Experimental design approach for development of spectrofluorimetric method for determination of favipiravir; a potential therapeutic agent against COVID-19 virus: Application to spiked human plasma.

The present work describes development of rapid, robust, sensitive and green spectrofluorimetric method for determination of favipiravir (FAV). Different factors affecting fluorescence were carefully studied and Box Behnken Design was applied to optimize experimental parameters. The proposed method is based on measuring native fluorescence of FAV in 0.2 M borate buffer (pH 8.0) at 432 nm after excitation at 361 nm. There was a linear relationship between FAV concentration and relative fluorescence intensity over the range 40-280 ng/mL with limit of detection of 9.44 ng/mL and quantitation limit of 28.60 ng/mL. The method was successfully implemented for determination of FAV in its pharmaceutical formulation with mean % recovery of 99.26 ± 0.87. Moreover, the high sensitivity of the method allowed determination of FAV in spiked human plasma over a range of 48-192 ng/mL. The proposed spectrofluorimetric method was proved to be eco-friendly according to analytical eco-scale.

A simple and useful method for evaluation of oxidative stress in vivo by spectrofluorometric estimation of urinary pteridines.

Pteridine derivatives are intermediate metabolites of folic acid and its cofactors. Oxidized-form pteridines, but not reduced-form pteridines, are fluorescent substances. The purpose of this study was to clarify whether oxidized-form pteridine level in urine, estimated by spectrofluorometry, reflects oxidative stress in vivo. The subjects were healthy middle-aged men (n = 258). Urinary pteridine level was estimated by spectrofluorometry with an excitation wavelength of 360 nm and an emission wavelength of 450 nm. Relationships of urinary pteridines with oxidative stress markers (urinary DNA/RNA oxidation products and 15-isoprostane F2t) and with smoking were analyzed. Concentrations of pteridines, DNA/RNA oxidation products and 15-isoprostane F2t were used after logarithmic transformation in linear analyses. Pteridine levels were significantly correlated with levels of DNA/RNA oxidation products (Pearson's correlation coefficient: 0.626, p < 0.01) and 15-isoprostane F2t (Pearson's correlation coefficient: 0.695, p < 0.01). These correlations were not confounded by age, body mass index, history of smoking and estimated glomerular filtration rate in multivariate analysis. The mean urinary pteridine level was significantly higher in heavy smokers (16 cigarettes or more per day) than in nonsmokers and light smokers (less than 16 cigarettes per day) and was higher in light smokers than in nonsmokers. Thus, urinary fluorometric pteridine levels were shown to be associated with known biomarkers of oxidative stress as well as smoking, which causes oxidative stress in vivo. We propose spectrofluorometrical estimation of urinary pteridines as a simple and useful method for evaluation of oxidative stress in vivo.

Potentiality of using front face fluorescence spectroscopy for quantitative analysis of cow milk adulteration in buffalo milk.

In current study, synchronous front-face fluorescence spectroscopy together with partial least squares regression (PLSR) is used to predict the adulteration of cow and buffalo milk quantitatively. Fresh (unprocessed milk) samples of cow and buffalo were collected from local dairy farms. Fluorescence emission from milk samples mixed in different concentrations, show intensity variations at wavelengths 370-380 nm, 410 nm, 442 nm and 520-560 nm. Among them, the emissions at band position of 442 nm and 525 nm are highly selective between the two species and could help in finding adulteration of cow milk in buffalo milk and vice versa. The emissions at these wavelength positions correspond to fat-soluble vitamin-A as well as ß-carotene. PLS regression is used as a statistical prediction model, which is developed by training with the emission spectra of milk samples having known level of adulterations. The developed model predicts the unknown level of adulterations by means of their spectral data. The goodness of the model is determined by the correlation coefficient R-square (r2) value, which in our case is 0.99. Furthermore, the model root mean square error in cross validation (RMSECV) and in prediction (RMSECP) remains 1.16 and 6.24 respectively. This approach can effectively be applied to determine milk adulterations among other species as well as in detecting external agents (fraudulent) added into milk and other dairy products by further studies.

Determination of flibanserin in the presence of confirmed degradation products by a third derivative emission spectrofluorometric method: Application to pharmaceutical formulation.

Flibanserin is a new drug used for the treatment of hypoactive sexual desire disorder. This work is considered the first study concerning the fluorimetric behaviour of flibanserin and its new florescent degradation products. A fast, cost-effective, stability-indicating spectrofluorometric method was developed and validated for the determination of flibanserin in the presence of oxidative degradation products. Stability studies are performed to predict the behaviour of substances under various harsh conditions. Thus, flibanserin was subjected to degradation using hydrogen peroxide. The stability-indicating method was developed and validated per ICH guidelines; it was linear in the range of 0.1-3 µg/mL. The method was accurate and precise as it showed good recoveries between 98.50 and 100.90% and relative standard deviation less than 2%, respectively, and no significant differences were found after statistical comparison with the in-house HPLC method. In addition, the structures of the oxidative degradation products were confirmed using infrared spectroscopy and mass spectrometry, and the proposed degradation pathway was predicted.

Rapid identification and quantification of cheaper vegetable oil adulteration in camellia oil by using excitation-emission matrix fluorescence spectroscopy combined with chemometrics.

Camellia oil is a high quality oil mainly produced in southern China. It is common that unscrupulous merchants attempt to make huge profits by adulterating camellia oil with other cheaper or lower-quality vegetable oils. Therefore, this paper proposed excitation-emission matrix fluorescence spectroscopy combined with chemometric methods for the rapid identification and quantification of camellia oil adulteration with other cheaper vegetable oils. A five-component parallel factor analysis (PARAFAC) model roughly completed spectral characterization of oil samples, and obtained chemically meaningful information. Four advanced chemometrics methods were used for the classification of camellia oil and other vegetable oils (model 1) and the classification of camellia oil and adulterated camellia oil (models 2 and 3), respectively. Two-directional two-dimensional linear discriminant analysis ((2D)2LDA) was used for chemical data for the first time and showed huge potential. Furthermore, the developed N-PLS regression model used for the prediction of adulteration level in camellia oil showed satisfactory accuracy.

ZnCdSe-CdTe quantum dots: A "turn-off" fluorescent probe for the detection of multiple adulterants in an herbal honey.

To enhance the power of untargeted detection, a "turn-off" fluorescent probe with double quantum dots (QDs) was developed and coupled with chemometrics for rapid detection of multiple adulterants in an herbal (Rhus chinensis Mill., RCM) honey. The double water-soluble ZnCdSe-CdTe QDs have two separate and strong fluorescent peaks, which can be quenched by honey and extraneous adulterants with varying degrees. Class models of pure RCM honey samples collected from 6 different producing areas (n = 122) were developed using one-class partial least squares (OCPLS). Four extraneous adulterants, including glucose syrup, sucrose syrup, fructose syrup, and glucose-fructose syrup were added to pure honey samples at the levels of 0.5% to 10% (w/w). As a result, the OCPLS model using the second-order derivative (D2) spectra could detect 1.0% (w/w) of different syrups in RCM honey, with a sensitivity of 0.949. The double water-soluble QDs, which can be adjusted for analysis of other water-soluble food samples, has largely extended the capability of traditional fluorescence and will provide a potentially more sensitive and specific analysis method for food frauds.

Potentiality of front-face fluorescence and mid-infrared spectroscopies coupled with partial least square regression to predict lipid oxidation in pound cakes during storage.

The potentialities of front-face fluorescence (FFF) and mid-infrared (MIR) spectroscopies coupled with partial least square regression (PLSR) were compared to predict the lipid oxidation of pound cakes. The level of lipid oxidation in pound cakes determined using classical methods showed some changes. Similarly, the fluorescence emission (305-490 nm) and excitation (252-390 nm) spectra and MIR spectra scanned in the 4000-700 cm-1 region showed some changes in pound cakes as a function of both storage time and the type of oil used in the formulation. The application of PLSR to the MIR spectra, provided excellent predictive results for free fatty acid (R2 = 0.97) and peroxide values (R2 = 0.87). Similar results were obtained from both tryptophan and MIR spectra for the prediction of TOTOX (R2 > 0.86) demonstrating the efficiency of the MIR and FFF spectroscopies to qualify and quantify the level of lipid oxidation in pound cakes.

Tea types classification with data fusion of UV-Vis, synchronous fluorescence and NIR spectroscopies and chemometric analysis.

The potential of selected spectroscopic methods - UV-Vis, synchronous fluorescence and NIR as well a data fusion of the measurements by these methods - for the classification of tea samples with respect to the production process was examined. Four classification methods - Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Regularized Discriminant Analysis (RDA) and Support Vector Machine (SVM) - were used to analyze spectroscopic data. PCA analysis was applied prior to classification methods to reduce multidimensionality of the data. Classification error rates were used to evaluate the performance of these methods in the classification of tea samples. The results indicate that black, green, white, yellow, dark, and oolong teas, which are produced by different methods, are characterized by different UV-Vis, fluorescence, and NIR spectra. The lowest error rates in the calibration and validation data sets for individual spectroscopies and data fusion models were obtained with the use of the QDA and SVM methods, and did not exceed 3.3% and 0.0%, respectively. The lowest classification error rates in the validation data sets for individual spectroscopies were obtained with the use of RDA (12,8%), SVM (6,7%), and QDA (2,7%), for the UV-Vis, SF, and NIR spectroscopies, respectively. NIR spectroscopy combined with QDA outperformed other individual spectroscopic methods. Very low classification errors in the validation data sets - below 3% - were obtained for all the data fusion data sets (SF + UV-Vis, SF + NIR, NIR + UV-Vis combined with the SVM method). The results show that UV-Vis, fluorescence and near infrared spectroscopies may complement each other, giving lower errors for the classification of tea types.

Chromophoric dissolved organic matter influence correction of algal concentration measurements using three-dimensional fluorescence spectra.

In view of the adverse effects of CDOM (chromophoric or colored dissolved organic matter) on in vivo algal pigment concentration measurements in natural water bodies, a CDOM influence correction method for algal concentration measurements based on three-dimensional fluorescence spectra is investigated. The three-dimensional fluorescence spectra of five common species of algae belonging to five categories, HA (humic acid), and natural water sampled from the Dongpu reservoir, Hefei were analyzed, and the spectral similarity of endogenous/exogenous CDOM in the algal fluorescence spectra region was compared. HA was selected to represent the CDOM spectrum group. The CDOM modified algal pigment concentration measurement method was developed using three-dimensional fluorescence spectra coupled with non-negative weighted least squares linear regression analysis. The results show that under the presence of CDOM interference factors, the recognition accuracy rate of Pyrrophyta, Bacillariophyta, Cyanophyta, and Chlorophyta increased 100%, 100%, 40%, and 40%, respectively. The average recovery rate of Cryptomonas, Pyrrophyta, Bacillariophyta, and Chlorophyta increased 162.7%, 50.3%, 106.4%, and 19.1%, respectively. In addition, the classification accuracy of Pyrrophyta, Bacillariophyta, Cyanophyta, Chlorophyta increased 83.9%, 100%, 38.2%, and 48%, respectively. This was concluded by comparing these results with the results of the algal pigment concentration measurement method without the CDOM modification. This study provides an experimental basis for the development of accurate phytoplankton fluorescence classification monitoring technology.

Studying backbone torsional dynamics of intrinsically disordered proteins using fluorescence depolarization kinetics.

Intrinsically disordered proteins (IDPs) do not autonomously adopt a stable unique 3D structure and exist as an ensemble of rapidly interconverting structures. They are characterized by significant conformational plasticity and are associated with several biological functions and dysfunctions. The rapid conformational fluctuation is governed by the backbone segmental dynamics arising due to the dihedral angle fluctuation on the Ramachandran φ- ψ conformational space. We discovered that the intrinsic backbone torsional mobility can be monitored by a sensitive fluorescence readout, namely fluorescence depolarization kinetics, of tryptophan in an archetypal IDP such as α-synuclein. This methodology allows us to map the site-specific torsional mobility in the dihedral space within picosecond-nanosecond time range at a low protein concentration under the native condition. The characteristic timescale of ~1.4 ns, independent of residue position, represents collective torsional dynamics of dihedral angles (φ and ψ) of several residues from tryptophan and is independent of overall global tumbling of the protein. We believe that fluorescence depolarization kinetics methodology will find broad application to study both short-range and long-range correlated motions, internal friction, binding-induced folding, disorder-to-order transition, misfolding and aggregation of IDPs.

In situ detection of live-to-dead bacteria ratio after inactivation by means of synchronous fluorescence and PCA.

The determination of live and dead bacteria is of considerable significance for preventing health care-associated infection in hospitals, field clinics, and other areas. In this study, the viable (live) and nonviable (dead) bacteria in a sample were determined by means of their fluorescence spectra and principal component analysis (PCA). Data obtained in this study show that it is possible to identify bacteria strains and determine the live/dead ratio after UV light inactivation and antibiotic treatment, in situ, within minutes. In addition, synchronous fluorescence scans enable the identification of bacterial components such as tryptophan, tyrosine, and DNA. Compared with the time-consuming plating and culturing methods, this study renders a means for rapid detection and determination of live and dead bacteria.

Enhanced spontaneous DNA twisting/bending fluctuations unveiled by fluorescence lifetime distributions promote mismatch recognition by the Rad4 nucleotide excision repair complex.

Rad4/XPC recognizes diverse DNA lesions including ultraviolet-photolesions and carcinogen-DNA adducts, initiating nucleotide excision repair. Studies have suggested that Rad4/XPC senses lesion-induced helix-destabilization to flip out nucleotides from damaged DNA sites. However, characterizing how DNA deformability and/or distortions impact recognition has been challenging. Here, using fluorescence lifetime measurements empowered by a maximum entropy algorithm, we mapped the conformational heterogeneities of artificially destabilized mismatched DNA substrates of varying Rad4-binding specificities. The conformational distributions, as probed by FRET between a cytosine-analog pair exquisitely sensitive to DNA twisting/bending, reveal a direct connection between intrinsic DNA deformability and Rad4 recognition. High-specificity CCC/CCC mismatch, free in solution, sampled a strikingly broad range of conformations from B-DNA-like to highly distorted conformations that resembled those observed with Rad4 bound; the extent of these distortions increased with bound Rad4 and with temperature. Conversely, the non-specific TAT/TAT mismatch had a homogeneous, B-DNA-like conformation. Molecular dynamics simulations also revealed a wide distribution of conformations for CCC/CCC, complementing experimental findings. We propose that intrinsic deformability promotes Rad4 damage recognition, perhaps by stalling a diffusing protein and/or facilitating 'conformational capture' of pre-distorted damaged sites. Surprisingly, even mismatched DNA specifically bound to Rad4 remains highly dynamic, a feature that may reflect the versatility of Rad4/XPC to recognize many structurally dissimilar lesions.

[Analysis of Chlorophyll Fluorescence Transient by Spectral Multi-exponential Approximation].

The method for analysis of chlorophyll fluorescence transient using approximation of measured signal by multi-exponential series is described. Visualization of partial sums of this series allows us to find amplitudes and characteristic times of individual phases of fluorescence induction curve. This method gives more rigid criteria of phase identification instead of semi-empirical approach currently used. Applied to Chlamidomonas reinhardtii sulfur deprivation case, it shows efficiency in finding visually undistinguishable phases of fluorescence transient for early detection of stress.

A parameter estimation method for fluorescence lifetime data.

BACKGROUND: When modeling single-molecule fluorescence lifetime experimental data, the analysis often involves fitting a biexponential distribution to binned data. When dealing with small sample sizes, there is the potential for convergence failure in numerical optimization, for convergence to local optima resulting in physically unreasonable parameter estimates, and also for overfitting the data. RESULTS: To avoid the problems that arise in small sample sizes, we have developed a gamma conversion method to estimate the lifetime components. The key idea is to use a gamma distribution for initial numerical optimization and then convert the gamma parameters to biexponential ones via moment matching. A simulation study is undertaken with 30 unique configurations of parameter values. We also performed the same analysis on data obtained from a fluorescence lifetime experiment using the fluorophore Cy3. In both the simulation study and the real data analysis, fitting the biexponential directly led to a large number of data sets whose estimates were physically unreasonable, while using the gamma conversion yielded estimates consistently close to the true values. CONCLUSIONS: Our analysis shows that using numerical optimization methods to fit the biexponential distribution directly can lead to failure to converge, convergence to physically unreasonable parameter estimates, and overfitting the data. The proposed gamma conversion method avoids these numerical difficulties, yielding better results.

Method of determining the optimal dilution ratio for fluorescence fingerprint of food constituents.

Quantitative determination by fluorescence spectroscopy is possible because of the linear relationship between the intensity of emitted fluorescence and the fluorophore concentration. However, concentration quenching may cause the relationship to become nonlinear, and thus, the optimal dilution ratio has to be determined. In the case of fluorescence fingerprint (FF) measurement, fluorescence is measured under multiple wavelength conditions and a method of determining the optimal dilution ratio for multivariate data such as FFs has not been reported. In this study, the FFs of mixed solutions of tryptophan and epicatechin of different concentrations and composition ratios were measured. Principal component analysis was applied, and the resulting loading plots were found to contain useful information about each constituent. The optimal concentration ranges could be determined by identifying the linear region of the PC score plotted against total concentration.

A PARAFAC-based long-term assessment of DOM in a multi-coagulant drinking water treatment scheme.

A parallel factor (PARAFAC) analysis approach was used to study the character and composition of dissolved organic matter (DOM) in a multicoagulant (two aluminum-based coagulants) full scale drinking water treatment plant. A three year, long-term assessment was conducted based on deconstruction of the excitation-emission matrices (EEM) of over 1000 water samples collected before and after parallel coagulation treatment basins. Two humic moieties and a protein-like group were identified in the raw and treated waters. Apportionment of fluorophores was established using a novel approach based on the overall fluorescence intensity (OFI) of PARAFAC components. Uncorrected matrix correlation (UMC) revealed minimal changes of the fluorescence moieties after treatment (UMC > 0.98), and a comparable effect of both coagulants on the structure (UMC > 0.99) and distribution of these groups. Coagulation increased the proportion of the protein-like fluorophore and preferentially removed a humic-like group irrespective of the coagulant. Preference for this moiety was supported by a coagulant-affinity factor derived from the association between PARAFAC components after treatment. The suitability of a PARAFAC-based approach for coagulant evaluation/selection was demonstrated when compared to a dissolved organic carbon (DOC)-based criterion. This paper contributes to the understanding of the behavior of PARAFAC components in water treatment processes and presents several approaches for the future monitoring and control of coagulation at full scale treatment facilities.

Simulating the peptide folding kinetic related spectra based on the Markov State Model.

Optical spectroscopic tools are used to monitor protein folding/unfolding dynamics after a fast triggering such as the laser induced temperature jump. These techniques provide new opportunities for comparison between theory and simulations and atom-level understanding protein folding mechanism. However, the direct comparison still face two main challenges: a gap between folding relevant timescales (microseconds or above) and length of molecular dynamics simulations (typically tens to hundreds of nanoseconds), and difficulty in directly calculating spectroscopic observables from simulation configurations. Markov State Model (MSM) approach is one of the most powerful means which can increase simulations timescale up to microsecond or even millisecond. We address progress on modeling infrared and fluorescence spectroscopic signals of temperature jump induced unfolding dynamics for a few small proteins. The harmoniousness between experiment and theoretical can both improve our understanding of protein folding mechanisms and provide direct validation of those theoretical models.

Fluorescence spectroscopy of rhodopsins: insights and approaches.

Fluorescence spectroscopy has become an established tool at the interface of biology, chemistry and physics because of its exquisite sensitivity and recent technical advancements. However, rhodopsin proteins present the fluorescence spectroscopist with a unique set of challenges and opportunities due to the presence of the light-sensitive retinal chromophore. This review briefly summarizes some approaches that have successfully met these challenges and the novel insights they have yielded about rhodopsin structure and function. We start with a brief overview of fluorescence fundamentals and experimental methodologies, followed by more specific discussions of technical challenges rhodopsin proteins present to fluorescence studies. Finally, we end by discussing some of the unique insights that have been gained specifically about visual rhodopsin and its interactions with affiliate proteins through the use of fluorescence spectroscopy. This article is part of a Special Issue entitled: Retinal Proteins - You can teach an old dog new tricks.

Analysis of dilute aqueous multifluorophoric mixtures using excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence (TSF) spectroscopy: a comparative evaluation.

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence (TSF) spectroscopy are two conceptually different fluorescence techniques that have been used to map the fluorescence responses of the fluorophores present in a multifluorophoric mixture. EEMF was introduced four decades back and most of the fluorimeters have the suitable computer program which allows the acquisition EEMF spectra. Recently introduced TSF spectroscopy has been shown to possess good application potential in analytical fluorimetry and has started attracting the attention of analytical chemists. TSF data structure, however, is intrinsically different from EEMF data structure and a better understanding of TSF data structure is crucial to utilising its application potential. In the present work, a comprehensive comparative study between EEMF and TSF spectroscopic data set was performed by taking aqueous mixtures containing low concentrations of benzo[a]pyrene, chrysene, and pyrene as test case. The EEMF and TSF data structures were clearly explained by taking pyrene as an example. The effects of Rayleigh and Raman scattering on the quality of EEMF and TSF data sets were studied. EEMF and TSF data sets of dilute aqueous mixtures of benzo[a]pyrene, chrysene, and pyrene were subjected to three chemometric techniques PARAFAC, N-PLS, and MCR-ALS analysis. TSF data set in particular was found to be highly attuned to MCR-ALS analysis. Obtained results of chemometric analyses on EEMF and TSF data sets show that TSF data of dilute aqueous mixtures provides more accurate spectral and concentration information than EEMF data sets. Therefore, TSF spectroscopy could be considered as an alternate to the EEMF for the analyses of dilute multifluorophoric mixtures.

Fluorescence correlation spectroscopy and photon-counting histogram analysis of receptor-receptor interactions.

Fluorescence correlation spectroscopy (FCS) performed using a laser scanning confocal microscope is a technique with single-molecule sensitivity that is becoming more accessible to cell biologists. In this chapter, we describe the use of FCS for the analysis of diffusion coefficients and receptor-receptor interactions in live cells in culture. In particular, we describe a protocol to collect fluorescence fluctuation data from fluorescence-tagged receptors as they diffuse into an out of a small laser-illuminated observation volume using a commercially available system such as the Zeiss ConfoCor 3 or LSM-780 microscope. Autocorrelation analysis of the fluctuations in fluorescence intensity provides information about the diffusion time and number of fluorescent molecules in the observation volume. A photon-counting histogram can be used to examine the relationship between fluorescence intensity and the number of fluorescent molecules to estimate the average molecular brightness of the sample. Since molecular brightness is directly proportional to the number of fluorescent molecules, it can be used to monitor receptor-receptor interactions and to decode the number of receptor monomers present in an oligomeric complex.