RESUMEN
The fraudulent adulteration of goat milk with cheaper and more available milk of other species such as cow milk is occurrence. The aims of the present study were to investigate the effect of goat milk adulteration with cow milk on the mid-infrared (MIR) spectrum and further evaluate the potential of MIR spectroscopy to identify and quantify the goat milk adulterated. Goat milk was adulterated with cow milk at 5 different levels including 10%, 20%, 30%, 40%, and 50%. Statistical analysis showed that the adulteration had significant effect on the majority of the spectral wavenumbers. Then, the spectrum was preprocessed with standard normal variate (SNV), multiplicative scattering correction (MSC), Savitzky-Golay smoothing (SG), SG plus SNV, and SG plus MSC, and partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLSR) were used to establish classification and regression models, respectively. PLS-DA models obtained good results with all the sensitivity and specificity over 0.96 in the cross-validation set. Regression models using raw spectrum obtained the best result, with coefficient of determination (R2), root mean square error (RMSE), and the ratio of performance to deviation (RPD) of cross-validation set were 0.98, 2.01, and 8.49, respectively. The results preliminarily indicate that the MIR spectroscopy is an effective technique to detect the goat milk adulteration with cow milk. In future, milk samples from different origins and different breeds of goats and cows should be collected, and more sophisticated adulteration at low levels should be further studied to explore the potential and effectiveness of milk mid-infrared spectroscopy and chemometrics.
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Contaminación de Alimentos , Cabras , Leche , Espectrofotometría Infrarroja , Animales , Leche/química , Análisis de los Mínimos Cuadrados , Contaminación de Alimentos/análisis , Espectrofotometría Infrarroja/métodos , Análisis Discriminante , Bovinos , Quimiometría/métodosRESUMEN
Absolute quantity imaging of biomolecules on a single cell level is critical for measurement assurance in biosciences and bioindustries. While infrared (IR) transmission microscopy is a powerful label-free imaging modality capable of chemical quantification, its applicability to hydrated biological samples remains challenging due to the strong IR absorption by water. Traditional IR imaging of hydrated cells relies on powerful light sources, such as synchrotrons, to mitigate the light absorption by water. However, we overcome this challenge by applying a solvent absorption compensation (SAC) technique to a home-built benchtop IR microscope based on an external-cavity quantum cascade laser. SAC-IR microscopy adjusts the incident light using a pair of polarizers to precompensate the IR absorption by water while retaining the full dynamic range. Integrating the IR absorbance over a cell yields the total mass of biomolecules per cell. We monitor the total mass of the biomolecules of live fibroblast cells over 12 h, demonstrating promise for advancing our understanding of the biomolecular processes occurring in live cells on the single-cell level.
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Análisis de la Célula Individual , Animales , Ratones , Fibroblastos/citología , Fibroblastos/química , Espectrofotometría Infrarroja/métodos , Microscopía/métodos , Rayos Infrarrojos , Células 3T3 NIHRESUMEN
BACKGROUND: Hepatocellular carcinoma (HCC) is the most common form of liver cancer, with cirrhosis being a major risk factor. Traditional blood markers like alpha-fetoprotein (AFP) demonstrate limited efficacy in distinguishing between HCC and cirrhosis, underscoring the need for more effective diagnostic methodologies. In this context, extracellular vesicles (EVs) have emerged as promising candidates; however, their practical diagnostic application is restricted by the current lack of label-free methods to accurately profile their molecular content. To address this gap, our study explores the potential of mid-infrared (mid-IR) spectroscopy, both alone and in combination with plasmonic nanostructures, to detect and characterize circulating EVs. RESULTS: EVs were extracted from HCC and cirrhotic patients. Mid-IR spectroscopy in the Attenuated Total Reflection (ATR) mode was utilized to identify potential signatures for patient classification, highlighting significant changes in the Amide I-II region (1475-1700 cm-1). This signature demonstrated diagnostic performance comparable to AFP and surpassed it when the two markers were combined. Further investigations utilized a plasmonic metasurface suitable for ultrasensitive spectroscopy within this spectral range. This device consists of two sets of parallel rod-shaped gold nanoantennas (NAs); the longer NAs produced an intense near-field amplification in the Amide I-II bands, while the shorter NAs were utilized to provide a sharp reflectivity edge at 1800-2200 cm-1 for EV mass-sensing. A clinically relevant subpopulation of EVs was targeted by conjugating NAs with an antibody specific to Epithelial Cell Adhesion Molecule (EpCAM). This methodology enabled the detection of variations in the quantity of EpCAM-presenting EVs and revealed changes in the Amide I-II lineshape. SIGNIFICANCE: The presented results can positively impact the development of novel laboratory methods for the label-free characterization of EVs, based on the combination between mid-IR spectroscopy and plasmonics. Additionally, data obtained by using HCC and cirrhotic subjects as a model system, suggest that this approach could be adapted for monitoring these conditions.
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Biomarcadores de Tumor , Carcinoma Hepatocelular , Vesículas Extracelulares , Neoplasias Hepáticas , Espectrofotometría Infrarroja , Humanos , Neoplasias Hepáticas/sangre , Neoplasias Hepáticas/diagnóstico , Vesículas Extracelulares/química , Vesículas Extracelulares/metabolismo , Biomarcadores de Tumor/sangre , Carcinoma Hepatocelular/sangre , Carcinoma Hepatocelular/diagnóstico , Espectrofotometría Infrarroja/métodos , Oro/química , Molécula de Adhesión Celular Epitelial/metabolismo , Nanopartículas del Metal/químicaRESUMEN
Yeast phenylalanine tRNA (tRNAphe) is a paradigmatic model in structural biology. In this work, we combine molecular dynamics simulations and spectroscopy modeling to establish a direct link between its structure, conformational dynamics, and infrared (IR) spectra. Employing recently developed vibrational frequency maps and coupling models, we apply a mixed quantum/classical treatment of the line shape theory to simulate the IR spectra of tRNAphe in the 1600-1800 cm-1 region across its folded and unfolded conformations and under varying concentrations of Mg2+ ions. The predicted IR spectra of folded and unfolded tRNAphe are in good agreement with experimental measurements, validating our theoretical framework. We then elucidate how the characteristic L-shaped tertiary structure of the tRNA and its modulation in response to diverse chemical environments give rise to distinct IR absorption peaks and line shapes. These calculations effectively bridge IR spectroscopy experiments and atomistic molecular simulations, unraveling the molecular origins of the observed IR spectra of tRNAphe. This work presents a robust theoretical protocol for modeling the IR spectroscopy of nucleic acids, which will facilitate its application as a sensitive probe for detecting the fluctuating secondary and tertiary structures of these essential biological macromolecules.
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Simulación de Dinámica Molecular , Conformación de Ácido Nucleico , ARN de Transferencia de Fenilalanina , Espectrofotometría Infrarroja , Espectrofotometría Infrarroja/métodos , ARN de Transferencia de Fenilalanina/química , ARN de Transferencia de Fenilalanina/metabolismo , Saccharomyces cerevisiae/química , Saccharomyces cerevisiae/metabolismo , ARN de Hongos/química , ARN de Hongos/metabolismo , Fenilalanina/química , Fenilalanina/metabolismoRESUMEN
Evaluation of the particle size distribution (PSD) of active pharmaceutical ingredients (APIs) in nasal suspension products is challenging due to the presence of both API and excipients. To characterize these intricate formulations, it is essential to have sophisticated analytical methods that offer high spatial resolution and the ability to chemically pinpoint and map out the presence of API particles. However, such advanced techniques have not been documented for nasal formulations yet. In this proof-of-concept study, we investigated the utility of optical photothermal infrared spectroscopy (O-PTIR) to analyze the PSD of commercially available Nasonex® and its generic Azonaire® nasal mometasone furoate (MM) suspensions. Simultaneous O-PTIR and Raman spectra, as well as IR chemical maps, were collected from the particles in both formulations. Spatially resolved spectra from the particles confirmed the presence of peaks related to MM (1727 cm-1, 1661 cm-1, and 1122 cm-1) and excipient microcrystalline cellulose (MCC) (1061 cm-1). The PSD of MM particles was characterized using chemical maps specific to MM (1661 cm-1) and automated imaging. Results confirmed that the PSD of both formulations were comparable. Spectral analysis also revealed the presence of free MM, free MCC, and particles containing co-localized MM and MCC. For suspension-based nasal products, O-PTIR enables the measurement of API PSD, which is critical for formulators in developing nasal suspension products. This approach holds potential as an innovative complimentary analytical tool that could diminish the need for extensive clinical endpoint bioequivalence studies when evaluating the comparability of generic and brand-name nasal suspension products.
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Excipientes , Furoato de Mometasona , Rociadores Nasales , Tamaño de la Partícula , Suspensiones , Furoato de Mometasona/química , Furoato de Mometasona/administración & dosificación , Excipientes/química , Celulosa/química , Administración Intranasal , Espectrofotometría Infrarroja/métodos , Espectrometría Raman/métodos , Química Farmacéutica/métodosRESUMEN
Proteases play a crucial role in industrial enzyme formulations, with activity fluctuations significantly impacting product quality and yield. Therefore, developing a method for precise and rapid detection of protease activity is paramount. This study aimed to develop a rapid and accurate method for quantifying trypsin activity using integrated infrared (IR) and ultraviolet (UV) spectroscopy combined with data fusion techniques. The developed method evaluates the enzymatic activity of trypsin under varying conditions, including temperature, pH, and ionic strength. By comparing different data fusion methods, the study identifies the optimal model for accurate enzyme activity prediction. The results demonstrated significant improvements in predictive performance using the feature-level data fusion approach. Additionally, substituting the spectral data of the samples in the validation sets into the best prediction model resulted in a minimal residual difference between predicted and true values, further verifying the model's accuracy and reliability. This innovative approach offers a practical solution for the efficient and precise quantification of enzyme activity, with broad applications in industrial processes.
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Espectrofotometría Ultravioleta , Tripsina , Tripsina/química , Tripsina/metabolismo , Espectrofotometría Ultravioleta/métodos , Concentración de Iones de Hidrógeno , Temperatura , Espectrofotometría Infrarroja/métodos , Concentración OsmolarRESUMEN
Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time-consuming, burden patients financially, and sometimes all test results can be negative. Therefore, rapid, cost-effective novel methods are essential for the early accurate diagnosis of MG. Here, we aimed to determine MG-induced spectral biomarkers from blood serum using infrared spectroscopy. Furthermore, infrared spectroscopy coupled with multivariate analysis methods e.g., principal component analysis (PCA), support vector machine (SVM), discriminant analysis and Neural Network Classifier were used for rapid MG diagnosis. The detailed spectral characterization studies revealed significant increases in lipid peroxidation; saturated lipid, protein, and DNA concentrations; protein phosphorylation; PO2-asym + sym /protein and PO2-sym/lipid ratios; as well as structural changes in protein with a significant decrease in lipid dynamics. All these spectral parameters can be used as biomarkers for MG diagnosis and also in MG therapy. Furthermore, MG was diagnosed with 100% accuracy, sensitivity and specificity values by infrared spectroscopy coupled with multivariate analysis methods. In conclusion, FTIR spectroscopy coupled with machine learning technology is advancing towards clinical translation as a rapid, low-cost, sensitive novel approach for MG diagnosis.
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Biomarcadores , Aprendizaje Automático , Miastenia Gravis , Humanos , Miastenia Gravis/diagnóstico , Miastenia Gravis/sangre , Femenino , Masculino , Biomarcadores/sangre , Persona de Mediana Edad , Adulto , Máquina de Vectores de Soporte , Análisis de Componente Principal , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Anciano , Espectrofotometría Infrarroja/métodosRESUMEN
Vibrational spectroscopy of protein structure often utilizes 13C18O-labeling of backbone carbonyls to further increase structural resolution. However, sidechains such as arginine, aspartate, and glutamate absorb within the same spectral region, complicating the analysis of isotope-labeled peaks. In this study, we report that the waiting time between pump and probe pulses in two-dimensional infrared spectroscopy can be used to suppress sidechain modes in favor of backbone amide I' modes based on differences in vibrational lifetimes. Furthermore, differences in the lifetimes of 13C18O-amide I' modes can aid in the assignment of secondary structure for labeled residues. Using model disordered and ß-sheet peptides, it was determined that while ß-sheets exhibit a longer lifetime than disordered structures, amide I' modes in both secondary structures exhibit longer lifetimes than sidechain modes. Overall, this work demonstrates that collecting 2D IR data at delayed waiting times, based on differences in vibrational lifetime between modes, can be used to effectively suppress interfering sidechain modes and further identify secondary structures.
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Espectrofotometría Infrarroja , Vibración , Espectrofotometría Infrarroja/métodos , Péptidos/química , Estructura Secundaria de ProteínaRESUMEN
The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and classifying pharmaceutical tablets containing acetaminophen (AAP) by brand has been developed. In total, 15 tablets of 11 brands for a total of 165 samples were analyzed. Mid-infrared vibrational spectroscopy with multivariate analysis was employed. Quantum cascade lasers (QCLs) were used as mid-infrared sources. IR spectra in the spectral range 980-1600 cm-1 were recorded. Five different classification methods were used. First, a spectral search through correlation indices. Second, machine learning algorithms such as principal component analysis (PCA), support vector classification (SVC), decision tree classifier (DTC), and artificial neural network (ANN) were employed to classify tablets by brands. SNV and first derivative were used as preprocessing to improve the spectral information. Precision, recall, specificity, F1-score, and accuracy were used as criteria to evaluate the best SVC, DEE, and ANN classification models obtained. The IR spectra of the tablets show characteristic vibrational signals of AAP and other APIs present. Spectral classification by spectral search and PCA showed limitations in differentiating between brands, particularly for tablets containing AAP as the only API. Machine learning models, specifically SVC, achieved high accuracy in classifying AAP tablets according to their brand, even for brands containing only AAP.
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Acetaminofén , Aprendizaje Automático , Análisis de Componente Principal , Espectrofotometría Infrarroja , Comprimidos , Acetaminofén/química , Acetaminofén/análisis , Comprimidos/química , Espectrofotometría Infrarroja/métodos , Redes Neurales de la Computación , Algoritmos , Máquina de Vectores de SoporteRESUMEN
Glycans are oligosaccharides attached to proteins or lipids and affect their functions, such as drug efficacy, structural contribution, metabolism, immunogenicity, and molecular recognition. Conventional glycosylation analysis has relied on destructive, slow, system-sensitive methods, including enzymatic reactions, chromatography, fluorescence labeling, and mass spectrometry. Herein, we propose quantum cascade laser (QCL) infrared (IR) spectroscopy as a rapid, nondestructive method to quantify glycans and their monosaccharide composition. Previously, we demonstrated high-sensitivity IR spectroscopy of protein solution using solvent absorption compensation (SAC) and double-beam modulation (DBM) techniques. However, the SAC-DBM approach suffered a limited frequency scanning range (<400 cm-1) due to the light dispersion by acousto-optic modulators (AOMs). Here, we implemented a mirror-based double-pass AOM in the SAC-DBM scheme and successfully extended the frequency range to (970 to 1840 cm-1), which encompasses the vibrational fingerprint of biomolecules. The extended frequency range allowed the simultaneous observation of monosaccharide ring bands (1000 to 1200 cm-1) and protein amide bands (1500 to 1700 cm-1). We compared the IR spectra of six glycoproteins and two nonglycosylated proteins with the results from intact mass spectrometry. The IR absorbance ratios of the ring band to the amide band of glycoproteins in solutions showed a linear correlation with the ratios of glycan to protein backbone masses. Furthermore, a multivariate analysis produced monosaccharide compositions consistent with the reported database for the glycoproteins, and the monosaccharide compositions were used to improve the predictability of the glycan-protein mass ratio from the IR-absorbance ratio. This nondestructive, high-sensitivity QCL-IR spectroscopy could be used as a standard method to monitor batch-to-batch comparability during drug manufacturing and quantify the glycosylation and monosaccharide composition of new glycoproteins and other glycosylated biosystems.
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Glicoproteínas , Polisacáridos , Espectrofotometría Infrarroja , Glicoproteínas/análisis , Glicoproteínas/química , Polisacáridos/análisis , Polisacáridos/química , Espectrofotometría Infrarroja/métodos , Láseres de Semiconductores , Soluciones , AnimalesRESUMEN
ANOVA-simultaneous component analysis (ASCA) was applied to short-wave infrared spectral fingerprints of 5 malting barley varieties collected using a hyperspectral imaging system to determine the effect of germination, the influence of time and the influence of barley by means of a full factorial experimental design. ASCA indicated that there was a significant (p < 0.0001) effect of the germination status, the germination time and interaction on the spectral data for all varieties. The biochemical and physiological modification of the samples were characterised by visualisation of the longitudinal scores obtained from simultaneous component analysis for the germination time factor. This resulted in the visualisation and explanation of biochemical change over the course of barley germination as a factor of time. The relevant loadings indicated a significant change to the proteome, lipid and starch structure as driven by the uptake of water over time. The ASCA model were extrapolated to include the effect of barley variety to the already mentioned germination status and germination time factors, resulting once again in all the effects being significant (p < 0.0001). Here it was shown that all the barley varieties are significantly different from one another pre- and post-modification, based on the molecular vibrations observed in the short wave-infrared (SWIR) spectra, suggesting that the detection of biotic stress factors, such as pre-harvest germination, also differ for each variety, by indicating that the germination profile of each barley variety varies as a function of germination time. Thus, also the malting performance, germinative energy and chemical profile of each barley variety tested will vary before, during and after imbibition and germination - indicating the importance of malting commercial barley malt true to variety. These results indicate that (SWIR) spectral imaging instrumentation can possibly be used to monitor controlled germination of barley grain. Due to the shown ability of SWIR spectral imaging to detect small biochemical changes over time of barley grain during germination.
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Germinación , Hordeum , Hordeum/crecimiento & desarrollo , Hordeum/química , Hordeum/fisiología , Germinación/fisiología , Espectrofotometría Infrarroja/métodos , Análisis de Varianza , Análisis de Componente PrincipalRESUMEN
The ability to track minute changes of a single amino acid residue in a cellular environment is causing a paradigm shift in the attempt to fully understand the responses of biomolecules that are highly sensitive to their environment. Detecting early protein dynamics in living cells is crucial to understanding their mechanisms, such as those of photosynthetic proteins. Here, we elucidate the light response of the microbial chloride pump NmHR from the marine bacterium Nonlabens marinus, located in the membrane of living Escherichia coli cells, using nanosecond time-resolved UV/vis and IR absorption spectroscopy over the time range from nanoseconds to seconds. Transient structural changes of the retinal cofactor and the surrounding apoprotein are recorded using light-induced time-resolved UV/vis and IR difference spectroscopy. Of particular note, we have resolved the kinetics of the transient deprotonation of a single cysteine residue during the photocycle of NmHR out of the manifold of molecular vibrations of the cells. These findings are of high general relevance, given the successful development of optogenetic tools from photoreceptors to interfere with enzymatic and neuronal pathways in living organisms using light pulses as a noninvasive trigger.
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Escherichia coli , Halorrodopsinas , Escherichia coli/química , Escherichia coli/metabolismo , Halorrodopsinas/química , Halorrodopsinas/metabolismo , Espectrofotometría Infrarroja/métodos , Luz , Halobacteriaceae/química , Halobacteriaceae/metabolismo , CinéticaRESUMEN
BACKGROUND: Inclusion bodies (IBs) are well-known subcellular structures in bacteria where protein aggregates are collected. Various methods have probed their structure, but single-cell spectroscopy remains challenging. Atomic Force Microscopy-based Infrared Spectroscopy (AFM-IR) is a novel technology with high potential for the characterisation of biomaterials such as IBs. RESULTS: We present a detailed investigation using AFM-IR, revealing the substructure of IBs and their variation at the single-cell level, including a rigorous optimisation of data collection parameters and addressing issues such as laser power, pulse frequency, and sample drift. An analysis pipeline was developed tailored to AFM-IR image data, allowing high-throughput, label-free imaging of more than 3500 IBs in 12,000 bacterial cells. We examined IBs generated in Escherichia coli under different stress conditions. Dimensionality reduction analysis of the resulting spectra suggested distinct clustering of stress conditions, aligning with the nature and severity of the applied stresses. Correlation analyses revealed intricate relationships between the physical and morphological properties of IBs. CONCLUSIONS: Our study highlights the power and limitations of AFM-IR, revealing structural heterogeneity within and between IBs. We show that it is possible to perform quantitative analyses of AFM-IR maps over a large collection of different samples and determine how to control for various technical artefacts.
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Escherichia coli , Cuerpos de Inclusión , Microscopía de Fuerza Atómica , Análisis de la Célula Individual , Espectrofotometría Infrarroja , Cuerpos de Inclusión/química , Escherichia coli/química , Microscopía de Fuerza Atómica/métodos , Espectrofotometría Infrarroja/métodos , Análisis de la Célula Individual/métodosRESUMEN
In this study, optical photothermal infrared (O-PTIR) spectroscopy combined with machine learning algorithms were used to evaluate 46 tissue cores of surgically resected cervical lymph nodes, some of which harboured oral squamous cell carcinoma nodal metastasis. The ratios obtained between O-PTIR chemical images at 1252 cm-1 and 1285 cm-1 were able to reveal morphological details from tissue samples that are comparable to the information achieved by a pathologist's interpretation of optical microscopy of haematoxylin and eosin (H&E) stained samples. Additionally, when used as input data for a hybrid convolutional neural network (CNN) and random forest (RF) analyses, these yielded sensitivities, specificities and precision of 98.6 ± 0.3%, 92 ± 4% and 94 ± 5%, respectively, and an area under receiver operator characteristic (AUC) of 94 ± 2%. Our findings show the potential of O-PTIR technology as a tool to study cancer on tissue samples.
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Carcinoma de Células Escamosas , Metástasis Linfática , Neoplasias de la Boca , Humanos , Metástasis Linfática/patología , Neoplasias de la Boca/patología , Carcinoma de Células Escamosas/patología , Ganglios Linfáticos/patología , Espectrofotometría Infrarroja/métodos , Aprendizaje Automático , Redes Neurales de la Computación , Femenino , Masculino , Curva ROCRESUMEN
BACKGROUND: Ubrogepant is a prescription medication used to prevent migraine headaches. It is currently available in tablet form. OBJECTIVE: The goal of this work is to investigate the drug degradation profile of ubrogepant, as well as to isolate and characterize undiscovered ubrogepant degradation products by utilizing LC-MS, NMR, and IR spectroscopic analytical techniques and, furthermore, to develop a high-resolution, sensitive, stability-indicating analytical approach for detecting and quantifying ubrogepant degradation products in its pharmaceutical formulation. METHODS: To identify and quantify the degradation products of ubrogepant in pharmaceutical products, a novel gradient reverse-phase HPLC (RP-HPLC) technique with a photo diode array (PDA) detector was developed by utilizing a C18 stationary phase column. The eluent comprised a mixture of acetonitrile and water with 0.1% (v/v) ortho-phosphoric acid. To establish the intrinsic stability of the ubrogepant pharmaceutical product, it was stress-tested under various degradation conditions, including water, alkaline, acid hydrolysis, photolytic, oxidative, and thermal. Flash chromatography was used to isolate the two major degradants, and the structures were determined using NMR (1H, 13C, distortionless enhancement by polarisation transfer-DEPT-135), IR, and LC-MS methods. RESULTS: The ubrogepant medication was relatively more degradable in alkaline and acidic conditions, and two unique degradation products were discovered. Based on spectroscopic and chromatographic evidence, it was conclusively demonstrated that these unique compounds were ubrogepant hydrolysis products. All degradation products were separated with a resolution greater than 2.0. The peak purity data showed that the ubrogepant peak in all of the stress samples examined was pure. Under all stress environments, ubrogepant achieved a minimum mass balance of 95%. The validated approach developed was sensitive enough to quantify ubrogepant degradation products at 0.03% of the ubrogepant test concentration. CONCLUSION: The proposed method was found to be stability-indicating since it fits all of the regulatory authorities' typical requirements. This method is highly efficient for detecting and quantifying impurities in ubrogepant drug substances and drug products in QC laboratories. HIGHLIGHTS: Two new degradation products of ubrogepant were successfully extracted and characterized using NMR, IR, and LC-MS spectroscopic methods. The proposed HPLC method can accurately quantify the degradation products of ubrogepant in pharmaceutical products and is sensitive enough to detect degradation products of ubrogepant as low as 0.17 µg/mL.
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Estabilidad de Medicamentos , Espectroscopía de Resonancia Magnética , Espectroscopía de Resonancia Magnética/métodos , Cromatografía Líquida de Alta Presión/métodos , Contaminación de Medicamentos , Espectrometría de Masas/métodos , Espectrofotometría Infrarroja/métodos , Pirroles/química , Pirroles/análisis , Comprimidos , Cromatografía Liquida/métodos , Cromatografía Líquida con Espectrometría de MasasRESUMEN
Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employed as a noninvasive alternative to the standard blood-glucose detection requiring blood-sampling via skin-puncturing, but improving the confidence level of such a replacement remains highly desirable. Here, we show that with an innovative metric of attributes in measurements and data-management, a high accuracy in correlating the test results of our improved spectral analysis to those of the standard detection is accomplished. First, our comparative laser speckle contrast imaging of subcutaneous interstitial fluid in fingertips, thenar and hypothenar reveal that spectral measurements from hypothenar, with an attenuated total reflection Fourier transform infrared spectrometer, give much stronger signals than the stereotype measurements from fingertips. Second, we demonstrate that discriminative selection of the spectral locations and ranges, to minimize spectral interference and maximize signal-to-noise, are critically important. The optimal band is pinned at that between 1000 ± 3 cm-1 and1040 ± 3 cm-1. Third, we propose an individual exclusive prediction model by adopting the support vector regression analysis of the spectral data from four subjects. The average predicted coefficient of determination, root mean square error and mean absolute error of four subjects are 0.97, 0.21 mmol/L, 0.17 mmol/L, respectively, and the average probability of being in Zone A of the Clark error grid is 100.00 %. Additionally, we demonstrate with the Bland and Altman plot that our proposed model has the highest consistency with portable blood glucose meter detection method.
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Glucemia , Máquina de Vectores de Soporte , Humanos , Glucemia/análisis , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Espectrofotometría Infrarroja/métodos , Masculino , Análisis de RegresiónRESUMEN
Infrared (IR) spectroscopy is an important analytical tool in various chemical and forensic domains and a great deal of effort has gone into developing in silico methods for predicting experimental spectra. A key challenge in this regard is generating highly accurate spectra quickly to enable real-time feedback between computation and experiment. Here, we employ Graphormer, a graph neural network (GNN) transformer, to predict IR spectra using only simplified molecular-input line-entry system (SMILES) strings. Our data set includes 53,528 high-quality spectra, measured in five different experimental media (i.e., phases), for molecules containing the elements H, C, N, O, F, Si, S, P, Cl, Br, and I. When using only atomic numbers for node encodings, Graphormer-IR achieved a mean test spectral information similarity (SISµ) value of 0.8449 ± 0.0012 (n = 5), which surpasses that the current state-of-the-art model Chemprop-IR (SISµ = 0.8409 ± 0.0014, n = 5) with only 36% of the encoded information. Augmenting node embeddings with additional node-level descriptors in learned embeddings generated through a multilayer perceptron improves scores to SISµ = 0.8523 ± 0.0006, a total improvement of 19.7σ (t = 19). These improved scores show how Graphormer-IR excels in capturing long-range interactions like hydrogen bonding, anharmonic peak positions in experimental spectra, and stretching frequencies of uncommon functional groups. Scaling our architecture to 210 attention heads demonstrates specialist-like behavior for distinct IR frequencies that improves model performance. Our model utilizes novel architectures, including a global node for phase encoding, learned node feature embeddings, and a one-dimensional (1D) smoothing convolutional neural network (CNN). Graphormer-IR's innovations underscore its value over traditional message-passing neural networks (MPNNs) due to its expressive embeddings and ability to capture long-range intramolecular relationships.
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Redes Neurales de la Computación , Espectrofotometría Infrarroja , Espectrofotometría Infrarroja/métodosRESUMEN
Automation of metabolite control in fermenters is fundamental to develop vaccine manufacturing processes more quickly and robustly. We created an end-to-end process analytical technology and quality by design-focused process by replacing manual control of metabolites during the development of fed-batch bioprocesses with a system that is highly adaptable and automation-enabled. Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation. This data was digitally connected to a process information management system, to enable continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes. Continuous metabolite data from mid-infrared spectra of cultures in stirred-tank reactors enabled feedback loops and control of the feed pumps in pharmaceutical development laboratories. This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude. Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites. The ability to develop quantitative metabolite templates quickly and simply for changing bioprocesses was instrumental for project acceleration and heightened process control and automation. ONE-SENTENCE SUMMARY: Intelligent digital control systems using continuous in-line metabolite data enabled end-to-end automation of fed-batch processes in stirred-tank reactors.
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Reactores Biológicos , Fermentación , Vacunas , Glucosa/metabolismo , Ácido Glutámico/metabolismo , Espectrofotometría Infrarroja/métodos , Medios de Cultivo/química , Técnicas de Cultivo Celular por Lotes/métodos , AutomatizaciónRESUMEN
A data fusion strategy based on near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were developed for rapid origin identification and quality evaluation of Lonicerae japonicae flos (LJF). A high-level data fusion for origin identification was formed using the soft voting method. This data fusion model achieved accuracy, log-loss value and Kappa value of 95.5%, 0.347 and 0.910 on the prediction set. The spectral data were converted to liquid chromatography data using a data fusion model constructed by the weighted average algorithm. The Euclidean distance and adjusted cosine similarity were used to evaluate the similarity between the converted and the real chromatographic data, with results of 247.990 and 0.996, respectively. The data fusion models all performed better than the models constructed using single data. This indicates that multispectral data fusion techniques have a wide range of application prospects and practical value in the quality control of natural products such as LJF.
Asunto(s)
Lonicera , Espectroscopía Infrarroja Corta , Lonicera/química , Espectroscopía Infrarroja Corta/métodos , Espectrofotometría Infrarroja/métodos , Control de Calidad , Algoritmos , Medicamentos Herbarios Chinos/química , Medicamentos Herbarios Chinos/análisis , Extractos VegetalesRESUMEN
The authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards. Some prevalent authenticity issues found in edible oils include blending expensive oils with cheaper substitutes or lower-grade oils, incorrect labeling regarding the oil's source or type, and falsely stating the oil's origin. Vibrational spectroscopy techniques, such as infrared (IR) and Raman spectroscopy, have emerged as effective tools for rapidly and non-destructively analyzing edible oils. This review paper offers a comprehensive overview of recent advancements in using vibrational spectroscopy for authenticating edible oils. The fundamental principles underlying vibrational spectroscopy are introduced and chemometric approaches that enhance the accuracy and reliability of edible oil authentication are summarized. Recent research trends highlighted in the review include authenticating newly introduced oils, identifying oils based on their specific origins, adopting handheld/portable spectrometers and hyperspectral imaging, and integrating modern data handling techniques into the use of vibrational spectroscopic techniques for edible oil authentication. Overall, this review provides insights into the current state-of-the-art techniques and prospects for utilizing vibrational spectroscopy in the authentication of edible oils, thereby facilitating quality control and consumer protection in the food industry.