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Pesticide poisoning constantly threatens bees as they forage for resources in pesticide-treated crops. This poisoning requires thorough investigation to identify its causes, underscoring the importance of reliable pesticide detection methods for bee monitoring. Infrared spectroscopy provides reflectance data across hundreds of spectral bands (hyperspectral reflectance), presumably enabling the efficient classification of pesticide contamination in bee carcasses using artificial intelligence (AI) models, such as machine learning. In this study, bee contamination by commercial formulations of three insecticides-dimethoate (organophosphate), fipronil (phenylpyrazole), and imidacloprid (neonicotinoid)-as well as glyphosate, the most widely used herbicide globally, was detected using machine learning models. These models classified the hyperspectral reflectance profiles of the body surfaces of contaminated bees. The best-performing model, the linear discriminant analysis, achieved 98 % accuracy in discriminating contamination across species Apis mellifera, Melipona mondury, and Partamona helleri, with prediction speeds of 0.27 s. Our pioneering study introduced an effective method for discerning multiple classes of bees contaminated with pesticides using hyperspectral reflectance. An AI-driven spectral data analysis tool (https://github.com/bernardesrodrigoc/MACSS) was developed for the purpose of identifying and characterizing new samples through their spectral characteristics. This platform aids efforts to monitor and conserve bee populations and holds potential importance in environmental monitoring, agricultural research, and industrial quality control., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could to influence the results or interpretation reported in this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The main proteases M pro are a group of highly conserved cysteine hydrolases in β-coronaviruses. They have been demonstrated to play an unavoidable role in viral replication, and consequently they have been suggested as key targets for treating coronavirus-caused infectious diseases, mainly from the COVID-19 epidemic. Since the most functional form for M pro enzymatic activity is associated to its homodimer, compounds inhibiting dimerization should also inhibit catalytic activity. We show how PIR-SEIRA (Plasmonic Internal Reflection-Surface Enhanced InfraRed Absorption) spectroscopy can be a noteworthy technique to study proteins subtle structural variations associated to inhibitor binding. Nanoantennas arrays can selectively confine and enhance electromagnetic field via localized plasmonic resonances, thus promoting ultrasensitive detection of biomolecules in close proximity of nanoantenna arrays and enabling the effective investigation of protein monolayers. By adopting this approach, reflection measurements conducted under back illumination of nanoantennas allow to probe anchored protein monolayers, with minimum contribution of environmental buffer molecules. PIR-SEIRA spectroscopy on M pro was carried out by ad hoc designed devices, resonating in the spectral region of Amide I and Amide II bands. We evaluated here the structure of anchored monomers and dimers in different buffered environment and in presence of a newly designed M pro inhibitor. Experimental results show that dimerization is not associated to relevant backbone rearrangements of the protein at secondary structure level, and even if the compound inhibits the dimerization, it is not effective at breaking preformed dimers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Vibrational non-Condon effects, which describe how molecular vibrational transitions are influenced by a system's rotational and translational degrees of freedom, are often overlooked in spectroscopy studies of biological macromolecules. In this work, we explore these effects in the modeling of infrared (IR) spectra for nucleic acids in the 1600-1800 cm -1 region. Through electronic structure calculations, we reveal that the transition dipole moments of the C═O and C═C stretching modes in nucleobases are highly sensitive to solvation, hydrogen bonding, and base stacking conditions. To incorporate vibrational non-Condon effects into spectroscopy modeling, we use local electric fields on chromophore atoms as collective coordinates and leverage experimental IR spectra of oligonucleotides to develop deep neural network-based transition dipole strength (TDS) maps for the C═O and C═C chromophores. By integrating molecular dynamics simulations with a mixed quantum/classical treatment of the line shape theory, we apply the TDS maps to calculate the IR spectra of nucleoside 5'-monophosphates, DNA double helices and yeast phenylalanine tRNA. The resulting theoretical spectra show quantitative agreement with experimental measurements. While the predictions for nucleoside 5'-monophosphates are comparable to baseline performance, the TDS maps yield significantly improved IR peak intensities across all oligonucleotides. This theoretical framework effectively bridges atomistic simulations and IR spectroscopy experiments, offering molecular insights into how vibrational non-Condon effects impact the observed spectral features.

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. Currently, the medical diagnosis of SLE mainly relies on the clinical experience of physicians, and there is no universally accepted objective method for diagnosing SLE. Therefore, there is an urgent need to design an intelligent approach to accurately diagnose SLE to assist physicians in formulating appropriate treatment plans. With the rapid development of intelligent medical diagnostic technology, medical data is becoming increasingly multimodal. Multimodal data fusion can provide richer information than single-modal data, and the fusion of multiple modalities can effectively enhance the richness of data features to improve modeling performance., Results: In this paper, a cross-modal specific transfer fusion technique based on infrared spectra and metabolomics is proposed to effectively integrate infrared spectra and metabolomics by fully exploiting the intrinsic relationships between features across different modalities, thus achieving the diagnosis of SLE. In this research, a Decision Level Fusion module is also proposed to fuse the representations of two specific transfers further, obtaining the final prediction scores. Comprehensive experimental results demonstrate that the proposed method significantly improves the performance of SLE prediction, with accuracy and Area Under Curve (AUC) reaching 94.98 % and 97.13 %, respectively, outperforming existing methods., Significance: Our framework effectively integrates infrared spectra and metabolomics to achieve a more accurate prediction of SLE. Our research indicates that prediction methods based on different modalities outperform those using single-modality data. The Cross-modal Specific Transfer Fusion module effectively captures the complex relationships within each single modality and models the complex relationships between different modalities., Competing Interests: Declaration of competing interest, (Copyright © 2024 Elsevier B.V. All rights reserved.)

To analyze the effect of various drying treatments (microwave drying (MD), hot air drying (HAD), vacuum drying (VD), and vacuum freeze drying (VFD)) on taste compounds in Penaeus vannamei, relevant indicators such as free amino acids, 5'-nucleotides, and organic acids were performed. Multidimensional infrared spectroscopy (MM-IR) results found that there were notable variations in taste properties of P. vannamei. There were 18 autocorrelation peaks in 3400-900 cm -1 were screened using second-derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR). Variations in functional groups were the major contributors to taste profiles. The TAV of glutamic acid (Glu), guanine (GMP), and inosinemonphosphate (IMP) were greater than one and had notable impacts on taste profiles. VD had the highest equivalent umami value, followed by VFD, HAD, and MD. This study may provide a theoretical guide for the production of dried P. vannamei products on an industrial scale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Metalated intact and deprotonated histidyl glycine and glycyl histidine dipeptides were investigated in the gas phase by using infrared multiple photon dissociation (IRMPD) spectroscopy with light from a free-electron laser (FEL). The dipeptides M 2+ (GlyHis), M 2+ (HisGly), [M(GlyHis-H)] + , and [M(HisGly-H)] + , where M = Zn and Cd, were probed to elucidate how the His position along the peptide chain and ligand charge state might influence the structures observed in the gas phase. Simulated annealing calculations were performed to determine energetically low-lying conformers and isomers of these structures. Quantum chemical calculations were used to optimize the structures at the B3LYP level of theory using the 6-311+G(d,p) and def2-TZVP basis sets for zinc and cadmium complexes, respectively. IRMPD and calculated linear absorption spectra were compared to evaluate which structures are present. Relative energies of the various species were evaluated using single-point energy calculations for low-lying structures at the B3LYP, B3LYP-GD3BJ, ωB97XD, and MP2(full) levels using the 6-311+G(2d,2p) and def2-TZVPP basis sets. For all species, structures for both metals mirror each other, and those that reproduce the experimental spectrum were determined to be iminol structures for the intact ligands or iminol-like structures for the deprotonated ligands. Additionally, when the spectra of the deprotonated dipeptides are compared to the intact dipeptides, the change in the spectra is correlated to the group that is deprotonated.

The incorporation of fluorine into amino acids is an important strategy to produce tailored building blocks with unique properties for peptide-based materials. Phenylalanine is frequently modified due to its role in cation-π interactions and the formation of amyloid fibres. Previous studies have utilized gas-phase vibrational spectroscopy to study interactions between canonical amino acids. In this study, we employ a combination of cryogenic gas-phase infrared spectroscopy and density functional theory to study the interactions in proton-bound dimers of side-chain fluorinated phenylalanines. Our findings reveal how the position and number of fluorine atoms affect the interactions and structures of the dimers. Monofluorinated phenylalanines adopt charge-solvated structures in which the two amino acids interact via their ammonium and amine functions (NH 3 + ⋯NH 2 ). The dimer with the perfluorinated side chain forms multiple charge-solvated and salt-bridged structures with varying interaction types. These structural changes are attributed to the significant reduction of electron density in the aromatic systems.

Forensic entomology plays an important role in medicolegal investigations by using insects, primarily flies, to estimate the time of colonization. This estimation relies on the development of the flies found at the (death) scene and can be affected (and sometimes corrected) by external factors, such as temperature and humidity, and internal factors, such as species and sex. This study leverages infrared (IR) spectroscopy combined with machine learning models-Partial Least Squares Discriminant Analysis (PLS-DA) and eXtreme Gradient Boosting trees Discriminant Analysis (XGBDA)-to differentiate between male and female Cochliomyia macellaria larvae, commonly found on human remains. Significant vibrational differences were detected in the infrared spectra of third instar C. macellaria larvae, with distinct peaks showing variations in relative absorbance between sexes, suggesting differences in biochemical compositions such as cuticular proteins and lipids. The application of PLS-DA and XGBDA yielded high classification accuracies of about 94% and 96%, respectively, with female spectra consistently having higher sensitivity than males. This non-destructive approach offers the potential to refine supplemental post-mortem interval estimations significantly, enhancing the accuracy of forensic analyses., (© 2024 American Academy of Forensic Sciences.)

Calcium-protein interactions are of paramount importance in biochemistry. They are a key element in a number of biological processes, such as neuronal signaling. Therefore, an understanding of the interaction at the molecular level is highly desirable. Here, we study the zwitterionic model peptide l-alanyl- l -alanine (2Ala), which has two distinct and competing binding sites for Ca 2+ : The carbonyl of the peptide bond and the C -terminus, the carboxylate group. We perform linear and two-dimensional IR spectroscopy experiments and find that the spectroscopic signatures of both moieties in the IR spectra change in amplitude and peak position upon the addition of CaCl 2 : A blueshift of the asymmetric carboxylate band and a redshift for the amide I mode. Ab initio molecular dynamics simulations confirm the direct interaction of the Ca 2+ ion at both the carboxylate and the amide CO site leading to different spectral responses. The blueshift of the asymmetric carboxylate band is caused by a localization of the charge, leading to a decoupling of the CO stretching modes of the carboxylate group. The slight redshift of the amide I mode of 2Ala upon the addition of CaCl 2 contrasts the blueshift that has been observed for isolated amide motifs, such as N -methylacetamide (NMA). This difference is caused by the smaller number of water molecules being replaced by the Ca 2+ ion for 2Ala's amide compared to less sterically hindered, isolated amide carbonyls, in conjunction with vibrational Stark effects. Our results highlight the importance of considering potential competing binding sites, such as the amide CO backbone, the termini and residues, as well as the nature of the hydration of both peptide and ion, when exploring ions' interacting with small peptides and larger proteins.

Since both top and bottom illuminations are widely used in infrared transmission measurements, in this paper, we study the effects of different illuminations on the signatures in infrared microspectroscopy. By simulating a series of dielectric samples, we show that their extinction efficiency, Q ext , remains unchanged when the direction of the incident plane wave is reversed, even though the field distributions both inside and outside of the sample may be dramatically different. We find features in Q ext that are correlated with whispering gallery modes for one beam direction and correspond to completely different field distributions for the opposite beam direction. In addition, by linking the optical theorem and the reciprocity relation of far-field scattered field, we rigorously prove the invariance of Q ext for arbitrary dielectric targets under opposite plane-wave illuminations. Furthermore, we show the difference in the apparent absorbance spectrum for opposite beam directions when considering numerical apertures., (© 2024 The Author(s). Journal of Biophotonics published by Wiley‐VCH GmbH.)

Myricetin (1), Quercetin (2), Kaempferol (3) and Kaempferide (4) were flavonoids with phenolic hydroxyl groups. The antioxidant and pharmacological mechanisms of them were investigated in detail. The lowest hydroxyl dissociation enthalpies of 1, 2, 3 and 4 were calculated by DFT, respectively. The hydroxyl dissociation enthalpies of the four flavonoids at the O2 site are the highest. By analyzing the intramolecular hydrogen bonds and HOMO-LUMO orbitals of the four flavonoids, the reasons for their divergence of hydroxyl dissociation enthalpies and antioxidant mechanisms were further investigated. The UV-vis and IR spectra of four flavonoids were compared. The interactions about electrostatic attraction, p-π conjugation and hydrogen bond combined the flavonoid with the target protein closely. The root mean square deviation of peroxisome proliferator-activated receptor γ combined with 1, 2 and 3 increased, while that of PPARγ combined with 4 decreased., (© 2024 Wiley-VHCA AG, Zurich, Switzerland.)

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm -1 ), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations., (© 2024 Wiley‐VCH GmbH.)

The combination of infrared spectroscopy (IR) and ion mobility mass spectrometry (IM-MS) has revealed that protein secondary structures are retained upon transformation from aqueous solution to the gas phase under gentle conditions. Yet the details about where and how these structural elements are embedded in the gas phase remain elusive. In this study, we employ long time scale molecular dynamics (MD) simulations to examine the extent to which proteins retain their solution structures and the impact of protonation state on the stability of secondary structures in the gas phase. Our investigation focuses on two well-studied proteins, myoglobin and β-lactoglobulin, representing typical helical and β-sheet proteins, respectively. Our simulations accurately reproduce the experimental collision cross section (CCS) data measured by IM-MS. Based on accurately reproducing previous experimental collision cross section data and dominant secondary structural species obtained from IM-MS and IR, we confirm that both proteins largely retain their native secondary structural components upon passing from aqueous solution to the gas phase. However, we observe significant reductions in secondary structure contents (19.2 ± 1.2% for myoglobin and 7.3 ± 0.6% for β-lactoglobulin) in specific regions predominantly composed of ionizable residues. Further mechanistic analysis suggests that alterations in protonation states of these residues after phase transition induce changes in their local interaction networks and backbone dihedral angles, which potentially promote the unfolding of secondary structures in the gas phase. We anticipate that similar protonation state induced unfolding may be observed in other proteins possessing distinct secondary structures. Further studies on a broader array of proteins will be essential to refine our understanding of protein structural behavior during the transition to the gas phase.

Although the measurement of tooth quality is necessary for precise prediction of caries formation, typical measurement methods include tooth-hardness measurements and absorption spectroscopy, which generally use infrared light irradiation. These methods are destructive or invasive, and obtaining two-dimensional information in the oral cavity is difficult. Mid-infrared emissions from the surface of an object reflect intrinsic vibrations of molecules in the object. In this study, a mid-infrared passive spectroscopic imaging system was developed using an inexpensive uncooled microbolometer array sensor with an optimized multi-slit, which eliminated the cancellation of interference intensities between two adjacent emission points, to obtain two-dimensional information from an object without external infrared light irradiation. First, the feasibility of obtaining two-dimensional information on tooth quality using the proposed system was examined, and emission spectra attributed to phosphate ions in hydroxyapatite (HAp), the main component of enamel, were successfully obtained from bovine teeth. Further, the hardness of bovine teeth was measured, and a correlation ( R 2 = 0.8067) between the Vickers hardness and peak area ratio of phosphate ions assigned to the crystalline and amorphous phases of a tooth was established. Additionally, tooth-hardness visualization in a non-contact manner was demonstrated as two-dimensional information using the obtained regression equation.

A mid-infrared label-free immunoassay-based biosensor is an effective device to help identify and quantify biomolecules. This biosensor employs a surface-enhanced infrared absorption spectroscopy, which is a highly potent sensing technique for detecting minute quantities of analytes. In this study, a biosensor was constructed using a metamaterial absorber, which facilitated strong coupling effects. For maximum coupling effect, it is necessary to enhance the near-field intensity and the spatial and spectral overlap between the optical cavity resonance and the vibrational mode of the analyte. Due to significant peak splitting, conventional baseline correction methods fail to adequately analyze such a coupling system. Therefore, we employed a coupled harmonic oscillation model to analyze the spectral distortion resulting from the peak splitting induced by the strong coupling effect. The proposed biosensor with a thrombin-binding aptamer-based immunoassay could achieve a limit of detection of 267.4 pM, paving the way for more efficient protein detection in clinical practice., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jongwon Lee reports financial support was provided by National Research Foundation of Korea. Joo-Yun Jung reports financial support was provided by Korea Ministry of Trade Industry and Energy. Joo-Yun Jung reports financial support was provided by National Research Council of Science and Technology. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Plastic pollution is now ubiquitous in the environment and represents a growing threat to wildlife, who can mistake plastic for food and ingest it. Tackling this problem requires reliable, consistent methods for monitoring plastic pollution ingested by seabirds and other marine fauna, including methods for identifying different types of plastic. This study presents a robust method for the rapid, reliable chemical characterisation of ingested plastics in the 1-50 mm size range using infrared and Raman spectroscopy. We analysed 246 objects ingested by Flesh-footed Shearwaters (Ardenna carneipes) from Lord Howe Island, Australia, and compared the data yielded by each technique: 92 % of ingested objects visually identified as plastic were confirmed by spectroscopy, 98 % of those were low density polymers such as polyethylene, polypropylene, or their copolymers. Ingested plastics exhibit significant spectral evidence of biological contamination compared to other reports, which hinders identification by conventional library searching. Machine learning can be used to identify ingested plastics by their vibrational spectra with up to 93 % accuracy. Overall, we find that infrared is the more effective technique for identifying ingested plastics in this size range, and that appropriately trained machine learning models can be superior to conventional library searching methods for identifying plastics., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Joseph Razzell Hollis reports financial support was provided by EU Framework Programme for Research and Innovation Marie Sklodowska-Curie Actions. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The aim of this study is to evaluate the ability of infrared wavenumber of calculus to predict postoperative infection in patients with upper urinary tract calculus (UUTC), and to establish a predictive model based on this. From March 2018 to March 2023, 480 UUTC patients from Fujian Provincial Hospital were included in this study. The infrared-wavenumbers related infection score (IR-infection score) was constructed by univariate analysis, multicollinearity screening, and Lasso analysis to predict postoperative infection. Continually, the Delong test was used to compare the predictive power between the IR-infection score and traditional indicators. Afterward, we performed urine metagene sequencing and stone culture to prove the correlation between calculus toxicity and IR-infection score. Finally, logistic regression was used to build a nomogram. IR-infection score composed of four independent wavenumbers could precisely predict postoperative infection (AUC validation cohort  = 0.707) and sepsis (AUC validation cohort  = 0.824). IR-infection score had better predictive ability than commonly used clinical indicators. Moreover, metagenomics sequencing and calculus culture confirmed the correlation between IR-infection score and calculus toxicity (all P < 0.05). The nomogram based on the IR-infection score had high predictive power (all AUCs > 0.803). Our study first developed a novel infrared spectroscopy marker and nomogram, which can help urologists better predict postoperative infection in UUTC patients., (© 2024. The Author(s).)

Electron spin resonance coupled with uranium-series dating (ESR/U-series) of carbonate hydroxyapatite in tooth enamel is the main technique used to obtain age determinations from Pleistocene fossils beyond the range of radiocarbon dating. This chronological information allows to better understand diachronic change in the palaeontological record, especially with regard to the evolution of the genus Homo. Given the relative paucity of human teeth at palaeontological and archaeological localities, ESR/U-series is widely applied to the teeth of ungulate species. However, the accuracy of ESR/U-series ages is greatly affected by the incorporation of uranium in the enamel during burial in sediments. It has been shown that uranium content is positively correlated with an increased degree of atomic order in carbonate hydroxyapatite crystals, the latter determined using infrared spectroscopy. Here we present a reference infrared spectral library of tooth enamel from African ungulates, based on the grinding curve method, which serves as baseline to track the diagenetic history of carbonate hydroxyapatite in different species and thus select the best-preserved specimens for dating., (© 2024. The Author(s).)

The dynamics of lysozyme is probed by attaching -SCN to all alanine residues. The one-dimensional infrared spectra exhibit frequency shifts in the position of the maximum absorption of 4 cm-1, which is consistent with experiments in different solvents and indicates moderately strong interactions of the vibrational probe with its environment. Isotopic substitution 12C → 13C leads to a redshift by -47 cm-1, which agrees quantitatively with experiments for CN-substituted copper complexes in solution. The low-frequency, far-infrared part of the protein spectra contains label-specific information in the difference spectra when compared with the wild type protein. Depending on the position of the labels, local structural changes are observed. For example, introducing the -SCN label at Ala129 leads to breaking of the α-helical structure with concomitant change in the far-infrared spectrum. Finally, changes in the local hydration of SCN-labeled alanine residues as a function of time can be related to the reorientation of the label. It is concluded that -SCN is potentially useful for probing protein dynamics, both in the high-frequency part (CN-stretch) and in the far-infrared part of the spectrum., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

The infrared spectroscopy (IR) signal of protein is prone to being covered by impurity signals, and the accuracy of the secondary structure content calculated using spectral data is poor. To tackle this challenge, a rapid high-precision quantitative model for protein secondary structure was proposed. Firstly, a two-dimensional correlation calculation was performed based on 60 groups of soybean protein isolates (SPI) infrared spectroscopy data, resulting in a two-dimensional correlation infrared spectroscopy (2DCOS-IR). Subsequently, the optimal characteristic bands of the four secondary structures were extracted from the 2DCOS-IR. Ultimately, partial least squares (PLS), long short-term memory (LSTM), and bidirectional long short-term memory (BILSTM) algorithms were used to model the extracted characteristic bands and predict the content of SPI secondary structure. The findings suggested that BILSTM combined with 2DCOS-IR model (2DCOS-BILSTM) exhibited superior predictive performance. The prediction sets for α-helix, β-sheet, β-turn, and random coil were designated as 0.9257, 0.9077, 0.9476, and 0.8443, respectively, and their corresponding RMSEP values were 0.26, 0.48, 0.20, and 0.15. This strategy enhances the precision of IR and facilitates the rapid identification of secondary structure components within SPI, which is vital for the advancement of protein industrial production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Due to their widespread production and known environmental contamination, the need for the detection and remediation of per- and polyfluoroalkyl substances (PFAS) has grown quickly. While destructive thermal treatment of PFAS at low temperatures (e.g., 200-500 °C) is of interest due to lower energy and infrastructure requirements, the range of possible degradation products remains underexplored. To better understand the low temperature decomposition of PFAS species, we have coupled gas-phase infrared spectroscopy with a multivariate curve resolution (MCR) analysis and a database of high-resolution PFAS infrared reference spectra to characterize and quantify a complex mixture resulting from potassium perfluorooctanesulfonate (PFOS-K) decomposition. Beginning at 375 °C, nine prevalent decomposition products (namely smaller perfluorocarbon species) are identified and quantified., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

C-phycocyanin (C-PC) is the main component of water-soluble light-harvesting complexes (phycobilisomes, PBS) of cyanobacteria. PBS are involved in the absorption of quantum energy and the transfer of electronic excitation energy to the photosystems. A specific environment of C-PC chromophoric groups is provided by the protein matrix structure including protein-protein contacts between different subunits. Registration of C-PC spectral characteristics and the fluorescence anisotropy decay have revealed a significant pH influence on the chromophore microenvironment: at pH 5.0, a chromophore is more significantly interacts with the solvent, whereas at pH 9.0 the chromophore microenvironment becomes more viscous. Conformations of chromophores and the C-PC protein matrix have been studied by Raman and infrared spectroscopy. A decrease in the medium pH results in changes in the secondary structure either the C-PC apoproteins and chromophores, the last one adopts a more folded conformation., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Enniatins are mycotoxins with well-known antibacterial, antifungal, antihelmintic and antiviral activity, which have recently come to attention as potential mitochondriotoxic anticancer agents. The cytotoxicity of enniatins is traced back to ionophoric properties, in which the cyclodepsipeptidic structure results in enniatin:cation-complexes of various stoichiometries proposed as membrane-active species. In this work, we employed a combination of surface-enhanced infrared absorption (SEIRA) spectroscopy, tethered bilayer lipid membranes (tBLMs) and density functional theory (DFT)-based computational spectroscopy to monitor the cation-dependence (M z+ =Na + , K + , Cs + , Li + , Mg 2+ , Ca 2+ ) on the mechanism of enniatin B (EB) incorporation into membranes and identify the functionally relevant EB n  : M z+ complexes formed. We find that Na + promotes a cooperative incorporation, modelled via an autocatalytic mechanism and mediated by a distorted 2 : 1-EB 2  : Na + complex. K + (and Cs + ) leads to a direct but less efficient insertion into membranes due to the adoption of "ideal" EB 2  : K + sandwich complexes. In contrast, the presence of Li + , Mg 2+ , and Ca 2+ causes a (partial) extraction of EB from the membrane via the formation of "belted" 1 : 1-EB : M z+ complexes, which screen the cationic charge less efficiently. Our results point to a relevance of the cation dependence for the transport into the malignant cells where the mitochondriotoxic anticancer activity is exerted., (© 2024 The Authors. ChemPlusChem published by Wiley-VCH GmbH.)

In this perspective, gas-phase studies of group 1 monocations and group 12 dications with amino acids and small peptides are highlighted. Although the focus is on two experimental techniques, threshold collision-induced dissociation and infrared multiple photon dissociation action spectroscopy, these methods as well as complementary approaches are summarized. The synergistic interplay with theory, made particularly powerful by the small sizes of the systems explored and the absence of solvent and support, is also elucidated. Importantly, these gas-phase methods permit quantitative insight into the structures and thermodynamics of metal cations interacting with biological molecules. Periodic trends in how these interactions vary as the metal cations get heavier are discussed as are quantitative trends with changes in the amino acid side chain and effects of hydration. Such trends allow these results to transcend the limitations associated with the biomimetic model systems.

Evaluating the dynamic interaction of microorganisms and mammalian cells is challenging due to the lack of suitable platforms for examining interspecies interactions in biologically relevant coculture conditions. In this work, we demonstrate the interaction between probiotic bacteria ( Lactococcus lactis and Escherichia coli ) and A498 human cancer cells in vitro , utilizing a hydrogel-based platform in a label-free manner by infrared spectroscopy. The L. lactis strain recapitulated in the compartment system secretes polypeptide molecules such as nisin, which has been reported to trigger cell apoptosis. We propose a mid-infrared (IR) spectroscopic imaging approach to monitor the variation of biological components utilizing kidney cells (A498) as a model system cocultured with bacteria. We characterized the biochemical composition (i.e., nucleic acids, protein secondary structures, and lipid conformations) label-free using an unbiased measurement. Several IR spectral features, including unsaturated fatty acids, β-turns in protein, and nucleic acids, were utilized to predict cellular response. These features were then applied to establish a quantitative relationship through a multivariate regression model to predict cellular dynamics in the coculture system to assess the effect of nisin on A498 kidney cancer cells cocultured with bacteria. Overall, our study sheds light on the potential of using IR spectroscopic imaging as a label-free tool to monitor complex microbe-host cell interactions in biological systems. This integration will enable mechanistic studies of interspecies interactions with insights into their underlying physiological processes.

We successfully designed curcumin (Cur)-loaded composite nanoparticles consisting of high-hydrostatic-pressure-treated (HHP-treated) zein and pectin with a pressure of 150 MPa (zein-150 MPa-P-Cur), showing nano-spherical structure with high zeta-potential (-36.72 ± 1.14 mV) and encapsulation efficiency (95.64 ± 1.23 %). We investigated the interaction mechanism of the components in zein-150 MPa-P-Cur using fluorescence spectroscopy, molecular dynamics simulation, Fourier-transform infrared spectrometry and scanning electron microscopy techniques. Compared with zein-P-Cur, the binding sites and binding energy (-53.68 kcal/mol vs. - 44.22 kcal/mol) of HHP-treated zein and Cur were increased. Meanwhile, the interaction force among HHP-treated zein, pectin, and Cur was significantly enhanced, which formed a tighter and more stable particle structure to further improve package performance. Additionally, Cur showed the best chemical stability in zein-150 MPa-P-Cur. And the bioavailability of Cur was increased to 65.53 ± 1.70 %. Collectively, composite nanoparticles based on HHP-treated zein and pectin could be used as a promising Cur delivery system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Diatoms, unicellular marine organisms, harness short peptide repeats of the protein silaffin to transform silicic acid into biosilica nanoparticles. This process has been a white whale for material scientists due to its potential in biomimetic applications, ranging from medical to microelectronic fields. Replicating diatom biosilicification will depend on a thorough understanding of the silaffin peptide structure during the reaction, yet existing models in the literature offer conflicting views on peptide folding during silicification. In our study, we employed two-dimensional infrared spectroscopy (2DIR) within the amide I region to determine the secondary structure of the silaffin repeat unit 5 (R5), both pre- and post-interaction with silica. The 2DIR experiments are complemented by molecular dynamics (MD) simulations of pure R5 reacting with silicate. Subsequently, theoretical 2DIR spectra calculated from these MD trajectories allowed us to compare calculated spectra with experimental data, and to determine the diverse structural poses of R5. Our findings indicate that unbound R5 predominantly forms β-strand structures alongside various atypical secondary structures. Post-silicification, there's a noticeable shift: a decrease in β-strands coupled with an increase in turn-type and bend-type configurations. We theorize that this structural transformation stems from silicate embedding within R5's hydrogen-bond network, prompting the peptide backbone to contract and adapt around the biosilica precursors.

Growing attention is being directed towards exploring the potential harmful effects of microplastic (MP) particles on human health. Previous reports on human exposure to MPs have primarily focused on inhalation, ingestion, transdermal routes, and, potentially, transplacental transfer. The intravenous transfer of MP particles in routine healthcare settings has received limited exploration in existing literature. Standard hospital IV system set up with 0.9 % NaCl in a laminar flow hood with MP contamination precautions. Various volumes of 0.9 % NaCl passed through the system, some with a volumetric pump. Fluid filtered with Anodisc filters washed with isopropyl alcohol. The IV cannula was immersed in Mili-Q water for 72 h to simulate vein conditions. Subsequently, the water was filtered and washed. Optical photothermal infrared (O-PTIR) microspectroscopy is used to examine filters for MP particles. All filters examined from the IV infusion system contained MP particles, including MPs from the polymer materials used in the manufacture of the IV delivery systems (polydimethylsiloxane, polypropylene, polystyrene, and polyvinyl chloride) and MP particles arising from plastic resin additives (epoxy resin, polyamide resin, and polysiloxane-containing MPs). The geometric mean from the extrapolated result data indicated that approximately 0.90 MP particles per mL of 0.9 % NaCl solution can be administered through a conventional IV infusion system in the absence of a volumetric pump. However, with the implementation of a pump, this value may increase to 1.57 particles per mL. Notably, over 72 h, a single cannula was found to release approximately 558 MP particles including polydimethylsiloxane, polysiloxane-containing MPs, polyamide resin, and epoxy resin. Routine IV infusion systems release microplastics. MP particles are also released around IV cannulas, suggesting transfer into the circulatory system during standard IV procedures., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jun-Li Xu and Abhrajyoti Tarafdar reports financial support was provided by Science Foundation Ireland. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Local H-bonding interactions are crucial for proteins to undergo various structural transitions and form different secondary structures. However, identifying slight distinctions in the local H-bonding of proteins is rather challenging. Here, we demonstrate that the Fermi resonance of the N-D stretching mode can provide an effective probe for the localized H-bonding environment of proteins both at the surface/interface and in the bulk. Using sum frequency generation vibrational spectroscopy and infrared spectroscopy, we established a correlation between the Fermi resonance of the N-D mode and protein secondary structures. The H-bond of N-D···C═O splits the N-D modes into two peaks (∼2410 and ∼2470 cm -1 ). The relative strength ratio ( R ) between the ∼2410 cm -1 peak and the ∼2470 cm -1 peak is very sensitive to H-bond strength and protein secondary structure. R is less than 1 for α-helical peptides, while R is greater than 1 for β-sheet peptides. For R < 2.5, both α-helical/loop structures and β-sheet structures exhibit almost identical Fermi coupling strengths ( W = 28 cm -1 ). For R > 2.5, W decreases from 28 to 14 cm -1 and depends on the aggregation degree of the β-sheet oligomers or fibrils. The initial local H-bonding status impacts the misfolding dynamics of proteins at the lipid bilayer interface.

Lanmodulins are small, ∼110-residue proteins with four EF-hand motifs that demonstrate a picomolar affinity for lanthanide ions, making them efficient in the recovery and separation of these technologically important metals. In this study, we examine the thermodynamic and structural complexities of lanthanide ion binding to a 41-residue domain, EF 2-3, that constitutes the two highest-affinity metal-binding sites in the lanmodulin protein from Methylorubrum extorquens . Using a combination of circular dichroism (CD) spectroscopy, isothermal titration calorimetry (ITC), two-dimensional infrared (2D IR) spectroscopy, and molecular dynamics (MD) simulations, we characterize the metal binding capabilities of EF 2-3. ITC demonstrates that binding occurs between peptide and lanthanides with conditional dissociation constants ( K d ) in the range 20-30 μM, with no significant differences in the K d values for La 3+ , Eu 3+ , and Tb 3+ at pH 7.4. In addition, CD spectroscopy suggests that only one binding site of EF 2-3 undergoes a significant conformational change in the presence of lanthanides. 2D IR spectroscopy demonstrates the presence of both mono- and bidentate binding configurations in EF 2-3 with all three lanthanides. MD simulations, supported by Eu 3+ luminescence measurements, explore these results, suggesting a competition between water-lanthanide and carboxylate-lanthanide interactions in the EF 2-3 domain. These results underscore the role of the core helical bundle of the protein architecture in influencing binding affinities and communication between the metal-binding sites in the full-length protein.

We present a detailed study of the time-dependent photophysics and photochemistry of a known conformation of the two protonated pentapeptides Leu-enkephalin (Tyrosine-Glycine-Glycine-Phenylalanine-Leucine, YGGFL) and its chromophore-swapped analogue FGGYL, carried out under cryo-cooled conditions in the gas phase. Using ultraviolet-infrared (UV-IR) double resonance, we record excited state IR spectra as a function of time delay between UV and IR pulses. We identify unique Tyr OH stretch transitions due to the S 1 state and the vibrationally excited triplet state(s) formed by intersystem crossing, T n (v). Photofragment mass spectra are recorded out of the S 1 origin and following UV-IR double resonance. Several competing site-specific fragmentation pathways are discovered involving peptide backbone cleavage, Tyr side chain loss, and N-terminal NH 3 loss mediated by electron transfer. In YGGFL, IR excitation in the S 1 state promotes electron transfer (ET) from the aromatic ring to the N-terminal R-NH 3 + group leading to loss of neutral NH 3 . This product channel is missing in FGGYL due to the larger distance for ET from Y(4) to NH 3 + . Selective loss of the Tyr side chain occurs out of an excited state process following UV excitation and is further enhanced by IR excitation in S 1 and T n (v) states of both YGGFL and FGGYL. Finally, IR excitation in the S 1 or T n (v) states fragments the peptide backbone exclusively at amide(4), producing the b 4 cation. We postulate that this selective fragmentation results from intersystem crossing to produce vibrationally excited triplets with enough energy to launch the proton along a proton conduit present in the known starting structure.

Vibrational circular dichroism (VCD) spectra have been computed with qualitatively correct sign patterns for α-helical peptides using various methods, ranging from empirical models to ab initio quantum mechanical computations. However, some details, such as deuteration effects and isotope substitution shifts and sign patterns for the resultant amide I' band shape, have remained a predictive challenge. Fully optimized computations for a 25-residue Ala-rich peptide, including implicit solvent corrections and explicit side chains that experimentally stabilize these model helical peptides in water, have been carried out using density functional theory (DFT). These fully minimized structures show minor changes in the (ϕ,ψ) torsions at the termini and yield an extra negative band to the low energy side of the characteristic amide I' couplet VCD, in agreement with experiments. Additionally, these calculations give the right sign and relative intensity patterns, as compared to experimental results, for several 13 C=O substituted variants. The differences from previously reported computations that used ideal helical structures and vacuum conditions imply that inclusion of distorted termini and solvent effects can have an impact on the final detailed spectral patterns. Inclusion of side chains in these calculations had very little effect on the computed amide I' IR and VCD. Tests of constrained geometries, varying dielectric, and different functionals indicate that each can affect the band shapes, particularly for the 12 C=O components, but these aspects do not fully explain the difference from previous spectral simulations. Inclusion of long-range amide coupling, as obtained from DFT computation of the full structure, or transfer of parameters from a somewhat longer peptide model, rather than shorter model, seems to be more important for the final detailed band shape under isotopic substitution. However, these corrections can also induce other changes, suggesting that previously reported, limited calculations may have been qualitatively useful due to a balance of errors. This may also explain the success of simple empirical IR models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Protonated ions of fucose-containing oligosaccharides are prone to undergo internal glycan rearrangement which results in chimeric fragments that obfuscate mass-spectrometric analysis. Lack of accessible tools that would facilitate systematic analysis of glycans in the gas phase limits our understanding of this phenomenon. In this work, we use density functional theory modeling to interpret cryogenic IR spectra of Lewis a and blood group type H1 trisaccharides and to establish whether these trisaccharides undergo the rearrangement during gas-phase analysis. Structurally unconstrained search reveals that none of the parent ions constitute a thermodynamic global minimum. In contrast, predicted collision cross sections and anharmonic IR spectra provide a good match to available experimental data which allowed us to conclude that fucose migration does not occur in these antigens. By comparing the predicted structures with those obtained for Lewis x and blood group type H2 epitopes, we demonstrate that the availability of the mobile proton and a large difference in the relative stability of the parent ions and rearrangement products constitute the prerequisites for the rearrangement reaction.

Robust classification algorithms for high-dimensional, small-sample datasets are valuable in practical applications. Faced with the infrared spectroscopic dataset with 568 samples and 3448 wavelengths (features) to identify the origins of Chinese medicinal materials, this paper proposed a novel embedded multiclassification algorithm, ITabNet, derived from the framework of TabNet. Firstly, a refined data pre-processing (DP) mechanism was designed to efficiently find the best adaptive one among 50 DP methods with the help of Support Vector Machine (SVM). Following this, an innovative focal loss function was designed and joined with a cross-validation experiment strategy to mitigate the impact of sample imbalance on algorithm. Detailed investigations on ITabNet were conducted, including comparisons of ITabNet with SVM for the conditions of DP and Non-DP, GPU and CPU computer settings, as well as ITabNet against XGBT (Extreme Gradient Boosting). The numerical results demonstrate that ITabNet can significantly improve the effectiveness of prediction. The best accuracy score is 1.0000, and the best Area Under the Curve (AUC) score is 1.0000. Suggestions on how to use models effectively were given. Furthermore, ITabNet shows the potential to apply the analysis of medicinal efficacy and chemical composition of medicinal materials. The paper also provides ideas for multi-classification modeling data with small sample size and high-dimensional feature., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The Coronavirus Disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has required the search for sensitive, rapid, specific, and lower-cost diagnostic methods to meet the high demand. The gold standard method of laboratory diagnosis is real-time reverse transcription polymerase chain reaction (RT-PCR). However, this method is costly and results can take time. In the literature, several studies have already described the potential of Fourier transform infrared spectroscopy (FTIR) as a tool in the biomedical field, including the diagnosis of viral infections, while being fast and inexpensive. In view of this, the objective of this study was to develop an FTIR model for the diagnosis of COVID-19. For this analysis, all private clients who had performed a face-to-face collection at the Univates Clinical Analysis Laboratory (LAC Univates) within a period of six months were invited to participate. Data from clients who agreed to participate in the study were collected, as well as nasopharyngeal secretions and a saliva sample. For the development of models, the RT-PCR result of nasopharyngeal secretions was used as a reference method. Absorptions with high discrimination (p < 0.001) between GI (28 patients, RT-PCR test positive to SARS-CoV-2 virus) and GII (173 patients who did not have the virus detected in the test) were most relevant at 3512 cm -1 , 3385 cm -1 and 1321 cm -1 after 2nd derivative data transformation. To carry out the diagnostic modeling, chemometrics via FTIR and Discriminant Analysis of Orthogonal Partial Least Squares (OPLS-DA) by salivary transflectance mode with one latent variable and one orthogonal signal correction component were used. The model generated predictions with 100 % sensitivity, specificity and accuracy. With the proposed model, in a single application of an individual's saliva in the FTIR equipment, results related to the detection of SARS-CoV-2 can be obtained in a few minutes of spectral evaluation., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Calebe Fernando Juchem reports financial support, equipment, drugs, or supplies, and travel were provided by BRF SA., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Boronate esters are a class of compounds containing a boron atom bonded to two oxygen atoms in an ester group, often being used as precursors in the synthesis of other materials. The characterization of the structure and properties of esters is usually carried out by UV-visible, infrared, and nuclear magnetic resonance (NMR) spectroscopic techniques. With the aim to better understand our experimental data, in this article, the density functional theory (DFT) is used to analyze the UV-visible and infrared spectra, as well as the isotropic shielding and chemical shifts of the hydrogen atoms 1 H, carbon 13 C and boron 11 B in the compound 4-(4,4,5,5-tetramethyl-1,3,2-dioxoborolan-2-yl)benzaldehyde. Furthermore, this study considers the change in its electronic and spectroscopic properties of this particular ester, when its boron atom is coordinated with a fluoride anion. The calculations were carried out using the LSDA and B3LYP functionals in Gaussian-16, and PBE in CASTEP. The results show that the B3LYP functional gives the best approximation to the experimental data. The formation of a coordinated covalent B-F bond highlights the remarkable sensitivity of the NMR chemical shifts of carbon, oxygen, and boron atoms and their surroundings. Furthermore, this bond also highlights the changes in the electron transitions bands n → π * and π → π * during the absorption and emission of a photon in the UV-vis, and in the stretching bands of the C=C bonds, and bending of BO 2 in the infrared spectrum. This study not only contributes to the understanding of the properties of boronate esters but also provides important information on the interactions and responses optoelectronic of the compound when is bonded to a fluorine atom.

In aqueous binary solvents with fluorinated alcohols, 2,2,2-trifluoroethanol (TFE) and 1,1,1,3,3,3-hexafluoroisopropanol (HFIP), and aliphatic alcohols, ethanol (EtOH) and 2-propanol (2-PrOH), the denaturation of hen egg white lysozyme (HEWL) with increasing alcohol mole fraction x A has been investigated in a wide view from the molecular vibration to the secondary and ternary structures. Circular dichroism (CD) measurement showed that the secondary structure of α-helix content of HEWL increases on adding a small amount of the fluorinated alcohol to the aqueous solution, while the β-sheet content decreases. On the contrary, the secondary structure does not significantly change by the addition of the aliphatic alcohols. Correspondingly, the infrared (IR) spectroscopic measurements revealed that the amide I band red-shifts on the addition of the fluorinated alcohol. However, the band remains unchanged in the aliphatic alcohol systems with increasing alcohol content. To observe the ternary structure of HEWL, small-angle neutron scattering (SANS) experiments with H/D substitution technique have been applied to the HEWL solutions. The SANS experiments were successful in revealing the details of how the geometry of the HEWL changes as a function of x A . The SANS profiles indicated the spherical structure of HEWL in all of the alcohol systems in the x A range examined. The mean radius of HEWL in the two fluorinated alcohol systems increases from ∼16 to ∼18 Å during the change in the secondary structure against the increase in the fluorinated alcohol content. On contrast, the radius does not significantly change in both aliphatic alcohol systems below x A = 0.3 but expands to ∼19 Å as the alcohol content is close to the limitation of the HEWL solubility. According to the present results, together with our knowledge of the alcohol cluster formation and the interaction of the trifluoromethyl (CF 3 ) groups with the hydrophobic moieties of biomolecules, the effects of alcohols on the denaturation of the protein have been discussed on a molecular scale.

The cortical anthraquinone yellow-orange pigment parietin is a secondary lichen substance providing UV-shielding properties that is produced by several lichen species. In our work, the secondary metabolite has been extracted from air-dried thalli of Xanthoria parietina. The aims of this study were to characterize parietin absorbance through UV-VIS spectrophotometry and with IR spectroscopy and to evaluate its photodegradability under UV radiation through in situ reflectance IR spectroscopy to understand to what extent the substance may have a photoprotective role. This allows us to relate parietin photo-degradability to the lichen UV tolerance in its natural terrestrial habitat and in extreme environments relevant for astrobiology such as Mars. Extracted crystals were UV irradiated for 5.59 h under N 2 flux. After the UV irradiation, we assessed relevant degradations in the 1614, 1227, 1202, 1160 and 755 cm -1 bands. However, in light of Xanthoria parietina survivability in extreme conditions such as space- and Mars-simulated ones, we highlight parietin UV photo-resistance and its relevance for astrobiology as photo-protective substance and possible bio-hint., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Committee on Space Research (COSPAR). Published by Elsevier B.V. All rights reserved.)

Cellulose, renowned for its excellent biocompatibility, finds extensive applications in both industrial and laboratory settings. However, few studies have specifically addressed the mechanistic evolution of hydrogen bond networks in cellulose during the dissolution and regeneration processes. In this research, the regeneration mechanism of cellulose in water and ethanol is investigated through molecular dynamics simulations. The results indicate that the ability of water molecules to disrupt hydrogen bonds between cellulose and ionic liquids is stronger than that of ethanol, which is more conducive to promoting the regeneration of cellulose. Besides, the Fourier transform infrared spectroscopy coupled with two-dimensional correlation infrared spectroscopy techniques are employed to unveil the evolution sequence of hydrogen bonds during dissolution and regeneration: ν(OH) (absorbed water) → ν(O3-H3···O5) (intrachain) → ν(O6-H6···O3') (interchain) → ν(O2-H2···O6) (intrachain) → ν(OH) (free). This study not only enhances our understanding of the intricate hydrogen bond dynamics in cellulose dissolution and regeneration but also provides a foundation for the expanded application of cellulose in diverse fields., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The use of simple and hybrid fragmentation techniques for the identification of molecules in tandem mass spectrometry provides different and complementary information on the structure of molecules. Nevertheless, these techniques have not been as widely explored for oligonucleotides as for peptides or proteins. The analysis of microRNAs (miRNAs) warrants special attention, given their regulatory role and their relationship with several diseases. The application of different fragmentation techniques will be very interesting for their identification., Results: Four synthetic miRNAs and a DNA sequence were fragmented in an ESI-FT-ICR mass spectrometer using both simple and hybrid fragmentation techniques: CID, nETD followed by CID, IRMPD, and, for the first time, nETD in combination with IRMPD. The main fragmentation channel was base loss. The use of nETD-IRMPD resulted in d/z, a/w, and c/y ions at higher intensities. Moreover, nETD-IRMPD provided high sequence coverage and low internal fragmentation. Native MS analysis revealed that only miR159 and the DNA sequence formed stable dimers under physiological ionic strength. The use of organic co-solvents or additives resulted in a lower sequence coverage due to lesser overall ionization efficiency., Novelty: This work demonstrates that the combination of nETD and IRMPD for miRNA fragmentation constitutes a suitable alternative to common fragmentation methods. This strategy resulted in efficient fragmentation of [miRNA] 5- using low irradiation times and fewer internal fragments while ensuring a high sequence coverage. Moreover, given that such low charge states predominate upon spraying in physiological-like conditions, native MS can be applied for obtaining structural information at the same time., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Protein-nanoparticle (NP) complexes are nanomaterials that have numerous potential uses ranging from biosensing to biomedical applications such as drug delivery and nanomedicine. Despite their extensive use quantifying the number of bound proteins per NP remains a challenging characterization step that is crucial for further developments of the conjugate, particularly for metal NPs that often interfere with standard protein quantification techniques. In this work, we present a method for quantifying the number of proteins bound to pegylated thiol-capped gold nanoparticles (AuNPs) using an infrared (IR) spectrometer, a readily available instrument. This method takes advantage of the strong IR bands present in proteins and the capping ligands to quantify protein-NP ratios and circumvents the need to degrade the NPs prior to analysis. We show that this method is generalizable where calibration curves made using inexpensive and commercially available proteins such as bovine serum albumin (BSA) can be used to quantify protein-NP ratios for proteins of different sizes and structures.

Here, we present the new application of solid-state Vibrational Circular Dichroism (VCD) spectroscopy to differentiate several dutasteride (DS) solvatomorphs - the model active pharmaceutical ingredient (API). Several crystalline DS hydrochloride hydrates solvated with methanol, ethanol, acetonitrile, acetone, and acetic acid were prepared. In contrast to almost identical IR spectra, the VCD ones were very sensitive to changes in the sample composition. We marked significant differences in the shape of VCD spectra of studied DS solvatomorphs, DS hydrates, and DS polymorphic forms. Our findings, supported by DFT calculations, show that VCD spectroscopy has the pronounced ability to distinguish their crystal arrangements. We believe that this contribution will extend the use of VCD in the pharmaceutical industry for developing and designing new chiral drug products for the identification, description, and in-depth probing of several pharmaceutical solvatomorphs in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Afghanistan and Myanmar are two overwhelming opium production places. In this study, rapid and efficient methods for distinguishing opium from Afghanistan and Myanmar were developed using infrared spectroscopy (IR) coupled with multiple machine learning (ML) methods for the first time. A total of 146 authentic opium samples were analyzed by mid-IR (MIR) and near-IR (NIR), within them 116 were used for model training and 30 were used for model validation. Six ML methods, including partial least squares discriminant analysis (PLS-DA), orthogonal PLS-DA (OPLS-DA), k-nearest neighbour (KNN), support vector machine (SVM), random forest (RF), and artificial neural networks (ANNs) were constructed and compared to get the best classification effect. For MIR data, the average of precision, recall and f1-score for all classification models were 1.0. For NIR data, the average of precision, recall and f1-score for different classification models ranged from 0.90 to 0.94. The comparison results of six ML models for MIR and NIR data showed that MIR was more suitable for opium geography classification. Compared with traditional chromatography and mass spectrometry profiling methods, the advantages of MIR are simple, rapid, cost-effective, and environmentally friendly. The developed IR chemical profiling methodology may find wide application in classification of opium from Afghanistan and Myanmar, and also to differentiate them from opium originating from other opium producing countries. This study presented new insights into the application of IR and ML to rapid drug profiling analysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In this study, phosphorylated derivatives of long-chain inulin with different substitution degrees were prepared. The synthesized samples were named PFXL-1, PFXL-2, PFXL-3, and PFXL-4 according to their degree of substitution (from low to high). The structures of FXL and PFXL were characterized by infrared spectroscopy and nuclear magnetic resonance spectroscopy, and the results indicated the successful introduction of phosphate groups. FXL and PFXL were composed of two types of sugar, fructose and glucose, with a molar ratio of 0.977:0.023. The SEM results showed that phosphorylation changed the morphology of FXL from an irregular mass to small spherical aggregates. The XRD pattern showed that the crystallinity was reduced by the introduction of phosphate groups. The Mw of FXL was 2649 g/mol, and the Mw of PFXL-4 increased the most (2965 g/mol). Additionally, PFXL was more stable and uniform, and the absolute value of the PFXL potential reached 7.83 mV. Phosphorylation decreased the weight loss rate of FXL and improved the viscoelastic properties and antioxidant activity of FXL. This study presents a method for the modification of FXL, demonstrating that phosphorylation can enhance its physicochemical properties and physiological activity and suggesting its potential as a functional food and quality modifier., Competing Interests: Declaration of competing interest There are no conflicts of interest to declare., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The exploration encompassed the synthesis and characterization of two innovative complexes, namely FePHNS and CuPHNS, employing a diverse array of analytical techniques such as elemental analysis, infrared and ultraviolet-visible spectroscopy, mass spectrometry, molar conductivity measurements, magnetic susceptibility assessments, and thermal analysis (TGA). In the spectral domain, infrared spectroscopy substantiated the tridentate ONS coordination of the PHNS ligand to the central metal atom. Thermal analysis offered valuable insights into the distribution and content of water molecules within the complexes. Density functional theory (DFT) calculations were harnessed to validate the molecular structures of both the PHNS ligand and its complex entities, providing an intricate comprehension of their quantum chemical parameters. The investigation extended to an evaluation of the in vitro antibacterial, antifungal, and antioxidant efficacy of the PHNS ligand and its complexes, revealing heightened biological activities for the complexes in comparison to the free PHNS ligand, notably with the CuPHNS complex demonstrating the highest activity, while the PHNS ligand exhibited the lowest. To delve into potential physiological activities, molecular docking studies were conducted, predicting the binding affinity of the compounds to proteins 2vf5 (Glucosamine-6-phosphate synthase in complex with glucosamine-6-phosphate) from Escherichia coli, 3cku (rate oxidase from Aspergillus flavus complexed with its inhibitor 8-azaxanthin and chloride) from Aspergillus flavus, and 5IJT (Crystal structure of Human Peroxiredoxin 2 Oxidized). The ensuing analysis of protein-ligand interactions and binding energies underscored the promising physiological activities of the investigated compounds, warranting further exploration for their potential in novel drug development., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: The degree to which Anopheles mosquitoes prefer biting humans over other vertebrate hosts, i.e. the human blood index (HBI), is a crucial parameter for assessing malaria transmission risk. However, existing techniques for identifying mosquito blood meals are demanding in terms of time and effort, involve costly reagents, and are prone to inaccuracies due to factors such as cross-reactivity with other antigens or partially digested blood meals in the mosquito gut. This study demonstrates the first field application of mid-infrared spectroscopy and machine learning (MIRS-ML), to rapidly assess the blood-feeding histories of malaria vectors, with direct comparison to PCR assays., Methods and Results: Female Anopheles funestus mosquitoes (N = 1854) were collected from rural Tanzania and desiccated then scanned with an attenuated total reflectance Fourier-transform Infrared (ATR-FTIR) spectrometer. Blood meals were confirmed by PCR, establishing the 'ground truth' for machine learning algorithms. Logistic regression and multi-layer perceptron classifiers were employed to identify blood meal sources, achieving accuracies of 88%-90%, respectively, as well as HBI estimates aligning well with the PCR-based standard HBI., Conclusions: This research provides evidence of MIRS-ML effectiveness in classifying blood meals in wild Anopheles funestus, as a potential complementary surveillance tool in settings where conventional molecular techniques are impractical. The cost-effectiveness, simplicity, and scalability of MIRS-ML, along with its generalizability, outweigh minor gaps in HBI estimation. Since this approach has already been demonstrated for measuring other entomological and parasitological indicators of malaria, the validation in this study broadens its range of use cases, positioning it as an integrated system for estimating pathogen transmission risk and evaluating the impact of interventions., (© 2024. The Author(s).)

Objective: To investigate the differences and applicability of free silica detection methods of different crystal forms in dust, and to provide a basis for the selection of various methods. Methods: From December 2021 to June 2022, dust samples from 20 enterprises in different industries in 18 cities in Henan Province were randomly selected as the investigation objects. X-ray diffraction (XRD) method was used to analyze the samples and classify the samples. Based on GBZ/T 192.4-2007 "Determination of Dust in the Air of Workplace-Part 4: Content of Free Silica in Dust", pyrophosphate method and infrared spectrophotometry were used for quantitative determination. The measured results were analyzed by paired sample t test to evaluate the advantages and disadvantages of the two methods and their applicable scope. Results: The XRD results of 20 dust samples could be divided into α, β, γ crystal types and the mixed type of α and γ. There was no significant difference between pyrophosphate method and infrared spectrophotometry ( P =0.180). The pyrophosphate method results of β, γ and α, γ mixed crystalline free silica were significantly higher than those of infrared spectrophotometry, and the difference was statistically significant ( P <0.001) . Conclusion: Pyrophosphate method and infrared spectrophotometry are suitable for α-type free silica, while pyrophosphate method is suitable for β, γ and α, γ mixed crystalline free silica.

Caffeine is the most widely consumed stimulant and is the subject of significant ongoing research and discussions due to its impact on human health. The industry's need to comply with country-specific food and beverage regulations underscores the importance of monitoring caffeine levels in commercial products. In this study, we propose an alternative technique for caffeine analysis that relies on mid-infrared laser-based photothermal spectroscopy (PTS). PTS exploits the high-power output of the quantum cascade laser (QCL) sources to enhance the sensitivity of the mid-IR measurement. The laser-induced thermal gradient in the sample scales with the analytes' absorption coefficient and concentration, thus allowing for both qualitative and quantitative assessment. We evaluated the performance of our experimental PTS spectrometer, incorporating a tunable QCL and a Mach-Zehnder interferometer, for detecting caffeine in coffee, black tea, and an energy drink. We calibrated the setup with caffeine standards (0.1-2.5 mg mL -1 ) and we benchmarked the setup's capabilities against gas chromatography (GC) and Fourier-transform infrared (FTIR) spectroscopy. Quantitative results aligned with GC analysis, and limits of detection matched the research-grade FTIR spectrometer, indicating an excellent performance of our custom-made instrument. This method offers an alternative to established techniques, providing a platform for fast, sensitive, and non-destructive analysis without consumables as well as with high potential for miniaturization.

The cocktail of pesticides sprayed to protect crops generates a miscellaneous and generalized contamination of water bodies. Sorption, especially on soils, regulates the spreading and persistence of these contaminants. Fine resolution sorption data and knowledge of its drivers are needed to manage this contamination. The aim of this study is to investigate the potential of Mid-Infrared spectroscopy (MIR) to predict and specify the adsorption and desorption of a diversity of pesticides. We constituted a set of 37 soils from French mainland and West Indies covering large ranges of texture, organic carbon, minerals and pH. We measured the adsorption and desorption coefficients of glyphosate, 2,4-dichlorophenoxyacetic acid (2,4-D) and difenoconazole and acquired MIR Lab spectra for these soils. We developed Partial Least Square Regression (PLSR) models for the prediction of the sorption coefficients from the MIR spectra. We further identified the most influencing spectral bands and related these to putative organic and mineral functional groups. The prediction performance of the PLSR models was generally high for the adsorption coefficients Kd ads (0.4 < R 2  < 0.9 & RPIQ >1.8). It was contrasted for the desorption coefficients and related to the magnitude of the desorption hysteresis. The most significant spectral bands in the PLSR differ according to the pesticides indicating contrasted interactions with mineral and organic functional groups. Glyphosate interacts primarily with polar mineral groups (OH) and difenoconazole with hydrophobic organic groups (CH 2 , CC, COO - , C-O, C-O-C). 2,4-D has both positive and negative interactions with these groups. Finally, this work suggests that MIR combined with PLSR is a promising and cost-effective tool. It allows both the prediction of adsorption and desorption parameters and the specification of these mechanisms for a diversity of pesticides including polar active ingredients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Accurate identification of insect species holds paramount significance in diverse fields as it facilitates a comprehensive understanding of their ecological habits, distribution range, and impact on both the environment and humans. While morphological characteristics have traditionally been employed for species identification, the utilization of empty pupariums for this purpose remains relatively limited. In this study, ATR-FTIR was employed to acquire spectral information from empty pupariums of five fly species, subjecting the data to spectral pre-processing to obtain average spectra for preliminary analysis. Subsequently, PCA and OPLS-DA were utilized for clustering and classification. Notably, two wavebands (3000-2800 cm -1 and 1800-1300 cm -1 ) were found to be significant in distinguishing A. grahami. Further, we established three machine learning models, including SVM, KNN, and RF, to analyze spectra from different waveband groups. The biological fingerprint region (1800-1300 cm -1 ) demonstrated a substantial advantage in identifying empty puparium species. Remarkably, the SVM model exhibited an impressive accuracy of 100 % in identifying all five fly species. This study represents the first instance of employing infrared spectroscopy and machine learning methods for identifying insect species using empty pupariums, providing a robust research foundation for future investigations in this area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)