Application of the stretched exponential function to fluorescence lifetime imaging

Understanding associative polymer self-assembly with shrinking gate fluorescence correlation spectroscopy

The self-assembly of polymers is integral to their role in liquid formulations. In this study, we combine a dye whose lifetime is sensitive to the nanoviscosity of its local environment with shrinking gate fluorescence correlation spectroscopy (sgFCS) to study the self-assembly of a model telechelic polymer, hydrophobically modified ethoxylated urethane (HEUR). Fluorescence lifetime measurements show a monotonic increase in average lifetime with increasing HEUR concentration driven by a small fraction of dye (<1%) with long lifetimes strongly bound to HEUR. Despite this small fraction, sgFCS isolates the diffusional dynamics of the bound fraction with no a priori assumptions as to the distribution of lifetimes. Sensitivity is greatly enhanced compared to standard FCS, revealing micellar aggregates forming between 0.2 and 1 wt% followed by formation of a percolated network. This sgFCS approach, which we apply for the first time to polymers in this work, is readily extendable to any dye that changes lifetime on binding.

A Reliable System for Quantitative G-Protein Activation Imaging in Cancer Cells

Fluorescence resonance energy transfer (FRET) biosensors have proven to be an indispensable tool in cell biology and, more specifically, in the study of G-protein signalling. The best method of measuring the activation status or FRET state of a biosensor is often fluorescence lifetime imaging microscopy (FLIM), as it does away with many disadvantages inherent to fluorescence intensity-based methods and is easily quantitated. Despite the significant potential, there is a lack of reliable FLIM-FRET biosensors, and the data processing and analysis workflows reported previously face reproducibility challenges. Here, we established a system in live primary mouse pancreatic ductal adenocarcinoma cells, where we can detect the activation of an mNeonGreen-Gαi3-mCherry-Gγ2 biosensor through the lysophosphatidic acid receptor (LPAR) with 2-photon time-correlated single-photon counting (TCSPC) FLIM. This combination gave a superior signal to the commonly used mTurquoise2-mVenus G-protein biosensor. This system has potential as a platform for drug screening, or to answer basic cell biology questions in the field of G-protein signalling.

Real-time, label-free detection and identification of bacteria through non-invasive optical imaging

Currently, traditional and newer molecular and mass spectrometry techniques of identifying bacteria from biological samples requires lengthy sample preparation, growth and labelling/staining assays. Thus, there is a pressing clinical need for an adjunct method that accurately identifies bacteria in real time. Here we report on the evaluation of confocal microscopy for the identification of clinically important and multi-drug resistant (MDR) bacteria in real time, using their intrinsic fluorescence features, i.e., emission spectra and fluorescence lifetime. The results demonstrate that difference in emission spectra and fluorescence lifetimes can be used as a fingerprint for identification of 12 bacterial species and MDR strains in real-time. Photostability or time-traces of bacteria demonstrated that these parameters could be used for tracking and recording without a need for labelling. Further, dilution experiments demonstrated that using intrinsic fluorescence S. aureus, Klebsiella pneumoniae and Escherichia coli bacteria can be detected and identified at clinically relevant concentrations as low as 2 × 102 CFU/mL. This non-invasive, non-labelling optical methodology may serve as the basis for development of a device that would quickly and accurately identify bacteria in biological samples. Thus, this intrinsic fluorescence technique would provide clinicians information, within minutes from sampling, to base accurate and specific treatments for patients.

Artificial Neural Network (ANN)-Based Determination of Fractional Contributions from Mixed Fluorophores using Fluorescence Lifetime Measurements

Here we present an artificial neural network (ANN)-approach to determine the fractional contributions Pi from fluorophores to a multi-exponential fluorescence decay in time-resolved lifetime measurements. Conventionally, Pi are determined by extracting two parameters (amplitude and lifetime) for each underlying mono-exponential decay using non-linear fitting. However, in this case parameter estimation is highly sensitive to initial guesses and weighting. In contrast, the ANN-based approach robustly gives the Pi without knowledge of amplitudes and lifetimes. By experimental measurements and Monte-Carlo simulations, we comprehensively show that accuracy and precision of Pi determination with ANNs and hence the number of distinguishable fluorophores depend on the fluorescence lifetimes' differences. For mixtures of up to five fluorophores, we determined the minimum uniform spacing Δτmin between lifetimes to obtain fractional contributions with a standard deviation of 5%. In example, five lifetimes can be distinguished with a respective minimum uniform spacing of approx. 10 ns even when the fluorophores' emission spectra are overlapping. This study underlines the enormous potential of ANN-based analysis for multi-fluorophore applications in fluorescence lifetime measurements.

Neural Networks Push the Limits of Luminescence Lifetime Nanosensing

Luminescence lifetime-based sensing is ideally suited to monitor biological systems due to its minimal invasiveness and remote working principle. Yet, its applicability is limited in conditions of low signal-to-noise ratio (SNR) induced by, e.g., short exposure times and presence of opaque tissues. Herein this limitation is overcome by applying a U-shaped convolutional neural network (U-NET) to improve luminescence lifetime estimation under conditions of extremely low SNR. Specifically, the prowess of the U-NET is showcased in the context of luminescence lifetime thermometry, achieving more precise thermal readouts using Ag2 S nanothermometers. Compared to traditional analysis methods of decay curve fitting and integration, the U-NET can extract average lifetimes more precisely and consistently regardless of the SNR value. The improvement achieved in the sensing performance using the U-NET is demonstrated with two experiments characterized by extreme measurement conditions: thermal monitoring of free-falling droplets, and monitoring of thermal transients in suspended droplets through an opaque medium. These results broaden the applicability of luminescence lifetime-based sensing in fields including in vivo experimentation and microfluidics, while, hopefully, spurring further research on the implementation of machine learning (ML) in luminescence sensing.

Probing Single-molecule Interfacial Electron Transfer Inside a Single Lipid Vesicle

Inhomogeneity in single molecule electron transfer at the surface of lipid in a single vesicle has been explored by single molecule spectroscopic technique. In our study we took Di-methyl aniline (DMA), as the electron donor (D) and three different organic dyes as acceptor. These dyes are C153, C480 and C152 and they reside in different regions in the vesicle depending upon their preference of residence. For each probe, we found fluctuations in the single-molecule fluorescence decay, which are attributed to the variation in the reactivity of interfacial electron transfer. We found a non-exponential auto-correlation fluctuation of the intensity of the probe, which is ascribed to the kinetic disorder in the rate of electron transfer. We have also shown the power law distribution of the dark state (off time), which obeys the levy's statistics. We found a shift in lifetime distribution for the probe (C153) from 3.9 ns to 3.5 ns. This observed quenching is due to the dynamic electron transfer. We observed the kinetic disorderness in the electron transfer reaction for each dye. This source of fluctuation in electron transfer rate may be ascribed to the inherent fluctuation, occurring on the time scale of ~ 1.1 ms (for C153) of the vesicle, containing lipids.

Spectrotemporal characterization of photoluminescent silicon nanocrystals and their energy transfer to dyes

Silicon nanocrystals (SiNCs) are a promising material for applications in bioanalysis and imaging. Compared to other types of semiconductor nanocrystals, the development and characterization of energy transfer (ET) configurations with SiNCs has been far more limited, resulting in an equally limited understanding of this process and its SiNC-specific nuances. Here, we present a systematic and detailed study of ET between SiNCs and dyes. A combination of spectroelectrophoresis and time-gated and time-resolved photoluminescence measurements were used to characterize the photophysical properties of ensembles of SiNCs and gain insight into how these properties varied as a function of nanocrystal size. ET between SiNC donors and a series of non-fluorescent Black Hole Quencher (BHQ) dyes and fluorescent sulfo-Cyanine 5.5 dye acceptors was evaluated in terms of spectral properties, wavelength-resolved efficiencies, trends with spectral overlap integral, and differences between two methods of BHQ association with the SiNCs. The overall results were consistent with a Förster resonance energy transfer (FRET) mechanism where the polydispersity of the SiNCs had a significant impact on the observed ET: the choice of wavelength and timing parameters were important, and ensemble measurements represented an average of heterogeneous ET behaviors. Prospective advantages and disadvantages of SiNCs as ET donors are discussed. This study serves as a foundation for the continued and optimized development of ET configurations with SiNCs.

Improving the performance of rapid lifetime determination for wide-field time-gated imaging in live cells

In biological research, rapid wide-field fluorescence lifetime imaging has become an important imaging tool. However, the biological samples with weak fluorescence signals and lower sensitivity often suffer from very low precision in lifetime determinations which restricts its widespread utilization in many bioimaging applications. To address this issue, a method is presented in this paper to substantially enhance the precision of rapid lifetime determination (RLD). It expedites the discrimination of fluorescence lifetimes, even for the weak signals coming from the cells, stained with long-lived biocompatible AIS/ZnS QDs. The proposed method works in two phases. The first phase deals with the systematic noise analysis based on the signal and contrast of the images in a time-gated imaging system, wherein acquiring the high-quality imaging data through optimization of hardware parameters improves the overall system performance. In the second phase, the chosen images are treated using total variation denoising method combined with the Max/Min filtering method for extracting the region of interest to reconstruct the intensity images for RLD. We performed several experiments on live cells to demonstrate the improvements in imaging performance by the systematic optimizations and data treatment. Obtained results demonstrated a great enhancement in signal-to-noise and contrast-to-noise ratios beside witnessing an obvious improvement in RLD for weak signals. This approach can be used not only to improve the quality of time-gated imaging data but also for efficient fluorescence lifetime imaging of live biological samples without compromising imaging speed and light exposure.

Can one detect intermediate denaturation states of DNA sequences by following the equilibrium open-close dynamic fluctuations of a single base pair?

Melting of DNA sequences may occur through a few major intermediate states, whose influence on the melting curve has been discussed previously, while their effect on the kinetics has not been explored thoroughly. Here, we chose a simple DNA sequence, forming a hairpin in its native (zipped) state, and study it using molecular dynamic (MD) simulations and a model integrating the Gaussian network model with bond-binding energies-the Gaussian binding energy (GBE) model. We find two major partial denaturation states, a bubble state and a partial unzipping state. We demonstrate the influence of these two states on the closing-opening base pair dynamics, as probed by a tagged bond auto-correlation function (ACF). We argue that the latter is measured by fluorescence correlation spectroscopy experiments, in which one base of the pair is linked to a fluorescent dye, while the complementary base is linked to a quencher, similar to the experiment reported by Altan-Bonnet et al. [Phys. Rev. Lett. 90, 138101 (2003)]. We find that tagging certain base pairs at temperatures around the melting temperature results in a multi-step relaxation of the ACF, while tagging other base pairs leads to an effectively single-step relaxation, albeit non-exponential. Only the latter type of relaxation has been observed experimentally, and we suggest which of the other base pairs should be tagged in order to observe multi-step relaxation. We demonstrate that this behavior can be observed with other sequences and argue that the GBE can reliably predict these dynamics for very long sequences, where MD simulations might be limited.

Classification of fluorescent anisotropy decay based on the distance approach in the frequency domain

Frequency-domain (FD) fluorometry is a widely utilized tool to probe unique features of complex biological structures, which may serve medical diagnostic purposes. The conventional data analysis approaches used today to extract the fluorescence intensity or fluorescence anisotropy (FA) decay data suffer from several drawbacks and are inherently limited by the characteristics and complexity of the decay models. This paper presents the squared distance (D²) technique, which categorized samples based on the direct frequency response data (FRD) of the FA decay. As such, it improves the classification ability of the FD measurements of the FA decay as it avoids any distortion that results from the challenged translation into time domain data. This paper discusses the potential use of the D² approach to classify biological systems. Mathematical formulation of D² technique adjusted to the FRD of the FA decay is described. In addition, it validates the D² approach using 2 simulated data sets of 6 groups with similar widely and closely spaced FA decay data as well as in experimental data of 4 samples of a fluorophore-solvent (fluorescein-glycerol) system. In the simulations, the classification accuracy was above 95% for all 6 groups. In the experimental data, the classification accuracy was 100%. The D² approach can help classify samples whose FA decay data are difficult to extract making FA in the FD a realistic diagnostic tool. The D² approach offers an advanced method for sorting biological samples with differences beyond the practical temporal resolution limit in a reliable and efficient manner based on the FRD of their time-resolved fluorescence measurements thereby achieving better diagnostic quality in a shorter time.

Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and that flimGANE provides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.

Resonance Energy Transfer to Track the Motion of Lanthanide Ions—What Drives the Intermixing in Core-Shell Upconverting Nanoparticles?

The imagination of clearly separated core-shell structures is already outdated by the fact, that the nanoparticle core-shell structures remain in terms of efficiency behind their respective bulk material due to intermixing between core and shell dopant ions. In order to optimize the photoluminescence of core-shell UCNP the intermixing should be as small as possible and therefore, key parameters of this process need to be identified. In the present work the Ln(III) ion migration in the host lattices NaYF₄ and NaGdF₄ was monitored. These investigations have been performed by laser spectroscopy with help of lanthanide resonance energy transfer (LRET) between Eu(III) as donor and Pr(III) or Nd(III) as acceptor. The LRET is evaluated based on the Förster theory. The findings corroborate the literature and point out the migration of ions in the host lattices. Based on the introduced LRET model, the acceptor concentration in the surrounding of one donor depends clearly on the design of the applied core-shell-shell nanoparticles. In general, thinner intermediate insulating shells lead to higher acceptor concentration, stronger quenching of the Eu(III) donor and subsequently stronger sensitization of the Pr(III) or the Nd(III) acceptors. The choice of the host lattice as well as of the synthesis temperature are parameters to be considered for the intermixing process.

Intrachain photophysics of a donor-acceptor copolymer

By taking advantage of bulk-heterojunction structures formed by blending conjugated donor polymers and non-fullerene acceptors, organic photovoltaic devices have recently attained promising power conversion efficiencies of above 18%. For optimizing organic photovoltaic devices, it is essential to understand the elementary processes that constitute light harvesters. Utilising femtosecond-resolved spectroscopic techniques that can access the timescales of locally excited (LE) state and charge-transfer (CT)/-separated (CS) states, herein we explored their photophysics in single chains of the top-notch performance donor-acceptor polymer, PM6, which has been widely used as a donor in state-of-the-art non-fullerene organic photovoltaic devices, in a single LE state per chain regime. Our observations revealed the ultrafast formation of a CT state and its equilibrium with the parent LE state. From the chain-length dependence of their lifetimes, the equilibrated states were found to idle until they reach a chain folding. At the chain folding, the CT state transforms into an interchain CT state that bifurcates into forming a CS state or annihilation within a picosecond. The observation of prevalent nonexponential behaviour in the relaxation of the transient species is attributed to the wide chain-length distribution that determines the emergence of the chain foldings in a single chain, thus, the lifetime of a LE and equilibrated CT states. Our findings indicate that the abundance of chain folding, where the generation of the "reactive" CS state is initiated from the interchain CT state, is essential for maximising charge carriers in organic photovoltaic devices based on PM6.

Method for controlled tissue theranostics using a single tunable laser source

Tissue diseases and related disorders need to be first recognized using diagnostic methods and then later treated by therapeutic methods-a joint procedure called theranostics. One of the main challenges in the field of retinal therapies remains in the success of the treatment, typically improving the local metabolism, by sparing the surrounding tissue and with the immediate information of the laser effect. In our study, we present a concept for real-time controlled tissue theranostics on a proof-of-concept study capable of using a single tunable ps laser source (in terms of irradiance, fluence, and repetition rate), done on ex-vivo human retinal pigment epithelium. We have found autofluorescence intensity and lifetime imaging diagnostics very promising for the recognition and quantification of laser effects ranging from selective non-destructive molecular tissue modification to complete tissue ablation. The main novelty of our work presents the developed algorithm for optimized theranostics based on the model function used to quantify laser-induced tissue changes through the diagnostics descriptors, fluorescence lifetime and fluorescence intensity parameters. This approach, together with the operation of the single adaptable laser source, can serve as a new theranostics method in personalized medicine in the future not only limited to treat retinal diseases.

Reaching Deeper: Absolute In Vivo Thermal Reading of Liver by Combining Superbright Ag2S Nanothermometers and In Silico Simulations

Luminescent nano-thermometry is a fast-developing technique with great potential for in vivo sensing, diagnosis, and therapy. Unfortunately, it presents serious limitations. The luminescence generated by nanothermometers, from which thermal readout is obtained, is strongly distorted by the attenuation induced by tissues. Such distortions lead to low signal levels and entangle absolute and reliable thermal monitoring of internal organs. Overcoming both limitations requires the use of high-brightness luminescent nanothermometers and adopting more complex approaches for temperature estimation. In this work, it is demonstrated how superbright Ag2S nanothermometers can provide in vivo, reliable, and absolute thermal reading of the liver during laser-induced hyperthermia. For that, a new procedure is designed in which thermal readout is obtained from the combination of in vivo transient thermometry measurements and in silico simulations. The synergy between in vivo and in silico measurements has made it possible to assess relevant numbers such as the efficiency of hyperthermia processes, the total heat energy deposited in the liver, and the relative contribution of Ag2S nanoparticles to liver heating. This work provides a new way for absolute thermal sensing of internal organs with potential application not only to hyperthermia processes but also to advanced diagnosis and therapy.

The coordination of spindle-positioning forces during the asymmetric division of the Caenorhabditis elegans zygote

In Caenorhabditis elegans zygote, astral microtubules generate forces essential to position the mitotic spindle, by pushing against and pulling from the cortex. Measuring microtubule dynamics there, we revealed the presence of two populations, corresponding to pulling and pushing events. It offers a unique opportunity to study, under physiological conditions, the variations of both spindle-positioning forces along space and time. We propose a threefold control of pulling force, by polarity, spindle position and mitotic progression. We showed that the sole anteroposterior asymmetry in dynein on-rate, encoding pulling force imbalance, is sufficient to cause posterior spindle displacement. The positional regulation, reflecting the number of microtubule contacts in the posterior-most region, reinforces this imbalance only in late anaphase. Furthermore, we exhibited the first direct proof that dynein processivity increases along mitosis. It reflects the temporal control of pulling forces, which strengthens at anaphase onset following mitotic progression and independently from chromatid separation. In contrast, the pushing force remains constant and symmetric and contributes to maintaining the spindle at the cell centre during metaphase.

Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach

The deconvolution process is a key step for quantitative evaluation of fluorescence lifetime imaging microscopy (FLIM) samples. By this process, the fluorescence impulse responses (FluoIRs) of the sample are decoupled from the instrument response (InstR). In blind deconvolution estimation (BDE), the FluoIRs and InstR are jointly extracted from a dataset with minimal a priori information. In this work, two BDE algorithms are introduced based on linear combinations of multi-exponential functions to model each FluoIR in the sample. For both schemes, the InstR is assumed with a free-form and a sparse structure. The local perspective of the BDE methodology assumes that the characteristic parameters of the exponential functions (time constants and scaling coefficients) are estimated based on a single spatial point of the dataset. On the other hand, the same exponential functions are used in the whole dataset in the global perspective, and just the scaling coefficients are updated for each spatial point. A least squares formulation is considered for both BDE algorithms. To overcome the nonlinear interaction in the decision variables, an alternating least squares (ALS) methodology iteratively solves both estimation problems based on non-negative and constrained optimizations. The validation stage considered first synthetic datasets at different noise types and levels, and a comparison with the standard deconvolution techniques with a multi-exponential model for FLIM measurements, as well as, with two BDE methodologies in the state of the art: Laguerre basis, and exponentials library. For the experimental evaluation, fluorescent dyes and oral tissue samples were considered. Our results show that local and global perspectives are consistent with the standard deconvolution techniques, and they reached the fastest convergence responses among the BDE algorithms with the best compromise in FluoIRs and InstR estimation errors.

Photon Statistics of Incoherent Cathodoluminescence with Continuous and Pulsed Electron Beams

Photon bunching in incoherent cathodoluminescence (CL) spectroscopy originates from the fact that a single high-energy electron can generate multiple photons when interacting with a material, thus, revealing key properties of electron-matter excitation. Contrary to previous works based on Monte Carlo modeling, here we present a fully analytical model describing the amplitude and shape of the second order autocorrelation function (g ⁽²⁾(τ)) for continuous and pulsed electron beams. Moreover, we extend the analysis of photon bunching to ultrashort electron pulses, in which up to 500 electrons per pulse excite the sample within a few picoseconds. We obtain a simple equation relating the bunching strength (g ⁽²⁾(0)) to the electron beam current, emitter decay lifetime, pulse duration, in the case of pulsed electron beams, and electron excitation efficiency (γ), defined as the probability that an electron creates at least one interaction with the emitter. The analytical model shows good agreement with the experimental data obtained on InGaN/GaN quantum wells using continuous, ns-pulsed (using beam blanker) and ultrashort ps-pulsed (using photoemission) electron beams. We extract excitation efficiencies of 0.13 and 0.05 for 10 and 8 keV electron beams, respectively, and we observe that nonlinear effects play no compelling role, even after excitation with ultrashort and dense electron cascades in the quantum wells.

Differences in the properties of porcine cortical and nuclear fiber cell plasma membranes revealed by saturation recovery EPR spin labeling measurements

Eye lens membranes are complex biological samples. They consist of a variety of lipids that form the lipid bilayer matrix, integral proteins embedded into the lipid bilayer, and peripheral proteins. This molecular diversity in membrane composition induces formation of lipid domains with particular physical properties that are responsible for the maintenance of proper membrane functions. These domains can be, and have been, effectively described in terms of the rotational diffusion of lipid spin labels and oxygen collision with spin labels using the saturation recovery (SR) electron paramagnetic resonance method and, now, using stretched exponential function for the analysis of SR signals. Here, we report the application of the stretched exponential function analysis of SR electron paramagnetic resonance signals coming from cholesterol analog, androstane spin label (ASL) in the lipid bilayer portion of intact fiber cell plasma membranes (IMs) isolated from the cortex and nucleus of porcine eye lenses. Further, we compare the properties of these IMs with model lens lipid membranes (LLMs) derived from the total lipids extracted from cortical and nuclear IMs. With this approach, the IM can be characterized by the continuous probability density distribution of the spin-lattice relaxation rates associated with the rotational diffusion of a spin label, and by the distribution of the oxygen transport parameter within the IM (i.e., the collision rate of molecular oxygen with the spin label). We found that the cortical and nuclear LLMs possess very different, albeit homogenous, spin lattice relaxation rates due to the rotational diffusion of ASL, indicating that the local rigidity around the spin label in nuclear LLMs is considerably greater than that in cortical LLMs. However, the oxygen transport parameter around the spin label is very similar and slightly heterogenous for LLMs from both sources. This heterogeneity was previously missed when distinct exponential analysis was used. The spin lattice relaxation rates due to either the rotational diffusion of ASL or the oxygen collision with the spin label in nuclear IMs have slower values and wider distributions compared with those of cortical IMs. From this evidence, we conclude that lipids in nuclear IMs are less fluid and more heterogeneous than those in cortical membranes. Additionally, a comparison of properties of IMs with corresponding LLMs, and lipid and protein composition analysis, allow us to conclude that the decreased lipid-to-protein ratio not only induces greater rigidity of nuclear IMs, but also creates domains with the considerably decreased and variable oxygen accessibility. The advantages and disadvantages of this method, as well as its use for the cluster analysis, are discussed.

Enhanced detection of oral dysplasia by structured illumination fluorescence lifetime imaging microscopy

We demonstrate that structured illumination microscopy has the potential to enhance fluorescence lifetime imaging microscopy (FLIM) as an early detection method for oral squamous cell carcinoma. FLIM can be used to monitor or detect changes in the fluorescence lifetime of metabolic cofactors (e.g. NADH and FAD) associated with the onset of carcinogenesis. However, out of focus fluorescence often interferes with this lifetime measurement. Structured illumination fluorescence lifetime imaging (SI-FLIM) addresses this by providing depth-resolved lifetime measurements, and applied to oral mucosa, can localize the collected signal to the epithelium. In this study, the hamster model of oral carcinogenesis was used to evaluate SI-FLIM in premalignant and malignant oral mucosa. Cheek pouches were imaged in vivo and correlated to histopathological diagnoses. The potential of NADH fluorescence signal and lifetime, as measured by widefield FLIM and SI-FLIM, to differentiate dysplasia (pre-malignancy) from normal tissue was evaluated. ROC analysis was carried out with the task of discriminating between normal tissue and mild dysplasia, when changes in fluorescence characteristics are localized to the epithelium only. The results demonstrate that SI-FLIM (AUC = 0.83) is a significantly better (p-value = 0.031) marker for mild dysplasia when compared to widefield FLIM (AUC = 0.63).

Nanoparticles for In Vivo Lifetime Multiplexed Imaging

Lifetime multiplexed imaging refers to the simultaneous labeling of different structures with fluorescent probes that present identical photoluminescence spectra and distinct fluorescence lifetimes. This technique allows extracting quantitative information from multichannel in vivo fluorescence imaging. In vivo lifetime multiplexed imaging requires fluorophores with excitation and emission bands in the near-infrared (NIR) and tunable fluorescence lifetimes, plus an imaging system capable of time-resolved image acquisition and analysis.

FLIM data analysis based on Laguerre polynomial decomposition and machine-learning

SIGNIFICANCE

The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis.

AIM

We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML).

APPROACH

The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker.

RESULTS

The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.

CONCLUSIONS

The ML-based approach shows great performance in FLIM data analysis.

Time-Resolved Fluorescence and Essential Dynamics Study on the Structural Heterogeneity of p53DBD Bound to the Anticancer p28 Peptide

Time-resolved fluorescence emission was combined with molecular dynamics (MD) simulations to investigate the DNA-binding domain (DBD) of the tumor suppressor p53 alone and its complex with the anticancer peptide p28 (DBD/p28). The fluorescence emission decay of the lone Trp residue, from both DBD and DBD/p28, was well-described by a stretched exponential function. Such a behavior was ascribed to heterogeneity in the Trp relaxation behavior, likely due to the coexistence of different conformational states. The increase of the stretching parameter, on passing from DBD to DBD/p28, indicates a reduced heterogeneity in the Trp146 environment for DBD/p28. Moreover, the effects of p28 on the global dynamics of DBD were analyzed by the essential dynamics method on 30 ns long MD trajectories of both DBD and DBD/p28. We found the establishment of wide-amplitude anharmonic modes throughout the DBD molecule, with a particularly high amplitude being detected in the DNA-binding region. These modes are significantly reduced when DBD is bound to p28, consistently with a structure stabilization. In summary, the results indicate that p28 binding has a strong effect on both the local and global heterogeneity of DBD, thus providing some hints to the understanding of its anticancer activity.

Use of Machine Learning with Temporal Photoluminescence Signals from CdTe Quantum Dots for Temperature Measurement in Microfluidic Devices

Because of the vital role of temperature in many biological processes studied in microfluidic devices, there is a need to develop improved temperature sensors and data analysis algorithms. The photoluminescence (PL) of nanocrystals (quantum dots) has been successfully used in microfluidic temperature devices, but the accuracy of the reconstructed temperature has been limited to about 1 K over a temperature range of tens of degrees. A machine learning algorithm consisting of a fully-connected network of seven layers with decreasing numbers of nodes was developed and applied to a combination of normalized spectral and time-resolved PL data of CdTe quantum dot emission in a microfluidic device. The data used by the algorithm was collected over two temperature ranges: 10 K to 300 K, and 298 K to 319 K. The accuracy of each neural network was assessed via mean absolute error of a holdout set of data. For the low temperature regime, the accuracy was 7.7 K, or 0.4 K when the holdout set is restricted to temperatures above 100 K. For the high temperature regime, the accuracy was 0.1 K. This method provides demonstrates a potential machine learning approach to accurately sense temperature in microfluidic (and potentially nanofluidic) devices when the data analysis is based on normalized PL data when it is stable over time.

Characterization of charge carrier behavior in photocatalysis using transient absorption spectroscopy

Photocatalysis is a promising sustainable method to generate solar fuels for the future, as well as having other applications such as water/air purification. However, the performance of photocatalysts is often limited by poor charge carrier dynamics. To improve charge carrier dynamics, it is necessary to characterize and understand charge carrier behavior in photocatalytic systems. This critical review will present Transient Absorption Spectroscopy (TAS) as a useful technique for understanding the behavior of photoexcited charges in semiconductor photocatalysts. The role of TAS amongst other techniques for characterizing charge carrier behavior will be outlined. Basic principles behind TAS will be introduced, and interpretation of TAS spectra and kinetics will be discussed in the context of exemplar literature. It will be demonstrated that TAS is a powerful technique to obtain fundamental understanding of the behavior of photoexcited charges.

Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications

SIGNIFICANCE

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique to distinguish the unique molecular environment of fluorophores. FLIM measures the time a fluorophore remains in an excited state before emitting a photon, and detects molecular variations of fluorophores that are not apparent with spectral techniques alone. FLIM is sensitive to multiple biomedical processes including disease progression and drug efficacy.

AIM

We provide an overview of FLIM principles, instrumentation, and analysis while highlighting the latest developments and biological applications.

APPROACH

This review covers FLIM principles and theory, including advantages over intensity-based fluorescence measurements. Fundamentals of FLIM instrumentation in time- and frequency-domains are summarized, along with recent developments. Image segmentation and analysis strategies that quantify spatial and molecular features of cellular heterogeneity are reviewed. Finally, representative applications are provided including high-resolution FLIM of cell- and organelle-level molecular changes, use of exogenous and endogenous fluorophores, and imaging protein-protein interactions with Förster resonance energy transfer (FRET). Advantages and limitations of FLIM are also discussed.

CONCLUSIONS

FLIM is advantageous for probing molecular environments of fluorophores to inform on fluorophore behavior that cannot be elucidated with intensity measurements alone. Development of FLIM technologies, analysis, and applications will further advance biological research and clinical assessments.

Microscopic Understanding of the Effect of Ionic Liquid on Protein from Molecular Simulation Studies

We have performed molecular dynamics (MD) simulations of the protein α-lactalbumin in aqueous solution containing the ionic liquid (IL) 1-butyl-3-methyl imidazolium tetrafluoroborate ([BMIM][BF₄]) as the cosolvent at different concentrations. Attempts have been made to obtain quantitative understanding of the effects of the IL on the conformational features of the protein as well as the distributions of the IL and water around it. The calculations revealed enhanced rigidity of the protein with reduced conformational fluctuations and increasingly correlated local motions in the presence of the IL. Nonuniform relative population of the BMIM⁺ and BF₄^- ions at the protein surface with respect to that in the bulk solution has been observed. It is demonstrated that exchange of water by the IL around the protein results in rearrangement of the hydrogen bond network at the interface with breaking of protein-water hydrogen bonds and formation of protein-IL hydrogen bonds. Importantly, it is found that the protein forms increased number of stronger salt bridges in the presence of IL. This shows that the formation of a greater number of such stronger salt bridges is the origin behind the enhanced rigidity of the protein in the presence of the IL.

Understanding the Self-Assembling Behavior of Biological Building Block Molecules: A Spectroscopic and Microscopic Approach

"Mother nature" utilizes molecular self-assembly as an efficient tool to design several fascinating supramolecular architectures from simple building blocks like amino acids, peptides, and nucleobases. The self-assembling behavior of various biologically important molecules, morphological outcomes, molecular mechanism of association, and finally their applications in the real world draw broad interest from chemical and biological point of views. In this present Feature Article, the amyloid hypothesis is extended to include nonproteinaceous single metabolites that invoke a new paradigm for the pathology of inborn metabolic disorders. In this scenario, we dedicate this paper to understanding the morphological consequences and mechanistic insight of the self-assembly of some important amino acids (e.g., l-phenylalanine, l-tyrosine, glycine, etc.) and nucleobases (adenine and eight uracil moiety derivatives). Using proper spectroscopic and microscopic tools, distinct assembling mechanisms of different amino acids and nucleobases have been established. Again, lanthanides, polyphenolic compounds such as crown ethers, and a worldwide drink, beer, are elegantly employed as inhibitors of the resulting fibrillar aggregated structures. As a consequence, this study will cover literally a vast region in the self-assembling outcomes of single biologically important molecules, and therefore, we expect that a detailed understanding of such morphological outcomes using spectroscopic and microscopic approaches may open a new paradigm in this burgeoning field.

Systematic Enzyme Mapping of Cellular Metabolism by Phasor-Analyzed Label-Free NAD(P)H Fluorescence Lifetime Imaging

In the past years, cellular metabolism of the immune system experienced a revival, as it has become clear that it is not merely responsible for the cellular energy supply, but also impacts on many signaling pathways and, thus, on diverse cellular functions. Label-free fluorescence lifetime imaging of the ubiquitous coenzymes NADH and NADPH (NAD(P)H-FLIM) makes it possible to monitor cellular metabolism in living cells and tissues and has already been applied to study metabolic changes both under physiologic and pathologic conditions. However, due to the complex distribution of NAD(P)H-dependent enzymes in cells, whose distribution continuously changes over time, a thorough interpretation of NAD(P)H-FLIM results, in particular, resolving the contribution of various enzymes to the overall metabolic activity, remains challenging. We developed a systematic framework based on angle similarities of the phase vectors and their length to analyze NAD(P)H-FLIM data of cells and tissues based on a generally valid reference system of highly abundant NAD(P)H-dependent enzymes in cells. By using our analysis framework, we retrieve information not only about the overall metabolic activity, i.e., the fraction of free to enzyme-bound NAD(P)H, but also identified the enzymes predominantly active within the sample at a certain time point with subcellular resolution. We verified the performance of the approach by applying NAD(P)H-FLIM on a stromal-like cell line and identified a different group of enzymes that were active in the cell nuclei as compared to the cytoplasm. As the systematic phasor-based analysis framework of label-free NAD(P)H-FLIM can be applied both in vitro and in vivo, it retains the unique power to enable dynamic enzyme-based metabolic investigations, at subcellular resolution, in genuine environments.

Computational Characterization of a Cholesterol-Based Molecular Rotor in Lipid Membranes

Biophysical properties of cellular membranes critically depend on their content of cholesterol and its interaction with various other lipid species. Cholesterol-dependent friction at the nanoscale can be studied with molecular rotors, whose quantum yield depends on rotational dynamics of functional groups during their excited state lifetime. Here, we present a detailed computational analysis of a phenyl-BODIPY-linked cholesterol based molecular rotor in direct comparison with the well-known TopFluor-cholesterol. We describe a new parametrization strategy of force field parameters for the BODIPY moiety and carry out extensive molecular dynamics simulations of the probe in membranes in the absence or presence of cholesterol. Our study quantifies the extent of membrane perturbation by these probes, analyzes their tilting resistance in the bilayer and derives dynamic properties directly related to the rotor propensity. We show that phenyl-BODIPY-cholesterol bears potential as a cholesterol-dependent molecular rotor to report about microviscosity of sterol-containing model and cell membranes.

Improving Diagnosis of Cervical Pre-Cancer: Combination of PCA and SVM Applied on Fluorescence Lifetime Images

We report a significant improvement in the diagnosis of cervical cancer through a combined application of principal component analysis (PCA) and support vector machine (SVM) on the average fluorescence decay profile of Fluorescence Lifetime Images (FLI) of epithelial hyperplasia (EH) and CIN-I cervical tissue samples, obtained ex-vivo. The fast and slow components of double exponential fitted fluorescence lifetimes were found to be higher for EH compared to the lifetimes of CIN-I samples. Application of PCA to the average time-resolved fluorescence decay profiles showed that the 2nd PC, in combination with 1st PC, enhanced the discrimination between EH and CIN-I tissues. Fluorescence lifetime and PC scores were then classified separately by using SVM support vector machine to identify the two. On applying SVM to a combination of fluorescence lifetime and PC scores, diagnostic capability improved significantly.

Micro-fluorescence lifetime and spectral imaging of ytterbium doped laser materials

We present the application of a confocal fluorescence microscope to the analysis of Yb-doped solid-state laser materials, with examples of Yb-doped crystals, photonic crystal fibers and fiber preforms made with different manufacturing processes. Beside the fluorescence lifetime image itself, a microscopic spectral fluorescence emission analysis is presented and spatially resolved emission cross sections are obtained. Doping concentration and its distributions and other laser optical parameters are measured, which help to analyze manufacturing steps. Further properties like photodarkening and saturation are addressed.

Complementary cathodoluminescence lifetime imaging configurations in a scanning electron microscope

Cathodoluminescence (CL) spectroscopy provides a powerful way to characterize optical properties of materials with deep-subwavelength spatial resolution. While CL imaging to obtain optical spectra is a well-developed technology, imaging CL lifetimes with nanoscale resolution has only been explored in a few studies. In this paper we compare three different time-resolved CL techniques and compare their characteristics. Two configurations are based on the acquisition of CL decay traces using a pulsed electron beam that is generated either with an ultra-fast beam blanker, which is placed in the electron column, or by photoemission from a laser-driven electron cathode. The third configuration uses measurements of the autocorrelation function g⁽²⁾ of the CL signal using either a continuous or a pulsed electron beam. The three techniques are compared in terms of complexity of implementation, spatial and temporal resolution, and measurement accuracy as a function of electron dose. A single sample of InGaN/GaN quantum wells is investigated to enable a direct comparison of lifetime measurement characteristics of the three techniques. The g⁽²⁾-based method provides decay measurements at the best spatial resolution, as it leaves the electron column configuration unaffected. The pulsed-beam methods provide better detail on the temporal excitation and decay dynamics. The ultra-fast blanker configuration delivers electron pulses as short as 30 ps at 5 keV and 250 ps at 30 keV. The repetition rate can be chosen arbitrarily up to 80 MHz and requires a conjugate plane geometry in the electron column that reduces the spatial resolution in our microscope. The photoemission configuration, pumped with 250 fs 257 nm pulses at a repetition rate from 10 kHz to 25 MHz, allows creation of electron pulses down to a few ps, with some loss in spatial resolution.

Bathophenanthroline Disulfonate Ligand-Induced Self-Assembly of Ir(III) Complexes in Water: An Intriguing Class of Photoluminescent Soft Materials

Strong evidence of concentration-induced and dissolved electrolyte-induced chromophore aggregation has been universally observed in numerous water soluble bis-cyclometalated Ir(III) photosensitizers bearing the sulfonated diimine ligands bathophenanthroline disulfonate and bathocuproine disulfonate. This new class of aqueous-based soft materials was highly photoluminescent in their aggregated state where detailed spectroscopic investigations of this phenomenon revealed significant blue shifts of their respective photoluminescence emission spectra with concomitant increases in excited-state lifetimes and quantum yields initiating even at micromolar chromophore concentrations in water or upon the addition of a strong electrolyte. A combination of nanoscale particle characterization techniques, static and dynamic photoluminescence spectroscopic studies, along with atomistic molecular dynamics (MD) simulations of these soft materials suggests the formation of small, heterogeneous nanoaggregate structures, wherein the sulfonated diimine ancillary ligand serves as a pro-aggregating subunit in all instances. Importantly, the experimental and MD findings suggest the likelihood of discovering similar aqueous aggregation phenomena occurring in all transition-metal complexes bearing these water-solubilizing diimine ligands.

Strong Purcell Effect on a Neutral Atom Trapped in an Open Fiber Cavity

We observe a sixfold Purcell broadening of the D_{2} line of an optically trapped ^{87}Rb atom strongly coupled to a fiber cavity. Under external illumination by a near-resonant laser, up to 90% of the atom's fluorescence is emitted into the resonant cavity mode. The sub-Poissonian statistics of the cavity output and the Purcell enhancement of the atomic decay rate are confirmed by the observation of a strongly narrowed antibunching dip in the photon autocorrelation function. The photon leakage through the higher-transmission mirror of the single-sided resonator is the dominant contribution to the field decay (κ≈2π×50  MHz), thus offering a high-bandwidth, fiber-coupled channel for photonic interfaces such as quantum memories and single-photon sources.

Quantitative Live Cell FLIM Imaging in Three Dimensions

In this chapter, the concept of fluorescence lifetime and its utility in quantitative live cell imaging will be introduced, along with methods to record and analyze FLIM data. Relevant applications in 3D tissue and live cell imaging, including multiplexed FLIM detection, will also be detailed.

Phasor-Based Endogenous NAD(P)H Fluorescence Lifetime Imaging Unravels Specific Enzymatic Activity of Neutrophil Granulocytes Preceding NETosis

Time-correlated single-photon counting combined with multi-photon laser scanning microscopy has proven to be a versatile tool to perform fluorescence lifetime imaging in biological samples and, thus, shed light on cellular functions, both in vitro and in vivo. Here, by means of phasor-analyzed endogenous NAD(P)H (nicotinamide adenine dinucleotide (phosphate)) fluorescence lifetime imaging, we visualize the shift in the cellular metabolism of healthy human neutrophil granulocytes during phagocytosis of Staphylococcus aureus pHrodo™ beads. We correlate this with the process of NETosis, i.e., trapping of pathogens by DNA networks. Hence, we are able to directly show the dynamics of NADPH oxidase activation and its requirement in triggering NETosis in contrast to other pathways of cell death and to decipher the dedicated spatio-temporal sequence between NADPH oxidase activation, nuclear membrane disintegration and DNA network formation. The endogenous FLIM approach presented here uniquely meets the increasing need in the field of immunology to monitor cellular metabolism as a basic mechanism of cellular and tissue functions.

Live-cell imaging of new polyene sterols for improved analysis of intracellular cholesterol transport

Analysis of intracellular cholesterol transport by fluorescence microscopy requires suitable fluorescent analogues of cholesterol. Most existing cholesterol analogues contain lipophilic dyes which can compromise the sterol properties in membranes. An alternative strategy is to introduce additional double bonds into the sterol ring system resulting in intrinsic fluorescence, while at the same time keeping the cholesterol-like properties of the analogues. Existing polyene sterols, such as dehydroergosterol (DHE) or cholestatrienol (CTL), however, contain only three double bonds and suffer from low brightness, significant photobleaching and excitation/emission in the ultraviolet region. Thus, special equipment is required to image such sterols. Here, we describe synthesis, characterization and intracellular imaging of new polyene sterols containing four conjugated double bonds in the sterol ring system. We show that such analogues have red-shifted excitation and emission by ∼20 nm compared to DHE or CTL. The red shift was even more pronounced when preventing keto-enol tautomer equilibration by protecting the 3'-hydroxy group with acetate. We show that the latter analogue can be imaged on a conventional wide field microscope with a DAPI/filipin filter cube. The new polyene sterols show reduced photobleaching compared to DHE or CTL allowing for improved deconvolution microscopy of sterol containing cellular membranes.

Inverse Transformation: Unleashing Spatially Heterogeneous Dynamics with an Alternative Approach to XPCS Data Analysis

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.

Comparison of Compressive Stress-Relaxation Behavior in Osteoarthritic (ICRS Graded) Human Articular Cartilage

Osteoarthritis (OA) is a common joint disorder found mostly in elderly people. The role of mechanical behavior in the progression of OA is complex and remains unclear. The stress-relaxation behavior of human articular cartilage in clinically defined osteoarthritic stages may have importance in diagnosis and prognosis of OA. In this study we investigated differences in the biomechanical responses among human cartilage of ICRS grades I, II and III using polymer dynamics theory. We collected 24 explants of human articular cartilage (eight each of ICRS grade I, II and III) and acquired stress-relaxation data applying a continuous load on the articular surface of each cartilage explant for 1180 s. We observed a significant decrease in Young’s modulus, stress-relaxation time, and stretching exponent in advanced stages of OA (ICRS grade III). The stretch exponential model speculated that significant loss in hyaluronic acid polymer might be the reason for the loss of proteoglycan in advanced OA. This work encourages further biomechanical modelling of osteoarthritic cartilage utilizing these data as input parameters to enhance the fidelity of computational models aimed at revealing how mechanical behaviors play a role in pathogenesis of OA.

Stabilization of the Cubic Crystalline Phase in Organometal Halide Perovskite Quantum Dots via Surface Energy Manipulation

Surface functionalization of nanoscale materials has a significant impact on their properties. We have demonstrated the effect of different passivating ligands on the crystal phase of organometal halide perovskite quantum dots (PQDs). Using static and dynamic spectroscopy, we studied phase transitions in CH₃NH₃PbBr₃ PQDs ligated with either octylaminebromide (P-OABr) or 3-aminopropyl triethoxysilane (P-APTES). Around 140 K, P-OABr underwent a structural phase transition from tetragonal to orthorhombic, established by the emergence of a higher energy band in the photoluminescence (PL) spectrum. This was not observed in P-APTES, despite cooling down to 20 K. Additionally, time-resolved and excitation power-dependent PL, as well as Raman spectroscopy over a range of 300-20 K, revealed that recombination rates and types of charge carriers involved are significantly different in P-APTES and P-OABr. Our findings highlight how aspects of PQD phase stabilization are linked to nanoscale morphology and the crystal phase diagram.