Front-face Fluorescence Spectroscopy Research Articles

Modulable 3D-printed plantibody-laden platform enabling microscale affinity extraction and ratiometric front-face fluorescence detection of microcystin-LR in marine waters

A 3D-printed stereolithographic platform for selective biorecognition is designed to enable convective microscale affinity extraction of microcystin-LR (MC-LR) followed by direct solid-phase optosensing exploiting ratiometric front-face fluorescence spectroscopy. For this purpose, a recombinant monoclonal plantibody (recAb) is covalently attached to a 3D-printed structure for sorptive immunoextraction, whereupon the free and unbound primary amino moieties of the recAb are derivatized with a fluorescent probe. The fluorophore-recAb-MC-LR laden device is then accommodated in the cuvette holder of a conventional fluorometer without any instrumental modification for the recording of the solid-phase fluorescence emission. Using Rodbard’s four-parameter sigmoidal function, the 3D-printed bioselective platform features a limit of detection (LOD) of 28 ng L−1 using a sample volume of 500 mL, device-to-device reproducibility down to 12%, and relative recoveries ranging from 91 to 100% in marine waters. Printed prototypes are affordable, just 0.4 € per print and ≤ 10 € per device containing recAb. One of the main assets of the miniaturized immunoextraction device is that it performs comparably well in terms of analytical figures of merit with costly mass spectrometric-based analytical methodologies, such as HPLC–MS/MS. The device is readily applicable to high-matrix samples, such as seawater, as opposed to previous biosensing platforms, just applied to freshwater systems.Graphical abstract

Combined Application of Fluorescence Spectroscopy and Principal Component Analysis in Characterisation of Selected Herbhoneys.

This study reports the use of front-face fluorescence spectroscopy with principal component analysis (PCA) as a tool for the characterisation of selected Polish herbhoneys (raspberry, lemon balm, rose, mint, black current, instant coffee, pine, hawthorn, and nettle). Fluorimetric spectra registered in the ranges ascribed to fluorescence of amino acids, polyphenols, vitamins, and products of Maillard's reaction enabled the comparison of herbhoney compositions. Obtained synchronous spectra combined with PCA were used to investigate potential differences between analysed samples and interactions between compounds present in them. The most substantial influence on the total variance had the intensities of polyphenols fluorescence. These intensities were the main factor differentiated by the analysed products.

Front-face fluorescence spectroscopy combined with chemometrics for the discrimination of wheat flour and cassava flour

Fluorescence and chemometric methods were used in this study to discriminate wheat flour samples mixed with cassava flour at different percentages (from 0 to 60). The fluorescence emission spectra of the different flours were obtained at excitation wavelengths of 349 nm and 373 nm. Principal component analysis (PCA) and Cluster Analysis (CA) showed that pure wheat flour can be distinguished from mixed wheat flour. The overall predictive accuracy of the principal component analysis and discriminant analysis (PCA-DA) and partial least squares discriminant analysis (PLS-DA) of the two-class discriminant models (pure and mixed wheat) reached 100%, showing that the model was able to correctly differentiate a pure wheat sample from a mixed wheat sample. The predictions of the three-class models (pure wheat, 10%,20%−60%; pure wheat, 10%+20%, 30%−60% and pure wheat, 10%−30%, 40%−60%) showed an overall accuracy of over 90% for the PCA-DA and PLS-DA models, the latter being the best performing. Thus, the specificity, sensitivity and precision values (>0.8) for the 10%, 10% + 20% and 10%− 30% classes in each PLS-DA model showed the ability of these models to predict the classes of blended wheat flour samples according to their level of mixing by cassava.

Chemometrics-driven monitoring of cheese ripening: a multimodal spectroscopic and scanning electron microscopy investigation.

The integration of spectroscopic techniques with chemometrics offers a means to monitor quality changes in dairy products throughout processing and storage. This study employed Attenuated Total Reflectance-Mid-Infrared Spectroscopy (ATR-MIR) coupled with Independent Components Analysis (ICA), and 3D Front-Face Fluorescence Spectroscopy (FFFS) paired with Common Components and Specific Weight Analysis (CCSWA). The research focused on Cheddar cheeses aged for 1, 2, 3, and 5 years, alongside Comté cheeses aged for 6, 9, and 12 months. The adopted approach offered valuable insights into the intricate cheese aging process within the food matrix. The ICA proportions and CCSWA scores highlighted the significant impact of biochemical transformations during maturation on the aging process. The extracted independent components (ICs) revealed variations in the vibration modes of amides, lipids, amino acids, and organic acids, facilitating the distinction between different cheese age categories. Additionally, CCSWA outcomes identified age-related differences through shifts in tryptophan fluorescence characteristics as the cheeses aged. These results were consistent with the observed alterations in the microstructure of cheese samples over time, corroborated by Scanning Electron Microscopy (SEM) imagery. The introduced multimodal methodology serves as a significant asset for determining the ripening stage of various types of cheese, offering a detailed perspective of cheese maturation beneficial to the dairy industry and researchers.

Nonchromatographic analysis of polyphenols in red wine samples: Evaluation of front-face fluorescence spectroscopy and third-order multivariate calibration to quantify catechin and epicatechin

In this work, an analytical approach based on third-order multivariate calibration and front-face fluorescence spectroscopy to determine the levels of (+)-catechin and (-)-epicatechin in wine samples was evaluated. An extra reaction mode (pH gradient) was incorporated into excitation-emission fluorescence second-order data, leading to higher predictivity and selectivity for catechin detection. Application of a Multivariate curve resolution-alternating least squares (MCR-ALS) algorithm resolved the systems, even in the presence of uncalibrated interferences, and yielded suitable figures of merit. Through the method, the level of (+)-catechin was directly determined, and the concentration of (-)-epicatechin was determined by the difference in total catechins (Epi + Cat) between synthetic samples. Finally, the levels of catechin were satisfactorily determined in real wine samples at mg L-1 levels with minimal sample treatment and in accordance with a reference method based on chromatographic separation.

Moroccan extra virgin argan oil authentication by using ultraviolet–visible and front face fluorescence spectroscopies combined with different descriptive and predictive chemometric tools

Moroccan extra virgin argan oil authentication by using ultraviolet–visible and front face fluorescence spectroscopies combined with different descriptive and predictive chemometric tools

Green Synthesis and Characterization of Novel Silver Nanoparticles Using Achillea maritima subsp. maritima Aqueous Extract: Antioxidant and Antidiabetic Potential and Effect on Virulence Mechanisms of Bacterial and Fungal Pathogens

Novel silver nanoparticles were synthesized based on a simple and non-toxic method by applying the green synthesis technique, using, for the first time, the aqueous extract of an extremophile plant belonging to the Achillea maritima subsp. maritima species. AgNP characterization was performed via UV-Visible, front-face fluorescence spectroscopy, and FTIR and XRD analyses. AgNP formation was immediately confirmed by a color change from yellow to brown and by a surface plasmon resonance peak using UV-Vis spectroscopy at 420 nm. The biosynthesized AgNPs were spherical in shape with a size ranging from approximatively 14.13 to 21.26 nm. The presented silver nanoparticles exhibited strong antioxidant activity following a DPPH assay compared to ascorbic acid, with IC50 values of about 0.089 µg/mL and 22.54 µg/mL, respectively. The AgNPs showed higher antidiabetic capacities than acarbose, by inhibiting both alpha amylase and alpha glucosidase. The silver nanoparticles could affect various bacterial mechanisms of virulence, such as EPS production, biofilm formation and DNA damage. The silver nanoparticles showed no lysozyme activity on the cell walls of Gram-positive bacteria. The AgNPs also had a strong inhibitory effect on the Candida albicans virulence factor (extracellular enzymes, biofilm formation). The microscopic observation showed abnormal morphogenesis and agglomeration of Candida albicans exposed to AgNPs. The AgNPs showed no cytotoxic effect on human cells in an MTT assay. The use of novel silver nanoparticles is encouraged in the formulation of natural antimicrobial and antidiabetic agents.

The use of non-invasive fluorescence spectroscopy to quantify phenolic content under red wine real-time fermentation conditions

Phenolic compounds play important roles in wine quality attributes such as colour, mouthfeel and ageing potential. The ability to monitor their extraction and implement appropriate vinification techniques relies on accurate phenolic analysis methods. Front-face fluorescence spectroscopy presents itself as a user-friendly, rapid and cost-effective alternative to other spectrophotometric methods. The main aim of the study was therefore to investigate the potential of fluorescence spectroscopy to directly measure phenolic content of red wine samples throughout red wine fermentations. Cabernet Sauvignon fermentations were monitored using fluorescence spectroscopy and UV–Visible spectrophotometry. Fermentation conditions were explored for their influence on the prediction accuracy of fluorescence-based regression models. The coefficient of correlation (R2val) and root mean square errors of validation (RMSEV) for models built using non-invasive spectral data obtained from unaltered samples were 0.96, 0.94 and 0.89 and 1.38 index units, 42.84 mg/L and 20.53 mg/L for total phenols (index units (IU)), total condensed tannins (mg/L), total anthocyanins (mg/L), respectively. Overall, the ability to obtain high quality spectra from unaltered samples simulating direct measurements from the fermentation vessel was demonstrated and holds potential for on-line automated systems or portable device applications.

Comparative study of the potentiality of front-face fluorescence, near- and mid-infrared spectroscopies to authenticate extra virgin argan oil using different chemometric tools

Comparative study of the potentiality of front-face fluorescence, near- and mid-infrared spectroscopies to authenticate extra virgin argan oil using different chemometric tools

Development of 2D and 3D front face fluorescence spectroscopy for monitoring ultrasound treatment in the removal of pesticides residues from fresh lettuces at the laboratory and pilot scales

Pesticide residues in vegetables are potentially toxic components to humans and can cause serious health problems. To remove pesticide residues from fresh agricultural products and improve consumer food safety, various pesticide removal methods have been investigated over the past decades. In this study, the effectiveness of laboratory and pilot scale ultrasonic cleaning on the removal of boscalid and pyraclostrobin residues from lettuce was examined. 2D fluorescence spectroscopy, 3D fluorescence spectroscopy represented by excitation-emission matrix (EEM), and parallel factor analysis (PARAFAC) were used to characterize and discriminate the fluorescence signatures of these pesticides in the cleaning water to determine the effectiveness of the ultrasonic cleaning method as a function of the level of pesticide removal. The 2D fluorescence results showed that the rate of removal of boscalid by ultrasonics at the laboratory scale increased with the cleaning time. The ultrasonic treatment showed a higher cleaning efficiency compared to only soaking in distilled water for 10 min. The same trends were observed at the pilot scale. The EEM also showed differences in the concentration of pesticides removed by ultrasonication between the different parts of the lettuce, the concentration was higher in the upper part than the lower part. This study showed that ultrasonication is an effective technique for the removal of pesticide residues on lettuce, and it also showed the significant potential of fluorescence spectroscopy coupled with PARAFAC for the discrimination and characterization of pesticides.

Fluorescent paper-based sensor integrated with headspace thin-film microextraction for the detection of acyclic N-nitrosamines following in situ photocatalytic decomposition

BackgroundIn this work, a novel analytical approach based on the photocatalytic decomposition of N-nitrosamines combined with headspace thin-film microextraction of the generated nitrogen oxides such as NO has been developed for the determination of the acyclic N-nitrosamine fraction in drinking water samples. A hydrophilic cellulose substrate modified with fluorescent silver nanoclusters (Ag NCs) was used both as extractant and sensing platform. A quenching effect of Ag NCs fluorescence occurs as the concentration of N-nitrosamines increases. Front-face fluorescence spectroscopy with a solid sample holder was employed for directly measuring the fluorescence quenching onto the cellulose substrate. ResultsIn order to achieve an optimal analytical response, different parameters involved in the photocatalytic reaction as well as those concerning the microextraction step were fully investigated. It is demonstrated that the photodegradation rate of cyclic N-nitrosamines at acidic pH is much lower than that of acyclic ones, which can be the basis for the determination of the later fraction in waters. Under optimal conditions, a detection limit for the acyclic N-nitrosamine fraction around 0.08 μg L−1 using N-nitrosodimethylamine (NDMA) as model compound for calibration was obtained. Several drinking waters were spiked with acyclic N-nitrosamines showing recoveries in the range of 98–102% with a relative standard deviation of 3–4% (N = 3). Significance and noveltyN-nitrosamines generated as by-products during disinfection processes applied to water cause multiple adverse effects on human health being classified as potential human carcinogens.This study highlights the suitability of a fluorescent paper-based sensor for the rapid analysis of the acyclic N-nitrosamine fraction (i.e. the most abundant fraction) as a total index in drinking water, being useful as screening tool before exhaustive chromatographic analysis, which saves costs, time and reduces waste generation.

Use of front face fluorescence spectroscopy coupled with multivariate data analysis for monitoring biscuits' quality during aging.

In this study, the potentiality of front face fluorescence spectroscopy (FFFS) for the evaluation of the quality of biscuits manufactured with butylated hydroxytoluene and pomegranate peel extract during aging was investigated. By using the principal component analysis, vitamin A and tryptophan spectra allowed a clear discrimination between biscuit samples according to the nature of antioxidants, while fluorescent Maillard reaction products spectra showed clear differentiation between samples according to the storage time. Clear differentiation between biscuits according to the used antioxidants and storage time was achieved by using common components and specific weights analysis. Using partial least-squares regression, excellent prediction of water activity (R 2=0.95), and L* values (R 2=0.92), and approximate prediction of hardness (R 2=0.78), b* values (R 2=0.74), and moisture content (R 2=0.74) were shown. However, the FFFS failed to predict a* values, primary and secondary oxidation products (R 2 < 0.6).

Non-invasive analysis of natural textile dyes using fluorescence excitation-emission matrices

Multidimensional fluorescence spectroscopy was assessed as a non-invasive and non-destructive method for the analysis of components in natural textile dyes. Results demonstrate that components in the natural dyes fluoresce and wool's intrinsic fluorescence is, in many cases, not a considerable analytical interferent. In the case of some self-dyed reference yarns, like those dyed with northern and lady's bedstraws, wood horsetail, safflower, salted shield lichen, dyer's madder and cochineal, the fluorescence excitation-emission matrices (EEMs) are sufficiently characteristic for using them as a primary means of identification (or assignment to a family of dyes). With most of the studied yellow and green dyes (heather, silver birch, some bloodred webcap treatments, alkanet), however, the spectra can be used as additional information for identification.This study reports multidimensional fluorescence data for a collection of wools dyed with natural dyes (31 dyed wool yarn samples that were self-dyed with 18 different natural dyes) that were used as references in a case study of two historical textiles for which liquid chromatography-mass spectrometry was used as a confirmatory technique. Given its utility as a rapid and non-destructive/non-invasive method with information-rich multidimensional EEM output, the front-face fluorescence spectroscopy of surfaces using a fiber optic probe is a promising technique for the analysis of dyes on cultural heritage textiles.

Determination of Adulteration of Chicken Meat into Minced Beef Mixtures using Front Face Fluorescence Spectroscopy Coupled with Chemometric.

The objective of this study was to explore the potential of front face fluorescence spectroscopy (FFFS) as rapid, non-destructive and inclusive technique along with multi-variate analysis for predicting meat adulteration. For this purpose (FFFS) was used to discriminate pure minced beef meat and adulterated minced beef meat containing (1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%) of chicken meat as an adulterant in uncooked beef meat samples. Fixed excitation (290 nm, 322 nm, and 340 nm) and fixed emission (410 nm) wavelengths were used for performing analysis. Fluorescence spectra were acquired from pure and adulterated meat samples to differentiate pure and binary mixtures of meat samples. Principle component analysis, partial least square regression and hierarchical cluster analysis were used as chemometric tools to find out the information from spectral data. These chemometric tools predict adulteration in minced beef meat up to 10% chicken meat but are not good in distinguishing adulteration level from 1% to 5%. The results of this research provide baseline for future work for generating spectral libraries using larger datasets for on-line detection of meat authenticity by using fluorescence spectroscopy.

Texture staling of pound cakes assessed by front face fluorescence spectroscopy in tandem with chemometric analysis.

Two vegetal oils have been selected for the formulation of pound cakes, rapeseed oil (RO) and palm oil (PO). The freshness of these products has been monitored during 58 days of storage. The RO pound cakes of 58 days as well as PO pound cakes presented higher values (p < .05) of hardness (N), Young's modulus (N.cm-2 ) and compressive stress (N.cm-2 ) than those aged of 5 days. For both vitamin A and tryptophan spectra, the maximum of fluorescence intensity varied according to the aging period. For both RO and PO recipes, lipid oxidation indicators (peroxide value, para-anisidine value, and total oxidation value [TOTOX]) were interestingly correlated to Young's modulus (R2 =0.99) as well as compressive stress (R2 =0.99), using polynomial model. The application of partial least squares regression to the vitamin A spectra provided excellent predictive results for both compressive stress (R2 = 0.99) and TOTOX (R2 =0.99). Good results were observed for tryptophan spectra for the prediction of TOTOX (R2 = 0.77). Thus, the use of front face fluorescence spectroscopy may provide rapid and accurate results for the monitoring of pound cakes freshness throughout storage.

Tryptophan front-face fluorescence and functional properties of whey: A preliminary study

This study investigated the potential of front-face fluorescence spectroscopy to predict the functional properties of whey. Whey has a commercial interest due to its excellent nutritional value and versatile functional properties. However, its attributes depend dramatically on heat treatment, which may alter its suitability for different food applications. Tryptophan front-face fluorescence of whey and its functional properties, i.e., foaming, gel-forming, and emulsifying properties, were evaluated after milk heat treatment (at 80 °C with seven holding times) to detect correlations between tryptophan fluorescence and functional parameters and generate predictive models. Whey samples were obtained by isoelectric precipitation of caseins from reconstituted skim milk powder enriched with whey protein isolate. As expected, heat treatments induced an increase in whey protein denaturation, as well as a decrease in total whey protein concentration and tryptophan fluorescence intensity. Gel-forming and emulsifying properties of whey significantly correlated with the maximum intensity of tryptophan (P < 0.001). Concerning foaming properties, only the foam stability index revealed a weak correlation with tryptophan maximum intensity (P < 0.05). Consequently, models presented strong significances (P < 0.001). Specifically, using only tryptophan fluorescence allowed successful prediction of emulsifying properties but was not enough for foaming and gel forming properties.

Noninvasive diagnosis of type 2 diabetes mellitus by hair analysis using laser-induced breakdown spectroscopy (LIBS)

Currently, the reference method for diagnosing the pathology of diabetes is the measurement of glycated hemoglobin HbA1c. As a major public health problem, as categorized by the World Health Organization, the need to develop new techniques that are more accessible, especially for developing countries, is necessary. The objective of this work is to propose a new technique based on laser-induced breakdown spectroscopy (LIBS) using the essential minerals calcium, sodium, magnesium, and zinc in hair as biomarkers for the screening of type 2 diabetes. The study involved 130 women: 24 were classified as low-level diabetics with a glycated hemoglobin HbA1c <7% and 56 were classified as high-level diabetics with an HbA1c >7% after clinical tests were performed at the Habib Thameur Hospital in Tunis. The other 50 women were healthy and used as controls. The correlation of the mineral concentrations in the hair with the values of glycated hemoglobin allow an economical and rapid detection of the disease. The results showed a strong negative correlation between the levels of calcium, magnesium, and zinc with the HbA1c values and a strong positive correlation between the intensity of the sodium lines and HbA1c. These results allowed the discrimination of the three groups in the cohort, offering a new approach to quickly classify the patients involved in a screening campaign. In addition, the strong correlation between laser-induced breakdown spectroscopy (LIBS) and the front face fluorescence spectroscopy (FFFS), previously applied on the same samples, may help identify the source of the fluorescence spectra. All of these results support the use of LIBS upon hair to evaluate minerals as effective biomarkers for the detection of type II diabetes to be a promising approach.

Non-invasive and rapid diagnosis of type 2 diabetes mellitus based on the analysis of hair by front-face fluorescence spectroscopy.

Rapid and early detection of pathologies for screening purposes is not always easy with traditional methods. New low-cost optical techniques that are suitable for preventive detection and, more specifically, for developing countries must be developed. The objective of this work is to propose UV-VIS fluorescence of hair as a promising technique for a simple and rapid preliminary diagnosis of type II diabetes. In this work, we analyzed 130 hair samples taken from volunteers of different ages at the Habib Thameur Hospital in Tunis, Tunisia. These samples were analyzed clinically beforehand, and 50 were classified as healthy acting as a control, 24 were classified as low-level diabetics with a glycated hemoglobin A1C (HbA1c) <7%, and the other 56 were classified as high-level diabetics having an HbA1c >7%. The fluorescence of the patients' hair led to several interesting results. Indeed, a clear discrimination was obtained not only between the healthy and patients with a disease, but also a discrimination between diabetics with low levels and high levels or diabetics with and without complication. Also, a strong correlation between fluorescence spectra and glycated HbA1c for the diabetic population was clearly established. A linear discriminant analysis shows that it is possible to predict the status of test patients after having trained a fraction of the population. All these results show the ability of the front-face fluorescence (FFF) technique to detect disease and predict advanced states simply by capturing the fluorescence of the hair illuminated by a single LED. This work shows for the first time, to our knowledge, the capability of the FFF technique on hair samples for the diagnosis of diabetes.

Front-Face Fluorescence Spectroscopy and Feature Selection for Fruit Classification Based on N-CovSel Method

Internal disorder is a major problem in fruit production and is responsible for considerable economical losses. Symptoms are not externally visible, making it difficult to assess the problem. In recent years, 3D fluorescence spectroscopy has been used to reveal features of interest in agronomical field, such as plant stress and plant infection. Such technique could provide useful information regarding changes that occur at the tissue level, in order to distinguish spectral differences between healthy and disordered fruits. This paper introduces the use of the new three-way feature extraction N-CovSel method, compared to the commonly used N-PLS-DA method. These approaches were used upon front-face fluorescence spectra of 27 fruit pulp and skin samples, by analysing excitation wavelengths ranging from 250 to 650 nm, and emission wavelengths varying from 290 to 800 nm. N-CovSel method was applied to identify the most relevant features on: 1) excitation-emission wavelength couples, 2) excitation wavelengths whatever the emission wavelengths and 3) emission wavelengths whatever the excitation wavelengths. Discriminant analysis of the selected features were performed across classes. The constructed models provided key features to differentiate healthy fruits from disordered ones. These results highlighted the capability of N-CovSel method to extract the most fitted features for enhanced fruit classification using front-face fluorescence spectroscopy. They revealed characteristic fluorophores involved in the structural modifications generated by the physiological disorder studied. This paper provides preliminary results concerning the suitability of N-CovSel method for the desired application. Further investigations could be performed on intact fresh fruits in a non-destructive way, allowing an earlier and faster detection of the internal disorder for in-field or industrial applications.

Prediction of riboflavin and ascorbic acid concentrations in skimmed heat-treated milk using front-face fluorescence spectroscopy

The objective of this work was to obtain degradation kinetic models of riboflavin and ascorbic acid, and to evaluate the potential of front-face fluorescence (FFF) spectroscopy to predict their concentration in milk after thermal processing. A factorial design with three temperatures (70, 80 and 90 °C) and nine times (from 0 to 60 min) of heat treatment was used. Degradation kinetics of both vitamins were of first order. Predictive kinetic models using the Arrhenius equation had a variability coefficient of 2.26 and 3.64% for riboflavin and ascorbic acid, respectively. With fluorescent predictors such as tryptophan, Maillard compounds and riboflavin, prediction models with coefficients of variation smaller than 3.57% for riboflavin and ranging from 4.24 to 14.25% for ascorbic acid were obtained. In conclusion, FFF is a viable alternative to predict riboflavin and ascorbic acid content of milk which could allow in-line monitoring and control of thermal damage.