Superpixels meet essential spectra for fast Raman hyperspectral microimaging.

In the context of spectral unmixing, essential information corresponds to the most linearly dissimilar rows and/or columns of a two-way data matrix which are indispensable to reproduce the full data matrix in a convex linear way. Essential information has recently been shown accessible on-the-fly via a decomposition of the measured spectra in the Fourier domain and has opened new perspectives for fast Raman hyperspectral microimaging. In addition, when some spatial prior is available about the sample, such as the existence of homogeneous objects in the image, further acceleration for the data acquisition procedure can be achieved by using superpixels. The expected gain in acquisition time is shown to be around three order of magnitude on simulated and real data with very limited distortions of the estimated spectrum of each object composing the images.

Assessment of Essential Information in the Fourier Domain to Accelerate Raman Hyperspectral Microimaging.

In the context of multivariate curve resolution (MCR) and spectral unmixing, essential information (EI) corresponds to the most linearly dissimilar rows and/or columns of a two-way data matrix. In recent works, the assessment of EI has been revealed to be a very useful practical tool to select the most relevant spectral information before MCR analysis, key features being speed and compression ability. However, the canonical approach relies on the principal component analysis to evaluate the convex hull that encapsulates the data structure in the normalized score space. This implies that the evaluation of the essentiality of each spectrum can only be achieved after all the spectra have been acquired by the instrument. This paper proposes a new approach to extract EI in the Fourier domain (EIFD). Spectral information is transformed into Fourier coefficients, and EI is assessed from a convex hull analysis of the data point cloud in the 2D phasor plots of a few selected harmonics. Because the coordinate system of a phasor plot does not depend on the data themselves, the evaluation of the essentiality of the information carried by each spectrum can be achieved individually and independently from the others. As a result, time-consuming operations like Raman spectral imaging can be significantly accelerated exploiting a chemometric-driven (i.e., based on the EI content of a spectral pixel) procedure for data acquisition and targeted sampling. The usefulness of EIFD is shown by analyzing Raman hyperspectral microimaging data, demonstrating a potential 50-fold acceleration of Raman acquisition.

Multivariate Curve Resolution Slicing of Multiexponential Time-Resolved Spectroscopy Fluorescence Data.

Time-resolved fluorescence spectroscopy (TRFS), i.e., measurement of fluorescence decay curves for different excitation and/or emission wavelengths, provides specific and sensitive local information on molecules and on their environment. However, TRFS relies on multiexponential data fitting to derive fluorescence lifetimes from the measured decay curves and the time resolution of the technique is limited by the instrumental response function (IRF). We propose here a multivariate curve resolution (MCR) approach based on data slicing to perform tailored and fit-free analysis of multiexponential fluorescence decay curves. MCR slicing, taking as a basic framework the multivariate curve resolution-alternating least-squares (MCR-ALS) soft-modeling algorithm, relies on a hybrid bilinear/trilinear data decomposition. A key feature of the method is that it enables the recovery of individual components characterized by decay profiles that are only partially describable by monoexponential functions. For TRFS data, not only pure multiexponential tail information but also shorter time delay information can be decomposed, where the signal deviates from the ideal exponential behavior due to the limited time resolution. The accuracy of the proposed approach is validated by analyzing mixtures of three commercial dyes and characterizing the mixture composition, lifetimes, and associated contributions, even in situations where only ternary mixture samples are available. MCR slicing is also applied to the analysis of TRFS data obtained on a photoswitchable fluorescent protein (rsEGFP2). Three fluorescence lifetimes are extracted, along with the profile of the IRF, highlighting that decomposition of complex systems, for which individual isomers are characterized by different exponential decays, can also be achieved.

Study of conformational transitions of i-motif DNA using time-resolved fluorescence and multivariate analysis methods.

Recently, the presence of i-motif structures at C-rich sequences in human cells and their regulatory functions have been demonstrated. Despite numerous steady-state studies on i-motif at neutral and slightly acidic pH, the number and nature of conformation of this biological structure are still controversial. In this work, the fluorescence lifetime of labelled molecular beacon i-motif-forming DNA sequences at different pH values is studied. The influence of the nature of bases at the lateral loops and the presence of a Watson-Crick-stabilized hairpin are studied by means of time-correlated single-photon counting technique. This allows characterizing the existence of several conformers for which the fluorophore has lifetimes ranging from picosecond to nanosecond. The information on the existence of different i-motif structures at different pH values has been obtained by the combination of classical global decay fitting of fluorescence traces, which provides lifetimes associated with the events defined by the decay of each sequence and multivariate analysis, such as principal component analysis or multivariate curve resolution based on alternating least squares. Multivariate analysis, which is seldom used for this kind of data, was crucial to explore similarities and differences of behaviour amongst the different DNA sequences and to model the presence and identity of the conformations involved in the pH range of interest. The results point that, for i-motif, the intrachain contact formation and its dissociation show lifetimes ten times faster than for the open form of DNA sequences. They also highlight that the presence of more than one i-motif species for certain DNA sequences according to the length of the sequence and the composition of the bases in the lateral loop.

Essential Spectral Pixels for Multivariate Curve Resolution of Chemical Images.

We propose a methodology to select essential spectral pixels (ESPs) of chemical images. These pixels are on the outer envelope of the principal component scores of the data and can be identified by convex-hull computation. As ESPs carry all the linearly mixed spectral information, large hyperspectral images can be dramatically reduced before multivariate curve resolution (MCR) analysis. We investigated chemical images of different spectroscopies, sizes, and complexities and show that the analysis of full data sets of hundreds of thousands of spectral pixels only require a few tenths of them.

SIMCA Modeling for Overlapping Classes: Fixed or Optimized Decision Threshold?

An approach exploiting the principles of Receiver Operating Characteristic (ROC) curves for the simultaneous optimization of both the complexity and the decision threshold in Soft Independent Modeling of Class Analogy (SIMCA) classification models is here proposed. The outcomes resulting from the analysis of two simulated and four real case-studies highlight that, in the presence of strong overlap among various categories of samples, the implemented method can lead to better classification efficiency in external validation, compared to fixing such a threshold a priori. This guarantees a higher robustness toward class dispersion. On the other hand, in cases of clearer and more definite separation among the different groups of observations, their classification performance is equally satisfactory for test samples.

Study of light-induced formation of photodimers in the i-motif nucleic acid structure by rapid-scan FTIR difference spectroscopy and hybrid hard- and soft-modelling.

The i-motif is a DNA structure formed by cytosine-rich sequences, very relevant from a biochemical point of view and potentially useful in nanotechnology as pH-sensitive nanodevices or nanomotors. To provide a different view on the structural changes and dynamics of direct excitation processes involving i-motif structures, the use of rapid-scan FTIR spectroscopy is proposed. Hybrid hard- and soft-modelling based on the Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) algorithm has been used for the resolution of rapid-scan FTIR spectra and the interpretation of the photochemically induced time-dependent conformational changes of i-motif structures. The hybrid hard- and soft-modelling version of MCR-ALS (HS-MCR), which allows the introduction of kinetic models to describe process behavior, provides also rate constants associated with the transitions modeled. The results show that UV irradiation does not produce degradation of the studied sequences but induces the formation of photodimers. The presence of these affect much more the stability of i-motif structures formed by short sequences than that of those formed by longer sequences containing additional structural stabilizing elements, such as hairpins.

Frame-Insensitive Expression Cloning of Fluorescent Protein from Scolionema suvaense.

Expression cloning from cDNA is an important technique for acquiring genes encoding novel fluorescent proteins. However, the probability of in-frame cDNA insertion following the first start codon of the vector is normally only 1/3, which is a cause of low cloning efficiency. To overcome this issue, we developed a new expression plasmid vector, pRSET-TriEX, in which transcriptional slippage was induced by introducing a DNA sequence of (dT)14 next to the first start codon of pRSET. The effectiveness of frame-insensitive cloning was validated by inserting the gene encoding eGFP with all three possible frames to the vector. After transformation with one of these plasmids, E. coli cells expressed eGFP with no significant difference in the expression level. The pRSET-TriEX vector was then used for expression cloning of a novel fluorescent protein from Scolionema suvaense. We screened 3658 E. coli colonies transformed with pRSET-TriEX containing Scolionema suvaense cDNA, and found one colony expressing a novel green fluorescent protein, ScSuFP. The highest score in protein sequence similarity was 42% with the chain c of multi-domain green fluorescent protein like protein "ember" from Anthoathecata sp. Variations in the N- and/or C-terminal sequence of ScSuFP compared to other fluorescent proteins indicate that the expression cloning, rather than the sequence similarity-based methods, was crucial for acquiring the gene encoding ScSuFP. The absorption maximum was at 498 nm, with an extinction efficiency of 1.17 × 105 M-1·cm-1. The emission maximum was at 511 nm and the fluorescence quantum yield was determined to be 0.6. Pseudo-native gel electrophoresis showed that the protein forms obligatory homodimers.

AIE phenomena of a cyanostilbene derivative as a probe of molecular assembly processes.

The initial processes of the crystallization of a solute molecule, 1-cyano-trans-1,2-bis-(4'-methylbiphenyl)-ethylene (CN-MBE) in binary solution (water and acetone), were investigated by means of fluorescence spectroscopy as well as scanning electron microscopy (SEM). With an increase in the volume fraction (Vw) of the poor solvent (water) in the solution, a drastic change in the fluorescence spectra and intensity of CN-MBE was observed. This change was attributed to aggregation induced emission (AIE). By analyzing the evolution of AIE by multivariate curve resolution-alternating least squares (MCR-ALS), it was revealed that four main species appeared in the solution depending on the Vw values. On the basis of molecular exciton theory, we assigned these four emissive states to the monomer, H-dimer, J-dimer, and H-aggregates. Interestingly, the J-dimer state was observed only in a Vw range of 40% to 50%, just before the formation of the aggregate. This result suggests that the J-dimer plays an important role as the precursor for larger aggregates leading to crystal formation. By integrating the present results with previous work on the crystallization of CN-MBA through solvent evaporation, we discussed the dynamics of the crystallization from the viewpoint of the sequence of molecular species appearing in the aggregation in solution.

Mapping pixel dissimilarity in wide-field super-resolution fluorescence microscopy.

Recent advances in fluorescence bioimaging with single-molecule sensitivity have relied on the analysis and visualization of single-molecule data obtained on smart fluorophores. We describe an alternative method to enhance the information content of densely labeled fluorescence images. Visualization is improved by representing pixels as the dissimilarities of the fluctuations of the fluorescence signals, with the dissimilarity being taken to the mean of the signals over all the pixels. Mapping pixel dissimilarity (Mappix) results in signal and information enhancement of the output images. In addition, the spatial distribution of the fluorescence brightness of the original image is not skewed. This allows large differences of molecular brightness to be handled which turns out to be critical to the fidelity of the final image. In this work, we provide testing of the Mappix approach with both simulated and real data. The results obtained on HEK cells expressing Dronpa photoswitchable fluorescent protein show that, for densely labeled samples, improvement can be obtained on fluorescence images allowing the observation of structural information. Despite some limitations, comparison to state of art methods reveals that Mappix can be very useful for biological imaging applications.

Sparse deconvolution in one and two dimensions: applications in endocrinology and single-molecule fluorescence imaging.

Deconvolution of noisy signals is an important task in analytical chemistry, examples being spectral deconvolution or deconvolution in microscopy. When the number of spectral peaks or single emitters in imaging is limited, the solution of the deconvolution is required to be sparse, and desirable results are obtained using a penalized estimation techniques. We impose sparseness by using penalized regression with a penalty based on the L0-norm, as discussed in earlier work. Several extensions to this approach are presented. Results are demonstrated on pulse identification in endocrine data where the aim is to model the secretion pattern as a sparse series of spikes. An application in single-molecule fluorescence imaging demonstrates the algorithm when applied to two-dimensional data.

A multifunctional photoswitch: 6π electrocyclization versus ESIPT and metalation.

A terthiazole-based molecular switch associating 6π electrocyclization, excited state intramolecular proton transfer (ESIPT), and strong metal binding capability was prepared. The photochemical and photophysical properties of this molecule and of the corresponding nickel and copper complexes were thoroughly investigated by steady-state and ultrafast absorption spectroscopy and rationalized by DFT/TDDFT calculations. The switch behaves as a biphotochrome with time-dependent photochemical outcome and displays efficient ESIPT-based fluorescence photoswitching. Both photochemical reactions are suppressed by nickel or copper metalation, and the main factors contributing to the quenching of the electrocyclization are discussed.

Vibrational spectra of chemical and isotopic variants of oxyluciferin, the light emitter of firefly bioluminescence.

The chemical complexity of oxyluciferin (OxyLH2), the light-emitting molecule in the bioluminescence of fireflies, originates from the possibility of keto/enol tautomerism and single or double deprotonation. Herein, we present detailed infrared spectroscopic analysis of OxyLH2 and several of its chemical isomers and isotopomers. To facilitate the future characterization of its biogenic forms, we provide accurate assignments of the solid-state and solution FTIR spectra of OxyLH2 based on comparison to six isotopically labeled variants ([2-(13)C]-OxyLH2, [3-(15)N]-OxyLH2, [4-(13)C]-OxyLH2, [5-(13)C]-OxyLH2, [2'-(13)C]-OxyLH2, [3'-(15)N]-OxyLH2), five closely related structural analogues, and theoretically computed spectra. The computed DFT harmonic vibrational force fields (B3LYP and M06 functionals with basis sets of varying flexibility up to 6-311++G**) reproduce well the observed shifts in the IR spectra of both isotopically labeled and structurally related analogues.

Per-pixel unmixing of spectrally overlapping fluorophores using intra-exposure excitation modulation.

Multilabel fluorescence imaging is essential for the visualization of complex systems, though a major challenge is the limited width of the useable spectral window. Here, we present a new method, exNEEMO, that enables per-pixel quantification of spectrally-overlapping fluorophores based on their light-induced dynamics, in a way that is compatible with a very broad range of timescales over which these dynamics may occur. Our approach makes use of intra-exposure modulation of the excitation light to distinguish the different emitters given their reference responses to this modulation. We use the approach to simultaneously image four green photochromic fluorescent proteins at the full spatial resolution of the imaging.

Blind instrument response function identification from fluorescence decays.

Time-resolved fluorescence spectroscopy plays a crucial role when studying dynamic properties of complex photochemical systems. Nevertheless, the analysis of measured time decays and the extraction of exponential lifetimes often requires either the experimental assessment or the modeling of the instrument response function (IRF). However, the intrinsic nature of the IRF in the measurement process, which may vary across measurements due to chemical and instrumental factors, jeopardizes the results obtained by reconvolution approaches. In this paper, we introduce a novel methodology, called blind instrument response function identification (BIRFI), which enables the direct estimation of the IRF from the collected data. It capitalizes on the properties of single exponential signals to transform a deconvolution problem into a well-posed system identification problem. To delve into the specifics, we provide a step-by-step description of the BIRFI method and a protocol for its application to fluorescence decays. The performance of BIRFI is evaluated using simulated and time-correlated single-photon counting data. Our results demonstrate that the BIRFI methodology allows an accurate recovery of the IRF, yielding comparable or even superior results compared with those obtained with experimental IRFs when they are used for reconvolution by parametric model fitting.

Class modelling by Soft Independent Modelling of Class Analogy: why, when, how? A tutorial.

This article contains a comprehensive tutorial on classification by means of Soft Independent Modelling of Class Analogy (SIMCA). Such a tutorial was conceived in an attempt to offer pragmatic guidelines for a sensible and correct utilisation of this tool as well as answers to three basic questions: "why employing SIMCA?", "when employing SIMCA?" and "how employing/not employing SIMCA?". With this purpose in mind, the following points are here addressed: i) the mathematical and statistical fundamentals of the SIMCA approach are presented; ii) distinct variants of the original SIMCA algorithm are thoroughly described and compared in two different case-studies; iii) a flowchart outlining how to fine-tune the parameters of a SIMCA model for achieving an optimal performance is provided; iv) figures of merit and graphical tools for SIMCA model assessment are illustrated and v) computational details and rational suggestions about SIMCA model validation are given. Moreover, a novel Matlab toolbox, which encompasses routines and functions for running and contrasting all the aforementioned SIMCA versions is also made available.

Kernelizing: A way to increase accuracy in trilinear decomposition analysis of multiexponential signals.

The unmixing of multiexponential decay signals into monoexponential components using soft modelling approaches is a challenging task due to the strong correlation and complete window overlap of the profiles. To solve this problem, slicing methodologies, such as PowerSlicing, tensorize the original data matrix into a three-way data array that can be decomposed based on trilinear models providing unique solutions. Satisfactory results have been reported for different types of data, e.g., nuclear magnetic resonance or time-resolved fluorescence spectra. However, when decay signals are described by only a few sampling (time) points, a significant degradation of the results can be observed in terms of accuracy and precision of the recovered profiles. In this work, we propose a methodology called Kernelizing that provides a more efficient way to tensorize data matrices of multiexponential decays. Kernelizing relies on the invariance of exponential decays, i.e., when convolving a monoexponential decaying function with any positive function of finite width (hereafter called "kernel"), the shape of the decay (determined by the characteristic decay constant) remains unchanged and only the preexponential factor varies. The way preexponential factors are affected across the sample and time modes is linear, and it only depends on the kernel used. Thus, using kernels of different shapes, a set of convolved curves can be obtained for every sample, and a three-way data array generated, for which the modes are sample, time and kernelizing effect. This three-way array can be afterwards analyzed by a trilinear decomposition method, such as PARAFAC-ALS, to resolve the underlying monoexponential profiles. To validate this new approach and assess its performance, we applied Kernelizing to simulated datasets, real time-resolved fluorescence spectra collected on mixtures of fluorophores and fluorescence-lifetime imaging microscopy data. When the measured multiexponential decays feature few sampling points (down to fifteen), more accurate trilinear model estimates are obtained than when using slicing methodologies.

A two-step ICT process for solvatochromic betaine pyridinium revealed by ultrafast spectroscopy, multivariate curve resolution, and TDDFT calculations.

This work deals with the photophysics of a pyridinium betaine, 2-pyridin-1-yl-1H-benzimidazole (SBPa), based on a combination of steady-state, femtosecond photoionization (gas phase) and femtosecond transient absorption (solution) spectroscopic measurements, supported by (LR)-PCM-(TD)DFT calculations. Preliminary and new electrochemical results have revealed a strongly negative solvatochromic charge transfer (CT) absorption due to a S(0) → S(2) vertical transition and a weakly-solvatochromic emission due to S(1) → S(0) transition. Advanced TDDFT optimizations of the Franck-Condon states S(2)(FC) and S(1)(FC) led to two additional CT levels with planar geometry, S(2)(CT) and S(1)(CT), respectively, allowing prediction of a two-step photoinduced ICT process, i.e., S(0) → S(2)(FC) and S(2)(CT) → S(1)(CT), separated by a S(2)(FC) → S(2)(CT) back charge transfer relaxation. While the pyridinium ring is the acceptor group in both steps, two different donor groups, the benzene ring and the imidazole bridge, are involved in the excitation and internal conversion processes, respectively. Femtosecond transient absorption experiments supported by MCR-ALS decomposition confirmed indeed the contribution of two distinct CT states in the photophysics of SBPa: following excitation to the S(2)(CT) state, ultrafast production of the emissive S(1) state (the only channel observable in the gas phase) was observed to occur in competition with a further ICT process toward the S(1)(CT) state, with a time constant ranging from 300 fs to 20 ps depending on the solvent. While in aprotic media this ICT process was found to be purely solvent controlled (double polarity and viscosity dependency), in protic solvents, the influence of the hydrogen bond network has to be taken into account. Comparison with data obtained for a pre-twisted SBPa analogue led us to exclude the presence of any large-amplitude geometrical change during ICT. Analyzing the solvent dependency using the power law approach, we concluded that the S(1)(CT) state decays essentially through IC in the 3-40 ps time range whereas the emissive S(1) state decays within 130-260 ps via IC, ISC and fluorescence.

Corrigendum: Hyperspectral Video Analysis by Motion and Intensity Preprocessing and Subspace Autoencoding.

[This corrects the article DOI: 10.3389/fchem.2022.818974.].

Optimising punctual water sampling with an on-the-fly algorithm based on multiparameter high-frequency measurements.

The way in which aquatic systems is sampled has a strong influence on our understanding of them, especially when they are highly dynamic. High frequency sampling has the advantage over spot sampling for representativeness but leads to a high amount of analysis. This study proposes a new methodology to choose when sampling accurately with an automated sampler coupled with a high frequency (HF) multiparameter probe. After each HF measurement, an optimised sampling algorithm (OSA) determines on-the-fly the relevance of taking a new sample in relation to previous waters already collected. Once the OSA was optimised, considering the number of HF parameters and their variabilities, it was demonstrated through a study case that the number of samples could be significantly reduced, while still covering periods of low and high variabilities. The comparison between the total HF dataset and the sampled subdataset shows that physicochemical parameter variability is preserved (Pearson correlations > 0.96) as well as the multiparameter variability (PCA axes remained similar with Tucker congruence > 0.99). This algorithm simplifies HF studies by making it easier to take samples during brief phenomena such as storms or accidental spills that are often poorly monitored. In addition, it optimises the number of samples to be taken to correctly describe a system and thus reduce the human and financial costs of these environmental studies.