Techniques useful in two-dimensional correlation and codistribution spectroscopy (2DCOS and 2DCDS) analyses

Molecular-level insights of microplastic-derived soluble organic matter and heavy metal interactions in different environmental occurrences through EEM-PARAFAC and FT-ICR MS

The interactions between microplastic-derived dissolved organic matter (MPs-DOM) and heavy metals (Cu, Pb, and Cd) regulate the complex environmental transport behavior of pollutants in terrestrial and aquatic environments. In this study, fluorescence excited emission matrix spectroscopy combined with parallel factor analysis (EEM-PARAFAC) and electrospray ionization coupled Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) were employed to investigate the complexation mechanism of MPs-DOM with heavy metals, as well as the effects of different environmental occurrences of MPs-DOM on the transport behaviors of heavy metals in saturated porous medium. The findings demonstrated that MPs-DOM, particularly humic-like substances containing aromatic structures and various oxygen functional groups, could form stable complexes with heavy metals. This interaction significantly altered the transport capacity of Pb and Cu in saturated porous media. It is noteworthy that MPs-DOM in the free and deposited states in the environment may have markedly disparate effects on heavy metal transport. MPs-DOM in the free state may facilitate the co-migration of heavy metal ions in porous media, thereby enhancing the mobility of heavy metals. In contrast, sedimentary-state MPs-DOM can retain heavy metals in porous media and inhibit their migration through complexation with them.

Insights into the photosensitivity and photobleaching of dissolved organic matter from microplastics: Structure-activity relationship and transformation mechanism

Revealing the structure-activity relationship between physicochemical properties and photoactivities of microplastic dissolved organic matter (MPDOM) is significant for understanding the environmental fate of MPs. Here, we systematically analyzed the physicochemical properties and molecular composition of DOM derived from MPs including polystyrene (PS), polyethylene glycol terephthalate (PET), polyadipate/butylene terephthalate (PBAT), polylactic acid (PLA), polypropylene (PP), and compared their photosensitivity and photobleaching behaviors. Results indicated that PSDOM and PETDOM had more similar properties and compositions, and showed stronger photosensitivity and photobleaching effects than PBATDOM, PLADOM and PPDOM. The [3DOM∗]SS and [1O2]SS varied in the range of 0.31-13.03 × 10-14 and 1.71-5.49 × 10-13 M, respectively, which were within the reported range of DOM from other sources. The SUVA254, HIX, AImodwa, Xcwa and lignin/CRAM-like component showed positive correlation with the [3DOM∗]SS, [1O2]SS and Φ3DOM*. The negative correlation between E2/E3 and [3DOM∗]SS was due to the higher proportion of low-molecular weight components in MPDOM. The lignin/CRAM-like component was identified to be the crucial photobleaching-component. The lignin/CRAM-like in PSDOM showed a deepened oxidation degree, while its change trend in PETDOM was from unsaturated to saturated. These findings provide new insights into the relevant photochemical fate of MPDOM.

Regional differences in lead (Pb) and tetracycline (TC) binding behavior of sediment dissolved organic matter (SDOM): Effects of DOM heterogeneity and microbial degradation

Lake Nansi, primarily dominated by macrophytes, faces threats from heavy metals and antibiotics due to human activity. This study investigated sediment dissolved organic matter (SDOM) characteristics and complexation of lead (Pb) and tetracycline (TC) in barren zone (BZ) and submerged macrophytes zone (PZ). Additionally, a microbial degradation experiment was conducted to examine its impact on the regional variations in complexation. SDOM abundance and protein-like materials in PZ was significantly greater than in BZ, indicating a probable contribution from the metabolism and decomposition of submerged macrophytes. Both zones exhibited a higher affinity of SDOM for Pb compared to TC, with all four components participating in Pb complexation. Protein-like materials in PZ had a higher binding ability (LogKPb=4.19 ± 1.07, LogKTC=3.89 ± 0.67) than in BZ (LogKPb=3.98 ± 0.61, LogKTC=3.69 ± 0.13), suggesting a potential presence of organically bound Pb and TC due to the higher abundance of protein-like materials in PZ. Although microbial communities differed noticeably, the degradation patterns of SDOM were similar in both zones, affecting the binding ability of SDOM in each. Notably, the fulvic-like component C4 emerged as the dominant binding material for both Pb and TC in both zones. Degradation might increase the amount of organically bound TC due to the increase in the LogKTC.

Adsorption of humic acid from different organic solid waste compost to phenanthrene, is fluorescence excitation or quenching?

Humic acid (HA) from different organic solid waste (OSW) compost has been shown good adsorption properties for phenanthrene. However, the raw material of HA can affect its structure, resulting in differences in adsorption capacity. Therefore, this study focused on the adsorption characteristics of phenanthrene by HA from different OSW compost. In this work, chicken manure (CM), rice straw (RS) and lawn waste (LW) were selected as sources of composted HA. The adsorption mechanism of HA from different OSW compost were revealed through analytical techniques including three-dimensional fluorescence spectroscopy (EEM), two-dimensional correlation spectroscopy (2DCOS), and Fourier-transform infrared spectroscopy (FTIR). The results suggested that HA from LW compost had a better adsorption affinity for phenanthrene because of its more complex fluorescent component, where C1 as a simple component determined the adsorption process specifically. Furthermore, after HA from LW compost adsorbed phenanthrene, the increase in aromatic -COOH and -NH was the main reason for fluorescence quenching. These results indicated that HA from LW compost had better adsorption effect for phenanthrene. The results of this study were expected to provide a selection scheme for the control of phenanthrene pollution and environmental remediation.

Composition characteristics and metal binding behavior of macrophyte-derived DOM (MDOM) under microbial combined photodegradation: A state closer to actual macrophytic lakes

In actual lakes, the "unstable components" of macrophyte-derived DOM (MDOM) are always degraded and cannot exist abidingly, but the environmental impact brought by it is ignored. In this study, MDOM from Potamogeton crispus was extracted to carry out microbial combined photodegradation (M-Photodegradation) and fluorescence titration experiments. Then the traits and metal binding reaction of MDOM under M-Photodegradation were analysed and compared with the features of lake-derived DOM (LDOM) from point monitoring of Dongping Lake through EEM-PARAFAC, 2D-SF-COS, and 2D-FTIR-COS. The results showed that the features of MDOM after M-Photodegradation were closer to those of LDOM. The degradation amplitudes were 93.53% ± 0.53% for C4 in microbial degradation and 78.31% ± 0.74% for C3 in photodegradation. Correspondingly, both were hardly detected in LDOM. Protein-like substances and aliphatic C-OH were preferentially selected by Cu2+, while humic-like matter and phenolic hydroxyl O-H responded faster to Pb2+. Although the binding sequences remained unchanged after M-Photodegradation, the LogKCu and LogKPb of components decreased overall, indicating increased environmental risks. This study proves that the refractory MDOM retained after degradation was more consistent with the actual state of macrophytic lakes and provides more information for the treatment of heavy metal pollution in lakes.

Streamlined Multi-Attribute Assessment of an Array of Clinical-Stage Antibodies: Relationship Between Degradation and Stability

Clinical antibodies are an important class of drugs for the treatment of both chronic and acute diseases. Their manufacturability is subject to evaluation to ensure product quality and efficacy. One critical quality attribute is deamidation, a non-enzymatic process that is observed to occur during thermal stress, at low or high pH, or a combination thereof. Deamidation may induce antibody instability and lead to aggregation, which may pose immunogenicity concerns. The introduction of a negative charge via deamidation may impact the desired therapeutic function (i) within the complementarity-determining region, potentially causing loss of efficacy; or (ii) within the fragment crystallizable region, limiting the effector function involving antibody-dependent cellular cytotoxicity. Here we describe a transformative solution that allows for a comparative assessment of deamidation and its impact on stability and aggregation. The innovative streamlined method evaluates the intact protein in its formulation conditions. This breakthrough platform technology is comprised of a quantum cascade laser microscope, a slide cell array that allows for flexibility in the design of experiments, and dedicated software. The enhanced spectral resolution is achieved using two-dimensional correlation, co-distribution, and two-trace two-dimensional correlation spectroscopies that reveal the molecular impact of deamidation. Eight re-engineered immunoglobulin G4 scaffold clinical antibodies under control and forced degradation conditions were evaluated for deamidation and aggregation. We determined the site of deamidation, the overall extent of deamidation, and where applicable, whether the deamidation event led to self-association or aggregation of the clinical antibody and the molecular events that led to the instability. The results were confirmed using orthogonal techniques for four of the samples.

New insights into the fate and interaction mechanisms of hydrolyzed aluminum-titanium species in the removal of aged polystyrene

Polyaluminum-titanium chloride composite coagulant (PATC) has been demonstrated to be a promising coagulant in microplastics (MPs) treatment. However, the interaction process between the dominant species of PATC and MPs remains unclear, which will hinder our understanding of the coagulation mechanisms. Here, the species transformation of PATC during its interaction with aged polystyrene powder (APSp) was studied. The results showed that the rise of O-containing functional groups in APSp increased the possibility of forming C-O-M coordination bonds and hydrogen bonds between APSp and PATC, which improved the removal of PSp. Furthermore, Al13(OH)53Ti13O17(H2O)204+ (Al13Ti13) was considered to be the most effective species of PATC. At pH 4, electrostatic attraction brought Al13Ti13 approached APSp first, followed by hydrogen bonding and complexation occurred, respectively. However, the Al13Ti13-APSp complexes were easily converted to monomers and dimers during coagulation, which influenced the coagulation efficiency. With the increase of pH, OH- in the solution would further polymerize the depolymerized Al2Ti into oligomers and mesomers. Under weakly acid conditions, the diversity of PATC hydrolysates and the increase in APSp binding sites correspondingly led to the maximum APSp removal of 75%. When the pH further increased to 10, PATC interacted with APSp mainly by hydrogen bonding and sweeping effect.

Enhanced Spectral Resolution and Two-Dimensional Correlation Spectroscopy (2D-COS)

The apparent enhancement of spectral resolution is one of the attractive features of two-dimensional correlation spectroscopy (2D-COS). Highly overlapped adjacent bands often encountered in one-dimensional spectra may be effectively differentiated and identified by spreading peaks along the second dimension. This differentiating feature or selectivity is especially prominent in asynchronous spectra, where even a slight difference in the variation patterns of overlapped bands in response to a given perturbation results in the generation of cross-peaks. While cross-peaks in asynchronous spectra can identify signals originating from different moieties or bands, they do not effectively specify which regions of spectra actually share the same molecular origin. Overreliance on asynchronous spectra alone risks the potential false negative assessment or lack of sufficient specificity, leading to the failure of classifying signals into a reasonable set of component groups. The combined use of synchronous and asynchronous spectra coupled with the scaling techniques, elimination of anti-correlated negative synchronous peaks, and a robust line shape narrowing method provides a means to achieve both selectivity and specificity for resolution-enhancement of 2D-COS.

Microcosmic mechanism analysis of the combined pollution of aged polystyrene with humic acid and its efficient removal by a composite coagulant

The composite pollutants formed by aged polystyrene (APS) and natural organic matter are complex and harmful, which lead to the deterioration of water quality. In this work, the interaction mechanism between humic acid (HA) and APS was discussed by investigating the changes in their functional groups. Besides, a novel polyaluminum-titanium chloride composite coagulant (PATC) was prepared, and its binding behaviors with HA@APS under different pH conditions were analyzed from a microscopic perspective. It was found that at pH 4, π-π conjugation was the dominant interaction between HA and APS. And the main removal mechanism of HA@APS by PATC was surface complexation. With the increase of pH, π-π conjugation, n-π electron donor-acceptor interaction (EDA), and hydrogen bonding gradually dominated the interaction between APS and HA. At pH 7, PATC hydrolyzed to form various polynuclear Al-Ti species, which could meet the demand for different binding sites of HA@APS. Under alkaline conditions, HB and n-π EDA in HA@APS were weakened, while π-π conjugation held a dominant position again. At this time, the main coagulation mechanism of PATC changed from charge neutralization to sweeping action, accompanied by hydrogen bonding. ENVIRONMENTAL IMPLICATION: Microplastics (MPs) have attracted the public's attention due to their potential toxicity to humans. The combined pollution of aged microplastics and humic acid (HA) will bring great harm to aquatic environment. The development of novel composite coagulants is hopeful to efficiently remove MPs and their combined pollutants. Elucidating the interactions between HA and aged MPs is helpful to understand the transformation and fate of MPs in actual environments, and to reveal the removal mechanism of composite pollutants by coagulation. The findings presented here will provide theoretical guidance for addressing the challenges of coagulation technology in treating new pollutants in practice.

Rapid Vector-Based Peak Fitting and Resolution Enhancement for Correlation Analyses of Raman Hyperspectra

Spectroscopic peak parameters are important since they provide information about the analyte under study. Besides obtaining these parameters, peak fitting also resolves overlapped peaks. Thus, the obtained parameters should permit the construction of a higher-resolution version of the original spectrum. However, peak fitting is not an easy task due to computational reasons and because the true nature of the analyte is often unknown. These difficulties are major impediments when large hyperspectral data sets need to be processed rapidly, such as for manufacturing process control. We have developed a novel and relatively fast two-part algorithm to perform peak fitting and resolution enhancement on such data sets. In the first part of the algorithm, estimates of the total number of bands and their parameters were obtained from a representative spectrum in the data set, using a combination of techniques. Starting with these parameter estimates, all the spectra were then iteratively and rapidly fitted with Gaussian bands, exploiting intrinsic features of the Gaussian distribution with vector operations. The best fits for each spectrum were retained. By reducing the obtained bandwidths and commensurately increasing their amplitudes, high-resolution spectra were constructed that greatly improved correlation-based analyses. We tested the performance of the algorithm on synthetic spectra to confirm that this method could recover the ground truth correlations between highly overlapped peaks. To assess effective peak resolution, the method was applied to low-resolution spectra of glucose and compared to results from high-resolution spectra. We then processed a larger spectral data set from mammalian cells, fixed with methanol or air drying, to demonstrate the resolution enhancement of the algorithm on complex spectra and the effects of resolution-enhanced spectra on two-dimensional correlation spectroscopy and principal component analyses. The results indicated that the algorithm would allow users to obtain high-resolution spectra relatively fast and permit the recovery of important aspects of the data's intrinsic correlation structure.

Two-Dimensional Clustering of Spectral Changes for the Interpretation of Raman Hyperspectra

Two-dimensional correlation spectroscopy (2D-COS) is a technique that permits the examination of synchronous and asynchronous changes present in hyperspectral data. It produces two-dimensional correlation coefficient maps that represent the mutually correlated changes occurring at all Raman wavenumbers during an implemented perturbation. To focus our analysis on clusters of wavenumbers that tend to change together, we apply a k-means clustering to the wavenumber profiles in the perturbation domain decomposition of the two-dimensional correlation coefficient map. These profiles (or trends) reflect peak intensity changes as a function of the perturbation. We then plot the co-occurrences of cluster members two-dimensionally in a manner analogous to a two-dimensional correlation coefficient map. Because wavenumber profiles are clustered based on their similarity, two-dimensional cluster member spectra reveal which Raman peaks change in a similar manner, rather than how much they are correlated. Furthermore, clustering produces a discrete partitioning of the wavenumbers, thus a two-dimensional cluster member spectrum exhibits a discrete presentation of related Raman peaks as opposed to the more continuous representations in a two-dimensional correlation coefficient map. We demonstrate first the basic principles of the technique with the aid of synthetic data. We then apply it to Raman spectra obtained from a polystyrene perchlorate model system followed by Raman spectra from mammalian cells fixed with different percentages of methanol. Both data sets were designed to produce differential changes in sample components. In both cases, all the peaks pertaining to a given component should then change in a similar manner. We observed that component-based profile clustering did occur for polystyrene and perchlorate in the model system and lipids, nucleic acids, and proteins in the mammalian cell example. This confirmed that the method can translate to "real world" samples. We contrast these results with two-dimensional correlation spectroscopy results. To supplement interpretation, we present the cluster-segmented mean spectrum of the hyperspectral data. Overall, this technique is expected to be a valuable adjunct to two-dimensional correlation spectroscopy to further facilitate hyperspectral data interpretation and analysis.

Molecular in situ monitoring of the pH-triggered response in adaptive polymers by two-dimensional Raman micro-correlation-spectroscopy

Stimuli-responsive polymers can switch specific physical properties in response to a change of the environmental conditions. This behavior offers unique advantages in applications where adaptive materials are needed. To tune the properties of stimuli-responsive polymers, a detailed understanding of the relationship between the applied stimulus and changes in molecular structure as well as the relationship between the latter and macroscopic properties is required, which until now has required laborious methods. Here, we present a straightforward way to investigate the progressing trigger, the change of the chemical composition of the polymer and the macroscopic properties simultaneously. Thereby, the response behavior of the reversible polymer is studied in situ with molecular sensitivity and spatial as well as temporal resolution utilizing Raman micro-spectroscopy. Combined with two-dimensional correlation analysis (2DCOS), this method reveals the stimuli-response on a molecular level and determines the sequence of changes and the diffusion rate inside the polymer. Due to the label-free and non-invasive approach, it is furthermore possible to combine this method with the investigation of macroscopic properties revealing the response of the polymer to the external stimulus on both the molecular and the macroscopic level.

The disinfectant residues promote the leaching of water contaminants from plastic pipe particles

Disinfection treatment is an indispensable water purification process, but it can leave trace concentrations of disinfectant in the purified water. Disinfectants oxidation can age plastic pipes and release hazardous microplastics and chemicals into drinking water. Lengths of commercially-available unplasticized polyvinyl chloride and polypropylene random copolymer water pipe were ground into particles and exposed to micro-molar concentrations of ClO₂, NaClO, trichloroisocyanuric acid, or O₃ for up to 75 days. The disinfectants aged the plastic and changed its surface morphology and functional groups. Meanwhile, disinfectants could significantly promote the release of organic matter from plastic pipes into the water. ClO₂ generated the highest concentrations of organic matter in the leachates from both plastics. Plasticizers, antioxidants and low molecular weight organic matter were detected in all of the leachates. Leachate samples inhibited the proliferation of CT26 mouse colon cancer and induced oxidative stress in the cells. Even trace concentrations of residual disinfectant can constitute a drinking water risk.

Properties and metal binding behaviors of sediment dissolved organic matter (SDOM) in lakes with different trophic states along the Yangtze River Basin: A comparison and summary

The nature of sediment dissolved organic matter (SDOM) can reflect the environmental background, nutritional status and human activities and is an important part of lakes. The differences in the binding capacity of heavy metals and organic matter in lake sediments with different trophic states at the catchment scale and the mechanism of the differences in binding are still unclear. To solve this problem, we collected bulk SDOMs (< 0.7 μm) from 6 respective lakes (from upstream to downstream) in the Yangtze River Basin (YRB) to qualitatively and quantitatively characterize their properties and metal binding behaviors using excitation-emission matrix spectroscopy combined with parallel factor analysis (EEM-FARAFAC) and two-dimensional correlation spectroscopy of synchronous fluorescence spectroscopy and Fourier transform infrared spectroscopy (2D-SF-COS and 2D-FTIR-COS). The results showed that sediment dissolved organic carbon (SDOC) was mainly enriched in low molecular weight (LMW: < 1 kDa) fractions. The total fluorescence intensity (F_max) of SDOM from upstream was larger than that from downstream (p = 0.033), and humic-like fluorophores were dominant in these lakes. The F_max of sediment humic-like components (C1+C2) was closely related to the trophic levels of the lakes. Protein-like substances and oxygen-containing functional groups (C-OH, C=O, and C-O) were preferred in the reaction between SDOM and copper (Cu²⁺) or cadmium (Cd²⁺), while a unique binding path was exhibited in the moderately eutrophic DCL. In terms of fluorophore types, higher Cu²⁺-binding abilities (LogK_Cu) were observed in the humic-like matter for the lakes in the upper reaches and tryptophan-like matter for the lakes from the midstream and downstream areas of the YRB. Although Cd²⁺ complexed only with humic-like matter, LogK_Cd was higher than LogK_Cu. In terms of molecular weight (MW), the LogK_Cu/Cd of components were enhanced after MW fractionation. The HMW (0.7 μm - 1 kDa) components possessed higher LogK_Cu in most lakes (except for CHL and C4). The different fluorophores and molecular weight fractions in SDOM make an important contribution to reducing the ecological risks of heavy metals in lakes.

Insight into the evolution characteristics on molecular weight of compost dissolved organic matters using high-performance size exclusion chromatography combined with a two-dimensional correlation analysis

The information on molecular weight (MW) characteristics of DOM and relevant evolution behaviors during composting are limited. In this study, DOM extracted from co-composting of chicken manure and rice husks were comprehensively analyzed by using high-performance size exclusion chromatography (HPSEC) combined with a two-dimensional correlation spectroscopy (2D COS) to explore the evolution characteristics of MW of compost DOM. The HPSEC detected at UV of 254 nm and at fluorescence (FL) Ex/Em wavelengths (315/410, 270/455 nm) all showed a gradual increase in both weight-average and number-average MW for DOM, suggesting that the large MW fractions were continuously generated and polymerized during composting. The 2D COS applied on HPSEC-UV and -FL further identified the key active MW chromophoric (i.e., 0.5, 7.2. 9.5, 26.3, 30.7, and 83.9 kDa) and fluorophoric (i.e., 0.55 and 3.5 kDa) molecules that mainly participated in the transformation processes of compost DOM. Moreover, these active MW species were preferentially formed by the order of small to large molecules. A hetero-2D COS analysis disclosed the change sequence in the order of 0.5 and 7.2 kDa chromophores → 3.5 kDa fluorophores, and the 0.55 and 3.5 kDa fluorophores → 26.3 and 83.9 kDa chromophores.

Machine learning and deep learning based on the small FT-MIR dataset for fine-grained sampling site recognition of Boletus tomentipes

This study proposed the necessity of identifying the sampling sites for Boletus tomentipes (B.tomentipes) in combination with cadmium content and environmental factors. Based on fourier transform mid-infrared spectroscopy (FT-MIR) preprocessing by 1st, 2nd, MSC, SNV and SG, five machine learning (ML) algorithms (NB, DT, KNN, RF, SVM) and three Gradient Boosting Machine (GBM) algorithms (XGBoost, LightGBM, CatBoost) were built. To avoid complex preprocessing, we construct BoletusResnet model, propose the concepts of 3DCOS, 3DCOS projected images, index images in addition to 2DCOS, and combine them with deep learning (DL) for classification for the first time. It shows that GBM has higher accuracy than ML and DL has better accuracy than GBM. The four DL models presented in this paper achieve fine-grained sampling sites recognition based on small samples with 100 % accuracy, and a computer application system was developed on them. Therefore, spectral image processing combined with DL is a rapid and efficient classification method which can be widely used in food identification.

Pb0 flue gas biosorption in denitrifying MBfR: Characteristics and binding ability of extracellular polymeric substances

Pb⁰ in flue gas which is ubiquitous in the environment, poses a certain threat to human and ecology, but the study on EPS-dependent stabilization of lead to remove Pb⁰ from flue gas remains insufficient. In this investigation, the characteristics and heavy metals-binding ability of four EPS fractions were evaluated. The EPS were extracted from denitrifying membrane biofilm reactor (MBfR) and divided into slime EPS (S-EPS), loosely-bound EPS (LB-EPS), tightly-bound EPS (TB-EPS) and EPS in circulating flow (Y-EPS). The S, LB, TB-EPS related to Pb stabilization on biofilm need more attention. Compared to Pb-S-EPS (0.013 mg g^-1) and Pb-LB-EPS (0.13 mg g^-1), the Pb-TB-EPS (0.26 mg g^-1) was mainly stable form of vapor Pb⁰, since TB-EPS's higher content (30.67-82.44 mg g^-1 VSS), proteins (13.47-36.32 mg g^-1 VSS) and polysaccharides (9.37-32.48 mg g^-1 VSS) concentration. Particularly, proteins related ligands were more effective in S, LB, TB-EPS dependent adsorption of Pb, complexing with hydrophobic acid ligands further strengthened in TB-EPS adsorption. The Pb-EPS complex formed via binding with functional groups (such as O-H, N-H, C-H and CC) on EPS, also facilitated by loose structure of proteins. This study enlightens the researchers on the bio-treatment and EPS-dependent biosorption of Pb⁰ in flue gas in denitrifying MBfR.

Mechanisms of interaction between polystyrene nanoplastics and extracellular polymeric substances in the activated sludge cultivated by different carbon sources

Nanoplastics (NPs) are ubiquitously present in wastewater treatment plants, which would be removed by the flocculation of extracellular polymeric substances (EPS) from activated sludge. However, the interaction mechanisms between NPs and EPS of activated sludge remain largely unexplored. This study investigated the interaction mechanisms between polystyrene nanoplastics (PS-NPs) and EPS with sodium acetate (NaAc), methanol (MeOH) and glucose (GLC) as carbon sources. The results showed that the functional group involved in the interactions between PS-NPs and EPS was the carbonyl of protein amide I region. The interaction between PS-NPs and EPS increased the β-sheets content, decreased the ratio of α-helix to (β-sheet + random coil), and changed the protein secondary structures to strong rigidity. This enhanced the flocculation of activated sludge cultivated by these three carbon sources. The flocculation between PS-NPs and EPS in activated sludge using NaAc as the carbon source was the strongest among these three carbon sources. Therefore, the degree of flocculation between NPs and EPS of activated sludge in wastewater treatment plants varies with carbon sources. This work provides a reference for the NPs removal mechanisms from wastewater, which will help to understand the migration behavior of MPs and NPs in wastewater treatment processes.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS), part I. Yesterday and today

This comprehensive survey review, as the first of three parts, compiles past developments and early concepts of two-dimensional correlation spectroscopy (2D-COS) and subsequent evolution, as well as its early applications in various fields for the last 35 years. It covers past review articles, books, proceedings, and numerous research papers published on 2D-COS. 2D-COS continues to evolve and grow with new significant developments and versatile applications in diverse scientific fields. The healthy, vigorous, and diverse progress of 2D-COS studies in many fields confirms that it is well accepted as a powerful analytical technique to provide the in-depth understanding of systems of interest.

Insight into the Soil Dissolved Organic Matter Ligand-Phenanthrene-Binding Properties Based on Parallel Faction Analysis Combined with Two-Dimensional Correlation Spectroscopy

Dissolved organic matter (DOM) can strongly bind to organic contaminants and control phenanthrene in soil. Herein, four individual parallel factor analysis (PARAFAC) components were found in soil DOM. Component C1 was the humic-like component ligand T, and component C2 was a combination of humic fluorophore ligands M1 and M2. Furthermore, components C3 and C4 were characterized as terrestrial and ubiquitous humic substances. Then, the modified Stern-Volmer complexation model was used to reveal soil DOM component-phenanthrene-binding properties. The overall binding characteristics of a PARAFAC component could not express the phenanthrene-binding properties. Therefore, two-dimensional correlation spectroscopy was used to reveal DOM ligand-phenanthrene-binding properties. After binding with phenanthrene, DOM ligands T, M2, A2, and C1 were quenched but DOM ligands M1, A1, and C2 were excited. The ligands with higher humification presented higher phenanthrene-binding ability. With these promising results, the DOM ligand-phenanthrene-binding characteristics offered theoretical support for soil pollution control.

Interactions between lead(II) ions and dissolved organic matter derived from organic fertilizers incubated in the field

This work was to study composition characteristics and the subsequent effect on the lead (Pb) binding properties of dissolved organic matter (DOM) derived from seaweed-based (SWOF) and chicken manure organic fertilizers (CMOF) during a one-year field incubation experiment using the excitation-emission matrix-parallel factor (EEM-PARAFAC) and two-dimensional correlation spectroscopy (2DCOS) analysis. Results showed that high aromatic and hydrophobic fluorescent substances were enriched in CMOF-derived DOM and SWOF-derived DOM and enhanced over time. And phenolic groups in the fulvic-like substances for SWOF-derived DOM and carboxyl groups in the humic-like substances for CMOF-derived DOM had the fastest responses over time, respectively. Moreover, both non-fluorescent polysaccharides and fluorescent humic-like substances or fulvic-like substances with aromatic (C=C) groups first participated in the binding process of Pb to SWOF-derived DOM on day 0 and 180 during the lead binding process. In contrast, humic-like substances associated with aromatic (C=C) and phenolic groups gave a faster response to Pb binding on day 360. Regarding CMOF-derived DOM, the fulvic-like substances associated with aromatic (C=C) and carboxylic groups displayed a faster response to Pb ions on day 0. Nonetheless, polysaccharides and humic-like associated with phenolic groups had a faster response on days 180 and 360. It is noteworthy that the polysaccharides, which participated in Pb binding to CMOF-derived DOM, posed a higher risk of Pb in the environment after 360 days. Therefore, these findings gave new insights into the long-term applications of commercial organic fertilizers for the amendment of soil.

Characteristics of oxytetracycline stress-sensitive microbe-dissolved organic matter component interactions during composting

Dissolved organic matter (DOM) has important impacts on the transportation of antibiotics through chemical and biological processes in composting. The interaction between DOM and antibiotics is reciprocal. The interaction between DOM ligands and antibiotics could be characterized based on a technique combining parallel factor analysis (PARAFAC) and microbial community structure analysis. However, PARAFAC cannot reveal the dynamic changes in each DOM peak in one PARAFAC component under antibiotic stress. In this study, two-dimensional correlation spectroscopy (2DCOS) combined with PARAFAC and bacterial community diversity analyses were employed to reveal the effects of oxytetracycline (OTC) stress and the key microorganisms on the transformation of different fluorescent peaks from DOM PARAFAC components during chicken manure composting. The results showed that OTC inhibits the transformation between DOM PARAFAC components by inhibiting the core microbial activities involved in the transformation of DOM components. Protein-like components (C1 and C2) were more sensitive to OTC residue, and components with a high humification degree promoted the degradation of OTC. The interaction between special DOM PARAFAC components and certain bacteria affects the degradation of OTC. The DOM PARAFAC components A2(C1), B1(C2), B2(C2) and Z1(C4) enhanced OTC degradation by stimulating the genera Pseudomonas, Glycomyces and Hyphomicrobium. With these promising results, the true effect of DOM PARAFAC components on the degradation of OTC can be revealed, which is helpful for addressing antibiotic contamination to improve the bioavailability of compost products.

Insight into complexation of Cd(II) and Cu(II) to fulvic acid based on feature recognition of PARAFAC combined with 2DCOS

Fulvic acid which could govern the environmental geochemistry behavior of heavy metals is considered as the eco-friendly substances for controlling heavy metal pollutants in environment. Knowledge on the individual fulvic acid ligand is crucial to characterize the effect of fulvic acid on the migration and toxicity of metal pollutants. Herein, fulvic acid substances were analyzed by fluorescence quenching associated with parallel factor analysis (PARAFAC). Three components were identified based on PARAFAC. Furthermore, two-dimensional correlation spectroscopy (2DCOS) associated with complexation model were used to elucidate the Cd(II)- and Cu(II)-binding characteristics of the individual fulvic acid ligand. The Cd(II)- and Cu(II)-binding capability and speed of different fulvic acid ligands were revealed and theoretical guidance and technical support were provided for the practical application. The Cd(II) contaminated soil could be amended with high fulvic acid ligands A1 and Y2 containing composting products and the Cu(II) contaminated soil could be amended with high fulvic acid ligands Y1, T1 and A1 containing composting products to control the pollution and improve the soil condition. Based on these excellent results, the different fulvic acid ligands-contaminants-binding properties was characterized for the theoretical supporting of environmental pollution control.

Regional-scale investigation of the molecular weight distribution and metal-binding behavior of dissolved organic matter from a shallow macrophytic lake using multispectral techniques

In this work, based on excitation-emission matrix spectroscopy combined with parallel factor analysis (EEM-FARAFAC) and two-dimensional correlation analysis of synchronous fluorescence spectroscopy, Fourier transform infrared spectroscopy, and combination of two spectra (2D-SF-COS, 2D-FTIR-COS, and Hetero-2D-COS), the characteristics and metal-binding behaviors of DOM in Dongping Lake were explored for molecular weight (MW), fluorescence components, and functional groups. The results showed that the entire lake was governed by protein-like materials with low MW(< 1 kDa). The complexation occurred preferentially in protein-like materials for bulk DOM after adding copper (Cu²⁺) and lead (Pb²⁺), which were changed by fractionation for MW. The active points were aliphatic C－OH for DOM-Cu and phenol －OH or polysaccharide for DOM-Pb from 2D-FTIR-COS. The protein-like components possessed higher LogK than humic-like component during binding to Cu²⁺ or Pb²⁺. Moreover, the complexing affinities of DOM-Cu (LogK_Cu: 3.26 ± 0.87-4.04 ± 0.49) were higher than those of DOM-Pb (LogK_Pb: 2.66 ± 0.52-3.78 ± 0.36). On a spatial scale, high LogK_Cu and LogK_Pb were found in the center and entrance of the lake, respectively. Humic-like component C2 in the LMW fraction possessed a stronger binding capacity with Cu²⁺. This study affords new insights into the migration and conversion of HMs in lakes.

Interactions between polypropylene microplastics (PP-MPs) and humic acid influenced by aging of MPs

As an emerging pollutant, microplastics (MPs) may interact with dissolved organic matter (DOM) which is prevalent in the aqueous environment. Meanwhile, the aging of MPs in the actual environment increases the uncertainty of their environmental fate. Here, the interaction mechanisms between pristine and aged polypropylene microplastics (PP-MPs) and humic acid (HA) at pH 7.0 were explored. Microstructural changes of HA were examined by fluorescence and Fourier transformation infrared (FT-IR) spectroscopy. Atomic force microscopy coupled with infrared (AFM-IR) and micro-Raman techniques were used to characterize and analyze the interacted PP-MPs. The addition of HA increased the surface roughness of both pristine and aged PP-MPs. Results of AFM-IR and Raman spectra showed that the interaction of PP-MPs with HA accelerated their surface oxidation and enhanced the characteristic signals. XPS spectra showed that the oxygen content ratio of pristine and aged PP-MPs increased by 0.95% and 1.48% after the addition of HA, respectively. PP-MPs after aging interacted more strongly with HA and there was a higher affinity between them. Two-dimensional correlation spectroscopy (2D-COS) combined with FT-IR spectra further elucidated the interaction mechanism at the molecular level. This work will help to evaluate the environmental impact of MPs in ecosystems and understand their interactions with DOM.

Estimating more than two pure component spectra from only two mixture spectra using two-dimensional correlation

A procedure is described to estimate the pure component spectra of mixtures from only a pair of available spectra even when there are more than two component species present in the system. In contrast, traditional multivariate curve resolution (MCR) technique cannot be used for such a case. The method relies on the use of two-trace two-dimensional (2T2D) correlation spectroscopy. Asynchronous 2T2D spectrum is used to identify the characteristic bands most strongly associated with the individual mixture component species. Correlation coefficients derived from the synchronous 2T2D spectrum are used to obtain a set of correlative filtering functions to distribute the spectral intensity of the average spectrum among the estimates of the pure component spectra. Efficacy of the method was demonstrated using a pair of ATR IR spectra obtained for two solution mixtures containing three main ingredients with very similar compositions. Relatively congested and overlapped spectral region was used first for the demonstration, and reasonable resolution was accomplished yielding a set of the estimates of pure component spectra with most of the expected pertinent features included. The analysis was then extended to a broader spectral region containing well-isolated spectral signatures of individual components for positive validation. While traditional MCR technique seems to perform better with a large number of spectra, this technique can be effectively used in conjunction with MCR to improve its stability and performance, especially under some challenging conditions.

Characterization of mercury binding to different molecular weight fractions of dissolved organic matter

Dissolved organic matter (DOM) can strongly complex with various contaminants. Therefore, DOM was deemed as an environmentally friendly substance for controlling the mobility, bioavailability, speciation, toxicity, and fate of metal contaminants in environment. In this study, composting-derived DOM was categorized into three fractions based on different molecular weights (MWs). Furthermore, parallel faction analysis (PARAFAC), two-dimensional correlation spectroscopy (2DCOS), and a complexation model were employed to reveal the contaminate-binding characterization. Two PARAFAC fluorescence components were identified in the MW < 1 kDa and the 1 kDa < MW < 5 kDa fractions, respectively. In the MW > 5 kDa fraction, three PARAFAC components were identified. Protein-like component C5 did not have the Hg²⁺-binding ability. Moreover, the results showed that not all the DOM ligands could bind with contaminants, but a high humification degree of composting DOM ligands could strongly bind Hg²⁺. In addition, DOM ligand with a low humification degree DOM ligands presented a higher Hg²⁺-binding speed. Subsequently, DOM from different MWs DOM could be applied separately to the different pollution forms. With these promising results, the different DOM ligand-Hg²⁺-binding properties were characterized to provide theoretical support for environmental pollution control.

Extracellular polymeric substances mediate defect generation and phytotoxicity of single-layer MoS2

Two-dimensional transition metal dichalcogenide (TMDC) nanomaterials have attracted tremendous research interest in various fields, but the effects of eco-corona formation on the transformation mechanisms and ecological risk of TMDCs remain largely unknown. The effect of eco-corona formation on TMDC reactivity was explored using extracellular polymeric substances (EPS) as the eco-corona constituents and single-layer molybdenum disulfide (SLMoS₂) as the model TMDC. We found that EPS promoted lattice distortion and the formation of defects (sulfur vacancies and pores) on SLMoS₂ after it was aged (precoated) with EPS under simulated visible-light irradiation. In addition, the EPS-corona induced higher free radical (especially hyperoxide radical) photogeneration by SLMoS₂. Furthermore, compared to pristine SLMoS₂, SLMoS₂-EPS exhibited stronger developmental inhibition, oxidative stress, membrane damage, photosynthetic toxicity and metabolic perturbation effects on Chlorella vulgaris. However, the endocytosis pathway (especially macropinocytosis) of SLMoS₂ entry into C. vulgaris was inhibited by EPS. Metabolic and transcriptomic analyses revealed that the enhanced toxicity of SLMoS₂-EPS was associated with the downregulation of fatty acid metabolism and transcription related to photosynthesis, respectively. The present work provides mechanistic insights into the roles of the EPS-corona on the environmental transformation and phytotoxicity of TMDCs, which benefit environmental safety assessments and sustainable applications of engineered nanomaterials.

Multi-spectroscopic investigation of the molecular weight distribution and copper binding ability of dissolved organic matter in Dongping Lake, China

The properties and metal-binding abilities of dissolved organic matter (DOM) rely on its molecular weight (MW) structure. In this study, the spatial differences of DOM in compositions, MW structures, and binding mechanisms with copper (Cu²⁺) in Dongping Lake were investigated by applying excitation-emission matrix combining parallel factor analysis (EEM-PARAFAC), synchronous fluorescence (SF) spectra, two-dimensional correlation spectra (2D-COS), and Fourier transform infrared (FTIR) spectra. The EDOM for the entrance of the Dawen River and PDOM for the macrophyte-dominated region were divided from DOM of Dongping Lake based on hierarchical clustering analysis (HCA) and principal component analysis (PCA) and were size-fractioned into MW < 500 kDa and <100 kDa fractions. According to EEM-PARAFAC, Dongping Lake was dominated by tryptophan-like substances with MW < 500 kDa. The concentration of PDOM was higher than that of EDOM (p < 0.05). 2D-COS showed that protein-like components preceded humic-like components binding to Cu²⁺ regardless of sample type (215 nm > 285 nm > 310-360 nm). The Cu²⁺ binding capacity of DOM exhibited specific differences in space, components, and molecular weights. The humic-like component 1 (C1) and tryptophan-like component 4 (C4) of PDOM showed stronger binding abilities than those of EDOM. Endogenous tryptophan-like component 4 (C4) had a higher binding affinity for Cu²⁺ than humic-like components (logK_a: C4 > C1 > C2) in PDOM irrespective of MW. Humic-like components with MW < 500 kDa displayed higher binding potentials for Cu²⁺. FTIR spectra showed that the main participants of DOM-Cu complexation included aromatic hydrocarbons, aliphatic groups, amide Ⅰ bands, and carboxyl functional groups. This study provides spatial-scale insights into the molecular weight structure of DOM in influencing the behavior, fate, and bioavailability of heavy metals in lakes.

Elevated temperature altered the binding sequence of Cd with DOM in arable soils

Dissolved organic matter (DOM) is one of the most active soil components, which plays pivotal roles in the migration and fate of heavy metals in soils. The interactions of heavy metals with DOM are controlled by the structure and properties of DOM. The changes of temperature have a significant effect on the content and composition of DOM and thus may affect the binding nature of heavy metals with DOM. In the current study, we conducted a 180-d incubation experiment with an arable soil at temperatures of 15, 30 and 45 °C. Fluorescence spectroscopy was used to examine the composition of DOM and two-dimensional correlation spectroscopy was applied to determine the binding intensity and sequence between cadmium (Cd) with DOM. Two humic-like substances (C1, C3) and a protein-like substance (C2) were identified from soil DOM. Elevated temperature changed the characteristic and structure of DOM. The humification degree and aromaticity of DOM increased from 15 °C to 30 °C but decreased at high temperature (45 °C). The alterations in temperature exert no impact on the type of organic functional groups in DOM binding with Cd. However, elevated temperature changed the binding sequence of Cd with DOM fractions. Polysaccharide, phenolic, and aromatic groups exhibited the fastest response to Cd at 15, 30, and 45 °C, respectively. These observations would provide a better understanding on the environmental behavior of Cd in arable soils under the context of global warming.

Investigation of the variations in dissolved organic matter properties and complexations with two typical heavy metals under the influence of biodegradation: A survey of an entire lake

Biodegradation is a key factor determining the properties and metal binding behaviour of dissolved organic matter (DOM). In this study, the contributions of biodegradation to DOM properties and metal binding behaviour in Dongping Lake were explored by using synchronous fluorescence (SF) spectroscopy, two-dimensional correlation spectroscopy (2D-COS) excitation-emission matrix and parallel factor analysis (EEM-PARAFAC). According to the ratio of the fluorescence intensity of different materials to the entire fluorescence intensity (%F_max), protein-like substances were the main substances of DOM in this lake. The reduction of protein-like substances and the enhancement of humification could be found in the whole lake under the influence of biodegradation. 3 areas (Area A, Area B and Area C) were obtained by principal component analysis (PCA), however, PCA results suggested that DOM properties and sources had some differences in the 3 areas, and DOM bioavailability in Area C was stronger than that in the other 2 areas. With copper (Cu²⁺) and lead (Pb²⁺) addition, different substances exhibited various affinities to different metal types. The locations of crosspeaks in asynchronous maps illustrated that protein-like substances were more affiliative with Cu²⁺, while humic-like substances were bound to Pb²⁺ earlier. Biodegradation had a conspicuous impact the metal binding ability of DOM in Dongping Lake. The effective quenching constants (LogK) of protein-like substances (protein-like component 2: LogK_Cu = 3.85 ± 0.23, LogK_Pb = 3.32 ± 0.23) were higher than those of humic-like substances (humic-like component 3: LogK_Cu = 3.15 ± 0.02, LogK_Pb = 2.93 ± 0.17) for both Cu²⁺ and Pb²⁺ before biodegradation. When biodegradation was finished, binding ability of humic-like substances was enhanced from 3.15 ± 0.02 to 3.41 ± 0.10 for DOM-Cu and 2.93 ± 0.17 to 3.79 ± 0.15 for DOM-Pb. On a spatial scale, metal binding ability of DOM in Dongping Lake also changed due to the influence of biodegradation. For both DOM-Cu and DOM-Pb, binding ability in south of Dongping Lake was stronger than that in other areas with the end of biodegradation.

Mechanism and kinetic study of Paal-Knorr reaction based on in-situ MIR monitoring

An in-depth understanding of reaction processes is beneficial to the development and quality control of chemical products. In this work, the mechanism and kinetics of the Paal-Knorr reaction for pyrrole derivatives are thoroughly studied using in-situ Fourier transform infrared (FTIR) spectroscopy. The hemiacetal amine intermediate, reactants, and products were identified and quantified by the treatment of real-time infrared spectra via chemometrics method and two-dimensional correlation spectroscopy (2DCOS) technique. Based on the IR quantitative models, influences of operating conditions on reaction processes were investigated, and the reaction kinetic model was built with kinetic parameters of two rate-limiting reaction steps calculated. This approach of analysis on the in-situ FTIR data demonstrated the ability to extract useful information on reaction components, especially the intermediate spectrum, from the confounding real-time IR data. The in-situ FTIR monitoring combined with the IR analysis methods is proved as a powerful tool for revealing the reaction mechanism and kinetics.

Critical Evaluation of Spectral Resolution Enhancement Methods for Raman Hyperspectra

Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.

The Storage Period Discrimination of Bolete Mushrooms Based on Deep Learning Methods Combined With Two-Dimensional Correlation Spectroscopy and Integrative Two-Dimensional Correlation Spectroscopy

Boletes are favored by consumers because of their delicious taste and high nutritional value. However, as the storage period increases, their fruiting bodies will grow microorganisms and produce substances harmful to the human body. Therefore, we need to identify the storage period of boletes to ensure their quality. In this article, two-dimensional correlation spectroscopy (2DCOS) images are directly used for deep learning modeling, and the complex spectral data analysis process is transformed into a simple digital image processing problem. We collected 2,018 samples of boletes. After laboratory cleaning, drying, grinding, and tablet compression, their Fourier transform mid-infrared (FT-MIR) spectroscopy data were obtained. Then, we acquired 18,162 spectral images belonging to nine datasets which are synchronous 2DCOS, asynchronous 2DCOS, and integrative 2DCOS (i2DCOS) spectra of 1,750–400, 1,450–1,000, and 1,150–1,000 cm^–1 bands. For these data sets, we established nine deep residual convolutional neural network (ResNet) models to identify the storage period of boletes. The result shows that the accuracy with the train set, test set, and external validation set of the synchronous 2DCOS model on the 1,750–400-cm^–1 band is 100%, and the loss value is close to zero, so this model is the best. The synchronous 2DCOS model on the 1,150–1,000-cm^–1 band comes next, and these two models have high accuracy and generalization ability which can be used to identify the storage period of boletes. The results have certain practical application value and provide a scientific basis for the quality control and market management of bolete mushrooms. In conclusion, our method is novel and extends the application of deep learning in the food field. At the same time, it can be applied to other fields such as agriculture and herbal medicine.

Superiority Verification of Deep Learning in the Identification of Medicinal Plants: Taking Paris polyphylla var. yunnanensis as an Example

Medicinal plants have a variety of values and are an important source of new drugs and their lead compounds. They have played an important role in the treatment of cancer, AIDS, COVID-19 and other major and unconquered diseases. However, there are problems such as uneven quality and adulteration. Therefore, it is of great significance to find comprehensive, efficient and modern technology for its identification and evaluation to ensure quality and efficacy. In this study, deep learning, which is superior to conventional identification techniques, was extended to the identification of the part and region of the medicinal plant Paris polyphylla var. yunnanensis from the perspective of spectroscopy. Two pattern recognition models, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM), were established, and the overall discrimination performance of the three types of models was compared. In addition, we also compared the effects of different sample sizes on the discriminant performance of the models for the first time to explore whether the three models had sample size dependence. The results showed that the deep learning model had absolute superiority in the identification of medicinal plant. It was almost unaffected by factors such as data type and sample size. The overall identification ability was significantly better than the PLS-DA and SVM models. This study verified the superiority of the deep learning from examples, and provided a practical reference for related research on other medicinal plants.

Insight into binding characteristics of copper(II) with water-soluble organic matter emitted from biomass burning at various pH values using EEM-PARAFAC and two-dimensional correlation spectroscopy analysis

The metal-binding characteristics of water-soluble organic matter (WSOM) emitted from biomass burning (BB, i.e., rice straw (RS) and corn straw (CS)) with Cu(II) under various pH conditions (i.e., 3, 4.5, and 6) were comprehensively investigated. Two-dimensional correlation spectroscopy (2D-COS) and excitation-emission matrix (EEM) -PARAFAC analysis were applied to investigate the binding affinity and mechanism of BB WSOM. The results showed that pH was a sensitive factor affecting binding affinities of WSOM, and BB WSOMs were more susceptible to bind with Cu(II) at pH 6.0 than pH 4.5, followed by pH 3.0. Therefore, the Cu(II)-binding behaviors of BB WSOMs at pH 6.0 were then investigated in this study. The 2D-absorption-COS revealed that the preferential binding with Cu(II) was in the order short and long wavelengths (237-239 nm and 307-309 nm) > moderate wavelength (267-269 nm). The 2D-synchronous fluorescence-COS results suggested that protein-like substances generally exhibited a higher susceptibility and preferential interaction with Cu(II) than fulvic-like substances. EEM-PARAFAC analysis demonstrated that protein-like (C1) substances had a greater complexation ability than fulvic-like (C2) and humic-like (C3) substances for both BB WSOM. This indicated that protein-like substances within WSOM played dominant roles in the interaction with Cu(II). As a comparison, RS WSOM generally showed stronger complexation capacity than CS WSOM although they exhibited similar chemical properties and compositions. This suggested the occurrence of heterogeneous active metal-binding sites even within similar chromophores for different WSOM. The results enhanced our understanding of binding behaviors of BB WSOM with Cu(II) in relevant atmospheric environments.

Temperature-Dependent Dynamical Evolution in Coum/SBE-β-CD Inclusion Complexes Revealed by Two-Dimensional FTIR Correlation Spectroscopy (2D-COS)

A combination of Fourier transform infrared spectroscopy in attenuated total reflectance geometry (FTIR-ATR) and 2D correlation analysis (2D-COS) was applied here for the first time in order to investigate the temperature-dependent dynamical evolution occurring in a particular type of inclusion complex, based on sulfobutylether-β-cyclodextrin (SBE-β-CD) as hosting agent and Coumestrol (7,12-dihydorxcoumestane, Coum), a poorly-soluble active compound known for its anti-viral and anti-oxidant activity. For this purpose, synchronous and asynchronous 2D spectra were calculated in three different wavenumber regions (960-1320 cm^-1, 1580-1760 cm^-1 and 2780-3750 cm^-1) and over a temperature range between 250 K and 340 K. The resolution enhancement provided by the 2D-COS offers the possibility to extract the sequential order of events tracked by specific functional groups of the system, and allows, at the same time, the overcoming of some of the limits associated with conventional 1D FTIR-ATR analysis. Acquired information could be used, in principle, for the definition of an optimized procedure capable to provide high-performance T-sensitive drug carrier systems for different applications.

Augmented Two-Dimensional Correlation Spectroscopy for the Joint Analysis of Correlated Changes in Spectroscopic and Disparate Sources

Here, we present an augmented form of two-dimensional correlation spectroscopy, that integrates in a single format data from spectroscopic and multiple non-spectroscopic sources for analysis. The integration is affected by augmenting every spectrum in a hyperspectral data set with relevant non-spectroscopic data to permit two-dimensional correlation analysis^(2D-COS) of the ensemble of augmented spectra. A k-means clustering is then applied to the results of the perturbation domain decomposition to determine which Raman peaks cluster with any of the non-spectroscopic data. We introduce and explain the method with the aid of synthetic spectra and synthetic non-spectroscopic data. We then demonstrate this approach with data using Raman spectra from human embryonic stem cell aggregates undergoing directed differentiation toward pancreatic endocrine cells and parallel bioassays of hormone mRNA expression and C-peptide levels in spent medium. These pancreatic endocrine cells generally contain insulin or glucagon. Insulin has disulfide bonds that produce Raman scattering near 513 cm^-1, but no tryptophan. For insulin-positive cells, we found that the application of multisource correlation analysis revealed a high correlation between insulin mRNA and Raman scattering in the disulfide region. In contrast, glucagon has no disulfide bonds but does contain tryptophan. For glucagon-positive cells, we also observed a high correlation between glucagon mRNA and tryptophan Raman scattering (∼757 cm^-1). We conclude with a discussion of methods to enhance spectral resolution and its effects on the performance of multisource correlation analysis.

Copper-binding properties of microplastic-derived dissolved organic matter revealed by fluorescence spectroscopy and two-dimensional correlation spectroscopy

Despite numerous studies on microplastics (MPs), little attention has been paid to the dissolved organic substances leached from MPs and their environmental fate. In this study, we explored the copper-binding characteristics of MP-derived dissolved organic matter (MP-DOM) leached from several MP types, including commercial polypropylene, polyvinylchloride, and expanded polystyrene, under dark and UV irradiation conditions. The copper-binding affinity of MP-DOM was examined using fluorescence quenching method based on different fluorophores identified via the excitation emission matrix-parallel factor analysis (EEM-PARAFAC). The heterogeneous distribution of binding sites across the functional groups of MP-DOM was further elucidated by utilizing two-dimensional correlation spectroscopy (2D-COS) based on Fourier transform infrared spectroscopy (FTIR). Phenol/protein-like fluorescence prevailed in all MP-DOM samples, whereas humic-like fluorescence was more pronounced in the irradiated MP-DOM. For all tested plastic types, two plastic-derived fluorescent components (C2 and C3) exhibited substantial fluorescence quenching with increasing copper concentrations. The calculated stability constants showed larger differences between the two leaching conditions than between the three MP types with higher log K_M values for the UV-irradiated (4.08-5.36) than dark-treated MP-DOM (1.05-3.60). The binding constants were comparable to those of natural organic matter with aquatic/terrestrial origins. The 2D-COS results further revealed that the oxygen-containing structures in MP-DOM generated by UV irradiation might be responsible for the higher binding affinity of the irradiated MP-DOM. This is the first study demonstrating the environmental reactivity of MP-DOM towards metal binding, highlighting the importance of leaching conditions for the metal-binding behavior of MP-DOM.

Analysis of Solid-State Reaction Mechanisms with Two-Dimensional Fourier Transform Infrared Correlation Spectroscopy

The utility of two-dimensional generalized correlation spectroscopy (2D-COS) for tracking complex solid-state reactions is demonstrated using infrared spectra acquired during a photochemically induced decomposition reaction. Eleven different thin films, consisting of six monometallic and five bimetallic 2-ethylhexanoate complexes, were tracked as a function of photolysis time. Overlapping peaks in the infrared fingerprint region are readily discriminated using 2D-COS, enabling individual vibrational components to be used to distinguish whether carboxylate ligands are free/ionic or bound in a chelating, bridging, or monodentate fashion. This classification enables the decomposition mechanism to be tracked for all 11 samples, revealing that ligands bound in monodentate and bridging fashions are first converted to chelates before being lost as volatile products for all samples. The magnitude of the measured first-order rate constants for loss of chelated ligands is found to correlate linearly to the asymmetric stretching frequency of monodentate ligands but exhibits a V shape when plotted against the electronegativity of the metal center. We propose that loss of chelated ligands proceeds via C-O scission for highly electronegative transition metals but M-O scission for transition metals with low electronegativity. These results establish 2D-COS as a powerful tool to deconvolute and correlate individual components, enabling mechanistic analysis of complex chemical reactions.

2D Correlation Spectroscopy (2DCoS) Analysis of Temperature-Dependent FTIR-ATR Spectra in Branched Polyethyleneimine/TEMPO-Oxidized Cellulose Nano-Fiber Xerogels

Fourier transform infrared spectroscopy in attenuated total reflectance geometry (FTIR-ATR), combined with a 2D correlation analysis, was here employed to investigate temperature-induced spectral changes occurring in a particular type of novel cellulosic-based nano-material prepared using 2,2,6,6-tetramethyl-piperidine-1-oxyl (TEMPO) oxidized and ultra-sonicated cellulose nano-fibers (TOUS-CNFs) as three-dimensional scaffolds, and branched polyethyleneimine (bPEI) as cross-linking agent. The aim was to highlight the complex sequential events involving the different functional groups of the polymeric network, as well as to gain insight into the interplay between the amount of bPEI and the resulting sponge-like material, upon increasing temperature. In this framework, synchronous and asynchronous 2D spectra were computed and analyzed in three wavenumber regions (900-1200 cm-1, 1500-1700 cm-1 and 2680-3780 cm-1), where specific vibrational modes of the cellulosic structure fall, and over a T-range between 250 K and 340 K. A step-by-step evolution of the different arrangements of the polymer functional groups was proposed, with particular regard to how the cooperativity degree of inter- and intramolecular hydrogen bonds (HBs) changes upon heating. Information acquired can be useful, in principle, in order to develop a next-generation, T-sensitive novel material to be used for water remediation applications or for drug-delivery nano-vectors.

Developability Assessment of an Isolated CH2 Immunoglobulin Domain

The IgG C_H2 domain continues to hold promise for the development of new therapeutic entities because of its bifunctional role as a biomarker and effector protein. The need for further understanding of molecular stability and aggregation in therapeutic proteins has led to the development of a breakthrough quantum cascade laser microscope to allow for real-time comparability assessment of an array of related proteins in solution upon thermal perturbation. Our objective was to perform a comprehensive developability assessment of three similar monoclonal antibody (mAb) fragments: C_H2, C_H2s, and m01s. The C_H2 construct consists of residues Pro238 to Lys340 of the IgG1 heavy chain sequence. C_H2s has a 7-residue deletion at the N-terminus and a 16-residue C-terminal extension containing a histidine tag. The m01s construct is identical to C_H2s, except for two cysteines introduced at positions 242 and 334. A series of hyperspectral images was acquired during thermal perturbation from 28 to 60 °C for all three proteins in an array. Co-distribution and two-dimensional infrared correlation spectroscopies yielded the mechanism of aggregation and stability for these three proteins. The level of detail is unprecedented, identifying the regions within C_H2 and C_H2s that are prone to self-association and establishing the differences in stability. Furthermore, C_H2 helical segments, β-sheets, β-turns, and random coil regions were less stable than in C_H2s and m01s because of the presence of the N-terminal 3₁₀-helix and β-turn type III. The engineered disulfide bridge in m01s eliminated the self-association process and rendered this mAb fragment the most stable.

Revealing the Inner Dynamics of Fulvic Acid from Different Compost-Amended Soils through Microbial and Chemical Analyses

The formation of fulvic acid (FA), an aromatic compound, is affected by the compost amendment. This study aimed to assess the extent of the humification of FA in soil amended with seven different composts. Results showed that composts improved the FA concentration in soil. Parallel factor (PARAFAC) analysis, combined with hetero-two-dimensional correlation spectroscopy (hetero-2DCOS), indicated that the inner changes in FA components determined the evolution of mineralization. The diversity in the composts used and the dominant microbes present might be responsible for the evolution of different mechanisms of FA transformation. Structural equation models (SEMs) demonstrated that the FA components were transformed directly by microbes, or indirectly via changes in the total organic carbon (TOC) and total nitrogen (TN) contents, C:N ratio, humic substance (HS) levels, and humic acid (HA): FA ratio, which regulate the microbial community structure. Our results will be useful for improving the bioavailability of compost products and realizing sustainable utilization of the soil.