Recent advancement in the field of two-dimensional correlation spectroscopy

Investigation of ion association kinetics in Na2SO4-H2O by excess Raman spectroscopy and 2D correlation Raman spectroscopy

The ion association of salts aqueous solutions have long captivated the attention of researchers within the field of physical chemistry. In this paper, we have performed a comprehensive analysis of ion interactions in sodium sulfate (Na2SO4) aqueous solutions using a combination of high-resolution techniques, including excess (ERS) and two-dimensional correlation (2DCRS) Raman spectroscopy in conjunction with molecular dynamics (MD) calculations. The Raman spectrum shows that two inflection points in the Raman shift of the O-H vibration are observed with the increase in Na2SO4 concentration. Simultaneously, a new peak of the SO42- vibration appears at first inflection point, representing the formation of ion association. Further analysis based on ERS and 2CRS reveals that these two inflection points correspond respectively to the formation of ion pairs (CIPs) and small ion clusters. Importantly, MD simulations confirm the above experimental results. Our study provides evidence for ion association and clustering in aqueous in salt ion aqueous solutions.

Influence of macromolecules and electrolytes on heteroaggregation kinetics of polystyrene nanoplastics and goethite nanoparticles in aquatic environments

Fate and transport of nanoplastics in aquatic environments are affected by their heteroaggregation with minerals in the presence of macromolecules. This study investigated the heteroaggregation of polystyrene nanoplastics (PSNPs) with goethite nanoparticles (GNPs) under the influence of macromolecules [humic acid (HA), bovine serum albumin (BSA), and DNA] and electrolytes. Under 1 mg C/L macromolecule, raising electrolyte concentration promoted heteroaggregation via charge screening, except that calcium bridging with HA also enhanced heteroaggregation at CaCl2 concentration above 5 mM. At all NaCl concentrations and CaCl2 concentration below 5 mM, 1 mg C/L macromolecules strongly retarded heteroaggregation, ranking BSA > DNA > HA. Raising macromolecule concentration strengthened such stabilization effect of all macromolecules in NaCl solution and that of DNA and BSA in CaCl2 solution by enhancing steric hindrance. However, 0.1 mg C/L BSA slightly promoted heteroaggregation in CaCl2 solution due to stronger electrostatic attraction than steric hindrance. In CaCl2 solution, raising HA concentration strengthened its destabilization effect via calcium bridging. Macromolecules having more compact globular structure and higher molecular weight may exert greater steric hindrance to inhibit heteroaggregation more effectively. This study provides new insights on the effects of macromolecules and electrolytes on heteroaggregation between nanoplastics and iron minerals in aquatic environments.

Accurate prediction of hyaluronic acid concentration under temperature perturbations using near-infrared spectroscopy and deep learning

Accurate prediction of the concentration of a large number of hyaluronic acid (HA) samples under temperature perturbations can facilitate the rapid determination of HA's appropriate applications. Near-infrared (NIR) spectroscopy analysis combined with deep learning presents an effective solution to this challenge, with current research in this area being scarce. Initially, we introduced a novel feature fusion method based on an intersection strategy and used two-dimensional correlation spectroscopy (2DCOS) and Aquaphotomics to interpret the interaction information in HA solutions reflected by the fused features. Subsequently, we created an innovative, multi-strategy improved Walrus Optimization Algorithm (MIWaOA) for parameter optimization of the deep extreme learning machine (DELM). The final constructed MIWaOA-DELM model demonstrated superior performance compared to partial least squares (PLS), extreme learning machine (ELM), DELM, and WaOA-DELM models. The results of this study can provide a reference for the quantitative analysis of biomacromolecules in complex systems.

Novel Developments and Progress in Two-Dimensional Correlation Spectroscopy (2D-COS)

This first of the two-part series of the comprehensive survey review on the progress of the two-dimensional correlation spectroscopy (2D-COS) field during the period 2021-2022, covers books, reviews, tutorials, novel concepts and theories, and patent applications that appeared in the last two years, as well as some inappropriate use or citations of 2D-COS. The overall trend clearly shows that 2D-COS is continually growing and evolving with notable new developments. The technique is well recognized as a powerful analytical tool that provides deep insights into systems in many science fields.

Diverse Applications of Two-Dimensional Correlation Spectroscopy (2D-COS)

This second of the two-part series of a comprehensive survey review provides the diverse applications of two-dimensional correlation spectroscopy (2D-COS) covering different probes, perturbations, and systems in the last two years. Infrared spectroscopy has maintained its top popularity in 2D-COS over the past two years. Fluorescence spectroscopy is the second most frequently used analytical method, which has been heavily applied to the analysis of heavy metal binding, environmental, and solution systems. Various other analytical methods including laser-induced breakdown spectroscopy, dynamic mechanical analysis, differential scanning calorimetry, capillary electrophoresis, seismologic, and so on, have also been reported. In the last two years, concentration, composition, and pH are the main effects of perturbation used in the 2D-COS fields, as well as temperature. Environmental science is especially heavily studied using 2D-COS. This comprehensive survey review shows that 2D-COS undergoes continuous evolution and growth, marked by novel developments and successful applications across diverse scientific fields.

Identification and determination of different processed products and their extracts of Crataegi Fructus by infrared spectroscopy combined with two-dimensional correlation analysis

The fruit of Crataegus sp. is known as "Shanzha (SZ)" in China and is widely used in the food, beverage, and traditional Chinese medicine (TCM) industries. SZ usually requires thermal processing to reduce the irritation of its acidity to the gastric mucosa. Different processed products of SZ resulting from thermal processing have different or even opposite functions in clinical applications. In addition, 5-hydroxymethylfurfural (5-HMF) intermediates produced during thermal processing are carcinogenic to humans. Therefore, the aim of this study was to explore a rapid and accurate method by Fourier transform infrared spectroscopy (FT-IR) for the identification of different processed products and the determination of 5-HMF in extracts. In qualitative identification, a three-stage infrared spectroscopy identification method (raw spectra, the second derivative spectra, and two-dimensional correlation (2DCOS) spectra) was developed to distinguish different processed products of SZ step by step. In quantitative determination, partial least squares regression combined with different variable selection methods, especially the 2DCOS method, was applied to determine the 5-HMF content. The results show that temperature-induced 2DCOS synchronous spectra can effectively identify different processed products of SZ by shape, intensity, and position of auto-peaks or cross-peaks, and the variables selected by power spectra from concentration-induced 2DCOS synchronous spectra have better prediction ability for 5-HMF compared to full variables. The above results demonstrate that 2D-COS analysis is a potential tool in qualitative and quantitative analysis, which can improve sample identification accuracy and determination capabilities. This study not only establishes a rapid and accurate method for the identification of different processed products but also provides a practical reference for food safety and the efficient use of TCM.

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.

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.

Microbial metabolism and humic acid formation in response to enhanced copper and zinc passivation during composting of wine grape pomace and pig manure

Copper (Cu) and zinc (Zn) in piglet feed can lead to heavy metals (HMs) accumulation in pig manure (PM). Composting is crucial for recycling biowaste and decreasing HMs bioavailability. This study aimed to investigate the impact of adding wine grape pomace (WGP) on the bioavailability of HMs during PM composting. WGP facilitated the passivation of HMs through Cytophagales and Saccharibacteria_genera_incertae_sedis which promoted the formation of humic acid (HA). Polysaccharide and aliphatic groups in HA dominated the transformation of chemical forms of HMs. Moreover, adding 60% and 40% WGP enhanced the Cu and Zn passivation effects by 47.24% and 25.82%, respectively. Polyphenol conversion rate and core bacteria were identified as key factors in affecting HMs passivation. These results offered new insights into the fate of HMs during PM composting in response to the addition of WGP, which is helpful to practical application of WGP to inactivate HMs for improving compost quality.

Mechanisms of antimony release from lacustrine sediments with increasing temperature

Antimony (Sb) is more mobile in lacustrine sediments with seasonal warming. However, the mechanisms of Sb mobility in sediments are still unclear, especially considering the interactions among Sb, iron (Fe), manganese (Mn), and dissolved organic matter (DOM). In this study, high-resolution dialysis (HR-Peeper) and multi-spectral techniques simultaneously investigated changes in Sb, Fe, Mn, and DOM in two different ecological types (algal and grass) sediments with increasing temperature. We found that the dissolved Sb rapidly increased with the increase in temperature. The oxidation of Sb(III) to Sb(V) by Fe/Mn oxides in oxygen (O₂) rich overlying water and surface sediment layers was one of the reasons for Sb concentration enhancement in pore water. Further, using excitation-emission matrix and parallel factor analysis (EEM-PARAFAC), synchronous fluorescence (SF) spectroscopy, fourier transform infrared (FTIR) spectroscopy, and two-dimensional correlation spectroscopy (2D-COS) revealed that complexation with DOM was the other reasons for Sb concentration increasing in sediments. This was demonstrated by the similar distribution pattern and significant correlation between Sb and tryptophan-like components. Titration experiments further revealed that Sb was more stably bound to tryptophan-like components in the aromatic C-H (660 cm^-1), alcoholic C-O (1115 cm^-1), alkene CC (1615 cm^-1), and carboxylic acid OH (3390 cm^-1) groups. The tryptophan-like components from the algae region had a higher binding force than that from the macrophytes region. Our study effectively promotes an understanding of Sb mobilization in lacustrine sediments.

Polarisation Control in Arrays of Microlenses and Gratings: Performance in Visible-IR Spectral Ranges

Microlens arrays (MLAs) which are increasingly popular micro-optical elements in compact integrated optical systems were fabricated using a femtosecond direct laser write (fs-DLW) technique in the low-shrinkage SZ2080^TM photoresist. High-fidelity definition of 3D surfaces on IR transparent CaF₂ substrates allowed to achieve ∼50% transmittance in the chemical fingerprinting spectral region 2-5 μm wavelengths since MLAs were only ∼10 μm high corresponding to the numerical aperture of 0.3 (the lens height is comparable with the IR wavelength). To combine diffractive and refractive capabilities in miniaturised optical setup, a graphene oxide (GO) grating acting as a linear polariser was also fabricated by fs-DLW by ablation of a 1 μm-thick GO thin film. Such an ultra-thin GO polariser can be integrated with the fabricated MLA to add dispersion control at the focal plane. Pairs of MLAs and GO polarisers were characterised throughout the visible-IR spectral window and numerical modelling was used to simulate their performance. A good match between the experimental results of MLA focusing and simulations was achieved.

Structural Analysis and Classification of Low-Molecular-Weight Hyaluronic Acid by Near-Infrared Spectroscopy: A Comparison between Traditional Machine Learning and Deep Learning

Confusing low-molecular-weight hyaluronic acid (LMWHA) from acid degradation and enzymatic hydrolysis (named LMWHA-A and LMWHA-E, respectively) will lead to health hazards and commercial risks. The purpose of this work is to analyze the structural differences between LMWHA-A and LMWHA-E, and then achieve a fast and accurate classification based on near-infrared (NIR) spectroscopy and machine learning. First, we combined nuclear magnetic resonance (NMR), Fourier transform infrared (FTIR) spectroscopy, two-dimensional correlated NIR spectroscopy (2DCOS), and aquaphotomics to analyze the structural differences between LMWHA-A and LMWHA-E. Second, we compared the dimensionality reduction methods including principal component analysis (PCA), kernel PCA (KPCA), and t-distributed stochastic neighbor embedding (t-SNE). Finally, the differences in classification effect of traditional machine learning methods including partial least squares-discriminant analysis (PLS-DA), support vector classification (SVC), and random forest (RF) as well as deep learning methods including one-dimensional convolutional neural network (1D-CNN) and long short-term memory (LSTM) were compared. The results showed that genetic algorithm (GA)-SVC and RF were the best performers in traditional machine learning, but their highest accuracy in the test dataset was 90%, while the accuracy of 1D-CNN and LSTM models in the training dataset and test dataset classification was 100%. The results of this study show that compared with traditional machine learning, the deep learning models were better for the classification of LMWHA-A and LMWHA-E. Our research provides a new methodological reference for the rapid and accurate classification of biological macromolecules.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS): Part III. 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.

A Combination of Near-Infrared Hyperspectral Imaging with Two-Dimensional Correlation Analysis for Monitoring the Content of Alanine in Beef

Alanine (Ala), as the most important free amino acid, plays a significant role in food taste characteristics and human health regulation. The feasibility of using near-infrared hyperspectral imaging (NIR-HSI) combined with two-dimensional correlation spectroscopy (2D-COS) analysis to predict beef Ala content quickly and nondestructively is first proposed in this study. With Ala content as the external disturbance condition, the sequence of chemical bond changes caused by synchronous and asynchronous correlation spectrum changes in 2D-COS was analyzed, and local sensitive variables closely related to Ala content were obtained. On this basis, the simplified linear, nonlinear, and artificial neural network models developed by the weighted coefficient based on the feature wavelength extraction method were compared. The results show that with the change in Ala content in beef, the double-frequency absorption of the C-H bond of CH₂ in the chemical bond sequence occurred prior to the third vibration of the C=O bond and the first stretching of O-H in COOH. Furthermore, the wavelength within the 1136-1478 nm spectrum range was obtained as the local study area of Ala content. The linear partial least squares regression (PLSR) model based on effective wavelengths was selected by competitive adaptive reweighted sampling (CARS) from 2D-COS analysis, and provided excellent results (R²_C of 0.8141, R²_P of 0.8458, and RPDp of 2.54). Finally, the visual distribution of Ala content in beef was produced by the optimal simplified combination model. The results show that 2D-COS combined with NIR-HSI could be used as an effective method to monitor Ala content in beef.

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.

Quantitative vibrational spectroscopy on liquid mixtures: concentration units matter

Quantitative vibrational absorption spectroscopies rely on Beer's law relating spectroscopic intensities in a linear fashion to chemical concentrations. To address and clarify contrasting results in the literature about the difference between volume- and mass-based concentrations units used for quantitative spectroscopy on liquid solutions, we performed near-infrared, mid-infrared, and Raman spectroscopy measurements on four different binary solvent mixtures. Using classical least squares (CLS) and partial least squares (PLS) as multivariate analysis methods, we demonstrate that spectroscopic intensities are linearly related to volume-based concentration units rather than more widely used mass-based concentration units such as weight percent. The CLS results show that the difference in root mean square error of prediction (RMSEP) values between CLS models based on mass and volume fractions correlates strongly with the density difference between the two solvents in each binary mixture. This is explained by the fact that density differences are the source of non-linearity between mass and volume fractions in such mixtures. We also show that PLS calibration handles the non-linearity in mass-based models by the inclusion of additional latent variables that describe residual spectroscopic variation beyond the first latent variable (e.g., due to small peak shifts), as observed in the experimental data of all binary solvent mixtures. Using simulation studies, we have quantified the relative errors (up to 10-15%) that are made in PLS modeling when using mass fractions instead of volume fractions. Overall, our results provide conclusive evidence that concentration units based on volume should be preferred for optimal spectroscopic calibration results in academic and industrial practice.

Development of a novel quantitative function between spectral value and metmyoglobin content in Tan mutton

This study was aimed to establish a quantitative function between spectral reflectance values and metmyoglobin (MetMb) content in Tan mutton during refrigeration. Near-infrared hyperspectral data combined with generalized two-dimensional correlation spectroscopy (G2D-COS) method to identify characteristic bands and investigate the sequence of chemical waveband changes. Characteristic wavebands identified by G2D-COS analysis had the best performance in predicting the content of MetMb, with a high R²p of 0.849, a low RMSEP of 2.695 and a high RPD of 2.786. The results showed that the G2D-COS may be a powerful tool for describing intensity changes of MetMb band. The partial least square regression method was used to develop the relationships between the spectral values and MetMb content in Tan mutton meat for predicting MetMb content. This study has provided a convenient and rapid non-destructive quantitative method for assessing the color of Tan mutton meat.

Microbial community composition turnover and function in the mesophilic phase predetermine chicken manure composting efficiency

The aim of this work was to study the influence of inoculation with microbial inoculants (MI) or mature compost (MC) by comparing the resultant composting efficiency with that in a noninoculated (CK) treatment. MI and MC application both accelerated the composting process according to fluorescence excitation-emission matrix (EEM) detection and germination index testing. Bacterial and fungal community composition both differed significantly over the composting period. However, the turnover of the initial bacterial community played a significant role in the composting process, and the key operational taxonomic units (OTUs) of MI (OTU_26, Thermicanus) and MC (OTU_48, Tepidimicrobium) showed significant explanatory power for the formation of humic acid-like and fulvic acid-like substances, respectively, during the stage of composting. Thus, our results indicate that microbial inoculation accelerates the composting process by stimulating key resident microbes in the initial stage.

PC 2D-COS: A Principal Component Base Approach to Two-Dimensional Correlation Spectroscopy

This paper introduces the newly developed principal component powered two-dimensional (2D) correlation spectroscopy (PC 2D-COS) as an alternative approach to 2D correlation spectroscopy taking advantage of a dimensionality reduction by principal component analysis. It is shown that PC 2D-COS is equivalent to traditional 2D correlation analysis while providing a significant advantage in terms of computational complexity and memory consumption. These features allow for an easy calculation of 2D correlation spectra even for data sets with very high spectral resolution or a parallel analysis of multiple data sets of 2D correlation spectra. Along with this reduction in complexity, PC 2D-COS offers a significant noise rejection property by limiting the set of principal components used for the 2D correlation calculation. As an example for the application of truncated PC 2D-COS a temperature-dependent Raman spectroscopic data set of a fullerene-anthracene adduct is examined. It is demonstrated that a large reduction in computational cost is possible without loss of relevant information, even for complex real world data sets.

Nondestructive Spectroscopic Tracing of Simulated Formation Processes of Humic-Like Substances Based on the Maillard Reaction

The formation processes of humic-like substances have been simulated by heating a glycine and ribose mixed solution (0.1 mol L^-1) at 80 ℃ using the Maillard reaction. Ultraviolet-visible (UV-Vis), three-dimensional excitation emission spectroscopy and size exclusion liquid chromatography succeeded in quantitatively tracing increases of the products during the heating of glycine and ribose mixed solution (0.1 mol L^-1). Two-dimensional correlation spectroscopic analyses suggested that a band area around 280 nm ( UV₂₈₀) and 254 nm absorbance ( UV₂₅₄) can be used as measures of the formation of furfural-like intermediates and humic-like products, respectively. They were monitored using in situ UV-Vis spectroscopy with the original heatable liquid cell at 60-80 ℃. Kinetic analyses of the obtained data gave activation energies of 91.4-96.6 kJ mol^-1. These nondestructive measurements by an in situ spectroscopic method did not require any additional procedures including drying or extracting the solution and they can be effectively used for direct tracing of the reaction progress and/or decomposition.

Two-dimensional correlation and codistribution spectroscopy (2DCOS and 2DCDS) analyses of time-dependent ATR IR spectra of d-glucose anomers undergoing mutarotation process in water

Two cyclic diastereoisomeric structures, known as α- and β-anomers of d-glucose with different configurations around C1 with OH groups in axial or equitroial positions, undergo the mutarotation conversion to each other in water. Two-dimensional correlation and codistribution spectroscopy (2DCOS and 2DCDS) analyses were applied to the time-dependent ATR IR spectra of aqueous solutions of α- and β-d-glucose undergoing such mutarotation conversion. 2DCOS analysis reveals that the increase and decrease in the IR intensities after the dissolution of α- or β-d-glucose are not fully synchronized, suggesting the mutarotation of d-glucose in water is not a simple binary conversion process but a multi-step reaction involving an intermediate species with a finite and observable concentration level and lifetime. 2DCDS analysis of the time-dependent ATR IR spectra clearly demonstrated the presence of intermediate species contributing to the band positions overlapped close to bands for α- and β-d-glucose. The fact that band positions identified for the intermediate species for α- to β-d-glucose conversion are the same for the reverse reaction suggests that they arise from the same species, most likely the open-ring structure produced by the hydrolysis.

Advancements of two dimensional correlation spectroscopy in protein researches

The developments of two-dimensional correlation spectroscopy (2DCOS) applications in protein studies are discussed, especially for the past two decades. The powerful utilities of 2DCOS combined with various analytical techniques in protein studies are summarized. The emphasis is on the vibration spectroscopic techniques including IR, NIR, Raman and optical activity (ROA), as well as vibration circular dichroism (VCD) and fluorescence spectroscopy. In addition, some new developments, such as hetero-spectral 2DCOS, moving-window correlation, and model based correlation, are also reviewed for their utility in the investigation of the secondary structure, denaturation, folding and unfolding changes of protein. Finally, the new possibility and challenges of 2DCOS in protein research are highlighted as well.

Feasibility of the simultaneous determination of polycyclic aromatic hydrocarbons based on two-dimensional fluorescence correlation spectroscopy

A new approach for quantitative determination of polycyclic aromatic hydrocarbons (PAHs) in environment was proposed based on two-dimensional (2D) fluorescence correlation spectroscopy in conjunction with multivariate method. 40 mixture solutions of anthracene and pyrene were prepared in the laboratory. Excitation-emission matrix (EEM) fluorescence spectra of all samples were collected. And 2D fluorescence correlation spectra were calculated under the excitation perturbation. The N-way partial least squares (N-PLS) models were developed based on 2D fluorescence correlation spectra, showing a root mean square error of calibration (RMSEC) of 3.50μgL^-1 and root mean square error of prediction (RMSEP) of 4.42μgL^-1 for anthracene and of 3.61μgL^-1 and 4.29μgL^-1 for pyrene, respectively. Also, the N-PLS models were developed for quantitative analysis of anthracene and pyrene using EEM fluorescence spectra. The RMSEC and RMSEP were 3.97μgL^-1 and 4.63μgL^-1 for anthracene, 4.46μgL^-1 and 4.52μgL^-1 for pyrene, respectively. It was found that the N-PLS model using 2D fluorescence correlation spectra could provide better results comparing with EEM fluorescence spectra because of its low RMSEC and RMSEP. The methodology proposed has the potential to be an alternative method for detection of PAHs in environment.

Two-dimensional correlation spectroscopy in protein science, a summary for past 20years

Two-dimensional correlation spectroscopy (2DCOS) has been widely used to Infrared, Raman, Near IR, Optical Activity (ROA), Vibrational Circular Dichroism (VCD) and Fluorescence spectroscopy. In addition, several new developments, such as 2D hetero-correlation analysis, moving-window two-dimensional (MW2D) correlation, model based correlation (βν and kν correlation analyses) have also well incorporated into protein research. They have been used to investigate secondary structure, denaturation, folding and unfolding changes of protein, and have contributed greatly to the field of protein science. This review provides an overview of the applications of 2DCOS in the field of protein science for the past 20 year, especially to memory our old friend, Dr. Boguslawa Czarnik-Matusewicz, for her great contribution in this research field. The powerful utility of 2DCOS combined with various analytical techniques in protein studies is summarized. The noteworthy developments and perspective of 2DCOS in this field are highlighted finally.

Vibrational two-dimensional correlation spectroscopy (2DCOS) study of proteins

A tutorial is provided for the generalized two-dimensional correlation spectroscopy (2DCOS), which is applicable to the vibrational spectroscopic study of proteins and related systems. In 2DCOS, similarity or dissimilarity among variations of spectroscopic intensities, which are induced by applying an external perturbation to the sample, is examined by constructing correlation spectra defined by two independent spectral variable axes. By spreading congested or overlapped peaks along the second dimension, apparent spectral resolution is enhanced and interpretation of complex spectra becomes simplified. A set of simple rules for the intensities and signs of correlation peaks is used to extract insightful information. Simulated IR spectra for a model protein are used to demonstrate the specific utility of 2DCOS. Additional tools useful in the 2DCOS analysis of proteins, such as data segmentation assisted with moving-window analysis, 2D codistribution analysis, Pareto scaling, and null-space projection are also discussed.

Prp40 Homolog A Is a Novel Centrin Target

Pre-mRNA processing protein 40 (Prp40) is a nuclear protein that has a role in pre-mRNA splicing. Prp40 possesses two leucine-rich nuclear export signals, but little is known about the function of Prp40 in the export process. Another protein that has a role in protein export is centrin, a member of the EF-hand superfamily of Ca²⁺-binding proteins. Prp40 was found to be a centrin target by yeast-two-hybrid screening using both Homo sapiens centrin 2 (Hscen2) and Chlamydomonas reinhardtii centrin (Crcen). We identified a centrin-binding site within H. sapiens Prp40 homolog A (HsPrp40A), which contains a hydrophobic triad W₁L₄L₈ that is known to be important in the interaction with centrin. This centrin-binding site is highly conserved within the first nuclear export signal consensus sequence identified in Saccharomyces cerevisiae Prp40. Here, we examine the interaction of HsPrp40A peptide (HsPrp40Ap) with both Hscen2 and Crcen by isothermal titration calorimetry. We employed the thermodynamic parameterization to estimate the polar and apolar surface area of the interface. In addition, we have defined the molecular mechanism of thermally induced unfolding and dissociation of the Crcen-HsPrp40Ap complex using two-dimensional infrared correlation spectroscopy. These complementary techniques showed for the first time, to our knowledge, that HsPrp40Ap interacts with centrin in vitro, supporting a coupled functional role for these proteins in pre-mRNA splicing.

Toward the two-step microdynamic phase transition mechanism of an oligo(ethylene glycol)methacrylate-based copolymer with a LCST-type poly(ionic liquid) block

A new LCST-type thermoresponsive polyelectrolyte P[P_4,4,4,4][SS], poly(tetrabutyl phosphonium styrene sulfonate), was introduced to PMEO₂MA (poly(2-(2-methoxyethoxy)ethyl methacrylate)) via RAFT polymerization, in order to explore the transition behavior of the block copolymer PMEO₂MA-b-P[P_4,4,4,4][SS] with two distinct LCST-type segments. A relatively sharp LCST-type phase transition with only one transition point is observed in the turbidity curves, while the whole phase transition is completely different from the micro perspective. The phase transition temperature range is relatively broad, according to the unsynchronized changes of different protons of the two blocks in the temperature-variable ¹H NMR analysis. From PCMW analysis, it is found that there exists an obvious two-step phase transition behavior, especially in the region of the C-H groups. Accordingly, we divided the whole transition process into two subregions: 20-40 °C and 40-55 °C in 2Dcos analysis. At the first stage of 20-40 °C, the CH₃ groups mainly belonging to the backbones of PMEO₂MA blocks have the earliest response to the heating and drive the first step of the dehydration process of PMEO₂MA-b-P[P_4,4,4,4][SS], resulting in the formation of an intermediate micelle state composed of the collapsed PMEO₂MA core and hydrophilic P[P_4,4,4,4][SS] corona. In particular, the conformational changes and the more compact structures due to the interaction between the C[double bond, length as m-dash]O groups and P[P_4,4,4,4][SS] segments (ν(C[double bond, length as m-dash]OD₂O-PILs)) were observed using IR analysis. With the continual increase of the temperature, when the second temperature range of 40-55 °C is reached, the P[P_4,4,4,4][SS] segments start to collapse and expel the water molecules, driven by the anions of the poly(ionic liquid)s, with the phosphonium cations being distributed over the relatively hydrophilic outside.

Chemical profiling and adulteration screening of Aquilariae Lignum Resinatum by Fourier transform infrared (FT-IR) spectroscopy and two-dimensional correlation infrared (2D-IR) spectroscopy

As a kind of expensive perfume and valuable herb, Aquilariae Lignum Resinatum (ALR) is often adulterated for economic motivations. In this research, Fourier transform infrared (FT-IR) spectroscopy is employed to establish a simple and quick method for the adulteration screening of ALR. First, the principal chemical constituents of ALR are characterized by FT-IR spectroscopy at room temperature and two-dimensional correlation infrared (2D-IR) spectroscopy with thermal perturbation. Besides the common cellulose and lignin compounds, a certain amount of resin is the characteristic constituent of ALR. Synchronous and asynchronous 2D-IR spectra indicate that the resin (an unstable secondary metabolite) is more sensitive than cellulose and lignin (stable structural constituents) to the thermal perturbation. Using a certified ALR sample as the reference, the infrared spectral correlation threshold is determined by 30 authentic samples and 6 adulterated samples. The spectral correlation coefficient of an authentic ALR sample to the standard reference should be not less than 0.9886 (p=0.01). Three commercial adulterated ALR samples are identified by the correlation threshold. Further interpretation of the infrared spectra of the adulterated samples indicates the common adulterating methods - counterfeiting with other kind of wood, adding ingredient such as sand to increase the weight, and adding the cheap resin such as rosin to increase the content of resin compounds. Results of this research prove that FT-IR spectroscopy can be used as a simple and accurate quality control method of ALR.

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

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

Revealing the distinct thermal transition behavior between PEGA-based linear polymers and their disulfide cross-linked nanogels

Description of the distinct thermal transition behavior between PEGA-based linear polymers and their disulfide cross-linked nanogels at a molecular level.

Research on the best measurement situation between optical probe and tissue surfaces in non-invasive detection

Near-infrared spectroscopy is often used for the non-invasive detection of composition in the human body, such as that of blood glucose and haemoglobin, due to its high penetration depth into tissues. Although it is feasible to position the optical probe precisely, contact situation between probe and human tissues is a difficult problem to determine because of physiological tremor and mechanical performance of bio-soft tissue. Here, we proposed a novel estimation method for the situation between the optical probe and tissue surfaces based on the dynamic auto-correlation matrix of two-dimensional correlation spectroscopy (2DCOS) and radar chart. The diffuse reflectance spectra from the left palm of 4 healthy volunteers were collected while the optical probe gradually approached and pressed bio-tissues with a custom-design controlling device. 2DCOS in the wavelength with lower absorption (1000-1400 nm) was calculated under the perturbation of relative-distance and contact pressure between the optical probe and tissue surface. The synchronous 2DCOS showed that the surface reflection and diffuse reflectance were greatly affected by the contact conditions in 1100 nm, 1220 nm, and 1300 nm. Then the dynamic auto-correlation matrix of 2DCOS was established for the adjacent spectra, and the significant difference wavelengths were used to build radar charts to determine the critical contact situation visually. Results showed that the maximum variations of dynamic auto-correlation matrix appeared at near 1300 nm, and the relative distance between the probe and tissue corresponding to the critical contact state can be easily observed with radar charts with 0.25 mm uncertainty, which was consistent with the self-feeling of each volunteer. So this method can be applied to exactly determine the optimal measurement status for the non-invasive body composition detection in vivo. It is important for the design of human-machine interface and the accuracy improvement of body composition measurements.

Exploration of Doubly Thermal Phase Transition Process of PDEGA-b-PDMA-b-PVCL in Water

Understanding of phase transition mechanism of thermoresponsive polymers is the basis for the rational design of smart materials with predictable properties. Linear ABC triblock terpolymer poly(di(ethylene glycol)ethyl ether acrylate)-b-poly(N,N-dimethylacrylamide)-b-poly(N-vinylcaprolactam) (PDEGA-b-PDMA-b-PVCL) was synthesized by reversible addition-fragmentation chain transfer (RAFT) polymerization. The doubly thermal phase transition of PDEGA-b-PDMA-b-PVCL in aqueous solution was investigated by a combination of nuclear magnetic resonance (NMR), differential scanning calorimetry (DSC), turbidimetry, and dynamic light scattering (DLS). The terpolymer self-assembles into micelles with PDEGA being the core-forming block during the first lower critical solution temperature (LCST) transition corresponding to PDEGA, which is followed by a second LCST transition corresponding to PVCL, resulting in the formation of micellar aggregates. The PDMA middle segment plays an important role as an isolation zone to prevent cooperative dehydration of the PDEGA and PVCL segments, and therefore, two independent LCST transitions corresponding to PDEGA and PVCL were observed. Furthermore, FT-IR with perturbation correlation moving window (PCMW) and two-dimensional spectroscopy (2DCOS) was applied to elucidate the two-step phase transition mechanism of this terpolymer. It was observed that the CH, ester carbonyl, and ether groups of PDEGA change prior to the CH and amide carbonyl groups of PVCL, further supporting that the two phase transitions corresponding to PDEGA and PVCL indeed occur without mutual interferences.

Identification of Serine Conformers by Matrix-Isolation IR Spectroscopy Aided by Near-Infrared Laser-Induced Conformational Change, 2D Correlation Analysis, and Quantum Mechanical Anharmonic Computations

The conformers of α-serine were investigated by matrix-isolation IR spectroscopy combined with NIR laser irradiation. This method, aided by 2D correlation analysis, enabled unambiguously grouping the spectral lines to individual conformers. On the basis of comparison of at least nine experimentally observed vibrational transitions of each conformer with empirically scaled (SQM) and anharmonic (GVPT2) computed IR spectra, six conformers were identified. In addition, the presence of at least one more conformer in Ar matrix was proved, and a short-lived conformer with a half-life of (3.7 ± 0.5) × 10(3) s in N2 matrix was generated by NIR irradiation. The analysis of the NIR laser-induced conversions revealed that the excitation of the stretching overtone of both the side chain and the carboxylic OH groups can effectively promote conformational changes, but remarkably different paths were observed for the two kinds of excitations.

In-depth study of the phase separation behaviour of a thermoresponsive ionic liquid and a poly(ionic liquid) in concentrated aqueous solution

The temperature-induced phase transition behaviors of a thermoresponsive ionic liquid (tributylhexylphosphonium 3-sulfopropylmethacrylate, [P4,4,4,6][MC3S]) and its polymer (poly-tributylhexylphosphonium 3-sulfopropylmethacrylate, P[P4,4,4,6][MC3S]) have been investigated using DSC, optical microscopy, temperature-variable (1)H NMR, and FT-IR in combination with two-dimensional analysis methods, including perturbation correlation moving window (PCMW) and two-dimensional correlation spectroscopy (2Dcos). We found that there exists a distribution gradient of water molecules in P[P4,4,4,6][MC3S] ranging from hydrophobic backbones to hydrophilic sulfonates. Linked together by covalent bonds, P[P4,4,4,6][MC3S] would form an "urchin-like" structure, which can improve its stability and strengthen the gradient distribution of water. Finally, 2Dcos was employed to elucidate the sequential order of chemical group motions during heating. It is concluded that both [P4,4,4,6][MC3S] and P[P4,4,4,6][MC3S] experience the anionic dominated phase transition process. Moreover, the driving force for the phase transitions is shown to be the dehydration of hydrophobic ester carbonyls.

Trifluoroacetic acid as excipient destabilizes melittin causing the selective aggregation of melittin within the centrin-melittin-trifluoroacetic acid complex

Trifluoroacetic acid (TFA) may be the cause of the bottleneck in high resolution structure determination for protein-peptide complexes. Fragment based drug design often involves the use of synthetic peptides which contain TFA (excipient). Our goal was to explore the effects of this excipient on a model complex: centrin-melittin-TFA. We performed Fourier transform infrared, two-dimensional infrared correlation spectroscopies and spectral simulations to analyze the amide I'/I'* band for the components and the ternary complex. Melittin (MLT) was observed to have increased helicity upon its interaction with centrin, followed by the thermally induced aggregation of MLT within the ternary complex in the TFA presence.

Comparison of LCST-transitions of homopolymer mixture, diblock and statistical copolymers of NIPAM and VCL in water

The LCST-transitions of linear, well-defined polymers of N-isopropylacrylamide (NIPAM) and N-vinylcaprolactam (VCL), including a homopolymer mixture, diblock and statistical copolymers, in water are explored and compared by applying turbidity and FTIR measurements in combination with two-dimensional correlation spectroscopy (2Dcos). Only one transition is observed in all polymer systems, suggesting a dependent aggregation of poly(N-isopropylacrylamide) (PNIPAM) and poly(N-vinylcaprolactam) (PVCL) parts in the phase transition processes. With the help of 2Dcos analysis, it is discovered that the hydrophobic interaction among C-H groups is the driving force for simultaneous collapse of the two distinct thermo-responsive segments. Additionally, the delicate differences within the LCST-transitions thereof have been emphasized, where the phase separation temperatures of the homopolymer mixture and the diblock copolymer are close while that of the statistical copolymer is relatively higher. Moreover, both diblock and statistical copolymers exhibit rather sharp phase transitions while the homopolymer mixture demonstrates a moderately continuous one.