Thermal effects and drugs competition on the palmitate binding capacity of human serum albumin.

Human serum albumin (HSA) is the most abundant plasma protein of the circulatory system. It is a multidomain, multifunctional protein that, combining diverse affinities and wide specificity, binds, stores, and transports a variety of biological compounds, pharmacores, and fatty acids. HSA is finding increasing uses in drug-delivery due to its ability to carry functionalized ligands and prodrugs. All this raises the question of competition for binding sites occupancy in case of multiple ligands, which in turn influences the protein structure/dynamic/function relationship and also has an impact on the biomedical applications. In this work, the effects of interactive binding of palmitic acid (PA), warfarin (War) and ibuprofen (Ibu) on the thermal stability of HSA were studied using DSC, ATR-FTIR, and EPR. PA is a high-affinity physiological ligand, while the two drugs are widely used for their anticoagulant (War) and anti-inflammatory (Ibu) efficacy, and are exogenous compounds that accommodate in the deputed drug site DS1 and DS2, respectively overlapping with some of the fatty acid binding sites. The results indicate that HSA acquires the highest thermal stability when it is fully saturated with PA. The binding of this physiological ligand does not hamper the binding of War or Ibu to the native state of the protein. In addition, the three ligands bind simultaneously, suggesting a synergic cooperative influence due to allosteric effects. The increased thermal stability subsequent to binary and multiple ligands binding moderates protein aggregation propensity and restricts protein dynamics. The biophysics findings provide interesting features about protein stability, aggregation, and dynamics in interaction with multiple ligands and are relevant in drug-delivery.

Analysis of the Dissolution Behavior of Theophylline and Its Cocrystal Using ATR-FTIR Spectroscopic Imaging.

Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopic imaging is a powerful tool to visualize the distribution of components, and it has been used to analyze drug release from tablets. In this work, ATR-FTIR spectroscopic imaging was applied for observing the dissolution of molecular crystals from tablet compacts. The IR spectra provided chemically specific information about the transformation of crystal structures during the dissolution experiments. Theophylline (TPL) anhydrate and its cocrystals were used as model systems of molecular crystals. The IR spectra during the dissolution of TPL revealed information about the crystal structure of TPL, which transformed from anhydrate to monohydrate in water. During a dissolution test of a model cocrystal system, it was suggested that an active pharmaceutical ingredient (API) and a coformer were dissolved in water simultaneously. The IR spectra that were acquired during the dissolution of a cocrystal tablet showed new spectral bands attributed to the API after 5 min. This suggested that the precipitation of API was observed during the dissolution experiment. Measurements from ATR-FTIR spectroscopic imaging can visualize the drug release from the tablet and determine the transformation of molecular crystals during their dissolution. These results will have an impact on clarifying the dissolution mechanism of molecular crystals.

How Does the Powder Mixture of Ibuprofen and Caffeine Attenuate the Solubility of Ibuprofen? Comparative Study for the Xanthine Derivatives to Recognize Their Intermolecular Interactions Using Fourier-Transform Infrared (FTIR) Spectra, Differential Scanning Calorimetry (DSC), and X-ray Powder Diffractometry (XRPD).

Molecular interactions between active pharmaceutical ingredients (APIs) and xanthine (XAT) derivatives were analyzed using singular value decomposition (SVD). XAT derivatives were mixed with equimolar amounts of ibuprofen (IBP) and diclofenac (DCF), and their dissolution behaviors were measured using high-performance liquid chromatography. The solubility of IBP decreased in mixtures with caffeine (CFN) and theophylline (TPH), whereas that of DCF increased in mixtures with CFN and TPH. No significant differences were observed between the mixtures of theobromine (TBR) or XAT with IBP and DCF. Mixtures with various molar ratios were analyzed using differential scanning calorimetry, X-ray powder diffraction, and Fourier-transform infrared spectroscopy to further explore these interactions. The results were subjected to SVD. This analysis provides valuable insights into the differences in interaction strength and predicted interaction sites between XAT derivatives and APIs based on the combinations that form mixtures. The results also showed the impact of the XAT derivatives on the dissolution behavior of IBP and DCF. Although IBP and DCF were found to form intermolecular interactions with CFN and TPH, these effects resulted in a reduction of the solubility of IBP and an increase in the solubility of DCF. The current approach has the potential to predict various interactions that may occur in different combinations, thereby contributing to a better understanding of the impact of health supplements on pharmaceuticals.

Identification of sudden cardiac death from human blood using ATR-FTIR spectroscopy and machine learning.

OBJECTIVE: The aim of this study is to identify a rapid, sensitive, and non-destructive auxiliary approach for postmortem diagnosis of SCD, addressing the challenges faced in forensic practice. METHODS: ATR-FTIR spectroscopy was employed to collect spectral features of blood samples from different cases, combined with pathological changes. Mixed datasets were analyzed using ANN, KNN, RF, and SVM algorithms. Evaluation metrics such as accuracy, precision, recall, F1-score and confusion matrix were used to select the optimal algorithm and construct the postmortem diagnosis model for SCD. RESULTS: A total of 77 cases were collected, including 43 cases in the SCD group and 34 cases in the non-SCD group. A total of 693 spectrogram were obtained. Compared to other algorithms, the SVM algorithm demonstrated the highest accuracy, reaching 95.83% based on spectral biomarkers. Furthermore, by combing spectral biomarkers with age, gender, and cardiac histopathological changes, the accuracy of the SVM model could get 100%. CONCLUSION: Integrating artificial intelligence technology, pathology, and physical chemistry analysis of blood components can serve as an effective auxiliary method for postmortem diagnosis of SCD.

Identifying hypothermia death in a mouse model by ATR-FTIR.

The identification of hypothermia death (HD) is difficult for cadavers, especially the distinction from death due to alternative causes. A large number of studies have shown that brown adipose tissue (BAT) plays critical roles in thermoregulation of mammals. In this study, BAT of mice was used for the discrimination of HD using attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR). A modified mouse HD model conducted by Feeney DM was used in this study to obtain infrared spectra of BAT. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to establish discrimination models. The PLS-DA and OPLS-DA models exhibit prominent discriminative efficiency, and the accuracy of HD identification using fingerprint regions and ratios of absorption intensity is near 100% in both the calibration and validation sets. Our preliminary study suggests that BAT may be an extremely effective target tissue for identification of cadavers of HD, and ATR-FTIR spectra combined with chemometrics have also shown potential for cadaver identification in forensic practice in a fast and accurate manner.

Sex and blood group determination from hair using ATR-FTIR spectroscopy and chemometrics.

Examination of hair with its intact root is commonly used for DNA profiling of the donor. However, its use for gathering other types of information is less explored. Using attenuated total reflectance-Fourier transform infrared spectroscopy, the present study aims to explore other relevant aspects in a non-destructive manner for forensics. Determining the sex and blood group of human hair samples were the major goals of the study. Sex determination was accomplished by analyzing the differential vibrational intensities and stretching of various chemical groups associated with hair and its proteins. Statistical inference of spectral data was performed using chemometric algorithms such as PCA and PLS-DA. The PLS-DA model determined sex with 100% accuracy and blood grouping with an average accuracy of 95%. The present study is the first of its kind to determine sex and blood grouping from human scalp hair shafts, as far as the author knows. By acting as a preliminary screening test, this study could have significant implications for forensic analysis of crime scene samples. Human and synthetic hair were used in validation studies, resulting in 100% accuracy, specificity, and sensitivity, with 0% false positives and false negatives. The technique ATR FTIR spectroscopy could complement the currently used methods of hair analysis such as physical examination and mitochondrial or genomic DNA analysis.

A novel approach using ATR-FTIR spectroscopy and chemometric analysis to distinguish male and female human hair samples.

This article presents an attempt to discriminate between human male and female hair samples using a single strand of scalp hair. The methodology involves the non-destructive application of ATR-FTIR spectroscopy coupled with chemometric analysis. A total of 96 hair samples, evenly distributed between 48 male and 48 female volunteers from India, were collected. Spectral analysis revealed subtle differences between the two groups, and reliance on visual interpretation might introduce biasness. To avoid subjective biases, chemometric techniques such as principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were employed for enhanced data visualization and separation. PCA results revealed that the first 10 principal components accounted for 93% of the total variance, with three significant PCs. The PLS-DA model demonstrated a remarkable sensitivity and specificity in sex discrimination from hair samples, establishing its efficacy as a robust classification tool. Furthermore, the proposed model exhibited 100% accuracy in predicting unknown samples, underscoring its potential applicability in real-world scenarios. These outcomes affirm the viability of our approach for non-invasive classification of human male and female hair based on single-strand scalp hair analysis.

A methodological approach to age estimation of the intra-puparial period of the forensically relevant blow fly Calliphora vicina via Fourier transform infrared spectroscopy.

Estimating the age of immature blow flies is of great importance for forensic entomology. However, no gold-standard technique for an accurate determination of the intra-puparial age has yet been established. Fourier transform infrared (FTIR) spectroscopy is a method to (bio-)chemically characterise material based on the absorbance of electromagnetic energy by functional groups of molecules. In recent years, it also has become a powerful tool in forensic and life sciences, as it is a fast and cost-effective way to characterise all kinds of material and biological traces. This study is the first to collect developmental reference data on the changes in absorption spectra during the intra-puparial period of the forensically important blow fly Calliphora vicina Robineau-Desvoidy (Diptera: Calliphoridae). Calliphora vicina was reared at constant 20°C and 25°C and specimens were killed every other day throughout their intra-puparial development. In order to investigate which part yields the highest detectable differences in absorption spectra throughout the intra-puparial development, each specimen was divided into two different subsamples: the pupal body and the former cuticle of the third instar, that is, the puparium. Absorption spectra were collected with a FTIR spectrometer coupled to an attenuated total reflection (ATR) unit. Classification accuracies of different wavenumber regions with two machine learning models, i.e., random forests (RF) and support vector machines (SVMs), were tested. The best age predictions for both temperature settings and machine learning models were obtained by using the full spectral range from 3700 to 600 cm-1. While SVMs resulted in better accuracies for C. vicina reared at 20°C, RFs performed almost as good as SVMs for data obtained from 25°C. In terms of sample type, the pupal body gave smoother spectra and usually better classification accuracies than the puparia. This study shows that FTIR spectroscopy is a promising technique in forensic entomology to support the estimation of the minimum post-mortem interval (PMImin), by estimating the age of a given insect specimen.

The first reported values of microplastics in prostate.

BACKGROUND: Microplastics are ubiquitous, widespread environmental pollutants with unavoidable human exposure. Herein, it was aimed to investigate the presence of microplastics in prostate tissue. METHODS: Prostate tissues from 12 patients who underwent Trans Urethral Resection of the Prostate (TUR-P) were analyzed to investigate the presence of microplastics. Initially, the prostate tissues were analyzed for microplastic particles using a light microscope after extraction. Subsequently, the chemical composition of the particles found in the prostate tissues was characterized using Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectrophotometry. RESULTS: Microplastic particles of various types were detected in 6 out of 12 patients. All detected plastic particles in this study were microplastics, with sizes below 26 µm in size. These microplastics exhibited different shapes as pellets, spheres or fibers. Overall, among the 12 analyzed prostate tissue samples, four different types of plastic were identified in six samples. The most common type of microplastic detected was Polyamide (Nylon 6), found in samples from three patients. Other detected types, Polypropylene, Polyacrylic Acid and Poly (dimethylsiloxane) were each determined in samples from one patient. CONCLUSIONS: This is the first study to demonstrate the presence of microplastics in prostate tissue, serving as an exploratory investigation, which can trigger further research to validate the results in a larger patient cohort.

Assessment of microplastics in coastal ecosystem of Bangladesh.

Microplastics (MPs) pose one of the major environmental threats to marine organisms and ecosystems on a global scale. The present study investigated MPs in surface water, beach sediments, and fish in two coastal areas of Bangladesh namely Cox's Bazar and Kuakata. The MPs were identified and characterized using three different techniques, including the binocular microscope, the ATR-FTIR (Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy), and SEM-EDS (Scanning Electron Microscopy- Energy Dispersive Spectroscopy). The number of MPs in seawater was 10.1 ± 3.10 and 8.52 ± 3.92 items/100 L and in beach sediment, 13.2 ± 3.68 and 9.48 ± 3.63 items/100 g in Cox's Bazar and Kuakata, respectively. In fish samples, the abundance of MPs was 7.82 ± 1.28 and 6.82 ± 1.87 items/individual species of Cox's Bazar and Kuakata, respectively, where the highest quantities of MP were found in Euthynnus affinisand Sillago sihama and the lowest in Terapon jarbua and Pampus chinensisin Cox's Bazar and Kuakata, respectively. The number of MPs in GITs (Gastrointestinal tracts) was 1.63 ± 0.991 and 1.25 ± 0.546 items/g GIT and in BW (Body Weight) were 0.042 ± 0.014 and 0.037 ± 0.014 items/g BW in Cox's Bazar and Kuakata, respectively. There revealed a positive correlation between MP abundance and GIT weight and body weight in fish species. MPs were predominantly fiber-shaped, white/transparent, and small size. The most common MP polymers were polyethylene and polypropylene. SEM images of MPs demonstrate surface roughness, cracks, mechanical weathering and oxidative weathering, demonstrating their ongoing environmental exposure. The EDS spectrum unearthed that the MPs contained several elements (C, N, O, Na, Al, Fe, and Si). Findings from this study might be useful in coastal plastic particle management and to mitigate the potential risks associated with them.

Identification of geographical origins of Gastrodia elata Blume based on multisource data fusion.

INTRODUCTION: Identifying the geographical origin of Gastrodia elata Blume contributes to the scientific and rational utilization of medicinal materials. In this study, infrared spectroscopy was combined with machine learning algorithms to distinguish the origin of G. elata BI. OBJECTIVE: Realization of rapid and accurate identification of the origin of G. elata BI. MATERIALS AND METHODS: Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectra and Fourier transform near-infrared (FT-NIR) spectra were collected for 306 samples of G. elata BI. SAMPLES: Firstly, a support vector machine (SVM) model was established based on the single-spectrum and the full-spectrum fusion data. To investigate whether feature-level fusion strategy can enhance the model's performance, the sequential and orthogonalized partial least squares discriminant analysis (SO-PLS-DA) model was established to extract and combine two types of spectral features. Next, six algorithms were employed to extract feature variables, SVM model was established based on the feature-level fusion data. To avoid complicated preprocessing and feature extraction processes, a residual convolutional neural network (ResNet) model was established after converting the raw spectral data into spectral images. RESULTS: The accuracy of the feature-level fusion model is better as compared to the single-spectrum model and the fusion model with full-spectrum, and SO-PLS-DA is simpler than feature-level fusion based on the SVM model. The ResNet model performs well in classification but requires more data to enhance its generalization capability and training effectiveness. CONCLUSION: Sequential and orthogonalized data fusion approaches and ResNet models are powerful solutions for identifying the geographic origin of G. elata BI.

Biodegradation of Polystyrene by Galleria mellonella: Identification of Potential Enzymes Involved in the Degradative Pathway.

Galleria mellonella is a lepidopteran whose larval stage has shown the ability to degrade polystyrene (PS), one of the most recalcitrant plastics to biodegradation. In the present study, we fed G. mellonella larvae with PS for 54 days and determined candidate enzymes for its degradation. We first confirmed the biodegradation of PS by Fourier transform infrared spectroscopy- Attenuated total reflectance (FTIR-ATR) and then identified candidate enzymes in the larval gut by proteomic analysis using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Two of these proteins have structural similarities to the styrene-degrading enzymes described so far. In addition, potential hydrolases, isomerases, dehydrogenases, and oxidases were identified that show little similarity to the bacterial enzymes that degrade styrene. However, their response to a diet based solely on polystyrene makes them interesting candidates as a potential new group of polystyrene-metabolizing enzymes in eukaryotes.

Enhancing Essential Oil Extraction from Lavandin Grosso Flowers via Plasma Treatment.

This study explores the impact of plasma treatment on Lavandin Grosso flowers and its influence on the extraction of essential oils (EOs) via hydrodistillation. Short plasma treatment times enhance the yield of EO extraction from 3.19% in untreated samples to 3.44%, corresponding to 1 min of plasma treatment, while longer treatment times (10 min) show diminishing returns to 3.07% of yield extraction. Chemical characterization (GC/MS and ATR-FTIR) indicates that plasma treatments do not significantly alter the chemical composition of the extracted EOs, preserving their aromatic qualities. Investigations into plasma-surface interactions reveal changes at the nanometer level, with XPS confirming alterations in the surface chemistry of Lavandin Grosso flowers by reducing surface carbon and increasing oxygen content, ultimately resulting in an increased presence of hydrophilic groups. The presence of hydrophilic groups enhances the interaction between the surface membrane of the glandular trichomes on Lavandin Grosso flowers and water vapor, consequently increasing the extraction of EOs. Furthermore, microscopic SEM examinations demonstrate that plasma treatments do not affect the morphology of glandular trichomes, emphasizing that surface modifications primarily occur at the nanoscale. This study underscores the potential of plasma technology as a tool to enhance EO yields from botanical sources while maintaining their chemical integrity.

Microplastics and plastisphere at surface waters in the Southwestern Caribbean sea.

Pollution generated by plastic waste has brought an environmental problem characterized by the omnipresence of smaller pieces of this material known as microplastics (MP). This issue was addresses by collecting samples with 250 µm pore size nets in two marine-coastal sectors of Southwestern Caribbean Sea during two contrasting seasons. Higher concentrations were found in rainy season than in dry season, reaching respectively 1.72 MP/m3 and 0.22 MP/m3. Within each sector, there were differences caused firstly by localities of higher concentrations of semi-closed water bodies localities during rainy season (Ciénaga Grande de Santa Marta and La Caimanera marsh), and secondly by lower concentrations of localities with less influenced of flow rates during dry season (Salamanca and Isla Fuerte). Moreover, the lowest concentration in dry season corresponding to La Caimanera marsh reflects how the community environmental management might decrease MP pollution. In both sectors and seasons, the particles of 0.3 mm (0.3-1.4 mm) size class dominated over those of 1.4 mm (1.4-5.0 mm) (reaching each respectively 1.33 MP/m3 and 0.39 MP/m3), with a dominance of fibers, except in the rainy season in Magdalena, where they were films. Using the FTIR technique, polypropylene was identified as the most abundant polymer in both sectors. The composition of the assemblage of microorganisms attached to microplastics presented higher richness and differed from that of free-living planktonic microbes. The most abundant members of the plastisphere were proteobacteria whose major representation was the pathogenic genus Vibrio, while the cyanobacteria dominated in seawater samples.

Alginate-Based Carriers Loaded with Mulberry (Morus alba L.) Leaf Extract: A Promising Strategy for Prolonging 1-Deoxynojirimicyn (DNJ) Systemic Activity for the Nutraceutical Management of Hyperglycemic Conditions.

The iminosugar 1-deoxynojirimicyn (DNJ) contained in mulberry leaves has displayed systemic beneficial effects against disorders of carbohydrate metabolism. Nevertheless, its effect is impaired by the short half-life. Alginate-based carriers were developed to encapsulate a DNJ-rich mulberry extract: Ca-alginate beads, obtained by external gelation, and spray-dried alginate microparticles (SDMs). Mean size and distribution, morphology, drug loading, encapsulation efficiency, experimental yield, and release characteristics were determined for the two formulations. Ca-alginate beads and SDMs exhibited an encapsulation efficiency of about 54% and 98%, respectively, and a DNJ loading in the range of 0.43-0.63 µg/mg. The in vitro release study demonstrated the carriers' capability in controlling the DNJ release in acid and basic conditions (<50% in 5 h), due to electrostatic interactions, which were demonstrated by 1H-NMR relaxometry studies. Thus, alginate-based particles proved to be promising strategies for producing food supplements containing mulberry leaf extracts for the management of hyperglycemic state.

Risk assessment of cigarette butts and microplastic pollution in a drinking and irrigation water basin of West Anatolia, Türkiye.

Cigarette butts (CBs) and Microplastics (MPs) have serious harmful effects on the environment and living organisms despite their small size. This research aims to investigate the abundance and pollution status of CBs and MPs in Tahtali Dam Basin (West Anatolia, Türkiye) which is the most important drinking and irrigation water resources. Clean Environment Index (CEI) and Cigarette Butt Pollution Index (CBPI) were used to determine pollution degree of the basin. The total number of CBs were 1.478 items, the total number of MPs were 477 items/m2 in the basin. As a result of this study, MP particles weren't found in Balaban Stream. Highest number of MP particles observed in 100-250 µm (45%) size class. The most abundant MP type and colour were, fragment (54%) and white (42%), respectively. Polyethylene terephthalate (50%) was the most abundant type of polymer according to the ATR- FTIR analysis. As a result of the CEI and CBPI, the upstream stations of the stream were classified as "clean" status, while downstream sampling points of the stream and Balaban Lake coasts were classified as "extremely dirty" status. The calculated volumes of MP particulates from mining facility, agricultural and recreational activities indicate that anthropogenic factors are the most important MP source in the Tahtali Dam Basin. This study is the first study about MP and CB pollution of the freshwater ecosystems in the region.

Forensic Discrimination of condom lubricants using ATR-FTIR spectroscopy in combination with chemometrics- effect of matrices, pre-coital and post-coital conditions.

The escalating rates of rape and sexual assault cases underscore the essential need to analyze associative evidence of sexual assault to ensure justice. The condom, when used during the act of sexual assault/rape, leaves behind traces of lubricant that could be instrumental in establishing the link between the victim and perpetrator. This leading evidence is crucial especially when the traditional DNA analysis is challenging owing to the lack of biological evidence. The present study employs the use of ATR FTIR spectroscopy coupled with the chemometric, to discern the chemical discrimination of condom lubricants. The study also aimed to investigate simulated real-case scenarios by analysing the effect of different matrices such as vaginal fluid, menstrual blood, and undergarment substrates (cotton, polyester and nylon) on condom traces. The difference in the spectral profile of pre-coitus and post-coitus samples was also investigated. The results of the present study are noteworthy, unveiling the efficacy of discriminating the condom lubricants of different brands and other frequently used household lubricants with 100% sensitivity, specificity, and accuracy. Condom lubricants are detected despite the presence of contaminants such as menstrual blood, and vaginal fluid, across different substrates and, in post-coital conditions. In conclusion, this study presents a comprehensive approach to analysing condom lubricants, offering a potential breakthrough in the investigation of sexual assault cases, coupled with the ability to counter false accusations.

Estimation of Time-Since-Deposition of bloodstains on different surfaces using ATR-FTIR Spectroscopy and Chemometrics.

Blood is commonly discovered at crime scenes in various forms, including stains, dried residue, pools, and fingerprints on assorted surfaces. Estimating the age of bloodstains is a crucial aspect of reconstructing crime scenes. This research aimed to investigate how the nature of different surfaces affects the estimation of bloodstain age, utilizing a reliable and non-destructive approach. The study employed ATR-FTIR spectroscopy in conjunction with Chemometric techniques such as PCA (Principal Component Analysis) and OPLSR (Orthogonal Signal Correction Partial Least Square Regression Analysis) to analyze spectral data and develop regression models for estimating bloodstain age on cement, metal, and wooden surfaces for up to eleven days. The chemometric models for bloodstains on all three substrates demonstrated strong performance, with predictive Root Mean Square Error (RMSE) values ranging from 1.1 to 1.43 and R2 values from 0.84 to 0.89. Notably, the model developed for metal surfaces was found to be the most accurate with minimal prediction error. The findings of the study showed that the porosity of the substrates upon which bloodstains were found had a discernible influence on the age-related transformations observed in bloodstains; the majority of which occured within the spectral range of 2800 cm- 1 to 3500 cm- 1.

Combined molecular spectroscopic techniques (SR-FTIR, XRF, ATR-FTIR) to study physiochemical and nutrient profiles of Avena sativa grain and nutrition and structure interactive association properties.

Synchrotron radiation based on Fourier transform infrared radiation (SR-FTIR), X-ray fluorescence (XRF) and attenuated total reflection based on Fourier transform infrared radiation (ATR-FTIR) spectroscopy are both fast determining and minimal sample preparing techniques. They are capable of detecting the internal molecular structures. However, these techniques are still not well understood by nutrition researchers for the analysis of feed. The purpose of this review is to introduce advanced SR-FTIR, XRF, and ATR-FTIR molecular techniques, use these techniques to study chemical and nutrient profiles of Avena sativa grain, and lastly to study the nutrition and structure interactive association properties. The review mainly focuses on the following aspects: 1) the background information of Avena sativa grain; its history, chemical composition, nutrient profile, inherent structure, and production; 2) molecular spectroscopic techniques; principles and spectral analysis methodology of SR-FTIR, XRF and ATR-FTIR; 3) the application of SR-FTIR, XRF, and ATR-FTIR as a novel approach. This review provides an insight on how molecular spectroscopic techniques could be used for the study of nutrition and structure interactive association properties.

Spectroscopic Investigation of Phosphorus Mineralization as Affected by the Calcite-Water Interfacial Chemistry.

The mineralization and bioavailability of phytic acid, the predominant organic phosphorus (OP) species in many soils, have generally been rendered limited due to its interaction with soil minerals. In particularly calcareous and neutral to slightly alkaline soils, phytic acid is known to actively react with calcite, although how this interaction affects phytic acid mineralization is still unknown. This study, therefore, investigated the mechanisms regarding how the calcite-water interface influences phytic acid mineralization by phytase, at pHs 6 and 8 using in situ spectroscopic techniques including solution nuclear magnetic resonance and attenuated total reflection Fourier transform infrared spectroscopy. The findings indicated a pH-specific effect of the calcite-water interface. Inhibited phytase activity and thus impaired phytic acid mineralization were induced by calcite at pH 6, while the opposite effect was observed at pH 8. How the interaction between phytic acid and calcite and between phytase and calcite differed between the two pH values contributed to the pH-specific effect. The results demonstrate the importance of soil pH, enzyme-, and OP-clay mineral interactions in controlling the mineralization and transformation of OP and, consequently, the release of phosphate in soils. The findings can also provide implications for the management of calcite-rich and limed soils.