Excitation-emission Fluorescence Spectroscopy Research Articles

Multidimensional fluorescence spectroscopic characterization of Spain’s top-selling gins: Category and alcohol content

Excitation-emission fluorescence spectroscopy (EEFS) is emerging as a powerful tool for food characterization and authentication. This study pioneers the use of EEFS to characterize and differentiate Spain’s top-selling gins, considering categories and alcohol content. Twenty gins, including alcoholic (ALC), light alcoholic (LIG), and non-alcoholic (NALC) types, were analyzed generating excitation-emission matrices (EEMs), which were processed with multi-way principal component analysis (MPCA) and PARAllel FACtor analysis (PARAFAC). Results revealed distinct spectral fingerprints for each gin type, with significant differences between alcoholic and non-alcoholic gins. Light gins closely resembled their full-alcohol counterparts, indicating minimal alteration in gin characteristics due to reduced alcohol content, while non-alcoholic gins showed substantial divergence. The MPCA model highlighted primary differences between ALC and NALC types, while the PARAFAC models identified specific fluorophores linked to juniper berries and other botanicals. This study confirms that EEFS, coupled with chemometrics, is effective in authenticating gin products, marking a significant advancement in spirit analysis.

Light-Emitting-Diode-Induced Fluorescence from Organic Dyes for Application in Excitation-Emission Fluorescence Spectroscopy for Food System Analysis.

An experimental study is presented on the possibility of using the fluorescence from organic dyes as a broadband light source together with a monochromator for applications in excitation-emission matrix (EEM) fluorescence spectroscopy. A high-power single-chip light-emitting diode (LED) was chosen as an excitation source with a central output wavelength at 365 nm to excite a fluorescent solution of Coumarin 1 dye dissolved in ethanol. Two excitation configurations were investigated: direct excitation from the LED and excitation through an optical-fiber-coupled LED. A Czerny-Turner monochromator with a diffraction grating was used for the spectral tuning of the fluorescence. A simple method was investigated for increasing the efficiency of the excitation as well as the fluorescence signal collection by using a diffuse reflector composed of barium sulfate (BaSO4) and polyvinyl alcohol (PVA). As research objects, extra-virgin olive oil (EVOO), Coumarin 6 dye, and Perylene, a polycyclic aromatic hydrocarbon (PAH), were used. The results showed that the light-emitting-diode-induced fluorescence was sufficient to cover the losses on the optical path to the monochromator output, where a detectable signal could be obtained. The obtained results reveal the practical possibility of applying the fluorescence from dyes as a light source for food system analysis by EEM fluorescence spectroscopy.

Feasibility of excitation-emission fluorescence spectroscopy in tandem with chemometrics for quantitation of trans-resveratrol in vine-shoot ethanolic extracts.

trans-Resveratrol (TR) is a well-known phytochemical compound with important biological properties. It can be recovered from agri-food by-products or wastes, such as vine shoots. Once recovered, its concentration should be measured, possibly in a green, non-destructive, and efficient manner. With these premises, this work aimed to explore the feasibility of excitation-emission fluorescence spectroscopy combined with chemometrics for the analysis of TR in raw extracts obtained from vine shoots. A total of 75 extracts were produced and analyzed by ultra-performance liquid chromatography method with diode array detection (UPLC-DAD) and spectrofluorimetry. Then, the feasibility of two calibration strategies for TR quantitation was assessed - a parallel factor analysis (PARAFAC)-based calibration and the N-way partial least squares (NPLS) regression. The extracts showed variable TR content, the excitation/emission maxima of which were at around 305/390 nm, respectively. The best PARAFAC-based calibration allowed a root mean square error of prediction (RMSEP) of 22.57 mg L-1 , and a relative prediction deviation (RPD) of 2.91 to be obtained but a large number of PARAFAC components should be considered to improve the predictions. The results of the NPLS regression were slightly better, with a RMSEP of 19.47 mg L-1 , and an RPD of 3.33 in the best case. Fluorescence could be an alternative analytical technique to measure TR in complex samples. Chemometric tools allowed the identification of the TR signal in the fluorescence landscapes, which could be further used for its non-destructive quantitation. The need for a more accurate criterion for optimal PARAFAC complexity emerged. © 2024 Society of Chemical Industry.

Effect of electrolytic zero-valent iron activated sodium hypochlorite on sludge dewatering performance.

Using electrolytic zero-valent iron-activated sodium hypochlorite (EZVI-NaClO) to pretreat sludge, the capillary suction time (CST) was utilized to evaluate sludge dewaterability. Ammonia nitrogen (NH4-N), dissolved phosphorus, and total phosphorus in the supernatant were used to analyze sludge disintegration. This approach aimed to evaluate the effectiveness of the pretreatment process and its impact on the sludge composition. The migration and transformation of extracellular polymeric substances (EPS), including dissolved EPS (S-EPS), loosely boundEPS, and tightly bound-EPS (TB-EPS), were analyzed by detecting protein and polysaccharide concentrations and three-dimensional fluorescence excitation-emission spectroscopy (3D-EEM). The sludge particle properties, including sludge viscosity and particle size, were also analyzed. The results suggested that the optimal pH value, NaClO dosage, current, and reaction time were 2, 100 mg/gDS (dry sludge), 0.2A, and 30 min, respectively, with a CST reduction of 43%. Protein and polysaccharide contents in TB-EPS were significantly reduced in the EZVI-NaClO group. Conversely, protein and polysaccharides contents in S-EPS increased, suggesting that EZVI-NaClO treatment could disrupt the EPS. Besides, the viscosity of the treated sludge decreased from 195.4 to 54.9 mPa·S, indicating that sludge fluidity became better. ZEVI-NaClO could enhance sludge dewaterability by destructing protein and polysaccharide structure and improving sludge hydrophobicity.

The bacterial influencing mechanisms of salinity fluctuations in a brackish-water lake on the dissolved organic matter characteristics of pore water

The dissolved organic matter (DOM) components in lake water have been widely studied; however, few previous studies have considered the growth of Phragmites australis in brackish lakes. It has not been well understood how salinity variations influence the DOM compositions in pore water and its bacterial mechanisms in lakes with Phragmites australis. This experiment included three salinity groups (1,200 mg/L, 3,600 mg/L, and 6,000 mg/L) to study the interactions between bacteria and DOM in pore water under a salinity gradient. The results showed that the maximum fluorescence intensity (Fmax) of DOM measured by excitation-emission fluorescence spectroscopy decreased with increasing salinity. Higher salinity reduced the Fmax of protein-like substances and resulted in DOM becoming more aromatic. Salinity affected DOM composition due to the responses of functional bacterial communities. Thiobacillus was salt-tolerant and dominated in the sediments, and its relative abundance was negatively correlated with the Fmax of protein-like components. The relative abundance of Flavobacterium showed a positive correlation with salinity and a negative correlation with the Fmax of the fulvic acid-like component. Pseudomonas, Brevundimonas, and Polaromonas were negatively correlated with salinity and the Fmax of the fulvic acid-like component, while being positively correlated with the Fmax of tyrosine-like and aromatic protein substances. Higher salinity inhibited the metabolism gene modules of tryptophan and tyrosine. The results of this study may offer a novel perspective on comprehending the biochemical cycling of fluorescent DOM, encompassing tryptophan-like, tyrosine-like, and fulvic acid-like components in brackish lakes with fluctuating salinity.

Characteristics and Influencing Factors of Dissolved Organic Matter in Cave Drip Water—A Case Study from Furong Cave, Southwest China

Understanding the hydrological processes of dissolved organic matter (DOM) in the surface karst zone is crucial for the utilization and safety of groundwater resources. However, research on DOM in drip water from karst caves is limited. In this study, continuous monitoring was conducted for four years at four drip water monitoring sites (MP1, MP2, MP3, and MP9) in Furong Cave, Southwest China. The three-dimensional fluorescence excitation–emission spectroscopy (3D-EEM) and fluorescence region integration (FRI) methods were employed, along with correlation analysis, to investigate the spectral characteristics, composition, sources, and influencing factors of the DOM in the drip water of Furong Cave. The results indicated that (1) the three-dimensional fluorescence peaks in the drip water were classified into six categories: A, B, C, T, Ti, and M. (2) The dominant source of the drip water DOM is endogenous organic matter. (3) The FRI analysis indicates a relatively high proportion of Type II substances in the drip water, predominantly composed of tryptophan-like substances. (4) The DOM in the drip water of Furong Cave was influenced by various factors, including the mixing effect of “new” and “old” water, water residence time in karst systems, and water–rock interactions (WRI), resulting in the complex responses of drip rates and DOM to surface precipitation and temperature at different drip water sites. This study provides a reference for comparative research on DOM in cave drip water in karst regions, which contributes to a better understanding of the migration mechanism of DOM in karst aquifers under different climate and karst ecological conditions.

Monitoring of cellulose-rich biowaste co-digestion with 3D fluorescence spectroscopy and mass spectrometry-based metabolomics

Anaerobic digestion (AD) is a promising waste management strategy that reduces landfilling while generating biogas. Anaerobic co-digestion involves mixing two or more substrates to enhance the nutrient balance required for microorganism growth and thus improve the degradation. Monitoring AD is crucial for comprehending the biological process, optimizing process stability, and achieving efficient biogas production. In this work, we have used three dimensional excitation emission fluorescence spectroscopy and mass spectrometry metabolomics, two complementary techniques, to monitor the anaerobic co-digestion (AcoD) of cellulose, ash wood or oak wood with food waste. The two approaches were compared together and to the biogas production records. Results of this experiment demonstrated the complementarity of both analytical techniques with the measurement of the biogas production since 3D fluorescence spectroscopy and MS metabolomics revealed the earlier molecular changes occurring in the bioreactors, mainly associated with the hydrolysis step, whereas the biogas production data reflected the biological activity in the last step of the digestion. Moreover, in all cases, the three data sets effectively delineated the differences among the substrates. While the two wood substrates were poorly degradable as they were richer in aromatic compounds, cellulose was highly degradable and was characterized by the production of several glycolipids. Then, the three tested AcoDs resulted in a similar 3D EEM fluorescence and metabolomics profiles, close to the one observed for the AD of food waste alone, indicating that the incorporation of the food waste drove the molecular degradation events in the AcoDs. Substrate-specific differences were appreciated from the biogas production data. The overall results of this research are expected to provide insight into the design of guidelines for monitoring AcoD.

Identification and quantification of ciprofloxacin, enrofloxacin and difloxacin residues in milk using excitation-emission fluorescence and second-order standard addition methods

In the presence of non-modeled components and analyte-matrix interaction in real samples, a combination of second-order multivariate calibration and standard addition is desired to achieve accurate results via second-order advantage. Enrofloxacin (ENR), Difloxacin (DIF), and Ciprofloxacin (CIP) are Fluoroquinolones widely considered antibiotic residues in milk. Excitation-emission fluorescence spectra of these antibiotics at pH = 9.1 provide second-order data for identifying and quantifying them in a mixture using second-order calibration modeling.Rank annihilation factor analysis (RAFA) and multivariate curve resolution-alternating least squares (MCR-ALS) with trilinearity constraints are applied to determine the CIP, ENR, and DIF residues in synthetic mixtures and milk using second-order excitation-emission fluorescence spectroscopy. In both methods, the trilinearity constraint guarantees a unique true solution to the spectral profiles of analytes. The combination of second-order standard addition and higher-order calibration modeling with RAFA and MCR-ALS supports the second-order advantage in milk analysis.

Excitation-emission fluorescence spectroscopy coupled with PARAFAC and MCR-ALS with area correlation for investigation of jet fuel contamination

The contamination of jet fuel has gained attention in the past years as a notable factor in aircraft accidents. Identifying the contamination sources is still a challenge, especially when they have a similar composition to the fuel, such as kerosene solvent (KS). A novel analytical methodology was developed by combining a set of excitation-emission matrix (EEM) fluorescence to area constrained multivariate curve resolution with alternating least-squares (MCR-ALS) and PARAllel FACtor (PARAFAC) analysis, in order to identify KS in blends with JET-A1. For this purpose, a dataset with 50 samples (KS and JET-A1 blends, 2.0–100% v/v) was used to build the multivariate models. Both PARAFAC and MCR-ALS allowed fuel quantification with 4.64% and 3.46% RMSEP, respectively; both models (PARAFAC and MCR-ALS) could quantify KS with high accuracy (RMSEP <5.36%). In addition, MCR-ALS model was able to recover the pure spectral profiles of KS, JET-A1 and interferers. GC-MS data of the samples proved the composition similarities between both petroleum distillates, thus being inefficient for identifying the contamination. These results indicate that the development of multivariate models using EEM was the key for contributing with a new low-cost and accurate method for on-line screening of jet fuel contamination.

Excitation-emission fluorescence spectroscopy and sparse chemometric methods for grape seed oil classification and authentication

Grape seed oil (GSO) authentication and classification have recently become the most important aspects of edible oil quality control due to its high nutritional values. In the present contribution, excitation-emission fluorescence spectroscopy and sparse chemometric methods were used for the classification of GSO obtained from different Iranian grape genotypes and the detection of GSO adulteration with refined sunflower oil (SFO). The fluorescence spectra were collected in the wavelength ranges of λex = 200–500 nm and λem = 200–800 nm. To develop multivariate models, more than 200 samples from five different varieties of GSO were used. The sparse version of N-way partial least squares discriminant analysis (sNPLS-DA) was utilized to build an interpretable classification model. Classification accuracies for the sNPLS-DA model were 1.00 for predicting all grape genotypes. The collected fluorescence data revealed a distinct intensity difference between the Chafteh GSO and other GSOs in λex = 270–310 nm, and λem = 300–350 nm. To simulate the adulteration of GSO with SFO, 35 binary blends of Chafteh GSO samples (as a higher-quality oil) were prepared at adulterant levels from 10% to 50%. Sparse multivariate regression techniques, including the least absolute shrinkage and selection operator (Lasso), Ridge, and Elastic net were applied for quantitative analysis of GSO adulteration. The coefficient of multiple determination (R2) and the RMSE for the Lasso model were 0.914 and 0.013, respectively, for the external test sets. The results showed that the sparse chemometric methods coupled with excitation-emission fluorescence spectroscopy can be used as interpretable and reliable tools for quality control and adulteration detection of oil samples in the food industry and commerce.

Liquid-liquid microextraction method using a deep eutectic solvent for the determination of total paraben content by fluorescence spectroscopy and second-order calibration

Concerns regarding the potential harm associated with endocrine dysfunction are increasing, particularly in children, due to the immaturity of their metabolic system and skin barrier. In this work, parabens, which are esters widely used as preservatives in cosmetics, were quantified in commercial samples of diaper rash cream. For this purpose, a green and efficient liquid–liquid microextraction (LLME) method was accomplished using a deep eutectic solvent (DES). To enhance recovery rates, the extraction parameters were optimized using a central composite design (CCD) on blank matrix samples spiked. The quantification was based on excitation-emission fluorescence spectroscopy, combined with parallel factor analysis (PARAFAC) decomposition, which proved be an advantageous tool to solve the overlap of uncalibrated constituents in the complex matrix. The PARAFAC modeling strategy provided satisfactory results within a linear range response of 100–1300 ng g−1, with LOD equal to 23 ng g−1. A validation set, with various proportions of methyl, ethyl, propyl, and butyl paraben standards, was used to validate the calibration model, resulting in root mean square error (RMSE) and relative error of prediction (REP) values of 32 ng g−1 and 4.5%, respectively. Moreover, acceptable root mean square error of prediction (RMSEP) and REP values (105 ng g−1 and 15%, respectively) were obtained, when a set of blank matrix samples spiked was applied. The proposed method was successfully applied to quantify total paraben content in commercial samples of diaper rash cream, yielding recoveries ranging from 83% to 125%. The method proved to be sensitive, accurate, and green, as it significantly reduced the consumption of organic solvents. Furthermore, it could serve as an alternative for the determination of preservatives in complex cosmetic samples.

Spatio-temporal characterization of dissolved organic matter in karst rivers disturbed by acid mine drainage and its correlation with metal ions

Dissolved organic matter (DOM) is widely present in surface water environments and plays a critical role in the biogeochemical cycling of metal ions. Metal ions in acid mine drainage (AMD) have seriously polluted karst surface water environments, but few studies have explored interactions between DOM and metal ions in AMD-disturbed karst rivers. Here, the composition and sources of DOM in AMD-disturbed karst rivers were investigated by fluorescence excitation-emission spectroscopy combined with parallel factor analysis. In addition, correlations between metal ions and other factors (DOM components, total dissolved carbon (TDC) and pH) were determined using structural equation modeling (SEM). Results showed that there were evident differences in the seasonal distribution of TDC and metal ion concentrations in AMD-disturbed karst rivers. The concentrations of DOC, dissolved inorganic carbon (DIC), and metal ions were generally higher in the dry season than in the wet season, with Fe and Mn pollution being the most pronounced. The DOM in AMD contained two types of protein-like substances that were mainly from autochthonous inputs, while DOM in AMD-disturbed karst rivers contained two additional types of humic-like substances from both autochthonous and allochthonous inputs. The SEM results showed that the influence of DOM components on the distribution of metal ions was greater than that of TDC and pH. Among the DOM components, the influence of humic-like substances was greater than that of protein-like substances. Additionally, DOM and TDC had direct positive effects on metal ions, while pH had a direct negative effect on these. These results further elucidated the geochemical interactions between DOM and metal ions in AMD-disturbed karst rivers, which will assist in the pollution prevention of metal ions in AMD.

An analytical approach based on excitation-emission fluorescence spectroscopy and chemometrics for the screening of prostate cancer through urine analysis: A proof–of–concept study

In the present feasibility study, excitation-emission fluorescence spectroscopy has been investigated, as a rapid and accurate analytical method for the development of a tentative model for the early screening of prostate cancer directly through urine analysis in order to provide reliable results while improving patient compliance.Sixty-nine urine samples (46 samples from patients with histologically proven prostate cancer and 23 from healthy donors) were provided, by the University of Pisa, Urology Unit. The excitation-emission fluorescence measurements were performed on centrifugated urine samples at room temperature on a Perkin-Elmer LS55B luminescence spectrometer and the corresponding data array was analysed with parallel factor analysis (PARAFAC).From a synergistic analysis of the obtained results, four main fluorophores, corresponding to four selected PARAFAC factors, were recognizable in the urine excitation-emission matrices (EEMs) and the respective species could be potential markers in the differentiation among healthy and cancer samples. PARAFAC results, in terms of extracted scores, coupled with discriminant algorithms, allowed to develop a first attempt of healthy/cancer discrimination model. The chemometrics models show promising correlation between some of the depicted fluorophores and the disease state. However, considering the limited cohort (not only in terms of number but also of representativeness), this study must be considered as a proof of concept; a more sound and statistically relevant sampling must be performed in order to consider the confounding factors in the cohort treated and to develop an analytical approach applicable in real scenarios.

Unsupervised recognition of components from the interaction of BSA with Fe cluster in different conditions utilizing 2D fluorescence spectroscopy

The excitation-emission fluorescence spectroscopy combined with three-way analysis was applied for discriminating the pure BSA and BSA/Fe3O(OAc)6ClO4 (Fe) using unsupervised classification methods. Herein, the interaction of bovine serum albumin (BSA) and Fe clusters as an artificial enzyme is studied by extracting the intrinsic excitation-emission (EEM) fluorescence of BSA. The conformation of BSA changes with pH, temperature, and Fe concentration. Three-way fluorescence data were recorded for BSA and BSA/Fe during different days. The obtained results showed that the Fe clusters cause changes in the structure of BSA conformation as a function of pH, temperature, and Fe concentration. Also, the denaturation pathway of the BSA molecule is significantly different in the presence of Fe clusters. Both techniques of PARAFAC and PCA were used in the excitation-emission fluorescence matrices (EEM) of solutions at three different pH (5.0, 7.0, and 9.0) and temperatures (15.0, 25.0, and 35.0 °C) values. Also, we reported the results of the change in concentrations of Fe (4.0, 6.0, and 8.0 mg) using these methods. These three amino acids (tyrosine, tryptophan, and phenylalanine) indicate all datasets and their similarities and differences. The spectral differences were more remarkable in different pH values compared to different temperatures. Also, we could distinguish between the groups of protein samples properly in different concentrations of Fe using low-cost EEM spectral images and PARAFAC.

Revealing the role of supernatant and granular sludge fractions on granular anaerobic membrane bioreactor fouling

In order to design efficient fouling mitigation strategies in granular anaerobic membrane bioreactors (G-AnMBR), foulant characteristics and their role have to be thoroughly investigated. Raw mixed liquor of G-AnMBR was split by sieving into granules and supernatant fractions at 0.125 mm. Then, the fouling potential and reversibility of the different samples (granules, supernatant and raw mixed liquor) were assessed by measuring critical fluxes and through filtration tests. Various hydrodynamic conditions, i.e. gas sparging and recirculation, were applied to evaluate the impact of shear stress on fouling propensity. Results revealed that the supernatant fraction, composed of fine compounds and micro-particles, had a strong fouling potential, whilst the granule fraction led to minor fouling filtration resistance. Three-dimensional excitation emission fluorescence spectroscopy emphasised the prominent role of colloidal proteins in G-AnMBR membrane fouling. During the filtration test of raw mixed liquor, the fouling propensity of the micro-particles was lowered, since the structural cake layer was modified. Gas sparging allowed for the mitigation of cake formation, but excess of shear forces may lead to granule break-up and more irreversible fouling. Liquid recirculation led to a higher filtration resistance, but almost all the membrane permeability was recovered by physical cleaning. A short filtration cycle without gas sparging followed by a short period of relaxation and gas sparging could be a suitable fouling mitigation method. In this way, release of micro-particles from granule break-up could be limited, the cake build-up would be mostly reversible by physical cleaning, and the energy demand of gas sparging would be greatly reduced, thereby improving the energy neutrality of the G-AnMBR biotechnology.

Using fluorescence excitation-emission matrices to predict bitterness and pungency of virgin olive oil: A feasibility study

Unlike other food products, virgin olive oil must undergo an organoleptic assessment that is currently based on a trained human panel, which presents drawbacks that might affect the efficiency and robustness. Therefore, disposing of instrumental methods that could serve as screening tools to support sensory panels is of paramount importance. The present work aimed to explore excitation-emission fluorescence spectroscopy (EEFS) to predict bitterness and pungency, since both attributes are related with fluorophore compounds, such as polar phenols. Bitterness and pungency intensities of 250 samples were provided by an official sensory panel and used to build and compare partial least squares regressions (PLSR) with the excitation-emission matrix. Both PARAFAC scores and two-way unfolded data led to successful PLSR. The most relevant PARAFAC scores agreed with virgin olive oil phenolic spectra, evidencing that EEFS would be the fit-for-purpose screening tool to support the sensory panel.

Pretreatment of rice straw by newly isolated fungal consortium enhanced lignocellulose degradation and humification during composting

The slow decomposition rate of the reluctant structure of lignocellulose in agricultural waste is the great limitation of composting processes, which can be averted by pretreatment-strategies. This study focused on the impacts of pretreating rice straw using a consortium of newly isolated fungal species on lignocellulose degradation and humic substances during composting. Fungal pretreatment had a significant impact on lignocellulose degradation (84%) of rice straw by producing higher lignocellulytic enzymes than chemical pretreatments (79%) or the control (61%). The compost with fungal pretreated rice straw (FPT) showed significantly high composting temperature in the late mesophilic stage, which enhanced the degradation of lignocellulose. The fluorescence excitation emission spectroscopy revealed that significantly more humic acid-like compounds were formed in FPT. These findings suggest that fungal pretreatment is a feasible method to accelerate straw degradation and humification.

Characterisation of Organic Matter and Its Transformation Processes in On-Site Wastewater Effluent Percolating through Soil Using Fluorescence Spectroscopic Methods and Parallel Factor Analysis (PARAFAC)

This research has used fluorescence spectroscopy and parallel factor analysis (PARAFAC) in order to characterize dissolved organic matter in septic tank effluent, as it passes through the biomat/biozone, infiltrating into the unsaturated zone beneath domestic wastewater treatment systems (DWWTSs). Septic tank effluent and soil moisture samples from the percolation areas of two DWWTSs have been analyzed using fluorescence excitation–emission spectroscopy. Using PARAFAC analysis, a six-component model was obtained whereby individual model components could be assigned to humified organic matter, fluorescent whitening compounds (FWCs), and protein-like compounds. This has shown that fluorescent dissolved organic matter (FDOM) in domestic wastewater was dominated by protein-like compounds and FWCs and that, with treatment in the percolation area, protein-like compounds and FWCs are removed and contributions from terrestrially derived (soil) organic decomposition compounds increase, leading to a higher degree of humification and aromaticity. The results also suggest that the biomat is the most important element determining FDOM removal and consequently affecting DOM composition. Furthermore, no significant difference was found in the FDOM composition of samples from the percolation area irrespective of whether they received primary or secondary effluent. Overall, the tested fluorometric methods were shown to provide information about structural and functional properties of organic matter which can be useful for further studies concerning bacterial and/or virus transport from DWWTSs.

Excitation-emission fluorescence matrix acquired from glutathione capped CdSeS/ZnS quantum dots in combination with chemometric tools for pattern-based sensing of neurotransmitters

The presented work concerns pattern-based sensing with quantum dots for the identification and quantification of neurotransmitters by means of excitation-emission fluorescence spectroscopy (2D fluorescence). In the framework of this study, glutathione capped CdSeS/ZnS nanocrystals were used as non-specific nanoreceptors capable of differentiated interaction with neurotransmitters. The pattern-based sensing with QDs was realized by using excitation-emission fluorescence spectroscopy to provide analyte-specific multidimensional optical information. These characteristic fluorescent response patterns were processed by unfolded partial least squares–discriminant analysis, showing that satisfactory identification of all investigated neurotransmitters: dopamine, norepinephrine, epinephrine, serotonin, GABA, and acetylcholine, can be achieved through the proposed sensing strategy. The impact of the considered fluorescence signal (datum, i.e. zeroth-order data acquired per sample; spectrum, i.e. first-order data acquired per sample; excitation-emission matrix, i.e. second-order data acquired per sample) on the sensing capability of glutathione capped QDs was also verified. The best performance parameters such as accuracy, precision, sensitivity, and specificity were obtained using excitation-emission matrices (88.9–93.3%, 0.93–0.95, 0.89–0.93, and 0.99–1.00, respectively). Thus, it was revealed that excitation-emission fluorescence spectroscopy may improve the recognition of neurotransmitters while using only one type of nanoreceptor. Furthermore, is was demonstrated that the proposed excitation-emission fluorescence spectroscopy assisted QD assay coupled with unfolded partial least squares regression can be successfully utilized for quantitative determination of catecholamine neurotransmitters at the micromolar concentration range with R2 in the range 0.916–0.987. Consequently, the proposed sensing strategy has the potential to significantly simplify the sensing element and to expand the pool of bioanalytes so far detectable with the use of QDs.Graphical abstract

Impact of C/N ratio on the fate of simultaneous Ca2+ precipitation, F− removal, and denitrification in quartz sand biofilm reactor

The coexistence of F−, Ca2+, nitrates, and other pollutants in water body has aroused widespread concern. In this research, a novel quartz sand biofilm reactor was established, aiming to study the key factors of different carbon to nitrogen (C/N) ratios (5:1, 4:1, and 3:1), initial Ca2+ concentration (180 mg L−1, 144 mg L−1, and 108 mg L−1), and hydraulic retention time (HRT) (4 h, 6 h, and 8 h) on simultaneous Ca2+ precipitation, F− removal, and denitrification. Results showed that the removal efficiencies of Ca2+, F−, and nitrate were 55.04%, 82.64%, and 97.69% under the low C/N ratio of 3:1, initial Ca2+ concentration of 180 mg L−1, and HRT of 8 h. 3-D Excitation-Emission Fluorescence Spectroscopy (3-D EEM) demonstrates that extracellular polymeric substances (EPS) was generated during the growth metabolism. Scanning Electron Microscopy (SEM) and X-ray diffractometer images showed that Ca2+, F− removed in the form of CaCO3, Ca5(PO4)3F and CaF2 under Acinetobacter sp. H12 induction. Moreover, high-throughput sequencing results display that the biomineralized bacteria Acinetobacter sp. H12 exerted great influence in the bioreactor. This research will underpin the practical use of multiple pollutants such as F− and Ca2+ wastewater under the different C/N ratios.