Integrating portable NIR spectrometry with deep learning for accurate Estimation of crude protein in corn feed

This study investigates the challenges encountered in utilizing portable near-infrared (NIR) spectrometers in agriculture, specifically in developing predictive models with high accuracy and robust generalization abilities despite limited spectral resolution and small sample sizes. The research concentrates on the near-infrared spectra of corn feed, utilizing spectral processing techniques and CNNs to precisely estimate crude protein content. Five preprocessing methods were implemented alongside two-dimensional (2D) correlation spectroscopy, resulting in the development of both one-dimensional (1D) and 2D regression models. A comparative analysis of these models in predicting crude protein content demonstrated that 1D-CNNs exhibited superior predictive performance within the 1D category. For the 2D models, CropNet and CropResNet were utilized, with CropResNet demonstrating more accurate and superior predictive capabilities. Overall, the integration of 2D correlation spectroscopy with suitable preprocessing techniques in deep learning models, particularly the 2D CropResNet, proved to be more precise in predicting the crude protein content in corn feed. This finding emphasis the potential of this approach in the portable spectrometer market.

Applying fluorescence spectroscopy coupled with Gaussian band fitting to reveal dynamic variation process of humus fractions from riparian soils along an urbanized river

Humus, an important fraction of soil organic matter, play an environmental role on nutrients, organic and inorganic pollutants in riparian zones of urbanized rivers. In this study, dynamic variation process of humus fractions from riparian soils was revealed along Puhe River. Composite soil samples of four depths were collected from four land-uses, i.e., eco-conservation area (ECA), industrial area (INA), urban/town area (UTA), rural/agricultural area (RAA). Based on synchronous fluorescence spectra coupled with Gaussian band fitting, fulvic/humic acid predominantly contained tyrosine-like (TYLF), tryptophan-like (TRLF), microbial-like (MLF), fulvic-like (FLF) and humic-like (HLF) substances within each soil profile. TRLF, MLF and FLF (89.43-90.30 %) are the representative components in fulvic-acid, while MLF and HLF (52.81-59.97 %) in humic-acid. Phenolic, carboxylic and humified materials were present in both humus. According to 2-dimensitonal correlation spectroscopy and canonical correlation analysis, fulvic/humic acid within the ECA soil profile could be mainly derived from the degradations of terrestrial plant metabolites and residuals. Within the INA, fulvic-acid could be associated with treated/untreated wastewater, which entered the river and flew into the riparian during high flow period; whereas humic-acid could be relative to the terrestrials. Fulvic-acid had the same source as humic-acid in the UTA, which might be concerned with scattered domestic sewage and livestock wastewater, rather than the fluvial water. Furthermore, the source of fulvic/humic acid in the RAA was the crop metabolites and residuals, apart from the livestock wastewater. Noticeably, the variations of humus fractions in the ECA and RAA roughly occurred in 0-60 cm, while approximately in 20-80 cm in the INA and UTA. This proved that humus fractions in the former were referred to the plant/crop residuals, whereas humus fractions in the latter were those the terrestrials and fluvial water. This study could provide a key support for the construction and restoration of the urbanized riparian zone.

Patterns of Cross-Peaks in Two-Dimensional Correlation Spectra to Probe Intermolecular Interactions Described by Two Reversible Reactions

Two-dimensional correlation spectroscopy is used to investigate the intermolecular interaction between two substances dissolved in the same solutions, where the intermolecular interaction is described by two reversible reactions producing two supramolecular aggregates. The severe overlappings expected among the characteristic peaks of the original solute and aggregates make conventional one-dimensional spectra difficult to accurately reflect the physiochemical nature of the intermolecular interaction. The double asynchronous orthogonal sample design (DAOSD) approach is utilized to analyze the simulated data for proof-of-principle demonstration. The patterns of cross-peaks are much more complex compared with the intermolecular interaction described by only a single reaction. Four major groups of cross-peaks with characteristic patterns observed in the pair of DAOSD asynchronous spectra are systematically analyzed and classified. Further analysis of the spectral feature of the cross-peaks of the DAOSD asynchronous spectra is helpful to exact additional information concerning the variation of the peak position and peak width of the aggregates compared with those of the original solute. The result is important to reveal the physicochemical nature of intermolecular interaction between the solutes (e.g., changes in conformation, dynamical behavior, etc.). The pattern of cross-peaks in the corresponding 2D asynchronous spectra may become rather complex when the peak position, peak width, and peak intensity of two supramolecular aggregates change simultaneously. Further work using artificial intelligence techniques to interpret the complex cross-peaks is still being carried out.

Two-Dimensional (2D) Hybrid Method: Expanding 2D Correlation Spectroscopy (2D-COS) for Time Series Analysis

We present a concise report on the two-dimensional (2D) hybrid method, an innovative extension of 2D correlation spectroscopy, tailored for quasar light curve analysis. Addressing the challenge of discerning periodic variations against the background of intrinsic "red" noise fluctuations, this method employs cross-correlation of wavelet transform matrices to reveal distinct correlation patterns between underlying oscillations, offering new insights into quasar dynamics.

Ag(I) Ion-Concentration-Dependent Dynamic Mechanism of Thiolactic-Acid-Capped Gold Nanoclusters Revealed by Fluorescence Spectra and Two-Dimensional Correlation Spectroscopy

Based on fluorescence spectroscopy, being combined with several spectral analysis techniques including principal component analysis (PCA), two-dimensional correlation spectroscopy (2D-COS), and moving window 2D-COS, the study disclosed the structural variations of gold nanoclusters capped by thiolactic acid (AuNCs@TLA) induced by Ag(I) ions. Transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) were applied to monitor the morphology evolution of the surface and composition of the nanoclusters induced by Ag(I) ions. Several spectral components, centered at (790, 607) nm, (670, 590) nm, and (740, 670) nm were revealed by 2D-COS analysis, suggesting new luminescent species or groups were generated with the introduction of Ag(I) ions. A two-stage mechanism was revealed for the photoluminescence variations of AuNCs@TLA induced by Ag(I) ion. The first stage was characterized by the emission quench of 790 nm followed by the emerging emission of 607 nm, which was attributed to the anti-galvanic reaction; and the second stage featured by the noticeable growth of the emission's intensity around 670 nm as result of the AuNCs' size effect. The present study will attract more focuses on near-infrared (NIR)-emitted metal nanoclusters and promote their synthesis and utilities.

Surface Structural Changes in Silicone Rubber Due to Electrical Tracking

There is a growing interest in the use of silicone composite insulators for electrical power transmission and distribution applications. However, such materials are susceptible to degradation as they are exposed to electrical and environmental stresses during operating conditions. Therefore, it is crucial to gain a thorough understanding of the degradation mechanism through changes in the material structure that may provide insight into potential failures in the electrical grid. Attenuated total reflection Fourier transform infrared spectroscopy and two-dimensional correlation spectroscopy (2D-COS) were used along with contact angle measurements to characterize changes in silicone rubber samples from actual insulators subjected to tracking wheel testing. The results showed a decrease in absorbance of different infrared bands representing different functional groups, such as Si-O-Si, methyl functional groups, and both Al-O and hydroxyl groups of alumina trihydrate as a function of the number of tracking cycles. The sequence of changes in the functional groups was determined by 2D-COS as Al-O and OH followed by Si-O-Si polymer backbone modes, followed by polymer methyl side chains. An enhancement in the average contact angle with the number of tracking cycles revealed a concomitant increase in surface roughness with electrical tracking.

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.

The structural transformation reversibility of biogas slurry derived dissolved organic matter and its binding properties with norfloxacin under temperature fluctuation

The widespread use of biogas slurry could potentially raise the environmental risk of antibiotics. Dissolved organic matter (DOM), as the most active part of biogas slurry, was able to interact with antibiotics and play a crucial role in the structure and function of soil and aquatic ecosystems. The recent shifts in global climate patterns have garnered significant attention due to their substantial impact on temperature, thereby exerting a direct influence on the characteristics of DOM and subsequently on the environmental behavior of antibiotics. However, there is limited research concerning the impact of temperature on the binding of DOM and antibiotics. Thus, this study aimed to explore the temperature-dependent structural transformation and driving factors of biogas slurry-derived DOM (BSDOM). Additionally, the binding characteristics between BSDOM and the commonly used antibiotic norfloxacin (NOR) at different temperatures were studied by using multi spectroscopic methods and two-dimensional correlation spectroscopy (2D-COS) analysis. The results suggested that the temperature-dependent structural transformation of BSDOM was reversible, with a slight lag in the transition temperature under cooling (13 °C for heating and 17 °C for cooling). Heating promoted the conversion of protein-like to humic-like substances while cooling favored the decomposition of humic-like substances. BSDOM and NOR were static quenching, with oxygen-containing functional groups such as C-O and -OH playing an important role. Temperature influenced the order of binding, the activity of the protein fraction, and its associated functional groups. At temperatures of 25 °C and 40 °C, the fluorescent components were observed to exhibit consistent binding preferences, whereby the humic-like component demonstrated a greater affinity for NOR compared to the protein-like component. However, the functional group binding order exhibited an opposite trend. At 10 °C, a new protein-like component appeared and bound preferentially to NOR, when no C-O stretch corresponding to the amide was observed. The finding will contribute to a comprehensive understanding of the interaction mechanisms between DOM and antibiotics under climate change, as well as providing a theoretical basis to reduce the environmental risks of biogas slurry and antibiotics.

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.

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.

Two-Dimensional Correlation Spectroscopy (2D-COS) Analysis of Evolving Hyperspectral Images

The evolutionary behavior is examined for heterogeneously distributed hyperspectral images of a simulated biological tissue sample comprising lipid-like and protein-like components during the aging process. Taking a simple planar average of a spectral image loses useful information about the spatially resolved nature of the data. In contrast, multivariate curve resolution (MCR) analysis of a spectral image at a given stage of aging produces a set of loadings of major component groups. Each loading represents the combined spectral contributions of a mixture of similar but not identical constituents (i.e., lipid-like and protein-like components). Temporal analysis of individual component groups using two-dimensional correlation spectroscopy (2D-COS) and MCR provides much-streamlined results without interferences from the overlapped contributions. Grouping of data into separate components also allows for the effective comparison of the parallel processes of lipid oxidation and protein denaturation involving a number of constituents using the heterocomponent 2D-COS analysis. The complex interplays of lipid constituents and protein secondary structures during the tissue aging process are unambiguously highlighted. The possibility of extending this approach to a much more general form of applications using a moving window analysis is also discussed.

Aging behavior of biodegradable polylactic acid microplastics accelerated by UV/H2O2 processes

The usage of biodegradable plastics is expanding annually due to worldwide plastic limits, resulting in a substantial number of microplastics (MPs) particles formed from biodegradable plastic products entering the aquatic environment. Until now, the environmental behaviors of these plastic product-derived MPs (PPDMPs) have remained unclear. In this work, commercially available polylactic acid (PLA) straws and PLA food bags were used to evaluate the dynamic aging process and environmental behavior of PLA PPDMPs under UV/H2O2 conditions. By combining scanning electron microscopy, two-dimensional (2D) Fourier transform infrared correlation spectroscopy (COS) and X-ray photoelectron spectroscopy, it was determined that the aging process of the PLA PPDMPs was slower than that of pure MPs. The 2D-COS analysis revealed that the response orders for the functional groups on the PLA MPs differed during the aging process. The results demonstrated that the oxygen-containing functional groups of the PLA PPDMPs were the first to react. Subsequently, the -C-H and -C-C- structural responses began, and the polymer backbone was ruptured by the aging process. However, the aging of the pure-PLA MPs started with a brief oxidation process and then breakage of the polymer backbones, followed by continuous oxidation. Moreover, compared to the PLA PPDMPs, the pure-PLA MPs exhibited a greater adsorption capacity, which was increased by 88% after aging, whereas those of the two PPDMPs only increased by 64% and 56%, respectively. This work provides new insights into the behaviors of biodegradable PLA MPs in aquatic environments, which is critical for assessing the environmental risks and management policies for degradable MPs.

Complexation of copper algaecide and algal organic matter in algae-laden water: Insights into complex metal-organic interactions

Copper-based algicides have been widely used to suppress algae blooms; however, the release of algal organic matter (AOM) on account of cell lysis may cause significant changes in the mitigation, transformation, and bioavailability of Cu(II). In the present work, the binding characteristics of Cu(II) with AOM were explored via combinative characterization methods, such as high-performance size exclusion chromatography, differential absorption spectra analysis, and joint applications of two-dimensional correlation spectroscopy (2D-COS), as well as heterospectral 2D-COS and moving window 2D-COS analyses of UV, synchronous fluorescence, and FTIR spectra. Carboxyl groups displayed a preferential interaction to Cu(II) binding, followed by polysaccharides. The spectral changes of C]O stretching occur after the change of chromophores in complexation with Cu(II). The AOM chromophores exhibit obvious conformations at Cu(II) concentrations higher than 120 μM, while AOM fluorophores and functional groups exhibit the greatest changes at Cu(II) concentrations lower than 20 μM. All these observations have verified the presence of binding heterogeneity and indicate that AOM could interact with Cu(II) through diverse functional moieties. Therefore, our study contributes to the better understanding of the fate of Cu(II)-AOM complexes in aquatic systems.

A new apparatus and the relevant method to retrieve IR spectra of solutes from the corresponding aqueous solutions

An apparatus and relevant approach to obtaining IR spectra of solutes from the corresponding aqueous solution were developed. In the experiment, aqueous solutions were converted into aerosols using an ultrasonic or a pneumatic device. Subsequently, water in the nebulized solution is completely gasified under a high-speed flow and low vacuum environment. Via this process, the aqueous solution changes into a mixture of a solute or solutes and gaseous water, whose single-beam IR spectra are collected. Then, the newly developed RMF (retrieving moisture-free IR spectrum) method and the relevant approach described in our recent papers have been adopted to treat the resultant single-beam sample spectrum. As a result, the spectral contribution of the vibrational-rotational peaks of gaseous water can be removed or significantly attenuated, and IR spectra of solutes can be obtained. The approach shows an obvious advantage in retrieving the IR spectrum of volatile solutes from its aqueous solution. This capability is showcased by obtaining IR spectra of isopropanol and ethyl acetate successfully. IR spectra of these compounds can be retrieved even if the concentration of the solute is below 10 wt%. Moreover, atomization via ultrasonic/pneumatic methods offers a mild way to gasify solutes whose boiling points are remarkably higher than that of water. This advantage is manifested by acquiring IR spectra of 1-butanol and 1,2-propanediol in the gaseous phase under ambient conditions.

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.

The role of organic and inorganic substituents of roxarsone determines its binding behavior and mechanisms onto nano-ferrihydrite colloidal particles

The retention and fate of Roxarsone (ROX) onto typical reactive soil minerals were crucial for evaluating its potential environmental risk. However, the behavior and molecular-level reaction mechanism of ROX and its substituents with iron (hydr)oxides remains unclear. Herein, the binding behavior of ROX on ferrihydrite (Fh) was investigated through batch experiments and in-situ ATR-FTIR techniques. Our results demonstrated that Fh is an effective geo-sorbent for the retention of ROX. The pseudo-second-order kinetic and the Langmuir model successfully described the sorption process. The driving force for the binding of ROX on Fh was ascribed to the chemical adsorption, and the rate-limiting step is simultaneously dominated by intraparticle and film diffusion. Isotherms results revealed that the sorption of ROX onto Fh appeared in uniformly distributed monolayer adsorption sites. The two-dimensional correlation spectroscopy and XPS results implied that the nitro, hydroxyl, and arsenate moiety of ROX molecules have participated in binding ROX onto Fh, signifying that the predominated mechanisms were attributed to the hydrogen bonding and surface complexation. Our results can help to better understand the ROX-mineral interactions at the molecular level and lay the foundation for exploring the degradation, transformation, and remediation technologies of ROX and structural analog pollutants in the environment.

Identification of Gentian-Related Species Based on Two-Dimensional Correlation Spectroscopy (2D-COS) Combined with Residual Neural Network (ResNet)

Gentian is a traditional Chinese herb with heat-clearing, damp-drying, inflammation-alleviating and digestion-promoting effects, which is widely used in clinical practice. However, there are many species of gentian. According to the pharmacopoeia, Gentiana manshurica Kitag, Gentiana scabra Bge, Gentiana triflora Pall and Gentianarigescens Franch are included. Therefore, accurately identifying the species of gentian is important in clinical use. In recent years, with the advantages of low cost, convenience, fast analysis and high sensitivity, infrared spectroscopy (IR) has been extensively used in herbal identification. Unlike one-dimensional spectroscopy, a two-dimensional correlation spectrum (2D-COS) can improve the resolution of the spectrum and better highlight the details that are difficult to detect. In addition, the residual neural network (ResNet) is an important breakthrough in convolutional neural networks (CNNs) for significant advantages related to image recognition. Herein, we propose a new method for identifying gentian-related species using 2D-COS combined with ResNet. A total of 173 gentian samples from seven different species are collected in this study. In order to eliminate a large amount of redundant information and improve the efficiency of machine learning, the extracted feature band method was used to optimize the model. Four feature bands were selected from the infrared spectrum, namely 3500-3000 cm^-1, 3000-2750 cm^-1, 1750-1100 cm^-1 and 1100-400 cm^-1, respectively. The one-dimensional spectral data were converted into synchronous 2D-COS images, asynchronous 2D-COS images, and integrative 2D-COS images using Matlab (R2022a). The identification strategy for these three 2D-COS images was based on ResNet, which analyzes 2D-COS images based on single feature bands and full bands as well as fused feature bands. According to the results, (1) compared with the other two 2D-COS images, synchronous 2D-COS images are more suitable for the ResNet model, and (2) after extracting a single feature band 1750-1100 cm^-1 to optimize ResNet, the model has the best convergence performance, the accuracy of training, test and external validation is 1 and the loss value is only 0.155. In summary, 2D-COS combined with ResNet is an effective and accurate method to identify gentian-related species.

Course of Plasmodium infection studied using 2D-COS on human erythrocytes

BACKGROUND

The threat of malaria is still present in the world. Recognizing the type of parasite is important in determining a treatment plan. The golden routine involves microscopic diagnostics of Giemsa-stained thin blood smears, however, alternative methods are also constantly being sought, in order to gain an additional insight into the course of the disease. Spectroscopic methods, e.g., Raman spectroscopy, are becoming increasingly popular, due to the non-destructive nature of these techniques.

METHODS

The study included patients hospitalized for malaria caused by Plasmodium falciparum or Plasmodium vivax, in the Department of Infectious Diseases at the University Hospital in Krakow, Poland, as well as healthy volunteers. The aim of this study was to assess the possibility of using Raman spectroscopy and 2D correlation (2D-COS) spectroscopy in understanding the structural changes in erythrocytes depending on the type of attacking parasite. EPR spectroscopy and two-trace two-dimensional (2T2D) correlation was also used to examine the specificity of paramagnetic centres found in the infected human blood.

RESULTS

Two-dimensional (2D) correlation spectroscopy facilitates the identification of the hidden relationship, allowing for the discrimination of Raman spectra obtained during the course of disease in human red blood cells, infected by P. falciparum or P. vivax. Synchronous cross-peaks indicate the processes taking place inside the erythrocyte during the export of the parasite protein towards the cell membrane. In contrast, moieties that generate asynchronous 2D cross-peaks are characteristic of the respective ligand-receptor domains. These changes observed during the course of the infection, have different dynamics for P. falciparum and P. vivax, as indicated by the asynchronous correlation cross-peaks. Two-trace two-dimensional (2T2D) spectroscopy, applied to EPR spectra of blood at the beginning of the infection, showed differences between P. falciparum and P. vivax.

CONCLUSIONS

A unique feature of 2D-COS is the ability to discriminate the collected Raman and EPR spectra. The changes observed during the course of a malaria infection have different dynamics for P. falciparum and P. vivax, indicated by the reverse sequence of events. For each type of parasite, a specific recycling process for iron was observed in the infected blood.

Molecular size-dependent compositions and lead (II) binding behaviors of two origins of organic fertilizers-derived dissolved organic matter

The application of organic fertilizers caused large amounts of dissolved organic matter (DOM) entering the soil environment and influencing the behaviors and fates of heavy metals. Here, we investigated the molecular weight-dependent (high molecular weight [HMW], 1 kDa-0.7 µm; low molecular weight [LMW], <1 kDa) compositions and lead (Pb) binding behaviors of DOM derived from sheep manure-based (SMOF) and shrimp peptide-based organic fertilizers (SPOF) using chromophoric and fluorescent spectroscopy, Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and two-dimensional correlation spectroscopy (2D-COS). Results showed that SMOF released more DOM with higher aromaticity and hydrophobicity, containing more fluvic-like components, carboxylic-rich alicyclic molecules (CRAMs) and lignin phenolic compounds compared to SPOF-DOM with more microbially-transformed heteroatom-containing compounds (CHON, CHONS and CHOS). Furthermore, there was more aromatic compounds with ample carboxyl and hydroxyl groups in HMW-DOM but abundant protein-like components and heteroatom-containing compounds (CHONS and CHOS) in LMW-DOM. SMOF-DOM exhibited more obvious MW-dependent heterogeneity in molecular components compared to SPOF-DOM with higher molecular diversity. Moreover, 2D-COS indicated phenol and carboxyl groups in SMOF-DOM and polysaccharides in SPOF-DOM exhibited superior binding affinities for Pb. Pb binding to HMW-DOM derived from SMOF first occurred in the phenolic groups in fulvic-like substances, while polysaccharides in LMW-DOM first participated in the binding of Pb. In contrast, irrespective of MWs, polysaccharides and humic-like substances with aromatic (CC) groups in SPOF-DOM displayed a faster response to Pb. Furthermore, the polysaccharides which preferentially participated in the binding of Pb to SPOF-DOM and SMOF-derived LMW-DOM may pose a higher risk of Pb in the environment. These results were helpful to understand the effects of sources and size-dependent compositions of DOM on the associated risks of heavy metals in the environments.

Competitive adsorption of lead and cadmium onto nanoplastics with different charges: Two-dimensional correlation spectroscopy study

The competitive adsorption ability and mechanisms of lead (Pb²⁺) and cadmium (Cd²⁺) by nanoplastics (NPs) with positive charges (PS-NH₂) and negative charges (PS-SO₃H) were investigated by using batch adsorption experiments coupled with the two-dimensional correlation spectroscopy (2D-COS) method. The adsorption isotherm results showed that PS-SO₃H exhibited a higher adsorption capacity for Pb²⁺ or Cd²⁺ compared to PS-NH₂. The adsorption affinity of NPs for Pb²⁺ was higher than that of Cd²⁺. The competitive adsorption results showed that Pb²⁺ had a more pronounced negative effect on the adsorption of Cd²⁺. The adsorption capacities of NPs were affected by the surface charge and solution pH. Electrostatic force was the main factor influencing PS-SO₃H to capture Pb²⁺ and Cd²⁺, while chelation was the main mechanism between PS-NH₂ and metals. The functional groups of NPs played significant roles in the sorption of Pb²⁺ or Cd²⁺ according to the FTIR spectra and 2D-COS analysis. This study provided new insights into the impact of NPs on the transport of other pollutants.

Ozonation facilitates the aging and mineralization of polyethylene microplastics from water: Behavior, mechanisms, and pathways

Microplastics (MPs) are ubiquitous in the environment, of which 94 % undergo the aging process. Accelerated aging induced by advanced oxidation processes (AOPs) is significant in explaining the formation pathway of secondary MPs and enables possible mineralization. In this study, ozonation coupled with hydrogen peroxide (O₃/H₂O₂), a type of AOPs, was applied for the aging of MPs (polyethylene, PE). Physiochemical properties of aged PE MPs were analyzed through scanning electron microscope, Fourier-transform infrared spectroscopy-attenuated total reflection, and X-ray photoelectron spectroscopy. The mechanism regarding the contribution of reactive oxygen species (•OH) was determined using chemical probe (p-chlorobenzoic acid) and quencher (tert-butanol). Possible transformation pathways were modeled via two-dimensional correlation spectroscopy. Mineralization of MPs, associated with aging was also studied, with the percentage of PE degradation determined by mass loss. Our results confirmed that ozonation promoted fragmentation of PE, with 20 mM H₂O₂ facilitating the production of •OH. The growth of oxygen-containing functional groups on the surface of PE was consistent with the alteration of the oxygen-to‑carbon atom ratio, revealing the formation of CO, CO, and C-O-C. The enhanced adsorption property of aged PE for triclosan was due to the increased specific surface area and negative charges on the surface. Moreover, the percentage of PE degradation was higher at lower concentrations, and the mass loss reached 32.56 % at a PE concentration of 0.05 g/L after 8-h ozonation. These results contribute to revealing the long-term aging behavior of MPs and providing significant guidance for employing AOPs to achieve efficient removal.

Comprehensive modified approaches to reducing the interference of moisture from an FTIR spectrum and the corresponding second derivative spectrum

We proposed a modified and improved approach to removing the interference of moisture from an IR spectrum and the corresponding second derivative spectrum. The temperature fluctuation in the air of the optical path and baseline-drift lead to the small but persistent presence of the interference of moisture. The problem has been successfully addressed by adopting a double-matching strategy. Additionally, two-dimensional correlationspectra (2D-COS) are generated using the second derivative or third derivative spectrum of the negative base 10 logarithms of the single-beam spectra, thereby removing the linear slope or quadratic portion of baseline-drift. Using the newly adopted approach, the residual interferences of moisture are attenuated. We applied the new approach to the IR spectra and the second derivative spectra of neat hexadecanol and biaxially oriented polypropylene (BOPP) film, and some promising preliminary results are obtained. In hexadecanol, two highly overlapping peaks at 1464 and 1463 cm^-1 are revealed. In BOPP, the envelope at 1458 cm^-1 is found to be composed of a number of sub-peaks.

Assessment of relationship between aging and contaminant-carryover for different filter layer of surgical mask under urban environmental stressors

Abundant disposable surgical masks (SMs) remain in the environment and continue to age under urban environmental stressors. This study aimed to investigate the aging characteristics of SMs and the effect of different aged layers of SMs on phenanthrene (PHE), tylosin (TYL), and sulfamethazine (SMT) under two different urban environmental stressors (UV and ozone). The results show that UV exposure causes more severe aging of the SM layers than ozone. The middle layer, made of melt-brown fabric, has displayed the highest degree of aging due to its smaller diameter and mechanical strength. The two-dimensional correlation spectroscopy (2D-COS) analysis reveals the different aging sequences of functional groups and three layers in aged SMs under the two urban environmental stressors. Whether the SMs are aged or not, the adsorptions of three organic pollutants on SMs are positively correlated with the octanol-water partition coefficient. Furthermore, except for the dominant hydrophobic interaction, aged SMs can promote the adsorption of three organic pollutants by accessory interactions (hydrogen bonding and partition), depending on their structures. These findings highlight the environmental effects of new microplastic (MP) sources and coexisting pollutants under the influence of COVID-19, which is helpful in accurately evaluating the biological toxicity of SMs.

Recent noteworthy developments

This comprehensive survey review compiles noteworthy developments and new concepts of two-dimensional correlation spectroscopy (2D-COS) for the last two years. It covers review articles, books, proceedings, and numerous research papers published on 2D-COS, as well as patent and publication trends. 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 strongly confirms that it is well accepted as a powerful analytical technique to provide an in-depth understanding of systems of interest.

Versatile applications

In this review, the comprehensive summary of two-dimensional correlation spectroscopy (2D-COS) for the last two years is covered. The remarkable applications of 2D-COS in diverse fields using many types of probes and perturbations for the last two years are highlighted. IR spectroscopy is still the most popular probe in 2D-COS during the last two years. Applications in fluorescence and Raman spectroscopy are also very popularly used. In the external perturbations applied in 2D-COS, variations in concentration, pH, and relative compositions are dramatically increased during the last two years. Temperature is still the most used effect, but it is slightly decreased compared to two years ago. 2D-COS has been applied to diverse systems, such as environments, natural products, polymers, food, proteins and peptides, solutions, mixtures, nano materials, pharmaceuticals, and others. Especially, biological and environmental applications have significantly emerged. This survey review paper shows that 2D-COS is an actively evolving and expanding field.

Impacts of algal organic matter and humic substances on microcystin-LR removal and their biotransformation during the biodegradation process

The application of bioaugmentation (i.e., injection of contaminant-degrading microorganisms) has shown its potential to remove harmful cyanotoxins like microcystin-LR (MC-LR) from drinking water sources. However, the natural organic matter (NOM) present in both natural and engineered water systems might affect the bacterial biodegradation of MC-LR. Therefore, for the successful application of bioaugmentation for MC-LR removal in water treatment, it is important to understand NOM effects on MC-LR biodegradation. In this study, the impact of NOM [algal organic matter (AOM) and humic substances (HS)] on MC-LR biodegradation was evaluated in the presence of varying concentrations of NOM by monitoring MC-LR biodegradation kinetics. The changes in NOM composition during MC-LR biodegradation were also characterized by a five-component Parallel factor (PARAFAC) model using 336 excitation-emission matrix (EEM) spectra collected at different sampling points. Our results showed decreases in MC-LR biodegradation rate of 1.6-and 3.4-fold in the presence of AOM and HS, respectively. The expression of the functional mlrA gene exhibited a similar trend to the MC-LR degradation rate at different NOM concentrations. EEM-PARAFAC analyses and NOM molecular size fractionation results indicated a relatively greater production of terrestrial humic-like components (57%) and a decrease of protein-like components. Two-dimensional correlation spectroscopy (2D-COS) analyses further confirmed that low molecular weight protein-like components were initially utilized by bacteria, followed by the formation of higher molecular weight humic-like components, likely due to microbial metabolism.

NH2-MIL-101(Fe) nanozyme-based dual-modality sensor for determination of alendronate sodium and study of two-dimensional correlation spectroscopy

We developed a dual-modality sensing platform for ratiometric fluorescence and colorimetric determination of alendronate sodium (ALDS). This platform was performed by using a NH₂- MIL-101(Fe) as a peroxidase mimic. Since preferential complexing between Fe³⁺ (active site for peroxidase) and ALDS, the production of 2,3-diaminophenazine (DAP, oxidized product of OPD) has been inhibited in the presence of H₂O₂. As a result, the ratiometric fluorescence value of F₅₅₆/F₄₅₆ and absorbance at 450 nm exhibited significant changes, which could be used as the dual-modality sensing platform. In addition, Two-dimensional correlation spectroscopy (2D-COS) analysis on Fourier-transform infrared (FTIR), ultraviolet visible and ratiometric fluorescence spectra were applied to investigate the binding features. Synchronous and asynchronous maps of these spectra confirmed our above hypothesis, in which Fe³⁺-ALDS complex was the critical factor that regulated dual-modality signals. To our knowledge, the 2D-COS method was applied to study the catalytic and sensing mechanism of nanozyme as NH₂- MIL-101(Fe) for the first time. This technique was helpful to understand interaction of substrates on nanozyme and develop more sensitive sensors for assaying.

Exploring the use of infrared absorption spectroscopy and two-trace two-dimensional correlation analysis for the resolution of multi-component drug mixtures

Community drug checking provides an essential service that responds to the unpredictable and variable supply of illicit drugs. Point of care detection of trace components using portable infrared spectrometers is a harm reduction measure to prevent overdose. This study investigates the ability of weighted subtraction and two-trace two-dimensional (2T2D) correlation analysis to reveal the presence of heroin in an opioid mixture that contains heroin and fentanyl mixed with caffeine as a cutting agent. In both methods, a spectral trace was identified that provided reasonably high correlation scores to heroin when compared to entries in drug libraries. The two-trace correlation analysis produced a higher match score, suggesting that future improvements in spectral unmixing methods may enhance the reliability of detecting trace components in drugs.

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.

Two-trace two-dimensional (2T2D) correlation applied to a number of spectra beyond a simple pair

The application of two-trace two-dimensional (2T2D) correlation analysis to a number of spectra consisting of more than a simple pair is explored, especially when such spectra are randomly collected without knowing the sampling order. Calculation and interpretation of 2T2D correlation spectra are briefly reviewed, and a systematic procedure to identify the set of characteristic bands, which are mutually asynchronous and least overlapped with each other, is described. 2T2D correlation is applied to individual spectra by selecting a representative reference spectrum, such as the average of the whole dataset. A slice of an asynchronous 2T2D spectrum at a characteristic band is devoid of the spectral contribution from the species represented by the band. Since 2T2D analysis may be applied to the whole set of spectra, and each 2T2D asynchronous spectrum yields a set of slices for different characteristic bands, it is possible to generate a series of 2T2D slices obtained at a given characteristic band. By applying the generalized 2D correlation or a successive 2T2D analysis to such slices, one can obtain excellent estimates of the pure component spectra of the mixture, which are comparable to the results from other curve resolution techniques.

Novel insights into the interaction reactive components and synergistic fouling mechanisms of ultrafiltration by natural organic matter fractions and kaolin

The mechanisms governing interactions among various natural organic matter (NOM) fractions and the subsequently impact on ultrafiltration process have not been systematically studied. In this work, bovine serum albumin (BSA), humic acid (HA), sodium alginate (SA) were applied as model NOM to explore the influence of the interactions among NOM on ultrafiltration process. Results indicated that tryptophan-like fluorescence fraction was the dominant reaction fraction of HA to react with SA and BSA. Different interactions among model NOM not only changed the interception order of fluorescence fractions by ultrafiltration from fulvic acid-like, humic-like and tryptophan-like in BSA/HA mixture to tryptophan-like, humic-like and fulvic acid-like in BSA/HA/SA/kaolin mixture, but also remarkably influence the membrane fouling behavior. In BSA/HA mixture, new-generated aggregates with molecular weight (MW) of 10 kDa could not pass though ultrafiltration membrane and mainly contributed to chemical reversible fouling. In BSA/HA/SA mixture, SA simultaneously reacted with BSA and HA to generate aggregates with larger MW which could be washed down by physical cleaning. In BSA/HA/SA/kaolin mixture, the aggregates with MW of 10 kDa and chemical reversible fouling were disappeared due to the adsorption role of kaolin. These findings could further improve our understanding regarding membrane fouling mechanisms of raw water with different components.

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.

Exposed facets mediated interaction of polystyrene nanoplastics (PSNPs) with iron oxides nanocrystal

Nanoplastics (NPs), which are often detected in the natural environment, are regarded as a group of emerging pollutants. Hematite is a substance that exists widely in the surface environment and has an important impact on the environmental behavior of pollutants. Clarifying the migration of NPs requires an in-depth understanding of intrinsic interaction mechanisms of NPs with iron-containing minerals. The interaction process of polystyrene nanoplastics (PSNPs) on the hematite exposed facets was systematically studied by experiments under different conditions, adsorption isotherm curves, Fourier Transform infrared (FTIR) spectroscopy and two-dimensional correlation spectroscopy (2D-COS) analyses. We found that PSNPs were adsorbed on the three exposed faces of hematite ({001}, {012}, and {100}) by electrostatic interaction, respectively, but the capacities for PSNPs were different. Adsorption models were established to explore the preferred interaction surface dependent on the exposed facets, and it was found that {012} surfaces were more favorable for PSNPs adsorption, while {001} surface has better adsorption capacity for PSNPs than {100} surface, which is due to the different density and proportion of hydroxyl groups on the exposed facets of hematite. These findings elucidated the dependence of PSNPs adsorption on the hematite facets, and illustrated t the effect of hematite on the migration of PSNPs in the environment.

Assessing the quality of stored red blood cells using handheld Spatially Offset Raman spectroscopy with multisource correlation analysis

In this work we employ Spatially Offset Raman Spectroscopy (SORS) to non-invasively identify storage-related changes in red blood cell concentrate (RCC) in-situ within standard plastic transfusion bags. To validate the measurements, we set up a parallel study comparing both bioanalytical data (obtained by blood-gas analysis, hematology analysis and spectrophotometric assays), and Raman spectrometry data from the same blood samples. We then employ Multisource Correlation Analysis (MuSCA) to correlate the different types of data in RCC. Our analysis confirmed a strong correlation of glucose, methemoglobin and oxyhemoglobin with their respective bioassay values in RCC units. Finally, by combining MuSCA with k-means clustering, we assessed changes in all Raman wavenumbers during cold storage in both RCC Raman data from the current study and parallel RCC supernatant Raman data previously acquired from the same units. Direct RCC quality monitoring during storage, would help to establish a basis for improved inventory management of blood products in blood banks and hospitals based on analytical data.

Process monitoring of photocatalytic degradation of 2,4-dinitrotoluene by Au-decorated Fe3O4@TiO2 nanoparticles: surface-enhanced Raman scattering method

Recently, the degradation and detection of 2,4-dinitrotoluene (2,4-DNT) capable of producing 2,4,6-trinitrotoluene (TNT) for environmental and human health risks have been developed. We prepared photoresponsive Au-decorated Fe₃O₄@TiO₂ nanoparticles (Fe₃O₄@TiO₂-Au NPs) under sunlight simulated Xe lamp irradiation. The photodegradation process of 2,4-DNT by Fe₃O₄@TiO₂-Au NPs was successfully monitored by surface-enhanced Raman scattering (SERS). Since SERS monitoring shows intrinsic information about the molecular structure, it was possible to predict the photodegradation of 2,4-DNT. The 2,4-DNT photodegradation mechanism based on two-dimensional correlation spectroscopy (2D-COS), which provides very beneficial information for a deeper understanding of systems, has been identified. We confirmed that Fe₃O₄@TiO₂-Au NPs can be widely used in organic pollutant degradation under sunlight. Furthermore, the combination of SERS based process monitoring and 2D-COS can be a convincing analytical technique for photodegradation studies of organic pollutants.

Comparison of the binding interactions of 4-hydroxyphenylpyruvate dioxygenase inhibitor herbicides with humic acid: Insights from multispectroscopic techniques, DFT and 2D-COS-FTIR

4-Hydroxyphenylpyruvate dioxygenase (HPPD) inhibitor is one of the important herbicides to solve the problem of weed control. With the widespread and continued use of HPPD inhibitor (HPPDi) herbicides, it may inevitably put pressure on the environment. Humic acid (HA) can effectively interact with pesticides through sorption or covalent bond formation and promote the degradation of pesticides, which can reduce the risk of pesticides in the environment. In the present study, the interactions of four HPPDi herbicides (sulcotrione, tembotrione, topramezone and mesotrione) with HA were reported and comparative assessment of the binding using multispectral technology, density functional theory (DFT) calculation and two-dimensional correlation spectroscopy (2D-COS). Time-resolved measurements and the Stern-Volmer constant at different temperature verified that HPPDi can bind with HA through the static quenching mechanism. From the thermodynamic parameters, the interaction force between HA and sulcotrione, tembotrione, topramezone and mesotrione was provided by electrostatic force. DFT, binding constant and three-dimensional (3D) fluorescence peak variation all indicated that the order of the binding ability of the four HPPDi and HA was mesotrione > tembotrione > sulcotrione > topramezone. According to dynamic light scattering (DLS), pH 7 is most conducive to the formation of HA-HPPDi complexes. Fourier transform infrared spectroscopy (FTIR) and 2D-COS showed that HA combined with HPPDi through aromatic C-H, CO and C-X, and the first binding group to HA was almost all CO. Sulcotrione, tembotrione, topramezone and mesotrione quench the endogenous fluorescence of HA by a static quenching mechanism and bind to HA through electrostatic interaction to form a complex. These results provide important insights into the combination of environmental pollutants with HA.

A Component Content Measurement Method Modified Using Indirect Hard Modeling for Polymer Blends Based on Raman Spectroscopy

Raman spectroscopy has been proven to be useful for the component content measurement of polymer blends. However, the soft modeling methods commonly used in quantitative analysis of Raman spectroscopy require a large number of training samples, resulting in a waste of materials and time. This work adopted a modified indirect hard modeling (IHM) method to measure the component content of polymer blends based on Raman spectroscopy. The Raman spectra of polypropylene (PP)/polystyrene (PS) blends with different component content were collected and resolved into the sum of multiple Voigt peak functions. For a large number of peak parameters, the two-dimensional correlation spectroscopy was used to screen out the characteristic Voigt peaks highly correlated with component content to reduce the parameter dimensions and build the parameterized spectral models. The spectral model of the blend was expressed as the weighted sum of the pure component spectral models, during which the parameters of the pure component models were adjusted within a range. According to the relationship between the weight and content of the pure component, a linear regression model for component content prediction was established. The coefficient of determination (R²)/root mean squared error of the IHM component content prediction model was 0.9931/0.4367 wt%. Besides, two popular soft modeling methods, partial least squares and artificial neural network, were compared with the IHM method, which showed that the IHM model had higher prediction accuracy with fewer training samples.

Random swapping, an effective and efficient way to boost the intensities of cross peaks in a 2D asynchronous spectrum

Analysis of mixture via chromatographic-spectroscopic and analogous experiments is a common task in analytical chemistry. A 2D/nD asynchronous spectrum is effective in retrieving spectra of pure substances even if different components cannot be separated. However, noise in the 2D/nD asynchronous spectrum becomes a bottleneck in the analysis. Finding a suitable sequence of the 1D spectra used in constructing the 2D/nD asynchronous spectrum is helpful to improve the signal-to-noise level. A 2D/nD asynchronous spectrum is often produced via a large number of 1D spectra. The resultant colossal number of the possible sequences makes stochastic search the only possible way to find a suitable sequence. Random changing (RC) and random swapping (RS) are two ways to obtain a new sequence. We found that the possibility of finding a better sequence via an RS is significantly higher than that via an RC in the advanced stage of stochastic searching. This is the reason why the performance of RS is superior to that of RC in two model systems where 2D asynchronous spectra are used. We applied the RS approach on the analysis of water/isopropanol mixtures, and satisfactory sequences are acquired with affordable computational cost. Thus, the RS approach brings about an opportunity increase the signal-to-noise level of a 2D asynchronous spectrum in the analysis of the bilinear data from complex mixed samples.

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.

FT-IR and synchronous fluorescence two-dimensional correlation spectroscopic analysis on the binding properties of mercury onto humic acids as influenced by pH modification and sulfide addition

Mercuric Hg²⁺ ion forms strong complexes with dissolved organic matter (DOM) in natural waters. The complexation of Hg²⁺ by sulfhydryl groups of DOM was regarded as the main mechanism for Hg²⁺-DOM interactions, particularly in anoxic sulfur and DOM-rich environments. In the present study, the influences of pH and sulfide addition on the molecular structure of Hg²⁺-DOM complexes and the characteristics of Hg²⁺ binding to DOM were investigated using FT-IR and synchronous fluorescence two-dimensional correlation spectroscopic analysis. Results showed that, during the Hg²⁺ binding process, the aromatic hydrogen CH in humic acids (HA) gave the fastest responses to pH perturbation and the S-reacted HA (S-HA) exhibited different reaction patterns from the unreacted HA. In S-HA, the esters/alcohols CO and carboxyl CO gave the fastest responses to Hg²⁺ binding. In the process of S-HA binding to Hg²⁺, the protein-like fractions including proteins, amino acids or monoaromatics played the leading role. Sulfide addition of HA enhanced the reactivity of small molecular weight compounds with low aromaticity and improved the binding ability of protein-like fractions to Hg²⁺. These findings provide a better understanding of the interaction mechanisms between Hg²⁺ and DOM at a molecular level and have important environmental implications in Hg²⁺ biogeochemical transformation, transport and cycling.

Smart Error Sum Based on Hybrid Two-Trace Two-Dimensional (2T2D) Correlation Analysis

Based on hybrid 2D correlation analysis, we recently derived and introduced a "smart error sum," a sophisticated loss function that can be used for solving nonlinear inverse problems like the determination of optical constants and oscillator parameters from a series of optical spectra in the infrared spectral region. The advantage of the smart error sum compared to the conventional sum of squared errors lies in its ability to marginalize multiplicative systematic errors such as, for example, reflectance values above unity in transflection spectra. This is enabled by a transformation, which allows fits to not exclusively focus on forcing fit spectra to agree with experimental spectra at every wavenumber point by all means, but also to take correlations such as spectral similarities and their changes with certain perturbations into account. In this work, we extend our approach to accommodate the treatment of individual spectra, instead of only series, based on hybrid two-trace two-dimensional (2T2D) correlation analysis. We evaluate and prove the value of our approach by individually analyzing experimental transflection spectra of polymethyl methacrylate (PMMA) layers on gold substrates. The comparison of the results with those obtained by the original smart error sum based on the whole set of spectra as well as those resulting from conventional fitting of series and individual spectra (using the conventional sum of squared errors) confirms the validity and soundness of the 2T2D smart error sum.

A new approach to removing interference of moisture from FTIR spectrum

An approach is developed to remove the interference of moisture from FTIR spectra. The interference arises from two aspects: the fluctuation on the temperature of the HeNe laser and the fluctuation on the transient concentration of moisture in the light - path of an FTIR spectrometer. The temperature fluctuation on the HeNe laser produces a systematic spectral shift between single-beam sample and background spectra, which often makes spectral subtraction method invalid in removing the interference of moisture. Herein, the Carbo similarity metric (the C_AB value) is used to reflect the subtle spectral shift. A database of single-beam background spectra is established based on the concept of big-data and the pigeon-hole theory. The spectral shift is corrected by selecting suitable single-beam background spectra from the database to match with the given single-beam sample spectrum according to the C_AB value. The interference caused by the fluctuation of the transient concentration of moisture is removed using a comprehensive 2D-COS method. We apply the approach on two polymeric samples to retrieve high-quality spectra and reliable second derivative spectra without the interference of moisture. The present work provides a new opportunity of obtaining the reliable second derivative spectra in the spectral region masked by moisture.

The photodegradation processes and mechanisms of polyvinyl chloride and polyethylene terephthalate microplastic in aquatic environments: Important role of clay minerals

It is well known that microplastics (MPs) may experience weathering and aging under ultraviolet light (UV) irradiation, but it remains unclear if these processes are impacted by natural components, such as clay minerals. In this study, we systematically investigated the photodegradation behaviors of polyvinyl chloride (PVC) and poly (ethylene terephthalate) (PET), two utmost used plastics, in the presence of clay minerals (kaolinite and montmorillonite). The results demonstrated that the clay minerals, particularly kaolinite, significantly promoted the MPs photodegradation, and the aging of PET was more prominent. The photodegradation was the most distinct at pH 7.0, regardless of the presence or absence of the clay minerals. The results of electron paramagnetic resonance and inhibition experiments of reactive oxygen species indicated that the minerals, particularly kaolinite, remarkably facilitated production of •OH, which was the key species contributing to the photodegradation of MPs. Specifically, UV irradiation facilitated the photo-ionization of MPs, producing hydrated electrons and MP radical cations (MP⁺). The Lewis base sites prevalent on the clay siloxane surfaces could stabilize the MP radical cations and prevent their recombination with hydrated electrons, which promoted the generation of •OH under aerobic conditions, and facilitated the degradation of MP. Two-dimensional (2D) Fourier transformation infrared (FTIR) correlation spectroscopy (COS) analysis and ultra-high-performance liquid chromatography coupled to a Q Exactive Orbitrap HF mass spectrometer were used to identify the sequential changes of functional groups, and the degradation products of the MPs. This study improves our understanding on the aging of MPs in the complex natural environment.

Distinguishing Resonant from Non-Resonant Nonlinear Optical Processes Using Intensity-Intensity Correlation Analyses

Three-color coherent anti-Stokes Raman scattering (CARS) represents non-degenerate four wave mixing that includes both non-resonant and resonant processes, the contributions of which depend upon how the molecular vibrational modes are being excited by the input laser pulses. The scattering signal due to resonant processes builds up progressively. An advanced analytical tool to reveal this deferred resonant signal buildup phenomenon is in need. In this work, we adapt a quantitative analytical tool by introducing one-dimensional and two-dimensional intensity-intensity correlation functions in terms of a new variable (probe pulse delay) and a new perturbation parameter (probe pulse linewidth). In particular, discrete diagonal directional sums are defined here as a tool to reduce both synchronous and asynchronous two-dimensional correlation spectroscopy (2D-COS) maps down to one-dimensional plots while maintaining the valuable analytical information. Detailed analyses using the all-Gaussian coherent Raman scattering closed-form solutions and the representative experimental data for resonant and non-resonant processes are presented and compared. The present work holds a promising potential for industrial application, e.g., by extractive industries to distinguish hydrocarbons (chemically resonant substance) from water (non-resonant contaminant) by utilizing the one- and two-dimensional correlation analyses.

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.

Probing Protein Secondary Structure Influence on Active Centers with Hetero Two-Dimensional Correlation (Resonance) Raman Spectroscopy: A Demonstration on Cytochrome C

The functionality of active centers in proteins is governed by the secondary and higher structure of proteins which often lead to structures in the active center that are different from the structures found in protein-free models of the active center. To elucidate this structure-function relationship, it is therefore necessary to investigate both the protein structure and the local structure of the active center. In this work, we investigate the application of hetero (resonance) Raman two-dimensional correlation spectroscopy (2D-COS) to this problem. By employing a combination of near-infrared-Fourier transform-Raman- and vis-resonance Raman spectroscopy, we could show that this combination of techniques is able to directly probe the structure-function relationship of proteins. We were able to correlate the transition of the heme center in cytochrome c from low to high spin with changes in the secondary structure with the above mentioned two spectroscopic in situ techniques and without sample preparation. Thereby, we were able to reveal that the combination of a spectroscopic method to selectively observe the active center with a technique that monitors the whole system offers a promising toolkit to investigate the structure-function relationship of proteins with photoactive centers in general.

Competitive arsenate and phosphate adsorption on α-FeOOH, LaOOH, and nano-TiO2: Two-dimensional correlation spectroscopy study

Competitive adsorption of arsenate (AsO₄^3-) and phosphate (PO₄^3-) on α-FeOOH, LaOOH, and nano-TiO₂ was studied using batch adsorption experiments and in-situ flow cell ATR-FTIR coupled with two-dimensional correlation spectroscopy (2D-COS) for the first time. With a higher temporal resolution, our results found a highly dynamic adsorption sequence for AsO₄^3- and PO₄^3-. When AsO₄^3- and PO₄^3- were simultaneously exposed to the adsorbents at the same concentrations, AsO₄^3- was preferentially adsorbed by α-FeOOH and TiO₂, but PO₄^3- adsorption was dominant on LaOOH. The results implied that the PO₄^3- adsorbed on LaOOH had to be remobilized to allow for AsO₄^3- adsorption, but that PO₄^3- adsorption on α-FeOOH and TiO₂ was hindered by faster AsO₄^3- adsorption. Crystal orbital Hamilton population (COHP) analysis revealed that AsO₄^3- complexes bonded more strongly on α-FeOOH and TiO₂, whereas PO₄^3- complexes were more stable on LaOOH. Different adsorption sequences and the stability of the complexes were attributed to the diverse geometric configurations of AsO₄^3- and PO₄^3- on metal oxides surfaces with specific bonding chemistry. The presence of Ca²⁺ did not affect AsO₄^3- and PO₄^3- adsorption sequence on α-FeOOH or LaOOH, but it reversed the adsorption sequence on TiO₂ due to the formation of ternary surface complexes on TiO₂ surfaces.

Non-invasive monitoring of red blood cells during cold storage using handheld Raman spectroscopy

BACKGROUND

The current best practices allow for the red blood cells (RBCs) to be stored for prolonged periods in blood banks worldwide. However, due to the individual-related variability in donated blood and RBCs continual degradation within transfusion bags, the quality of stored blood varies considerably. There is currently no method for assessing the blood product quality without compromising the sterility of the unit. This study demonstrates the feasibility of monitoring storage lesion of RBCs in situ while maintaining sterility using an optical approach.

STUDY DESIGN AND METHODS

A handheld spatially offset Raman spectroscopy (RS) device was employed to non-invasively monitor hemolysis and metabolic changes in 12 red cell concentrate (RCC) units within standard sealed transfusion bags over 7 weeks of cold storage. The donated blood was analyzed in parallel by biochemical (chemical analysis, spectrophotometry, hematology analysis) and RS measurements, which were then correlated through multisource correlation analysis.

RESULTS

Raman bands of lactate (857 cm^-1 ), glucose (787 cm^-1 ), and hemolysis (1003 cm^-1 ) were found to correlate strongly with bioanalytical data over the length of storage, with correlation values 0.98 (95% confidence interval [CI]: 0.86-1.00; p = .0001), 0.95 (95% CI: 0.71-0.99; p = .0008) and 0.97 (95% CI: 0.79-1.00; p = .0004) respectively.

DISCUSSION

This study demonstrates the potential of collecting information on the clinical quality of blood units without breaching the sterility using Raman technology. This could significantly benefit quality control of RCC units, patient safety and inventory management in blood banks and hospitals.

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.