First order Rayleigh scatter as a separate component in the decomposition of fluorescence landscapes

Monitoring small-scale bioreactor studies for media development using polarized total synchronous fluorescence spectroscopy (pTSFS) and synchronous light scattering (SyLS)

Biopharmaceutical process development often involves the use of small-scale bioreactors (SSBR) for optimizing media formulations and process conditions during scale up to commercial scale production. Two key process parameters (CPP) used in SSBR studies are protein titre and viable cell density (VCD). Here, we explore the efficacy of parallel polarized total synchronous fluorescence spectroscopy (TSFS||) and Synchronous Light Scattering (SyLS||) to qualitatively monitor these CPPs and quantitatively predict titre and VCD for a large-scale cell culture media optimization SSBR study. The study involved 71 different media formulations (50+ components each), and the bioprocess was run for 13 days or more. Samples were extracted at set times (Day 0, 3, 9, and 13) and clarified by centrifugation. TSFS|| spectra showed significant emission changes along with increased light scatter over the course of the bioprocess. SyLS|| measurements strongly correlated with particle size data obtained from Dynamic Light Scattering but did not correlate well with VCD probably because of the centrifugation-based sample preparation. Statistical and principal component analysis (PCA) of the pTSFS data showed that spectral variation was greater between media formulations than due to the evolving bioprocess. This prevented the development of accurate global prediction models for media performance (e.g., predicting product titre at day 9 from media spectra measured at day 0). However, classification methods were successfully used to select media subsets with better quantitative prediction accuracy based on spectral similarities. A practical binary (high/low performance) classification model based on Support Vector Machines was generated for media formulation screening. Combining emission and scatter measurements with multivariate data analysis provides a more holistic, multi-attribute bioprocess monitoring method that minimizes the need to use different offline analytical methods. This methodology can be used to monitor process trajectories and deviations, and ultimately be used to predict bioprocess CPPs when implemented on production scale processes where there is much less compositional variation in the media. We believe this SSBR-pTSFS/SyLS approach will provide a valuable resource to develop the design/parameter space for in-process monitoring at production scale from early-stage process/media development studies.

Rapid elimination of scattering in three-dimensional fluorescence spectra via deep learning

Three-dimensional fluorescence spectra are often affected by scattering effects, traditional scattering elimination methods rely excessively on parameter settings and cannot automatically eliminate scattering in batches, thereby limiting the application of fluorescence spectroscopy technology in rapid online monitoring and analysis of samples. In this study, we have developed a model based on a deep learning CycleGAN to rapidly eliminate scattering from three-dimensional fluorescence spectra. The proposed model efficiently eliminates scattering by simply inputting single or batches of contaminated fluorescent spectra. By training the CycleGAN using a large dataset of simulated three-dimensional fluorescence spectra and employing data augmentation, to the model can transform fluorescence spectra with scattering into ones without scattering. To validate the effectiveness of the proposed methed, we confirmed its generalization and reliability by eliminating scattering from two sets of previously unseen real experimental three-dimensional fluorescence spectra. We evaluated the effectiveness of scattering elimination across various noise levels and scattering widths, using metrics such as the mean absolute error, peak signal-to-noise ratio, structural similarity and cosine similarity. Furthermore, we conducted a component analysis using PARAFAC on the spectra post-scattering elimination, yielding correlation coefficients of >0.97 when compared to that in case of actual components. Finally, we compared the proposed model with traditional mathematical methods, such as blank subtraction and Delaunay triangulation. Results showed that the proposed model can automatically and efficiently eliminate scattering from fluorescence spectra in batches, substantially improving the efficiency of scattering elimination.

A simple light path modifying device to reduce scattering in front-face fluorescence spectra

This technical note presents a device to diminish scattering signal in front-face fluorescence spectra while obtaining fluorescence signal. The beam path in a commercial fluorescence spectrometer was modified by two deflecting mirrors, leading reflections away from the sensor. This light path modifying (LPM) device was tested with two fluid and three solid substances, where the scattering-to-fluorescence ratio improved by a factor of 1.7 to 7.6. The spectra obtained with the LPM were much clearer, and distortion of the fluorescence peaks was avoided. Scans of quinine sulphate complied well with reference spectra.

Deciphering DOM-metal binding using EEM-PARAFAC: Mechanisms, challenges, and perspectives

Dissolved organic matter (DOM) is a pivotal component of the biogeochemical cycles and can combine with metal ions through chelation or complexation. Understanding this process is crucial for tracing metal solubility, mobility, and bioavailability. Fluorescence excitation emission matrix (EEM) and parallel factor analysis (PARAFAC) has emerged as a popular tool in deciphering DOM-metal interactions. In this review, we primarily discuss the advantages of EEM-PARAFAC compared with other algorithms and its main limitations in studying DOM-metal binding, including restrictions in spectral considerations, mathematical assumptions, and experimental procedures, as well as how to overcome these constraints and shortcomings. We summarize the principles of EEM to uncover DOM-metal association, including why fluorescence gets quenched and some potential mechanisms that affect the accuracy of fluorescence quenching. Lastly, we review some significant and innovative research, including the application of 2D-COS in DOM-metal binding analysis, hoping to provide a fresh perspective for possible future hotspots of study. We argue the expansion of EEM applications to a broader range of areas related to natural organic matter. This extension would facilitate our exploration of the mobility and fate of metals in the environment.

The response of nitrifying activated sludge to chlorophenols: Insights from metabolism and redox homeostasis

The specialized wastewater treatment plants for the chemical industry are rapidly developed in China and many other countries. But there is a common bottleneck in that the toxic pollutants in chemical wastewater often cause shock impacts on biological nitrogen removal systems, which directly affects the stability and cost of operation. As the research on nitrification inhibition characteristics is not sufficient till now, there is a great lack of theoretical guidance on the control of the inhibition. This study investigated the response of nitrifying activated sludge to chlorophenols (CPs) inhibition in terms of metabolism disorder and oxidative stress. At the initial stage of reaction (i.e., 1 h), reactive oxygen species (ROS)-induced membrane damage which might account for declining nitrification performance. Simultaneously excessive extracellular polymeric substances (EPS) were secreted to alleviate oxidative stress injury and protected microorganisms to some extent. In particular tyrosine-like substances in LB-EPS with a Fmax increase of 242.30% were confirmed to efficiently resist phenols inhibition. Thus, as the inhibition proceeded, metabolism disorder replaced oxidative stress as the main cause of nitrification inhibition. The affected metabolic processes include weakened enzyme catalysis, restricted electron transport and lessened energy generation. At 4 h, nitrifying production of sludge amended with 5 mg/L chlorophenols was 89.27 ± 9.51%-98.15 ± 9.60% lower than blank, the inhibition could be attributed to comprehensively affected metabolism. The structural equation modeling indicated that phenols restricted nitrification enzymes and bacterial electron transport efficiency which was critical to nitrification performance. Moreover, the lessened energy generation weakens enzyme activity to further suppress nitrification. These findings enriched our knowledge of nitrifiers' responses to CPs inhibition and provided the basis for addressing nitrification inhibition.

Using Rayleigh Scattering to Correct the Inner Filter Effect of the Fluorescence Excitation-Emission Matrix

Excitation-emission matrix (EEM) spectroscopy has been proven to be an effective tool for offline fluorescence analysis. However, the pretreatment of EEM data requires an additional ultraviolet-visible (UV-vis) absorption spectrum for inner filter effect (IFE) correction. This complicates the instrument structure and increases the test flow, thus hindering the practical application of EEM in environmental online monitoring. In this work, Rayleigh scattering in EEM, which is often masked, is leveraged to address this challenge as Rayleigh scattering light itself passes through the sample and experiences absorption. We establish a translation-corrected estimation by the Rayleigh scattering (TCERS) method to estimate absorbance, not only enabling the IFE self-correction of EEM but also providing orthogonal spectroscopy information. TCERS is hierarchically tested in real solutions, simulated turbid liquids, and various natural water samples. Results indicate that the predicted UV-vis absorption spectra have a cosine similarity of over 0.95 with the actual spectra. When using the predicted spectra to correct the IFE of EEM, only about 0.005/1.440 bits of information entropy are lost and the absolute errors in EEM are negligible. The proposed method has the potential to streamline the design of fluorescence spectrometers, making it possible to miniaturize, optimize, and popularize these instruments for various practical applications such as environmental monitoring.

The sensitive detection and mechanism of Fe-3,5-dimethyl pyrazole fluorescent sensor to diethylenetriamine pentamethylene phosphonic acid: Experimental study and quantum chemical calculation

Diethylenetriamine pentamethylene phosphonic acid (DTPMP) is one of the most commonly used amino organic phosphonates. The existing methods for DTPMP detection are complicated, time-consuming, and cannot detect trace DTPMP in the natural environment. In the present work, the Fe-based 3,5-dimethyl pyrazole fluorescent sensor (Fe-DP) was constructed. The addition of Fe³⁺ to DP solution can greatly decrease the fluorescent intensity of DP, while the addition of different concentrations of DTPMP will restore the fluorescence intensity of DP to different degrees, to achieve quantitative detection of DTPMP, and the detection limit (LOD) of DTPMP was lower as 0.105 μΜ. The Fe-DP fluorescent sensor exhibited excellent anti-interference ability and good stability. Moreover, the fluorescence quenching mechanism of DP by Fe³⁺ was revealed by UV absorption spectrum and Multiwfn wavefunction analysis based on density function theory (DFT). The results revealed that the excitation of DP belonged to local excitation, in which the electrons were donated primarily by the N atom with double bond and redistributed within the pyrazole ring.The fluorescence quenching of adding Fe³⁺ was not caused by resonance energy transfer or charge transfer, which did not belong to dynamic quenching, but due to the ground state complex formed by the coordination of Fe³⁺ and the double bond N atom on the DP pyrazole ring.

Effects of N-acyl-homoserine lactones-based quorum sensing on biofilm formation, sludge characteristics, and bacterial community during the start-up of bioaugmented reactors

Bioaugmentation is an effective technology for treating wastewater containing recalcitrant organic pollutants. However, it is restricted by several technical problems, including the difficult colonization and survival of the inoculated bacteria, and the time-consuming start-up process. Considering the important roles of quorum sensing (QS) in regulating microbial behaviors, this study investigated the effects of N-acyl-homoserine lactones (AHLs)-based manipulation on the start-up of biofilm reactors bioaugmented with a pyridine-degrading strain Paracoccus sp. BW001. The results showed that, in the presence of two specific exogenous AHLs (C6-HSL and 3OC6-HSL), the biofilm formation process on carriers was significantly accelerated, producing thick and structured biofilms. The protein and polysaccharide contents of the extracellular polymeric substances (EPS) and soluble microbial products (SMP) in sludge were also elevated, possibly due to the increased abundance of several EPS-producing bacterial genera. Specifically, the stability and complexity of protein structures were improved. Besides the reactor running time, the AHL-manipulation was proved to be the main factor that drove the shift of bacterial community structures in the reactors. The addition of exogenous AHLs significantly increased the succession rate of bacterial communities and decreased the bacterial alpha diversity. Most importantly, the final proportions of the inoculated strain BW001 were elevated by nearly 100% in both sludge and biofilm communities via the AHL-manipulation. These findings strongly elucidated that AHL-based QS was deeply involved in biofilm formation, sludge characteristics, and microbial community construction in bioaugmented reactors, providing a promising start-up strategy for bioaugmentation technology.

Quantitative analysis of weakly bound insulin oligomers in solution using polarized multidimensional fluorescence spectroscopy

Being able to measure the size and distribution of oligomers in solution is a critical issue in the manufacture and stability of insulin and other protein formulations. Measuring oligomers reliably can however be complicated, due to their fragile self-assembled structures, which are held together by weak forces. This can cause issues in chromatographic based methods, where dissociation or re-equilibration of oligomer populations can occur e.g. upon dilution in a different eluting buffer, but also for light scattering based methods like dynamic light scattering (DLS) where the size difference involved (often less than a factor 3) does not allow mixtures of oligomers to be resolved. Intrinsic fluorescence offers an attractive alternative as it is non-invasive, sensitive but also because it contains scattered light when implemented via excitation emission matrix (EEM) measurements, that is sensitive to changes in particle size. Here, using insulin at formulation level concentrations, we show for the first time how EEM can both discriminate and quantify the proportion of oligomeric states in solution. This was achieved by using the Rayleigh scatter (RS) band and the fluorescence signal contained in EEM. After validating size changes with DLS, we show in particular how the volume under the RS band correlated linearly with protein/oligomer molecular weight, in agreement with the Debye-Zimm relationship. This was true for the RS data from both EEM and polarized EEM (pEEM) measurements, the latter providing a stronger scatter signal, more sensitive to particle size changes. The fluorescence signal was then used with multivariate curve resolution (MCR) to quantify more precisely the soluble oligomer composition of insulin solutions. In conditions that promoted the formation of mainly one type of oligomer (monomer, dimer, or hexamer), pEEM-MCR helped identify the presence of small amounts of other oligomeric forms, while in conditions that were previously said to favour the insulin tetramer, we show that in the presence of zinc, these insulin samples were instead a heterogenous mixture composed of mostly dimers and hexamers. These MCR results correlated in all cases with the observed discrimination by principal component analysis (PCA), and deviations observed in the RS data. In conclusion, using pEEM scatter and emission components with chemometric data analysis provides a unique analytical method for characterising and monitoring changes in the soluble oligomeric state of proteins.

Missing data recovery combined with Parallel factor analysis model for eliminating Rayleigh scattering in the process of detecting pesticide mixture

Excitation-Emission Matrix (EEM) fluorescence spectroscopy combined with Parallel factor analysis (PARAFAC) provides a widely used method to extract useful information containing unknown components. However, the inherent scattering especially Rayleigh scattering will influence the accuracy of PARAFAC so that appropriate procedure to the scattering becomes an essential problem when processing the EEM data. Many methods have been proposed to solve the problems about eliminating scattering. Missing data recovery combined with PARAFAC model has been discussed in this paper. For EEM data, this method extracted the signal values in the missing area which can effectively correct scattering region. It can eliminate Rayleigh scattering effectively by choosing Gaussian contour constraint. The results of the correlation coefficient (R), the root mean square error of prediction (RMSEP) and average recovery rate (AR) are better which can prove that the combined method is easier to implement and provide better concentration prediction results in detecting pesticide mixture.

Performance of microaeration hydrolytic acidification process in the pretreatment of 2-butenal manufacture wastewater

The performance of the microaeration hydrolytic acidification (MAHA) process and microbial community were investigated under different organic loading rates (OLRs) for the pretreatment of 2-butenal manufacture wastewater (2-BMW). Results indicated that OLRs had different impact on the performance of MAHA process. More than 23.7 ± 2.3% of the chemical oxygen demand (COD) removal and the highest acidification degree (20.9 ± 3.1%) were obtained when OLRs were less than 4.0 ± 0.1 kgCOD/m³ d. However, further increasing OLRs to 6.1 ± 0.1 kgCOD/m³ d subsequently led to the significant reductions of COD removal and acidification degree. In addition, it could be preliminarily inferred that 2H-pyran-2-one tetrahydro-4-(2-methyl-1-propen-3-yl), 5-formyl-6-methyl-4,5-dihydropyran and ethyl sorbate were the main refractory and toxic organics for microorganisms in the wastewater. The soluble microbial product (SMP) and extracellular polymeric substance (EPS) contents (protein, polysaccharide, nucleic acid) had obvious changes under different OLRs. With parallel factor (PARAFAC) model, four fluorescent components were identified. The F_max of protein-like substances in SMP significantly decreased with increasing OLRs to 6.1 ± 0.1 kgCOD/m³ d, which might attribute to fluorescence quenching. Illumina MiSeq sequencing revealed that Pseudomonas, Longilinea, T78, Clostridium, WCHB1-05, Acinetobacter, SHD-231 and Oscillospira were dominant genera at different OLRs.

Adaptive handling of Rayleigh and Raman scatter of fluorescence data based on evaluation of the degree of spectral overlap

At present the general scatter handling methods are unsatisfactory when scatter and fluorescence seriously overlap in excitation emission matrix. In this study, an adaptive method for scatter handling of fluorescence data is proposed. Firstly, the Raman scatter was corrected by subtracting the baseline of deionized water which was collected in each experiment to adapt to the intensity fluctuations. Then, the degrees of spectral overlap between Rayleigh scatter and fluorescence were classified into three categories based on the distance between the spectral peaks. The corresponding algorithms, including setting to zero, fitting on single or both sides, were implemented after the evaluation of the degree of overlap for individual emission spectra. The proposed method minimized the number of fitting and interpolation processes, which reduced complexity, saved time, avoided overfitting, and most importantly assured the authenticity of data. Furthermore, the effectiveness of this procedure on the subsequent PARAFAC analysis was assessed and compared to Delaunay interpolation by conducting experiments with four typical organic chemicals and real water samples. Using this method, we conducted long-term monitoring of tap water and river water near a dyeing and printing plant. This method can be used for improving adaptability and accuracy in the scatter handling of fluorescence data.

The multi-resolution capability of Tchebichef moments and its applications to the analysis of fluorescence excitation-emission spectra

Fluorescence spectroscopy with an excitation-emission matrix (EEM) is a fast and inexpensive technique and has been applied to the detection of a very wide range of analytes. However, serious scattering and overlapping signals hinder the applications of EEM spectra. In this contribution, the multi-resolution capability of Tchebichef moments was investigated in depth and applied to the analysis of two EEM data sets (data set 1 consisted of valine-tyrosine-valine, tryptophan-glycine and phenylalanine, and data set 2 included vitamin B1, vitamin B2 and vitamin B6) for the first time. By means of the Tchebichef moments with different orders, the different information in the EEM spectra can be represented. It is owing to this multi-resolution capability that the overlapping problem was solved, and the information of chemicals and scatterings were separated. The obtained results demonstrated that the Tchebichef moment method is very effective, which provides a promising tool for the analysis of EEM spectra. It is expected that the applications of Tchebichef moment method could be developed and extended in complex systems such as biological fluids, food, environment and others to deal with the practical problems (overlapped peaks, unknown interferences, baseline drifts, and so on) with other spectra.

Calibration, standardization, and quantitative analysis of multidimensional fluorescence (MDF) measurements on complex mixtures (IUPAC Technical Report)

This IUPAC Technical Report describes and compares the currently applied methods for the calibration and standardization of multi-dimensional fluorescence (MDF) spectroscopy data as well as recommendations on the correct use of chemometric methods for MDF data analysis. The paper starts with a brief description of the measurement principles for the most important MDF techniques and a short introduction to the most important applications. Recommendations are provided for instrument calibration, sample preparation and handling, and data collection, as well as the proper use of chemometric data analysis methods.

Accurate anisotropy recovery from fluorophore mixtures using Multivariate Curve Resolution (MCR)

Anisotropy resolved multidimensional emission spectroscopy (ARMES) provides valuable insights into multi-fluorophore systems like proteins that have complex overlapping emission bands. The method combines multidimensional fluorescence, anisotropy, and chemometrics to facilitate the differentiation of fluorophores with very similar emission properties. Here, we address the critical issue of standardizing the chemometric methods required to accurately extract spectral and anisotropy information from fluorophore mixtures using two standard sample sets: perylene in glycerol, and a mixture of Erythrosin B and Phloxine B with overlapping emission but different anisotropies. We show for the first time how to accurately model component anisotropy using Multivariate Curve Resolution (MCR) from data collected using total synchronous fluorescence scan (TSFS) and Excitation Emission Matrix (EEM) measurement methods. These datasets were selected to avoid the presence of inner filter effects (IFE) or Förster resonance energy transfer (FRET) that would depolarize fluorescence emission or reduce data tri-linearity. This allowed the non-trilinear TSFS data to yield accurate component anisotropy data once modelled using the correct data augmentation strategy, however, the EEM data proved to be more accurate once optimal constraints (non-negativity and correspondence among species) were employed. For perylene (S₂) and Phloxine B which both have very weak anisotropy (<0.06), while the spectral recovery was excellent, the modelled anisotropy values were reasonably accurate (±20% of the real value) because of large relative noise contributions. However, for perylene (S₁) and Erythrosin B which have large (>0.2) anisotropies, bilinear and trilinear EEM models built using a total tri-linearity constraint, yielded solutions without any rotational ambiguities and very accurate (±4% of real value) anisotropy values. These sample systems thus provide simple and robust test systems for validating the spectral measurement and chemometric data analysis elements of ARMES.

Extended wavelength anisotropy resolved multidimensional emission spectroscopy (ARMES) measurements: better filters, validation standards, and Rayleigh scatter removal methods

Anisotropy resolved multidimensional emission spectroscopy (ARMES) provides valuable insights into multi-fluorophore proteins (Groza et al 2015 Anal. Chim. Acta 886 133-42). Fluorescence anisotropy adds to the multidimensional fluorescence dataset information about the physical size of the fluorophores and/or the rigidity of the surrounding micro-environment. The first ARMES studies used standard thin film polarizers (TFP) that had negligible transmission between 250 and 290 nm, preventing accurate measurement of intrinsic protein fluorescence from tyrosine and tryptophan. Replacing TFP with pairs of broadband wire grid polarizers enabled standard fluorescence spectrometers to accurately measure anisotropies between 250 and 300 nm, which was validated with solutions of perylene in the UV and Erythrosin B and Phloxine B in the visible. In all cases, anisotropies were accurate to better than ±1% when compared to literature measurements made with Glan Thompson or TFP polarizers. Better dual wire grid polarizer UV transmittance and the use of excitation-emission matrix measurements for ARMES required complete Rayleigh scatter elimination. This was achieved by chemometric modelling rather than classical interpolation, which enabled the acquisition of pure anisotropy patterns over wider spectral ranges. In combination, these three improvements permit the accurate implementation of ARMES for studying intrinsic protein fluorescence.

Temperature-dependent conformational variation of chromophoric dissolved organic matter and its consequent interaction with phenanthrene

Temperature variation caused by climate change, seasonal variation and geographic locations affects the physicochemical compositions of chromophoric dissolved organic matter (CDOM), resulting in difference in the fates of CDOM-related environmental pollutants. Exploration into the thermal induced structural transition of CDOM can help to better understand their environmental impacts, but information on this aspect is still lacking. Through integrating fluorescence excitation-emission matrix coupled parallel factor analysis with synchronous fluorescence two-dimensional correlation spectroscopy, this study provides an in-depth insight into the temperature-dependent conformational transitions of CDOM and their impact on its hydrophobic interaction with persistent organic pollutants (with phenanthrene as an example) in water. The fluorescence components in CDOM change linearly to water temperature with different extents and different temperature regions. The thermal induced transition priority in CDOM is protein-like component → fulvic-like component → humic-like component. Furthermore, the impact of thermal-induced conformational transition of CDOM on its hydrophobic interaction with phenanthrene is observed and explored. The fluorescence-based analytic results reveal that the conjugation degree of the aromatic groups in the fulvic- and humic-like substances, and the unfolding of the secondary structure in the protein-like substances with aromatic structure, contribute to the conformation variation. This integrated approach jointly enhances the characterization of temperature-dependent conformational variation of CDOM, and provides a promising way to elucidate the environmental behaviours of CDOM.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components.

A multi-spectral approach to differentiate the effects of adsorbent pretreatments on the characteristics of NOM and membrane fouling

Pretreatment of feed water is widely applied to mitigate NOM-induced fouling of low-pressure membranes. This research investigated the effectiveness of two pretreatment modes for NOM removal by heated aluminum oxide particles (HAOPs) and the associated reductions in membrane fouling and trihalomethane (THM) formation potential. One mode, referred to here as pre-adsorption, is the conventional process in which adsorbent particles are added to and thoroughly mixed with the feed, after which the particles are separated from the water either upstream of or by the membrane. By contrast, in the pre-deposition mode, a thin layer of adsorbent particles is deposited on a support media (which could be the membrane) prior to passing feed through the layer and the membrane. Although both pretreatment methods remove similar amounts of DOC at the same adsorbent dose, pre-deposition is superior with respect to mitigating membrane fouling and reducing DBP formation. UV and fluorescence spectroscopy and HPSEC analysis indicate that a pre-deposited adsorbent layer removes more chromophores and low apparent molecular weight (AMW) material than pre-adsorption does. Based on absorbance ratios at selected wavelengths, a pre-deposited HAOPs layer removes more aromatic moieties than aliphatic carboxyls, especially at higher HAOPs doses. In addition, pre-deposition is more effective than pre-adsorption at reducing the THM formation potential. The results provide new insights into the interactions between HAOPs and NOM molecules and shed light on the significantly different effects of different adsorbent contacting modes on the fouling potential of the pretreated water.

Identification of the function of extracellular polymeric substances (EPS) in denitrifying phosphorus removal sludge in the presence of copper ion

Industrial wastewater containing heavy metals that enters municipal wastewater treatment plants inevitably has a toxic impact on biological treatment processes. In this study, the impact of Cu(II) (0, 1.5, 2, 2.5, 3 mg/L) on the performance of denitrifying phosphorus removal (DPR) and microbial community structures was investigated. Particularly, the dynamic change in the amount and composition of extracellular polymeric substances (EPS), and the role of EPS in P removal, were assessed using three-dimensional excitation-emission matrix fluorescence spectroscopy combined with parallel factor (PARAFAC) analysis. The results showed that, after long-term adjustment, the P removal efficiency was maintained at 95 ± 2.7% at Cu(II) addition up to 2.5 mg/L, but deteriorated when the Cu(II) addition was 3 mg/L. The EPS content, including proteins and humic substances, increased with increasing Cu(II) additions at concentrations ≤2.5 mg/L. This property of EPS was beneficial for protecting phosphate-accumulating organisms (PAOs) against heavy metals, as both proteins and humic substances are strong ligands for Cu(II). Therefore, the PAOs abundance was still relatively high (67 ± 3%) when Cu(II) accumulation in sludge was up to 10 mg/g SS. PARAFAC confirmed that aromatic proteins could be transformed into soluble microbial byproduct-like material when microorganisms were subjected to Cu(II) stress, owing to their strong metal ion complexing capacity. The increase in the percentage of humic-like substances enhanced the detoxification function of the sludge EPS. EPS accounted for approximately 26-47% of P removed by adsorption when Cu(II) additions were between 0 and 2.5 mg/L. The EPS function, including binding toxic heavy metals and P storage, enhanced the operating stability of DPR systems. This study provides us with a better understanding of (1) the tolerance of DPR sludge to copper toxicity and (2) the function of sludge EPS in the presence of heavy metals in biological P removal systems.

Reply to the ‘Comment on “Simple fluorescence-based detection of Cr(iii) and Cr(vi) using unmodified gold nanoparticles”’ by M. R. Hormozi-Nezhad, J. Mohammadi and A. Bigdeli, Anal. Methods, 2015, , DOI: 10.1039/c5ay00005j

AuNP aggregation by Cr(iii) causes the reduction of the fluorescence emission intensity at 582 nm (λ_ex = 490 nm).

Thermodynamic analysis on the binding of heavy metals onto extracellular polymeric substances (EPS) of activated sludge

Metal binding to microbial extracellular polymeric substances (EPS) greatly influences the distribution of heavy metals in microbial aggregates, soil and aquatic systems in nature. In this work, the thermodynamic characteristics of the binding between aqueous metals (with copper ion as an example) and EPS of activated sludge were investigated. Isothermal titration calorimetry was employed to estimate the thermodynamic parameters for the binding of Cu²⁺ onto EPS, while three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis was used for quantifying the complexation of Cu²⁺ with the EPS. The binding mechanisms were further explored by X-ray absorption fine structure (XAFS) and Fourier transform infrared (FTIR) spectroscopy analysis. The results show that the proteins and humic substances in EPS were both strong ligands for Cu²⁺. The binding capacity N, binding constant K, binding enthalpy ΔH were calculated as 5.74 × 10⁻² mmol/g, 2.18 × 10⁵ L/mol, and -11.30 kJ/mol, respectively, implying that such a binding process was exothermic and thermodynamically favorable. The binding process was found to be driven mainly by the entropy change of the reaction. A further investigation shows that Cu²⁺ bound with the oxygen atom in the carboxyl groups in the EPS molecules of activated sludge. This study facilitates a better understanding about the roles of EPS in protecting microbes against heavy metals.

Application of parallel factor analysis to total synchronous fluorescence spectrum of dilute multifluorophoric solutions: addressing the issue of lack of trilinearity in total synchronous fluorescence data set

In recent years, total synchronous fluorescence (TSF) spectroscopy has become popular for the analysis of multifluorophoric systems. Application of PARAFAC, a popular deconvolution tool, requires trilinear structure in the three-way data array. The present work shows that TSF based three-way array data set of dimension sample × wavelength × Δλ does not have trilinear structure and hence it should not be subjected to PARAFAC analysis. This work also proposes that a TSF data set can be converted to an excitation-emission matrix fluorescence (EEMF) like data set which has trilinear structure, so that PARAFAC analysis can be performed on it. This also enables the retrieval of PARAFAC-separated component TSF spectra.

Characterizing the extracellular and intracellular fluorescent products of activated sludge in a sequencing batch reactor

Three-dimensional excitation-emission-matrix (EEM) fluorescence spectrometry was used to characterize the extracellular and intracellular substances of activated sludge in a sequencing batch reactor (SBR). Parallel factor analysis (PARAFAC) was applied to extract the pure spectra from the overlapped spectra. Three main components, proteins, fulvic- and humic-like substances, were identified from the extracellular substances. Their fluorescence peaks were at an excitation/emission (Ex/Em) of 280/350, 340/400 and 390/450 nm, respectively. The fluorescence of the extracellular proteins had a similar changing pattern with the wastewater chemical oxygen demand, the fulvic-like substance did not vary significantly in a cycle and the humic-like substances accumulated in the substrate uptake phase but decreased later. Proteins and nicotinamide adenine dinucleotide, reduced form (NADH), were identified as the two main intracellular fluorophores, and their fluorescence peaks (Ex/Em) were at 280/340 and 350/450 nm, respectively. The fluorescence intensity scores of the intracellular fluorophores were closely related to the bioreactor performance. Thus, the results of this work provide a foundation for potential utilization of the EEM fluorescence spectroscopy to monitor the activated sludge systems for wastewater treatment.

Independent component analysis as a pretreatment method for parallel factor analysis to eliminate artefacts from multiway data

Parallel factor analysis (PARAFAC) has successfully been used in many applications for the analysis of excitation-emission fluorescence data. However, some measurement "artefacts", such as Rayleigh or Raman scattering, can pose a problem for the extraction of the PARAFAC components and their interpretation. Replacing the spectral zones corresponding to these signals by missing values in the data is not necessarily a method of choice in the cases where informative signals lie in the same wavelength regions. In this article, independent component analysis (ICA) is used on the unfolded cubic array, and the independent components related to the Rayleigh and Raman scattering are identified and removed prior to the reconstruction of the excitation-emission fluorescence data cube. PARAFAC is then applied on these data reconstructed after selective artefact removal, and satisfactory models can be obtained. This procedure, although particularly useful for 3D fluorescence data, may be applied to other types of data as well.

Spectrofluorimetric studies on the binding of salicylic acid to bovine serum albumin using warfarin and ibuprofen as site markers with the aid of parallel factor analysis

The interactions of salicylic acid (SL) and two different site markers (warfarin for site I and ibuprofen for site II) with bovine serum albumin (BSA) in pH 7.4 Tris-HCl buffer have been investigated with the use of spectrofluorimetry. An equilibrium solution of BSA and SA was titrated separately with the two markers. This initial work showed that the binding of SL with BSA could be quite complex, and that there was probably a competitive interaction occurring between ibuprofen and SL. However, the spectral results were difficult to interpret clearly for the interaction of warfarin and SL in similar circumstances. To extract more information from the resolution of fluorescence excitation-emission spectra, the contour plots of the fluorescence spectra indicated that the optimal excitation wavelengths for BSA, SL, warfarin and ibuprofen were different, and were found to be at 278, 295, 306 and 218 nm, respectively. The spectral information was arranged into three-way excitation-emission fluorescence matrix (EEM) stack arrays, and was submitted for analysis by the parallel factor analysis (PARAFAC) algorithm. Firstly, it was demonstrated that the estimated excitation and emission spectral responses for SL, BSA and the site markers, warfarin and ibuprofen, agreed well with the measured spectra. Then, the interpretation of the plots of simultaneously extracted (by PARAFAC) equilibrium concentrations for the above four reactants, showed that: (i) the SL primarily appears to bind in site I but at a different location from the high-affinity binding site (HAS) for warfarin, and the interaction partially overlaps with the low-affinity binding site (LAS) for warfarin. (ii) The SL may have two LAS-one in site II where the HAS for ibuprofen is located, and the other in site I at the LAS for ibuprofen. Thus, application of the PARAFAC method for the study of competitive interaction of SL and BSA with the aid of two different site markers has extracted information unobtainable by traditional methods such as the Scatchard plot, and provided useful means of data visualization.

Identification and quantification of enrofloxacine in poultry feeding water through excitation emission fluorescence and three-way PARAFAC calibration

In this work an excitation emission molecular fluorescence technique with PARAFAC calibration is proposed for enrofloxacine determination in feeding water from poultry farms. In accordance with the working criteria of the 2002/657/EC European Decision, the proposed method has a capability of detection, CCbeta, of 6.8 microg l(-1), for both probabilities of false positive and false negative of 5%. The accuracy of the method is demonstrated and its precision is 1.7 microg l(-1), expressed as standard deviation. This method allows one to identify and determine the quantity of enrofloxacine present in water samples from poultry farms without it being necessary to determine the possible interferents, nor separate them in a step previous to calibration.