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.

Accurate and sensitive determination of human immunoglobulin G (HIgG) level is critical for diagnosis and treatment of various diseases, including rheumatoid arthritis, humoral immunodeficiencies, and infectious disease. In this study, versatile tri-signal probes were developed by preparing CdS@SiO2 nanorods that integrate photoluminescence (PL), multi-phonon resonant Raman scattering (MRRS) and infrared absorption (IRA) properties. Through the coating of multiple CdS nanoparticles as cores within SiO2 shells, the PL and MRRS properties of CdS were improved, resulting in a significantly lowered limit of detection (LOD), with the lowest LOD of 12.37 ag mL-1. Integration with the distinctive IRA property of SiO2 shells widened the detection range towards higher concentrations, establishing a final linear range of 50 ag mL-1 to 10 μg mL-1. The remarkable consistency among the three signals highlighted the robust internal verification capability for accurate detection. This approach enhances flexibility in selecting detection methodologies to suit diverse scenarios, facilitating HIgG detection. The tri-signal nanoprobes also exhibited excellent detection selectivity, specificity and repeatability. This study presents a fresh idea for developing high-performance detection strategies.

Insect protein extract is one of the high-quality protein sources and is frequently viewed as a potential nutrition alternative. However, a more precise method for protein measurement is still needed due to protein overestimation by the Kjeldahl method due to the presence of a large amount of chitin in insects. Therefore, we demonstrated the monitoring of chitin and protein extracted from yellow mealworm larvae through the information on molecular vibration obtained using Raman spectroscopy and infrared (IR) spectroscopy. The NH vibration at 3475 cm-1 is the characteristic peak of chitin in defatted product observed in the Raman spectra. The nitrogen-to-protein conversion factor in protein extracted from larvae by the Raman method was determined based on the NH vibration and found to be 5.66 ± 0.01. We also compared these experimental data to theoretical Raman and IR spectra and determined the possible reasons for why nitrogen elements in chitin affect the determination of protein content. The method of sequentially removing fat and protein could provide more accurate quantification of protein and chitin. Raman spectroscopy is feasible for various types of insects with high chitin content. Compared with the Kjeldahl method, the Raman method is a faster and more accurate measurement method. Moreover, it provides the content of impurities, purity, and structural information.

In this work, we propose a Multi-dot Ensemble Regression AI detector (MER) based on the Lambert-Beer law. We pre-trained a model using the infrared spectral data of target additives collected in advance to detect the target additives in unknown oil samples. The algorithm\'s feasibility was validated by assessing the content of additives in a series of simulated commercial oil samples that were not part of the training set. We established models for three common lubricating oil additives (anti-friction, anti-wear, and antioxidant agents), demonstrating their effectiveness in oil sample detection. Additionally, by comparing with other algorithms, we established the superiority of MER in small-sample learning scenarios.

This study introduces two novel sandwich-type tungsten-oxygen cluster compounds synthesized by hydrothermal methods, H4(C6H12N2H2)3{Na(H2O)2[Mn2(H2O)(GeW9O34)]}2 (Compound 1) and H2(C6H12N2H2)3.5{Na3(H2O)4[Co2(H2O)(GeW9O34)]2}·17H2O (Compound 2). The two compounds comprise cluster anions [GeW9O34]10- coordinated with transition metal atoms, either Mn or Co, and are stabilized by organic ligands. These compounds are crystallized in the hexagonal crystal system and P63/m space group. The two compounds were characterized through various techniques. Fourier transform infrared (IR) spectroscopy showed absorption peaks of anionic backbone vibrations of the Keggin cluster at 500-1000 cm-1, IR spectral peaks of δ(N-H) and νas(C-N) of the ligand triethylenediamine at 1000-2000 cm-1, and IR spectral peaks of the ligand νas(N-H) and νas(O-H) of water at 3000-3500 cm-1. Despite similar one-dimensional (1D) IR spectra due to the same cluster anions and similar molecular structures, the two compounds exhibited distinct responses in two-dimensional correlation spectroscopy with IR under magnetic and thermal perturbations. Under magnetic perturbation, Compound 1 showed a strong response peak for νas(W-Ob-W), while Compound 2 exhibited a strong response peak for νas(W=Od), possibly linked to differing magnetic particles. Similarly, Compound 1 displayed a strong response peak under thermal perturbation for νas(W-Oc-W). In contrast, Compound 2 showed a strong response peak for νas(W=Od); these results may be attributed to the different hydrogen bonding connections between the two compounds, which affect the groups in distinct ways through vibration and transmit these vibrations to the W-O bonds. The research presented in this paper expands the theoretical and experimental data of 2D correlation IR spectroscopy.

The characterization of structure of organic salts in complex mixtures has been a difficult problem in analytical chemistry. In the analysis of Scutellariae Radix (SR), the pharmacopoeia of many countries stipulates that the quality control component is baicalin (≥9% by high performance liquid chromatography (HPLC)). The component with highest response in SR was also baicalin detected by liquid chromatography-mass spectrometry (LC-MS). However, in the attenuated total reflection Fourier transform infrared spectroscopy, the carbonyl peak of glucuronic acid of baicalin did not appear in SR. The results of element analysis, time of flight secondary ion mass spectrometry, matrix assisted laser desorption ionization mass spectrometry and solid-state nuclear magnetic resonance all supported the existence of baicalin magnesium salt. Based on this, this study proposes an analysis strategy guided by infrared spectroscopy and combined with multi-spectroscopy techniques to analyze the structure of organic salt components in medicinal plant. It is meaningful for the research of mechanisms, development of new drugs, and quality control.

BACKGROUND: Crohn\'s disease (CD) is often misdiagnosed as intestinal tuberculosis (ITB). However, the treatment and prognosis of these two diseases are dramatically different. Therefore, it is important to develop a method to identify CD and ITB with high accuracy, specificity, and speed.
OBJECTIVE: To develop a method to identify CD and ITB with high accuracy, specificity, and speed.
METHODS: A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB. Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.
RESULTS: The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm-1 and 1234 cm-1 bands, and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy, specificity, and sensitivity of 91.84%, 92.59%, and 90.90%, respectively, for the differential diagnosis of CD and ITB.
CONCLUSIONS: Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level, and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

Biofilms are thought to play a vital role in the beneficial effects of probiotic bacteria. However, the structure and function of probiotic biofilms are poorly understood. In this work, biofilms of Escherichia coli (E. coli) Nissle 1917 were investigated and compared with those of pathogenic and opportunistic strains (E. coli MG1655, O157:H7) using crystal violet assay, confocal laser scanning microscopy, scanning electron microscopy and FTIR microspectroscopy. The study revealed significant differences in the morphological structure, chemical composition, and spatial heterogeneity of the biofilm formed by the probiotic E. coli strain. In particular, the probiotic biofilm can secrete unique phospholipid components into the extracellular matrix. These findings provide new information on the morphology, architecture and chemical heterogeneity of probiotic biofilms. This information may help us to understand the beneficial effects of probiotics for various applications.

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.

The Diels-Alder (D-A) reaction between furan and maleimide is a thermally reversible reaction that has become a vital chemical technique for designing polymer structures and functions. The kinetics of this reaction, particularly in polymer bulk states, have significant practical implications. In this study, we investigated the feasibility of utilizing infrared spectroscopy to measure the D-A reaction kinetics in bulk-state polymer. Specifically, we synthesized furan-functionalized polystyrene and added a maleimide small-molecule compound to form a D-A adduct. The intensity of the characteristic absorption peak of the D-A adduct was quantitatively measured by infrared spectroscopy, and the dependence of conversion of the D-A reaction on time was obtained at different temperatures. Subsequently, the D-A reaction apparent kinetic coefficient kapp and the Arrhenius activation energy Ea,D-A were calculated. These results were compared with those determined from 1H-NMR in the polymer solution states.