifetime Single-Molecule Localization Microscopy.

Fluorescence Resonance Energy Transfer (FRET)-basedapproaches are unique tools for sensing the immediate surroundings and interactions of (bio)molecules. FRET imaging and Fluorescence Lifetime Imaging Microscopy (FLIM) enable the visualization of the spatial distribution of molecular interactions and functional states. However, conventional FLIM and FRET imaging provide average information over an ensemble of molecules within a diffraction-limited volume, which limits the spatial information, accuracy, and dynamic range of the observed signals. Here, an approach to obtain super-resolved FRET imaging based on single-molecule localization microscopy using an early prototype of a commercial time-resolved confocal microscope is demonstrated. DNA Points Accumulation for Imaging in Nanoscale Topography with fluorogenic probes provides a suitable combination of background reduction and binding kinetics compatible with the scanning speed of usual confocal microscopes. A single laser is used to excite the donor, a broad detection band is employed to retrieve both donor and acceptor emission, and FRET events are detected from lifetime information.

Towards precise optical measurements of steady state of and small changes in resting membrane potentials.

While great progress has been achieved in developing optical methods for measuring fast changes in membrane potential (like action potentials) in excitable cells, less progress has been made in precise (and calibrated) measurements of steady state resting membrane potentials (RMPs) and small changes in RMPs (in excitable or non-excitable cells). In excitable cells, small changes in RMPs are associated with multiple physiological processes such as sub-threshold events in neuronal signaling and in synaptic plasticity. They also play an important role in cell differentiation and proliferation of cardiomyocytes. In non-excitable cells, such as bacterial colonies, RMP changes play important roles in intercellular communication, coordination, metabolism, and stress response. Accurate and precise recordings of minute RMP changes require noise-immune optical tools. We have been developing an RMP (calibrated) recording approach that is capable of measuring small changes RMPs. Our approach relies on 3 components: (i) a novel optical transducer (voltage sensing dye) that utilizes intrinsic photoinduced electron transfer (PeT) mechanism to sense RMP by fluorescence lifetime changes; (ii) a novel time-gated SPAD array imager that allows widefield fluorescence lifetime imaging (FLIM); (iii) a quantitative phasor analysis of the recoded FLIM data. This package provides high-throughput, quantification of pixel-wise lifetime information. Two aspects of our approach - the novel VSD and the data analysis - have been tested in excitable cardiac muscle cells (NVRM) and in non-excitable bacterial cells (B. subtilis). B. subtilis RMPs have been estimated for normal cultures and for cultures under perturbing chemical conditions. Drug induced changes of NVRM RMPs have been also estimated. Implementation of our 3-pronged approach towards studying electrical signaling/coupling networks in bacterial biofilms and in cardiomyocytes will be discussed.

Simultaneous single-particle tracking and fluorescence lifetime measurement with a single-photon detector array.

Fluorescence single-particle tracking (SPT) techniques are a fundamental tool for providing information on the complex functions and interactions of individual particles in biological environments. The main concern about following single particles resides mostly in how to make registered photons informative and the solution is usually optimized only to better extrapolate either the temporal or the spatial information. This tradeoff ultimately reflects into the contraposition of wide-field camera-based techniques and real-time SMT, with the latter representing the state of the art, but at the cost of high technical complexity. Furthermore, fluorescence lifetime information, despite being accessible in many cases, has yet to be measured consistently. Within the context of the BrightEyes ERC-2018-COG project, we present a real-time three-dimensional SPT implementation based on a confocal laser-scanning microscope featuring a 5×5 single-photon avalanche photodiode (SPAD) array detector capable of overcoming the above limitations due to an hybrid approach. Briefly, each sensitive element of the detector acts as a confocal pinhole, and the recorded intensity distribution mirrors the position of the particle with respect to the center of the excitation volume. The estimation is then used as input for a real-time feedback tracking system. Notably, each pixel is an independent photon counting detector, allowing for concurrent measurement of the fluorescence lifetime. The system is capable of experimentally tracking single particles with localization precision up to 30 nm with 100 photons and microsecond time resolution. The same photon stream is used to perform fluorescence lifetime measurements. The technique has been validated by tracking 20 nm fluorescent beads moved along a predetermined path and by measuring the diffusion coefficient when freely diffusing in water-glycerol solutions. As application, the movement of lysosomes in living cells has been investigated while assessing the lifetime of the GFP marker.