Novel Method of Constructing Two-Dimensional Correlation Spectroscopy without Subtracting a Reference Spectrum

Chemical Dynamics of Selenium Nanoparticles in Archaeal Systems

Methanogenic archaea, characterized by their cell membrane lipid molecules consisting of isoprenoid chains linked to glycerol-1-phosphate via ether bonds, exhibit exceptional adaptability to extreme environments. However, this distinct lipid architecture also complicates the interactions between methanogenic archaea and nanoparticles. This study addresses this challenge by exploring the interaction and transformation of selenium nanoparticles (SeNPs) within archaeal Methanosarcina acetivorans C2A. We demonstrated that the effects of SeNPs are highly concentration-dependent, with chemical stimulation of cellular processes at lower SeNPs concentrations as well as oxidative stress and metabolic disruption at higher concentrations. Notably, we observed the formation of a protein corona on SeNPs, characterized by the selective adsorption of enzymes critical for methylotrophic methanogenesis and those involved in selenium methylation, suggesting potential alterations in protein function and metabolic pathways. Furthermore, the intracellular transformation of SeNPs into both inorganic and organic selenium species highlighted their bioavailability and dynamic transformation within archaea. These findings provide vital insights into the nano-bio interface in archaeal systems, contributing to our understanding of archaeal catalysis and its broader applications.

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.

A new approach to recognizing the correct pattern of cross-peaks from a noisy 2D asynchronous spectrum by detecting intrinsic symmetry via the Kolmogorov-Smirnov test

The characteristic cluster pattern of cross-peaks in a 2D asynchronous spectrum provides an effective way to reveal the specific physicochemical nature of subtle spectral changes caused by intermolecular interactions. However, the inevitable presence of noise in the 1D spectra used to construct a 2D asynchronous spectrum is significantly amplified, which poses a serious challenge in identifying the correct cluster pattern of the cross-peaks. While mirror symmetry occurs in some types of cross-peaks, it does not occur in other types. The Kolmogorov-Smirnov test provides a statistical means to check whether the mirror symmetry exists or not between a pair of cross-peaks covered by heavy noise. Thus, different types of cross-peak clusters can be distinguished by excavating intrinsic spectral features from the noisy 2D asynchronous spectrum. The effectiveness of this approach in investigating the nature of intermolecular interactions was showcased in both a simulated model system and a real artemisinin/N-methyl pyrrolidone system.

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.

Cyclodextrin Complexation of Fenofibrate by Co-Grinding Method and Monitoring the Process Using Complementary Analytical Tools

Solvent-free preparation types for cyclodextrin complexation, such as co-grinding, are technologies desired by the industry. However, in-depth analytical evaluation of the process and detailed characterization of intermediate states of the complexes are still lacking in areas. In our work, we aimed to apply the co-grinding technology and characterize the process. Fenofibrate was used as a model drug and dimethyl-β-cyclodextrin as a complexation excipient. The physical mixture of the two substances was ground for 60 min; meanwhile, samples were taken. A solvent product of the same composition was also prepared. The intermediate samples and the final products were characterized with instrumental analytical tools. The XRPD measurements showed a decrease in the crystallinity of the drug and the DSC results showed the appearance of a new crystal form. Correlation analysis of FTIR spectra suggests a three-step complexation process. In vitro dissolution studies were performed to compare the dissolution properties of the pure drug to the products. Using a solvent-free production method, we succeeded in producing a two-component system with superior solubility properties compared to both the active ingredient and the product prepared by the solvent method. The intermolecular description of complexation was achieved with a detailed analysis of FTIR spectra.

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.

Novel Method for Extracting the Spectrum of a Supramolecular Complex via a Comprehensive Approach Involving Two-Dimensional Correlation Spectroscopy, Genetic Algorithm, and Grid Searching

A supramolecular complex may be formed by two solutes via a weak intermolecular interaction in a solution. The spectrum of the complex is often inundated by the spectra of the solutes that are not involved in the intermolecular interaction. Herein, a novel spectral analysis approach is proposed to retrieve the spectrum of the supramolecular complex. First, a two-dimensional (2D) asynchronous spectrum is constructed. Then, a genetic algorithm is used to obtain a heuristic spectrum of the supramolecular complex. The heuristic spectrum is a linear combination of the spectrum of the complex and the spectrum of a solute. The coefficients of the linear combination are then obtained, according to which the equilibrium constants are invariant among the sample solutions used to construct the 2D asynchronous spectrum. We have applied the approach to a supramolecular system formed by benzene and I₂. In the analysis, several binding models are evaluated, and a benzene molecule interacting with two iodine molecules via halogen bonding turns out to be the only possible model. Hence, the characteristic band of the benzene/I₂ supramolecular complex around 1819 cm^-1 in the Fourier transform infrared (FTIR) spectrum and the corresponding equilibrium constant are obtained. The above results indicate that the novel approach provides a chance to get new insight into various intermolecular interactions studied by spectroscopy.

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.

Investigation on the luminescence behavior of terbium acetylsalicylate/bilirubin system via 2D-COS approaches

Terbium acetylsalicylate has been prepared, and the ethanol solution of the complex exhibits strong luminescence under the excitation of ultraviolet radiation. When a small amount of bilirubin solution is introduced into the solution containing a high concentration of terbium acetylsalicylate, a remarkable diminution of the luminescence of the terbium complex was observed. Investigations on the behavior and life-time of luminescence indicate that the quenching is not caused by forming a stable non-luminescent product via a reaction between terbium acetylsalicylate and bilirubin. A π-π interaction between the chromophore of bilirubin and the aromatic moiety of ligand was revealed via the pattern of cross peaks in the 2D asynchronous spectrum generated using the DAOSD (double asynchronous orthogonal sample design) approach. Such an interaction paves a route for energy transfer in the quenching process. The combination of a high concentration of the terbium complex and a long life-time of luminescence in the lanthanide complex/bilirubin system forms a special scenario: a bilirubin molecule by diffusion may visit and deactivate dozens of excited terbium complexes within the half-life period of the lanthanide complex. This is why a small amount of bilirubin can bring about the significant reduction of luminescence on the solution containing a high concentration of the terbium complex.

Intensity Enhancement of a Two-Dimensional Asynchronous Spectrum Without Noise Level Fluctuation Escalation Using a One-Dimensional Spectra Sequence Change

Previously, we demonstrated that the intensities of cross-peaks in a two-dimensional asynchronous spectrum could be enhanced using sequence change of the corresponding one-dimensional spectra. This unusual approach becomes useful when the determination of the sequential order of physicochemical events is not essential. However, it was not known whether the level of noise in the two-dimensional asynchronous spectrum was also escalated as the sequence of one-dimensional spectra changed. We first investigated the noise behavior in a two-dimensional asynchronous spectrum upon changing the sequence of the corresponding one-dimensional spectra on a model system. In the model system, bilinear data from a chromatographic-spectroscopic experiment on a mixture containing two components were analyzed using a two-dimensional asynchronous spectrum. The computer simulation results confirm that the cross-peak intensities in the resultant a two-dimensional asynchronous spectrum were indeed enhanced by more than 100 times as the sequence of one-dimensional spectra changed, whereas the fluctuation level of noise, reflected by the standard deviation of the value of a two-dimensional asynchronous spectrum at a given point, was almost invariant. Further analysis on the model system demonstrated that the special mathematical property of the Hilbert-Noda matrix (the modules of all column vectors of the Hilbert-Noda matrix being a near constant) accounts for the moderate variation of the noise level during the changes of the sequence of one-dimensional spectra. Next, a realistic example from a thermogravimetry-Fourier transform infrared spectroscopy experiment with added artificial noise in seven one-dimensional spectra was studied. As we altered the sequence of the seven FT-IR spectra, the variation of the cross-peak intensities covered four orders of magnitude in the two-dimensional asynchronous spectra. In contrast, the fluctuation of noise in the two-dimensional asynchronous spectra was within two times. The above results clearly demonstrate that a change in the sequence of one-dimensional spectra is an effective way to improve the signal-to-noise level of the two-dimensional asynchronous spectra.

Identification of systematic absence of cross-peaks (SACPs) in a two-dimensional asynchronous Spectrum using an auxiliary 2D quotient Spectrum and a statistical test

Systematic Absence of Cross Peaks (SACPs) in a two-dimensional (2D) asynchronous spectrum, a sensitive indicator of the signal purity, is very important in analyzing bilinear data. However, identification of SACPs in practice remains a challenge because of noise in the corresponding 2D asynchronous spectrum. We firstly show that SACP can be identified via a statistical test using a large amount of 2D asynchronous spectra. To meet the practical demand that SACPs must be identified based on a single 2D asynchronous spectrum in many cases, we use a 2D quotient spectrum (Q (x, y)) as an effective auxiliary tool to recognize SACPs. The expectation of Q(x, y) is zero when (x, y) is within SACP or background regions in the corresponding 2D asynchronous spectrum. When (x, y) is in a cross-peak region, the expectation of the absolute value of Q(x, y) is a constant regardless of whether the cross-peak in a 2D asynchronous spectrum is strong or weak. Thus, a unified threshold can be set up to differentiate the SACP region from cross-peak region via the auxiliary 2D quotient spectrum. We have applied this approach on two real-world examples and satisfactory results have been obtained. This result demonstrates that the statistical test with a 2D quotient spectrum is applicable in real-world systems.

Application of two-dimensional correlation fluorescence spectroscopy to detect the presence of trace amount of substances

Although fluorescence spectroscopy is a highly sensitive method, it is still rather difficult to identify a minor fluorescent component whose fluorescent peak is overlapped and masked by a dominant fluorescent component in a sample solution. Herein, we describe a two-dimensional correlation spectroscopy (2D-COS) approach based on the Kasha's rule to solve the above common problem. We initially suppose that a sample solution contains the major component only, and the spectral behavior of the major component obeys the Kasha's rule. Then, the shapes of emission spectra obtained under excitation lights of different wavelengths remain invariant. Under this condition, the introduction of a minor fluorescent component can be reflected by the changes on the shapes of emission peaks in the series of emission spectra. Moreover, subtle changes, which are difficult to be found in the original spectra, can be clearly visualized as cross peaks in 2D asynchronous spectrum constructed using a series of emission spectra. In addition, we demonstrate that the intensities of cross peaks can be enhanced by changing the sequence of the series of emission spectra. We utilize the approach on an aqueous solution containing eosin Y and a trace amount of bromocresol green. The presence of bromocresol green with the concentration as low as 400 nM can be revealed via the cross peaks in the resultant 2D asynchronous spectra. In a preliminary study, we suggest that 2D disrelation spectrum might provide an alternative chance to reveal the presence of small amount bromocresol green.

A novel systematic absence of cross peaks-based 2D-COS approach for bilinear data

A novel approach to use two-dimensional correlation spectroscopy (2D-COS) to analyze bilinear data is proposed. A phenomenon called Systematic Absence of Cross Peaks (SACPs) is observed in a 2D asynchronous spectrum. Two theorems relevant to SACPs have been derived. The SACP-based 2D-COS method has been successfully applied on analyzing bilinear data from mixed samples (including one model system and two real systems). Implicit isolated peaks can be identified and assigned to different components based on characteristic pattern of SACPs even if the time-related profiles of different components are severely overlapped. Based on the results of SACPs, spectra of pure components can be retrieved. Identification of SACPs can still be achieved in the presence of artifacts. Thus, neither noise nor baseline drift can produce significant influence on the results obtained from the approach described in this paper. We have used several well-established chemometric methods, including N-Findr, VCA, and MCR with various initial settings, on two systems that can be successfully solved using the 2D-COS method. The chemometric methods mentioned above cannot provide correct spectra of pure components because of severe problem of rotational ambiguity derived from severe overlapping of the time-related profiles. Only when the information from SACPs in 2D-COS is used as additional constraints in MCR calculation, correct spectra can be obtained. That is to say, the SACP-based 2D-COS method provides intrinsic information which is crucial in the analysis of chromatographic-spectroscopic and analogous data even if the time-related profiles of different components overlap severely.

A Novel Approach Based on Two-Dimensional Correlation Spectroscopy to Determine the Stoichiometric Ratio of Two Substances Involved in Intermolecular Interactions

A novel technique called AOSD@Job's, combining asynchronous orthogonal sample design scheme (AOSD) with Job's method, is proposed to estimate the stoichiometric ratio of two substances that form a supramolecular aggregate under intermolecular interactions. First, a mathematical analysis was performed along with the procedure of the AOSD@Job's method. Then, the validity of the AOSD@Job's method was manifested by computer simulation on two model systems. Finally, the AOSD@Job's method was applied on two real chemical systems. The stoichiometric ratio between the coordination complex of Ni²⁺ and ethylenediaminetetraacetic acid disodium salt (EDTA) was estimated to be 1.0. Benzyl alcohol (BA) and β-cyclodextrin (β-CD) were determined to form a 1 : 1 host-guest complex. These values were consistent with the values reported in the literature. Compared with the traditional Job's method, the AOSD@Job's method has an evident advantage since it is still valid even if all the peaks of the supramolecular aggregate severely overlap with the peaks of the substances that form the aggregate.

A preliminary study on constructing a high-dimensional asynchronous spectrum to analyze bilinear data

A novel approach to constructing high-dimensional asynchronous spectra (nD-Asyn) is proposed. Three theorems relevant to 1D slices of nD-Asyn are revealed. nD-Asyn is used to analyze bilinear data from mixtures containing multiple components obtained via hyphenated techniques. The spectral contribution of different components can be removed in a stepwise manner by increasing the dimensions of asynchronous spectra. As a result, the spectra of different components can be faithfully recovered even if the time-related profiles of different components severely overlap. Moreover, correct results can still be obtained via the nD-Asyn even if a considerable level of noise and baseline drift are present. The nD-Asyn approach is compared with MCR-ALS using different constraints in analyzing the data for a simulated and also for a real system. The nD-Asyn produced correct spectrum of every component. Only when complete constraints obtained from nD-Asyn method is utilized in the MCR-ALS calculation, correct spectra of all the components can be obtained. Thus, nD-Asyn can be used alone or in conjunction with MCR-ALS to analyze bilinear data containing contributions of multiple components.