Characterization of industrial TNT in ammunition shells: An in-depth study of artificial aging effects using Fourier-Transform infrared spectroscopy and gas chromatography-mass spectrometry

In this study, we comprehensively investigated the degradation of industrial trinitrotoluene (TNT), focusing on the effects of aging and direct contact with steel surfaces, mirroring real-world usage conditions. While practical knowledge exists regarding this degradation, the existing literature lacks in-depth insights into the underlying processes. To address this gap, we conducted experiments using small steel samples, representative of military ammunition casings, which were coated with TNT and subjected to 30 days of heating at 75 °C under vacuum conditions. A subset of these samples was coated with a protective red alkyd paint. After the aging process, the TNT was carefully removed from the metal surfaces and subjected to a comprehensive analysis encompassing scanning electron microscopy, Fourier-transform infrared spectroscopy, and gas chromatography-mass spectrometry. Our results reveal a remarkable preservation of the chemical integrity of industrial TNT, even in the presence of thermal stress and direct steel contact. Although superficial changes were observed in the TNT's appearance, all analytical data consistently demonstrated the maintenance of its chemical composition. Notably, the sole change in composition was attributed to the presence of degradation products associated with the alkyd paint coating, rather than intrinsic TNT degradation. These findings underscore the negligible impact of degradation processes on TNT in scenarios involving the solid-phase thermal stress of TNT in direct contact with metal, significantly enhancing our understanding of TNT safety when packaged within steel artifacts-a common context in military ammunition.

Application of UV-Vis-NIR and FTIR spectroscopy coupled with chemometrics for quality prediction of katsuobushi based on the number of smoking treatments

Katsuobushi, a smoked, dried skipjack tuna, is a traditional Japanese food additive with a unique flavor and taste. Gas chromatography mass spectrometry (GC-MS), fourier transform infrared (FTIR), and ultraviolet-visible-near infrared spectroscopy (UV-Vis-NIR) combined with chemometric methods were evaluated the quality of katsuobushi according to the number of smoking treatments. Using GC-MS, 46 metabolites were identified and five metabolites were selected as key compounds. All samples were classified according to their smoking number via principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA) and hierarchical cluster analysis (HCA) of the FTIR and NIR spectra. Partial least squares regression (PLSR) analysis revealed that the FTIR and NIR spectra were highly correlated with the metabolites by GC-MS. These results demonstrated the potential of using the FTIR and NIR spectroscopy combined with chemometrics to assess the quality of katsuobushi based on the smoking treatments, with NIR spectroscopy showed particularly promising.

Distinction and quantification of Panax polysaccharide extracts via attenuated total reflectance-Fourier transform infrared spectroscopy with first-order derivative processing

Derivative spectroscopy is used to separate the small absorption peaks superimposed on the main absorption band, which is widely adopted in modern spectral analysis to increase both the valid spectral information and the identification accuracy. In this study, a method based on attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) with first-order derivative (FD) processing combined with chemometrics is proposed for rapid qualitative and quantitative analysis of Panax ginseng polysaccharides (PGP), Panax notoginseng polysaccharides (PNP), and Panax quinquefolius polysaccharides (PQP). First, ATR-FTIR with FD processing was used to establish the discriminant model combined with principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA). After that, two-dimensional ATR-FTIR based on single-characteristic temperature as external interference (2D-sATR-FTIR) was established using ATR-FTIR with FD processing. Then, ATR-FTIR with FD processing was combined with PLS to establish and optimize the quantitative regression model. Finally, the established discriminant model and 2D-sATR-FTIR successfully distinguished PGP, PNP and PQP, and the optimal PLS regression model had a good prediction ability for the Panax polysaccharide extracts content. This strategy provides an efficient, economical and nondestructive method for the distinction and quantification of PGP, PNP and PQP in a short detection time.

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.

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.

Quality comparison of plastic packaging waste from different separation systems: Result enhancement with non-negative matrix factorization of FTIR spectra

Whether plastic packaging waste is disposed of in different bins (source separation, S) or in a single bin (post source separation, P) is generally assumed to impact the waste stream's quality. To elucidate this question, we evaluated the quality of LDPE, HDPE, and PP plastic waste from both separation systems (S and P) through a concise analytical strategy. The materials received similar treatment after collection (e.g., washing, NIR-sorting). A multivariate approach to ATR-FTIR spectroscopy was developed to assess their material composition and the effect of washing. Results were complemented by TGA, DSC, and py-GC/MS analysis. The material performance was investigated by a lab-scale extrusion and granulation, followed by an assessment of the mechanical properties and the melt volume rate. Our study reveals the HDPE materials to be of good quality, regardless of their source. For LDPE and PP, the P-materials are fractionally more contaminated after washing. Both PP-materials display poor material performance with highly fluctuating elongations-at-break (between 30% and 380%). S-LDPE was found to contain more polymeric impurities than P-LDPE. We conclude that the quality depends strongly on the material type and on the treatment after collection (washing, sorting). The multivariate approach to FTIR data evaluation we propose aims at simplifying the quality evaluation of polyolefin waste plastics and may serve as a basis for future work in this field.

Towards quantifying biomarkers for respiratory distress in preterm infants: Machine learning on mid infrared spectroscopy of lipid mixtures

Neonatal respiratory distress syndrome (nRDS) is a challenging condition to diagnose which can lead to delays in receiving appropriate treatment. Mid infrared (IR) spectroscopy is capable of measuring the concentrations of two diagnostic nRDS biomarkers, lecithin (L) and sphingomyelin (S) with the potential for point of care (POC) diagnosis and monitoring. The effects of varying other lipid species present in lung surfactant on the mid IR spectra used to train machine learning models are explored. This study presents a lung lipid model of five lipids present in lung surfactant and varies each in a systematic approach to evaluate the ability of machine learning models to predict the lipid concentrations, the L/S ratio and to quantify the uncertainty in the predictions using the jackknife + -after-bootstrap and variant bootstrap methods. We establish the L/S ratio can be determined with an uncertainty of approximately ±0.3 mol/mol and we further identify the 5 most prominent wavenumbers associated with each machine learning model.

Toxic effects of aniline in liver, gills and kidney of freshwater fish Channa punctatus after acute exposure

Aniline (C6H5NH2) is one of the hazardous aromatic amine where an amino group -NH2) is connected to phenyl ring (C6H5). Based on the evaluation of the 96-hour LC50 of aniline, two sublethal concentrations (4.19 mg/l and 8.39 mg/l) were selected for acute exposure tests in freshwater fish Channa punctatus. The liver, gills and kidney of fish being the principal sites of xenobiotic material accumulation, respiration, biotransformation, and excretion are the focus of the present study. Throughout the exposure time, the comet assay revealed increased tail length and tail DNA percentage indicating maximum damage to liver, gills and kidney of treated group after 96 h. After acute exposure, there was a significant (p ≤ 0.05) increase in the enzymatic activity of glutathione-S-transferase (GST) and acetylcholinesterase (AChE), whereas decline in superoxide dismutase (SOD) and catalase (CAT) activity was observed. Meanwhile, levels of malondialdehyde (MDA) increased over the exposure period for both concentrations. After 96 h of exposure, degree of tissue change (DTC) was evaluated in liver, gill and kidney of aniline exposed fish. Additionally, light microscopy revealed multiple abnormalities in liver, gills and kidney of all the treated groups. Significant changes were observed in the levels of biochemical markers viz., glucose, triglyceride, cholesterol, aspartate transaminase, alanine transaminase and urea following a 96-hour exposure to aniline. Studies using ATR-FTIR and transmission electron microscopy (TEM) revealed changes in biomolecules and structural abnormalities in several tissues of the aniline-exposed groups in comparison to the control group respectively.

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.

Differential effects of the lipidic and ionic microenvironment on NPP1's phosphohydrolase and phosphodiesterase activities

Ecto-nucleotide pyrophosphatase/phosphodiesterase 1 (NPP1) is an enzyme present in matrix vesicles (MV). NPP1 participates on the regulation of bone formation by producing pyrophosphate (PPi) from adenosine triphosphate (ATP). Here, we have used liposomes bearing dipalmitoylphosphatidylcholine (DPPC), sphingomyelin (SM), and cholesterol (Chol) harboring NPP1 to mimic the composition of MV lipid rafts to investigate ionic and lipidic influence on NPP1 activity and mineral propagation. Atomic force microscopy (AFM) revealed that DPPC-liposomes had spherical and smooth surface. The presence of SM and Chol elicited rough and smooth surface, respectively. NPP1 insertion produced protrusions in all the liposome surface. Maximum phosphodiesterase activity emerged at 0.082 M ionic strength, whereas maximum phosphomonohydrolase activity arose at low ionic strength. Phosphoserine-Calcium Phosphate Complex (PS-CPLX) and amorphous calcium-phosphate (ACP) induced mineral propagation in DPPC- and DPPC:SM-liposomes and in DPPC:Chol-liposomes, respectively. Mineral characterization revealed the presence of bands assigned to HAp in the mineral propagated by NPP1 harbored in DPPC-liposomes without nucleators or in DPPC:Chol-liposomes with ACP nucleators. These data show that studying how the ionic and lipidic environment affects NPP1 properties is important, especially for HAp obtained under controlled conditions in vitro.

Landfill leachate from Municipal Solid Waste: Multi-technique approach for its fine characterization and determination of the thermodynamic and sequestering properties towards some toxic metals

Landfill leachate is a multicomponent aqueous matrix generated by the percolation of rainwater into the body of a landfill. Considering its content of natural and xenobiotic components, it must be considered as a waste, whose composition depends on type of waste, biodegradation processes, rainwater, composition and compaction of waste and their age; these factors influence the transport, absorption, toxicity, bioaccumulation of the contaminants. Leachates sampled from landfill and downhill piezometers, in periods characterized by different rainfall, were studied by ATR-FTIR and SEM-EDX techniques; analyses were carried out on dried and calcinated residues obtained at T = 383 and 923 K, respectively. The chemical-physical characterization of all the leachates was carried out by using the official methods of analysis, obtaining for many metals and some organic contaminants exceedance of the concentrations with respect to the limits established by the Italian Legislative Decree 152/2006. From potentiometric titrations carried out at T = 298.15 K in NaCl(aq) and applying the Polyprotic Like model, each leachate resulted to have a different composition in terms of COOH and OH groups and various acid-base properties. The interacting ability of leachates with metal cations (Cd2+, Zn2+, Cu2+) was studied by potentiometric and voltammetric (only for Pb2+) techniques in NaCl (NaNO3 for Pb2+) aqueous solutions, at I = 0.15 mol dm-3 and T = 298.15 K, obtaining diverse speciation models and complexes of very different stability. The leachates sequestering ability towards the metal cations was quantified at various pH values using the pL0.5 parameter, proving that each leachate has a different strength of interaction towards the metals, that tends to increase with the pH and confirming that they behave as carriers of contaminants through the soil and towards groundwater, with the consequent problems of contamination and/or environmental disaster and risks for the human health.

Optimization of the selection of suitable harvesting periods for medicinal plants: taking Dendrobium officinale as an example

BACKGROUND

Dendrobium officinale is a medicinal plant with high commercial value. The Dendrobium officinale market in Yunnan is affected by the standardization of medicinal material quality control and the increase in market demand, mainly due to the inappropriate harvest time, which puts it under increasing resource pressure. In this study, considering the high polysaccharide content of Dendrobium leaves and its contribution to today's medical industry, (Fourier Transform Infrared Spectrometer) FTIR combined with chemometrics was used to combine the yields of both stem and leaf parts of Dendrobium officinale to identify the different harvesting periods and to predict the dry matter content for the selection of the optimal harvesting period.

RESULTS

The Three-dimensional correlation spectroscopy (3DCOS) images of Dendrobium stems to build a (Split-Attention Networks) ResNet model can identify different harvesting periods 100%, which is 90% faster than (Support Vector Machine) SVM, and provides a scientific basis for modeling a large number of samples. The (Partial Least Squares Regression) PLSR model based on MSC preprocessing can predict the dry matter content of Dendrobium stems with Factor = 7, RMSE = 0.47, R2 = 0.99, RPD = 8.79; the PLSR model based on SG preprocessing can predict the dry matter content of Dendrobium leaves with Factor = 9, RMSE = 0.2, R2 = 0.99, RPD = 9.55.

CONCLUSIONS

These results show that the ResNet model possesses a fast and accurate recognition ability, and at the same time can provide a scientific basis for the processing of a large number of sample data; the PLSR model with MSC and SG preprocessing can predict the dry matter content of Dendrobium stems and leaves, respectively; The suitable harvesting period for D. officinale is from November to April of the following year, with the best harvesting period being December. During this period, it is necessary to ensure sufficient water supply between 7:00 and 10:00 every day and to provide a certain degree of light blocking between 14:00 and 17:00.

Face-dependent phosphate speciation on goethite: CD-MUSIC modeling and ATR-FTIR/2D-COS study

Understanding the face-dependent phosphate adsorption mechanisms and their variations with environmental conditions is of great significance for revealing phosphate adsorption mechanisms on various goethites and predicting phosphorus speciation in iron-rich soils. In this study, micro- (MicroGoe) and nano-sized goethite (NanoGoe) were synthesized and used to investigate the face-dependent adsorption behaviors of proton and phosphate on goethite by combining the charge distribution-multisite surface complexation (CD-MUSIC) model and attenuated total reflectance Fourier transform infrared (ATR-FTIR). The results demonstrated that MicroGoe had a higher charge density and phosphate adsorption capacity than NanoGoe, which could be attributed to the higher site density of ≡FeOH-0.5 and inner-layer capacitance arising from a higher proportion of capping face and rougher surface of MicroGoe. The logKH of ≡FeOH-0.5 on the main and capping face was 8.2 and 8.9, respectively. Three types of monodentate mononuclear phosphate complexes in different protonated states were identified, along with the non-protonated bidentate complex. Protonated monodentate complexes were formed at relatively low pH and high surface loadings, whereas non-protonated complexes were the predominant species at intermediate to high pH. MicroGoe had a higher percentage of monodentate complexes than NanoGoe, and both goethites had considerably lower phosphate adsorption on the capping face than on the main face. The results provide valuable insights into the interfacial reactivity of goethite prepared with various methods and facilitate further prediction of phosphorus speciation and availability in iron-rich soils.

Quantitative phase analysis and molecular structure of human gallstones using synchrotron radiation X-ray diffraction and FTIR spectroscopy

Human gallstones are the most common disorder in the biliary system, affecting up to 20 % of the adult population. The formation of gallstones is primarily due to the supersaturating of cholesterol in bile. In order to comprehend gallstone disease in detail, it is necessary to have accurate information about phase identification and molecular structure. Different types of gallstone samples were collected from the Middle East area after surgical operations including; cholesterol, pigment, and mixed gallstones. To estimate the basic information about the stone formation and the pathophysiology of cholelithiasis as well as to classify the collected human gallstones, attenuated total reflection Fourier transform Infrared spectrometry (ATR-FTIR) was used to analyze the different gallstone structures in the wavenumber range from 400 to 4000 cm-1. Calcium bilirubinate was specified by the bands at 1662 cm-1, 1626 cm-1, and 1572 cm-1, while cholesterol rings were designated by the bands at 1464, 1438, 1055, and 1022 cm-1. It can be assumed that all samples consist of mixed gallstones based on the doublets at 1375 cm-1 and 1365 cm-1. The levels of calcium bilirubin and various minerals varied among the analyzed samples, indicating the heterogeneity in their composition and suggesting potential implications for gallstone formation. Based on the quantitative phase analysis using synchrotron radiation X-ray diffraction (SR-XRD), two phases of anhydrous cholesterol as a major content and one phase of monohydrate cholesterols as trace content represent the main components of most of the gallstones. Additional phases of calcium carbonate in the form of calcite, vaterite, aragonite, and bilirubinate were also quantified. According to the outcomes of the FTIR and the SR-XRD measurements, there exists a statistical correlation between the different types of chemical constituents of the gallstones.

Enhancing forensic investigations: Identifying bloodstains on various substrates through ATR-FTIR spectroscopy combined with machine learning algorithms

The forensic analysis of bloodstains on various substrates plays a crucial role in criminal investigations. This study presents a novel approach for analyzing bloodstains using Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR) in combination with machine learning. ATR-FTIR offers non-destructive and non-invasive advantages, requiring minimal sample preparation. By detecting specific chemical bonds in blood components, it enables the differentiation of various body fluids. However, the subjective interpretation of the spectra poses challenges in distinguishing different fluids. To address this, we employ machine learning techniques. Machine learning is extensively used in chemometrics to analyze chemical data, build models, and extract useful information. This includes both unsupervised learning and supervised learning methods, which provide objective characterization and differentiation. The focus of this study was to identify human and porcine blood on substrates using ATR-FTIR spectroscopy. The substrates included paper, plastic, cloth, and wood. Data preprocessing was performed using Principal Component Analysis (PCA) to reduce dimensionality and analyze latent variables. Subsequently, six machine learning algorithms were used to build classification models and compare their performance. These algorithms comprise Partial Least Squares Discriminant Analysis (PLS-DA), Decision Trees (DT), Logistic Regression (LR), Naive Bayes Classifier (NBC), Support Vector Machine (SVM), and Neural Network (NN). The results indicate that the PCA-NN model provides the optimal solution on most substrates. Although ATR-FTIR spectroscopy combined with machine learning effectively identifies bloodstains on substrates, the performance of different identification models still varies based on the type of substrate. The integration of these disciplines enables researchers to harness the power of data-driven approaches for solving complex forensic problems. The objective differentiation of bloodstains using machine learning holds significant implications for criminal investigations. This technique offers a non-destructive, simple, selective, and rapid approach for forensic analysis, thereby assisting forensic scientists and investigators in determining crucial evidence related to bloodstains.

Improved discrimination of COVID-19 based on data enhancement technology and an information balance feature selection (INB) method

The coronavirus disease (COVID-19) ravaged the world in late 2019 and posed a serious threat to human life and property destruction on a global scale. In this paper, the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) method was selected for balancing the data sample, and an information balance feature selection (INB) method was first proposed to realize the accurate discrimination of COVID-19 saliva samples based on the attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. The results of the experiment showed that the INB method obtained higher classification accuracy than the traditional feature selection methods in both the original spectrum and the second-order derivative spectrum, especially in the second-order derivative spectrum where all the indexes reached about 85 %. In addition, the combination of WGAN_GP data augmentation and the INB method resulted in an accuracy of 88.7 % for the original spectrum and even 90.6 % for the second-order derivative spectrum. According to these findings, classification research using the WGAN_GP data enhancement model may increase classification accuracy. Additionally, the ability to successfully separate COVID-19 indicates that the INB method to identify spectral data features is a workable method, which also offers a fresh viewpoint on feature selection.

Microplastic prevalence in epipelagic layer: Evidence from epipelagic inhabiting prawns of north-west Arabian Sea

The escalating global microplastic (MP) pollution severely threatens marine life due to insufficient waste management and widespread single-use plastic. This study focuses on assessing MP contamination in commercial prawns from Gujarat State, India. Ten prawn species collected at five main fishing harbors revealed 590 MP particles in their gastrointestinal tracts, averaging 6.08 ± 5.96 MPs/g and 1.15 ± 0.78 MPs/individual. Significant variations in contamination levels were observed between species and study sites. Pollution indices indicated very high contamination throughout the study sites. Threads were the predominant shape, with blue and black as prevalent colors. Size-wise, 1-2 mm MPs dominated. Polymer analysis identified polyethylene terephthalate, polyurethane, polystyrene, polypropylene, polyvinyl chloride, and acrylonitrile butadiene styrene. The findings provided crucial preliminary information for ecotoxicology and seafood safety investigations regarding MP contamination in commercially important prawns.

Fast screening using attenuated total reflectance- fourier transform infrared (ATR-FTIR) spectroscopy of patients based on D-dimer threshold value

Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is an emerging technology in the medical field. Blood D-dimer was initially studied as a marker of the activation of coagulation and fibrinolysis. It is mainly used as a potential diagnosis screening test for pulmonary embolism or deep vein thrombosis but was recently associated with COVID-19 severity. This study aimed to evaluate the use of ATR-FTIR spectroscopy with machine learning to classify plasma D-dimer concentrations. The plasma ATR-FTIR spectra from 100 patients were studied through principal component analysis (PCA) and two supervised approaches: genetic algorithm with linear discriminant analysis (GA-LDA) and partial least squares with linear discriminant (PLS-DA). The spectra were truncated to the fingerprint region (1800-1000 cm-1). The GA-LDA method effectively classified patients according to D-dimer cutoff (≤0.5 μg/mL and >0.5 μg/mL) with 87.5 % specificity and 100 % sensitivity on the training set, and 85.7 % specificity, and 95.6 % sensitivity on the test set. Thus, we demonstrate that ATR-FTIR spectroscopy might be an important additional tool for classifying patients according to D-dimer values. ATR-FTIR spectral analyses associated with clinical evidence can contribute to a faster and more accurate medical diagnosis, reduce patient morbidity, and save resources and demand for professionals.

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.

Evidence of microplastics accumulation in the gills and gastrointestinal tract of fishes from an estuarine system in Ghana

The contamination of aquatic environments by microplastics (MPs) and their subsequent ingestion by fish continues to be a universal ecological challenge. Although numerous studies have been conducted on the accumulation of MPs by fishes globally, not much work has been done within the major estuaries along the Atlantic Coast. This study explored and characterized microplastics in the gills and gastrointestinal tract in 98 specimens of 10 fish taxa (Sarotherodon melanotheron, Pseudotolithus senegalensis, Gobionellus occidentalis, Ethmalosa fimbriata, Chrysichthys nigrodigitalus, Elops lacerta, Mugil bananesis, Cynoglossus senegalensis, Apsilus fuscus and Galeoides decadactylus) from the Pra Estuary, Ghana. The gastrointestinal contents of the fish were extracted, analysed and characterized using a stereomicroscope fitted with an Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR). A total of 529 MP particles were found in the fishes. C. nigrodigitalus recorded the highest MP levels in the gills with an average of 4.83 ± 2.08 items/individual whiles S. melanotheron recorded the highest in the gastrointestinal tract at 9.83 ± 4.63 items/individual. Within the fish, transparent fibrous MPs of size <0.5 mm were the dominate types found. A vertical prevalence of MPs was observed across the feeding and habitat preference of the species suggesting a possible linkage with the ecological niche of fishes. Our findings further demonstrate the need for advance studies on the impacts and level of threat microplastic accumulation pose to the sampled fishes and potential consumers.

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.

Identification of sources of coarse mode aerosol particles (PM10) using ATR-FTIR and SEM-EDX spectroscopy over the Himalayan Region of India

This study attempts to examine the morphological, elemental and physical characteristics of PM10 over the Indian Himalayan Region (IHR) using FTIR and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis. The study aimed at source identification of PM10 by exploring the inorganic ions, organic functional groups, morphology and elemental characteristics. The pollution load of PM10 was estimated as 63 ± 22 μg m-3; 53 ± 16 μg m-3; 67 ± 26 μg m-3 and 55 ± 11 μg m-3 over Mohal-Kullu, Almora, Nainital and Darjeeling, respectively. ATR-FTIR spectrum analysis revealed the existence of inorganic ions (SiO44-, TiO2, SO42-, SO3-, NO3-, NO2-, CO32-, HCO3-, NH4+) and organic functional groups (C-C, C-H, C=C, C≡C, C=O, N-H, C≡N, C=N, O-H, cyclic rings, aromatic compounds and some heterogeneous groups) in PM10 which may arise from geogenic, biogenic and anthropogenic sources. The morphological and elemental characterization was performed by SEM-EDX, inferring for geogenic origin (Al, Na, K, Ca, Mg and Fe) due to the presence of different morphologies (irregular, spherical, cluster, sheet-like solid deposition and columnar). In contrast, particles having biogenic and anthropogenic origins (K, S and Ba) have primarily spherical with few irregular particles at all the study sites. Also, the statistical analysis ANOVA depicts that among all the detected elements, Na, Al, Si, S and K are site-specific in nature as their mean of aw% significantly varied for all the sites. The trajectory analysis revealed that the Uttarakhand, Jammu and Kashmir, the Thar Desert, Himachal Pradesh, Pakistan, Afghanistan, Nepal, Sikkim, the Indo-Gangetic Plain (IGP) and the Bay of Bengal (BoB) contribute to the increased loading of atmospheric pollutants in various locations within the IHR.

Cold atmospheric pressure air plasma jet disinfection of table eggs: Inactivation of Salmonella enterica, cuticle integrity and egg quality

Eggshell cuticles are first lines of defense against egg-associated pathogens, such as Salmonella enterica serovar Enteritidis (SE). Infections from eggs contaminated with this strain remain a significant risk. In addition, changes in the cuticle are closely related to changes in egg safety. The emerging non-thermal atmospheric pressure plasma technology enables a high rate of microbial inactivation at near-ambient temperatures, making it ideal for food safety applications. This study examines the effects of a cold atmospheric pressure air plasma jet (CAAP-J) on eggshell cuticle and egg quality whilst inactivating SE. Shell eggs inoculated with SE (7 log10 cfu/egg) were used as the samples to test the decontamination performance of the device. The tests were conducted using an industrial CAAP-J with different power levels (600-800 W), exposure times (60-120 s), at a fixeddistance of 20 mm from the plasma jet and an air flow rate of 3600 L/h. It was found that the best results were obtained after 120 s at maximum plasma power (800 W). Subsequent to the implementation of this plasma procedure, it was determined that no viable cells could be detected. After CAAP-J treatment, the temperature remains below 50.5 °C, thereby minimizing the risk of altering egg quality. All specific measurements (egg white pH, yolk pH, yolk color, HU, and eggshell breaking strength) have shown that CAAP-J treatment has no negative effect on egg quality. No changes in eggshell cuticle quality after CAAP-J treatment was confirmed through scanning electron microscope (SEM).

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.

In-situ quantitative prediction of pesticide residues on plant surface by ATR-FTIR technique coupled with chemometrics

Pesticide residues on plant surfaces pose a severe threat to food security, yet most research has focused on monitoring the liquid matrix, with few reports conducting in-situ analysis of the residues. This study was the first to attempt to utilize portable attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) for in-situ characterization of broad-spectrum fungicide boscalid residues on plant surfaces. ATR-FTIR scanning of tomato fruits with pre-determined concentrations of boscalid residues was conducted without any pre-treatment, and the obtained spectra were then processed using chemometrics methods. The results demonstrated a negative correlation between the residual concentrations and their corresponding absorption intensities of several well-resolved peaks from the spectra, resulting in a high accuracy of 93.33% for the classification model created by probabilistic neural network (PNN) coupled with principal component analysis (PCA). By employing correlation analysis and the interval partial least squares method (iPLS), quantitative analysis was conducted on the wavenumber ranges of 1000-1800 cm-1 and 2700-2900 cm-1 from the spectra. The regression model, established through partial least squares regression (PLSR), demonstrated exceptional performance with an R2 value of 0.80, RMSE of 1.02 μg/cm2, RPD of 2.0, and RPIQ of 2.1 for validation. Meanwhile, the detection limit (LOD) of the model was calculated as 3.06 μg/cm2. This report highlights the potential of using portable ATR-FTIR for conducting qualitative and quantitative monitoring of pesticide residues both in-situ and on-site. It also provides references for other measuring techniques.

Exploration of microplastic concentration in indoor and outdoor air samples: Morphological, polymeric, and elemental analysis

Microplastics are ubiquitously pervasive throughout the environment, but unlike aquatic and terrestrial microplastics, airborne microplastics have received less scientific attention. This study is the first of its kind to explicitly examine microplastics in the indoor and outdoor air (PM2.5) samples collected using active air samplers in Islamabad, Pakistan. The suspected synthetic particles were analyzed using ATR-FTIR, μ-Raman and SEM-EDX to categorize them based on their morphological characteristics, polymeric composition, and elemental makeup. Microplastics were found in all indoor and outdoor air samples, with indoor air samples (4.34 ± 1.93 items/m3) being significantly more contaminated than outdoor air samples (0.93 ± 0.32 items/m3) (P < 0.001). Among all the indoor air samples, samples taken from classroom (6.12 ± 0.51 items/m3) were more contaminated than samples taken from hallway (4.94 ± 0.78 items/m3) and laboratory (1.96 ± 0.44 items/m3). Fibers were found to be the prevalent shape type in indoor and outdoor airborne microplastics followed by fragments. Transparent- and black colored microplastic particles were predominant in both indoor and outdoor air samples. According to ATR-FTIR analysis, polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), and polystyrene (PS) were the most prevalent polymer types in both indoor and outdoor environments. Results from μ-Raman analysis corroborated the presence of the polymers identified by ATR-FTIR. Morphological analysis of particles by SEM indicated signs of weathering on particles' surface i.e., grooves, breaks, shredded edges, pits etc. SEM-EDX of randomly chosen particles unraveled the presence of C and O as core elements, along with the presence of heavy metals at some spots due to foreign material adhering to their surface. Correlation analysis of environmental factors i.e., PM2.5, relative humidity, temperature, and wind speed with MPs abundance revealed non-significant relationships. The findings of this study call for further research on airborne MPs to better comprehend their dispersion, toxicity, interactions with other air pollutants, and attributable health risks.

Condition of composted microplastics after they have been buried for 30 years: Vertical distribution in the soil and degree of degradation

Microplastics in soils are a growing concern. Composting household wastes can introduce microplastics to agroecosystems, because when unsorted compost is used as a fertilizer, the plastic debris it contains degrades to microplastics. This paper examines the distribution and degradation of microplastics in agricultural soil samples to investigate their potential mobility. The source of microplastics was a household waste compost added to the soil more than 30 years before the study. The microplastics were sorted from a plot-composite soil and characterised by Attenuated Total Reflectance combined with Fourier transform infrared spectroscopy (ATR-FTIR). The microplastics are present in the cultivated depth but have not been transferred deeper (2.9 g kg-1 in the 0-5 cm soil depth against 0.9 g kg-1 in the 30-35 cm soil depth). Polyethylene (PE), polypropylene (PP), polystyrene (PS) and Polyvinylchloride (PVC) were identified in the forms of heterogeneous fragments, films, and fibres and accounted for 90% of the total microplastics. Advanced degradation observed was mainly assumed to be due to composting, though the plastic may have degraded further in the soil matrix. Highly degraded plastics are a greater danger for further leaching of contaminants into soil and our food supply.

Ordered structural changes of retrograded instant rice noodles during the long-term storage

Temperature-induced textural, cooking properties and structural variations of retrograded instant rice noodles (IRN) during the long-term storage were systematically investigated. IRN samples stored at 4 °C exhibited a relative high cooking loss (2.45 %), and their hardness values gradually increased with prolonged storage. Moreover, the higher storage temperature (35 °C) accelerated the deterioration of IRN texture. Fresh IRN displayed a typical B-type XRD pattern with 9.65 % relative crystallinity (RC). During the initial 2 weeks of storage, the formation of a long-range ordered structure led to an increase in RC, which was closely related to the duration and temperature of storage (ranging from 4 °C to 25 °C to 35 °C). Over the 12-week storage period, there was likely a disorganization of the supra-molecular structure, as evidenced by the considerably decreased RC and reduced water mobility. Furthermore, Pearson's correlation analysis highlighted that the tight integration between starch molecules and water molecules endowed IRN samples with enhanced smoothness and tenderness in flavor profiles. Hence, the study is expected to provide a comprehensive understanding of the mechanisms underlying molecular order changes in retrograded starch gel products during the long-term storage.

First ATR-FTIR Characterization of Black, Green and White Teas (Camellia sinensis) from European Tea Gardens: A PCA Analysis to Differentiate Leaves from the In-Cup Infusion

ATR-FTIR (Attenuated Total Reflectance Fourier Transform InfraRed) spectroscopy, combined with chemometric, represents a rapid and reliable approach to obtain information about the macromolecular composition of food and plant materials. With a single measurement, the chemical fingerprint of the analyzed sample is rapidly obtained. Hence, this technique was used for investigating 13 differently processed tea leaves (green, black and white) all grown and processed in European tea gardens, and their vacuum-dried tea brews, prepared using both hot and cold water, to observe how the components differ from tea leaf to the in-cup infusion. Spectra were collected in the 1800-600 cm-1 region and were submitted to Principal Component Analysis (PCA). The comparison of the spectral profiles of leaves and hot and cold infusions of tea from the same country, emphasizes how they differ in relation to the different spectral regions. Differences were also noted among the different countries. Furthermore, the changes observed (e.g., at ~1340 cm-1) due to catechin content, confirm the antioxidant properties of these teas. Overall, this experimental approach could be relevant for rapid analysis of various tea types and could pave the way for the industrial discrimination of teas and of their health properties without the need of time-consuming, lab chemical assays.

Microplastic in industrial aquaculture: Occurrence in the aquatic environment, feed and organisms (Dicentrarchus labrax)

The increasing use of plastics and the growing concern about their impact on the environment and living beings makes it necessary to study how microplastics (MP) affect aquaculture systems. In order to gain an in-depth understanding of these systems, this study covers the water intake, the purification treatment at the inlet, the water in the culture tanks, as well as the feed used in the feeding and the organism itself. For this purpose, five samples were taken, both in the water line, feed and sea bass during the weeks of the experiment. It is shown that the available purification systems reduce the amount of MP entering from the receiving environment. However, new MP are observed in the sea bass tank, which may be due mainly to those added through the feed and found in the feed, as well as in the piping and other materials used in current aquaculture systems (PTFE, PA, among others). If focusing on the feed that can reach the consumer, in the case of this study, carried out with sea bass, some types of MP (PE, PTFE, PS and PA) were found in 4 head samples and 4 skin/muscle samples. Although inlet water purification systems manage to reduce a high percentage of MPs in the system, it is observed that there are other access routes that should be considered and reduced in aquaculture facilities to prevent them from reaching the human consumer.

ATR-FTIR spectroscopy combined with chemometrics to assess the spectral markers of irradiated baijius and their potential application in irradiation dose control

Although some methods have been proposed for the identification of irradiated baijius, they are often costly, time-consuming, and destructive. It is also unclear what instrumentation can be used to fully characterize the quality changes in irradiated baijius. To address this issue, this study pioneers the use of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy in combination with chemometrics to open up new avenues for characterizing irradiated baijius and their quality control. Principal component analysis, five spectral pre-processing methods (Savitzky-Golay smoothing (S-G), second-order derivative (SD), multiple scattering correction (MSC), S-G + SD and S-G + MSC), five wavelength selection methods (random forest variable importance (RFVI), two-dimensional correlation spectroscopy (2D-COS), variable importance in projection (VIP), ReliefF, and Venn), and three classification models (partial least squares-discriminant analysis (PLS-DA), random forest (RF), and grasshopper optimization algorithm-based support vector machine (GOA-SVM)) were integrated into the analytical framework of ATR-FTIR spectroscopy, aiming to accurately identify baijiu samples according to different irradiation doses and to search for irradiation-induced spectral difference characteristics (spectral markers). The results showed that SD was the best spectral pre-processing method, and RF models constructed using the 20 most competitive and discriminative spectral markers (selected by Venn) could achieve accurate identification of baijiu samples based on irradiation dose (0, 4, 6, and 8 kGy). After Pearson correlation analysis, the five significantly (P＜0.05) changed spectral markers (1596, 2025, 2309, 2329, and 2380 cm-1) were attributed to changes in the content of total acids, alcohols, and aromatic compounds. These findings demonstrate for the first time the potential of ATR-FTIR spectroscopy as a fast, low-cost, and non-destructive tool for the characterization and identification of irradiated baijiu samples. This approach may also offer a promising solution for labeling management of irradiated foods, vintage identification of baijius, and brand protection.

Ancient Grain Flours with Different Degrees of Sifting: Advances in Knowledge of Nutritional, Technological, and Microbiological Aspects

Ancient grains have gained considerable attention in recent years, as some research suggests they may be healthier than modern wheat. The present study aims to evaluate the chemical, rheological, and microbiological features of three Southern Italian cultivated ancient wheat varieties: Risciola, Carosella, and Saragolla. ATR-FTIR analyses were performed on the finely ground grain samples of the three varieties. The selected grains were ground with a stone mill, and different sifting degrees (whole-100%, type 1-80%, and type 0-72%) were evaluated. The flours showed a good nutritional profile, a higher amylose/amylopectin ratio, and a lower glycemic index than the literature. The gluten index of the samples was in the range 2.6-28.9%, and the flours can be classified as weak, having a value <30%. The farinographic test showed a short development time, low dough stability, a high softening degree, and water absorption, which increased with the degree of sifting. Microbiological analyses performed on flours from ancient grains at different degrees of sifting show their safety, according to their microbiological parameters, which fall within the legal microbiological requirements established by the European Commission Regulation (EC).

A Linear Predictor Based on FTIR Spectral Biomarkers Improves Disease Diagnosis Classification: An Application to Multiple Sclerosis

Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system that can lead to long-term disability. The diagnosis of MS is not simple and requires many instrumental and clinical tests. Sampling easily collected biofluids using spectroscopic approaches is becoming of increasing interest in the medical field to integrate and improve diagnostic procedures. Here we present a statistical approach where we combine a number of spectral biomarkers derived from the ATR-FTIR spectra of blood plasma samples of healthy control subjects and MS patients, to obtain a linear predictor useful for discriminating between the two groups of individuals. This predictor provides a simple tool in which the contribution of different molecular components is summarized and, as a result, the sensitivity (80%) and specificity (93%) of the identification are significantly improved compared to those obtained with typical classification algorithms. The strategy proposed can be very helpful when applied to the diagnosis of diseases whose presence is reflected in a minimal way in the analyzed biofluids (blood and its derivatives), as it is for MS as well as for other neurological disorders.

Interaction of a Porphyrin Aluminum Metal-Organic Framework with Volatile Organic Sulfur Compound Diethyl Sulfide Studied via In Situ and Ex Situ Experiments and DFT Computations

The study presents complementary experiments and quantum chemical DFT computations to reveal the molecular-level interactions of an advanced nanomaterial, porphyrin aluminum metal-organic framework (compound 2), with the volatile organic sulfur compound diethyl sulfide (DES). First, the intermolecular host-guest interactions during the sorption of DES were explored under dynamic conditions, using the vapor of DES in flowing air. The in situ time-dependent ATR-FTIR spectroscopy in a controlled atmosphere was significantly improved though the use of a new facilely built spectroscopic mini-chamber. The binding site of DES in compound 2 involves the μ(O-H) and COO- groups of the linker of the sorbent. Further, the chemical kinetics of the sorption of DES was investigated, and it follows the Langmuir adsorption kinetic model. That is, depending on the time interval, the process obeys either the pseudo-first- or pseudo-second-order rate law. For the Langmuir adsorption of the pseudo-first order, the rate constant is robs = 0.165 ± 0.017 min-1. Next, the interaction of compound 2 with the saturated vapor of DES yields the adsorption complex compound 3 [Al-MOF-TCPPH2]2(DES)7. The adsorbed amount of DES is very large at 36.5 wt.% or 365 mg/g sorbent, one of the highest values reported on any sorbent. The molecular modes of bonding of DES in the complex were investigated through quantum chemical DFT computations. The adsorption complex was facilely regenerated by gentle heating. The advanced functional material in this work has significant potential in the environmental remediation of diethyl sulfide and related volatile organic sulfur compounds in air, and it is an interesting target of mechanistic studies of sorption.

Extreme weather events as an important factor for the evolution of plastisphere but not for the degradation process

Marine plastics, with their negative effects on marine life and the human health, have been recently recognized as a new niche for the colonization and development of marine biofilms. Members of the colonizing communities could possess the potential for plastic biodegradation. Thus, there is an urgent need to characterize these complex and geographically variable communities and elucidate the functionalities. In this work, we characterize the fungal and bacterial colonizers of 5 types of plastic films (High Density Polyethylene, Low Density Polyethylene, Polypropylene, Polystyrene and Polyethylene Terepthalate) over the course of a 242-day incubation in the south-eastern Mediterranean and relate them to the chemical changes observed on the surface of the samples via ATR-FTIR. The 16s rRNA and ITS2 ribosomal regions of the plastisphere communities were sequenced on four time points (35, 152, 202 and 242 days). The selection of the time points was dictated by the occurrence of a severe storm which removed biological fouling from the surface of the samples and initiated a second colonization period. The bacterial communities, dominated by Proteobacteria and Bacteroidetes, were the most variable and diverse. Fungal communities, characterized mainly by the presence of Ascomycota, were not significantly affected by the storm. Neither bacterial nor fungal community structure were related to the polymer type acting as substrate, while the surface of the plastic samples underwent weathering of oscillating degrees with time. This work examines the long-term development of Mediterranean epiplastic biofilms and is the first to examine how primary colonization influences the microbial community re-attachment and succession as a response to extreme weather events. Finally, it is one of the few studies to examine fungal communities, despite them containing putative plastic degraders.

Fiber optic probe-based ATR-FTIR spectroscopy for rapid breast cancer detection: A pilot study

Breast cancer diagnosis is crucial for timely treatment and improved outcomes. This paper proposes a novel approach for rapid breast cancer diagnosis using optical fiber probe-based attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy from 750 to 4000 cm-1 . The technique enables direct analysis of tissue samples, eliminating the need for microtome sectioning and staining, thus saving time and resources. By capturing molecular fingerprint information, various machine-learning models were used to analyze the spectroscopic data to classify cancerous and non-cancerous tissues accurately. Comparing deparaffinized and paraffinized samples reveals the impact of sample preparation and experimental methods. The study demonstrates a strong correlation between the cancerous nature of a sample and its ATR-FTIR spectrum, suggesting its potential for breast cancer diagnosis (sensitivity of 74.2% and specificity of 78.3%). The proposed approach holds promise for integration into clinical operations, providing a rapid method for preliminary breast cancer diagnosis.

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.

The Dynamic Accumulation Rules of Chemical Components during the Medicine Formation Period of Angelica sinensis and Chemometric Classifying Analysis for Different Bolting Times Using ATR-FTIR

The dried roots of the perennial herb Angelica sinensis (Oliv.) Diels (AS) are commonly used as medicinal and edible resources. In commercial planting, early bolting and flowering (EB) of ca. 60% in the medicine formation period reduces root yield and quality, becoming a significant bottleneck in agricultural production. In the cultivation process, summer bolting (SB) occurs from June to July, and autumn bolting (AB) occurs in September. The AB root is often mistaken for the AS root due to its similar morphological characteristics. Few studies have involved whether the root of AB could be used as herbal medicine. This study explored and compared the accumulation dynamics of primary and secondary metabolites in AS and EB roots during the vegetative growth stage (from May to September) by light microscopy, ultraviolet spectrometry, and HPLC methods. Under a microscope, the amount of free starch granules and oil chamber in the AS root increased. On the contrary, they decreased further from EB-Jul to EB-Sep. By comparison, the wall of the xylem vessel was slightly thickened and stacked, and the cell walls of parenchyma and root cortex tissue were thickened in the EB root. Early underground bolting reduces soluble sugar, soluble protein, free amino acids, total C element, total N element, ferulic acid, and ligustilide accumulation, accompanied by the lignification of the root during the vegetative growth stage. Furthermore, a total of 55 root samples from different bolting types of AS root (29 samples), SB root (14 samples), and AB root (12 samples) were collected from Gansu Province during the harvesting period (October). The later the bolting occurred, the less difference there was between unbolted and bolted roots in terms of morphological appearance and efficacy components. Fourier transform infrared spectroscopy with the attenuated total reflection mode (ATR-FTIR) provides a "holistic" spectroscopic fingerprinting of all compositions in the tested sample. The ATR-FTIR spectrum of the AB root was similar to that of the AS root. However, the number and location of absorption peaks in the spectra of SB were different, and only one strong absorption peak at 1021 cm-1 was regarded as the characteristic peak of C-O stretching vibration in lignin. The ATR-FTIR spectra can be effectively differentiated based on their various characteristics using orthogonal partial least squares discrimination analysis (OPLS-DA). Results were assessed using multiple statistical techniques, including Spearman's correlation, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and OPLS-DA. Among these methods, the ATR-FTIR data demonstrated the most effective outcomes in differentiating between viable and non-viable roots for their application in herbal medicine. Essential substances are ferulic acid and flavonoid, which are much more abundant in the AB root. It provides a material basis for the pharmacological action of the AB roots and a theoretical basis for improving their availability.

Metagenomic Analysis of the Composition of Microbial Consortia Involved in Spruce Degradation over Time in Białowieża Natural Forest

Deadwood plays an important role in forest ecology; its degradation and, therefore, carbon assimilation is carried out by fungi and bacteria. To quantify the abundance and distribution of microbial taxa inhabiting dead spruce logs fallen over a span of 50 years and the soil beneath, we used taxonomic profiling with NGS sequencing of hypervariable DNA fragments of ITS1 and 16S V3-V4, respectively. The analysis of sequencing data revealed a high level of diversity in microbial communities participating in the degradation of spruce logs. Differences in the relative abundance of microbial taxa between the samples of the wood that died in 1974 and 2014, and of the soil in its immediate vicinity, were visible, especially at the genus level. Based on the Lefse analysis significantly higher numbers of classified bacterial taxa were observed in the wood and soil samples from 2014 (wood: 1974-18 and 2014-28 taxa; soil: 1974-8 and 2014-41 taxa) while the number of classified fungal taxa was significantly higher in the wood and soil samples from 1974 (wood: 1974-17 and 2014-9 taxa; soil: 1974-57 and 2014-28 taxa). Most of the bacterial and fungal amplicon sequence variants (ASVs) unique to wood were found in the samples from 1974, while those unique to soil were detected in the samples from 2014. The ATR-FTIR method supported by CHN analysis revealed physicochemical changes in deadwood induced by the activity of fungal and bacterial organisms.

Spectroscopic characterization of calcium phosphate precipitated under human eye conditions: An in vitro study

Calcification is a well-known process of calcium phosphate mineralization observed in intraocular lenses. Despite the many works conducted in this field, there is no strict explanation of the mechanisms of this process. In order to better understand the phenomenon, i.e., the mechanisms and structural conditions that promote calcification, any research observations should be conducted under conditions that best reflect those of the human eye. Taking into account the specific anatomy and physicochemical conditions of the human eye, the problem under discussion becomes difficult to solve in vitro. In the present study, calcium phosphates formed under conditions similar to those in the human eye were characterized using SEM/EDS and infrared spectroscopy. Conducted study showed the formation of white spherical precipitates, which are unstable when extracted from solution. Such precipitates were characteristic of solutions containing 1.5-3.0 mM² of solutes. Elemental analysis showed a Ca/P ratio of 1.64-1.65, which is similar to the ratio for hydroxyapatite (1.67). Chemical structure analysis revealed the presence of broad bending and stretching bands at 475-830 cm^-1 and 880-1250 cm^-1, respectively, which are characteristic of PO₄^3- groups in apatite calcium phosphates. In further analysis involving numerical fitting the bands corresponding to apatitic PO₄^3- and indicating the presence of calcium phosphates hydration were found. The results allow the selection of immersion media for further studies involving the incubation of hydrogel intraocular lenses.

Assessment of heavy metals migrated from food contact plastic packaging: Bangladesh perspective

Plastic-based food-contact materials are potentially threatening the environment and public health by releasing toxic heavy metals. This study aimed to identify the types of plastic commonly used in Bangladesh as food-contact materials (FCMs) and assess the migration of heavy metals from these FCMs. Plastic types were identified using attenuated total reflectance fourier transform infrared spectroscopy (ATR-FTIR), and 25 samples were selected based on the category, including Polyethylene Terephthalate (PET), Polyethylene (PE), Polypropylene (PP), Polystyrene (PS), and Polycarbonate (PC). Distilled water, 3% acetic acid, and 15% ethanol were used as food simulants to assess the overall migration of chemicals at 70 °C for 2 h. The concentrations of heavy metals (Pb, Cd, Hg, Cr, and Sb) were analyzed using an Atomic Absorption Spectrophotometer (AAS). Results revealed that the highest overall migration occurred in coffee cups measuring 3.50 ± 0.17 mg/kg (using water simulant) and in yogurt containers with a measurement of 9.17 ± 0.1 mg/kg (using 3% acetic acid). The highest concentrations of Pb, Cd, Hg, Cr, and Sb were found in PP-2 (0.45 ± 0.01 mg/kg), PP-2 (0.36 ± 0.01 mg/kg), PC-5 (0.27 ± 0.01 mg/kg), PET-2 (0.12 ± 0.01 mg/kg), and PET-1 (0.09 ± 0.01 mg/kg), respectively. The concentration of heavy metals migrated from the containers is likely to induce a health risk due to bioaccumulation from long-term ingestion of food packaged in them. The findings of this study added knowledge about harmful heavy metals leached from the FCMs in Bangladesh.

Chemical alterations of grain surface by cold plasma technology: Comparison of buckwheat and wheat grain responses to oxygen low-pressure plasma

Cold plasma (CP) has a great potential for decontamination or improvement of grain germination. However, disputing results have been reported, as plasma treatment can affect species and varieties of grains in different ways. The differences may be due to the chemical composition of grain pericarps, the structure of the grains and metabolic response mechanisms. CP treatment decreased grain germination rate, speed and activity of α-amylase of buckwheat grains. Such effects on both varieties of wheat grains were present after longer exposure to plasma. Lipid peroxidation was highest in buckwheat grains, whereas wheat grains were less affected. Plasma-treated Gorolka variety exhibited a low level of lipid peroxidation, no different to untreated grains, compared to Primorka grains, where longer treatment triggered higher levels of lipid peroxidation. The response of grains to CP treatment depends on the chemical and structural properties of grains pericarp, as well as plant tolerance to certain abiotic conditions.

Spatio-temporal distribution of microplastic abundances in Izmir Bay (eastern Aegean Sea)

Microplastics (MPs) and their impacts have been extensively studied in the Mediterranean region. However, more research has yet to be conducted on assessing the extent of microplastic (MP) pollution in the eastern Aegean Sea, specifically in Izmir Bay. This study aims to evaluate the current state of MP pollution in surface water and sediment samples collected from Izmir Bay. Ten sampling stations were specifically selected, including locations near stream discharge points, maritime transportation piers, and port areas. Surface water samples were collected using a manta trawl net, while sediment samples were obtained using a Van Veen grab. The mean MP abundances in surface water ranged from 1,083,882 to 8,091,684 items/km2. Fragment type MPs were dominant. In terms of size category, it was found that MP s of 500µm size were dominant. The dominant color of MPs was white. ATR-FTIR analyses revealed that polyethylene and polypropylene were the dominant polymer types. MP concentrations in sediment ranged from 2,125 to 4,925 items/m2, with fiber-type MPs being the most abundant. Black-colored MPs were found to dominate in sediment samples. Overall, the MP levels in Izmir Bay were higher than previous studies findings. Therefore, it is crucial to conduct long-term monitoring studies to obtain more consistent and reliable data on MP pollution levels in Izmir Bay.

Attenuated Total Reflection Fourier-Transform Infrared Spectral Discrimination in Human Tissue of Oesophageal Transformation to Adenocarcinoma

This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4-100% sensitivity and 89.5-100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium.

Prevalence of microplastics in commonly consumed fish species of the river Old Brahmaputra, Bangladesh

Microplastics (MPs) are pervasive in aquatic environments, but inland waterbodies (rivers and floodplains) have received much less attention. The present study assesses the incidence of MPs in the gastrointestinal tracts of five commercially important edible fish species-two column feeders (n = 30) and three benthivores (n = 45) from upstream, midstream, and downstream of the Old Brahmaputra river in north-central Bangladesh. MPs were detected in 58.93% of fish, with the highest level in freshwater eel, Mastacembelus armatus (10.31 ± 0.75/fish). Fibers (49.03%) and pellets (28.02%) were the most frequent MPs. Nearly 72% MPs were smaller than 1 mm, and 50.97% were black. FTIR analysis showed 59% polyethelene (PE), followed by polyamide (40%) and unidentified (1%). MP ingestion was linked to fish size and weight, and a high incidence was recorded in the downstream river. Two omnivorous benthic fish ingest more MPs than others. The results corroborate the presence of MPs in the inland river and fish fauna and augment our understanding of heterogeneous MP uptake by fish.

Isolation and Characterization of Protein Fractions for Valorization of Sacha Inchi Oil Press-Cake

The growing interest in plant-based food protein sources has provided opportunities for the valorization of agri-food by-products, driving the food industry towards more sustainable development. In this study, three extraction procedures (varying the pH value (7.0 and 11.0) and the addition of salt (0 and 5%)) were investigated to obtain seven different protein fractions (SIPF) from Sacha Inchi oil press-cake (SIPC), which were characterized in terms of their protein content, electrophoretic profile, secondary structure, and techno-functional properties. Extractions at pH 11.0 without salt addition produced the highest values of protein content, extraction yield, protein recovery, and protein concentration increase (84.0%, 24.7%, 36.5%, and 1.5-fold, respectively). Under these extraction conditions, the electrophoretic analysis indicated that most of the SIPC proteins were extracted. SIPF displayed an excellent oil absorption capacity (4.3-9.0 w/w), and interesting foam activity (36.4-133.3%). The solubility and emulsifying activity of the albumin fractions were significantly higher than those of the other fractions (~87 vs. <15.8%, and 280-370 vs. <140 m²/g, respectively). Correlation analysis showed that the secondary structure of the SIPF significantly influences their techno-functional properties. These results indicate that SIPC is a by-product of great potential for protein extraction processes, and as a valorization strategy for technical cycle solutions for the Sacha Inchi productive chain in the circular economy context.

Oil Media on Paper: Investigating the Interaction of Cold-Pressed Linseed Oil with Paper Supports with FTIR Analysis

Previous works of the authors have presented the changes in the optical, mechanical, and chemical properties of the oiled areas of the supports that occur upon ageing due to oil-binder absorption in works of art on paper and printed material. In this framework, transmittance FTIR analysis has indicated that the presence of linseed oil induces the conditions to promote the deterioration of the oil-impregnated areas of the paper supports. However, the analysis of oil-impregnated mock-ups did not provide detailed information about the input of linseed oil formulations and the different types of paper support on the chemical changes that occur upon ageing. This work presents the results of ATR-FTIR and reflectance FTIR, which were used for compensating the previous results, proving indications on the effect of different materials (linseed oil formulations, and cellulosic and lignocellulosic papers) on the development of chemical changes, thus, on the condition of the oiled areas upon ageing. Although linseed oil formulations have a determining effect on the condition of the oiled areas of the support, the paper pulp content appears to have an input to the chemical changes that occur in the system of paper-linseed oil upon ageing. The results presented are more focused on the oil-impregnated mock-ups with cold-pressed linseed oil since results have indicated that this causes more extended changes upon ageing.

Type 2 diabetes alters the viscoelastic behavior and macromolecular composition of vertebra

Type 2 diabetes (T2D) affects the functional behavior of vertebra bone by altering its structural and mechanical properties. The vertebral bones are responsible to carry the body weight and it remains under prolonged constant load which results to viscoelastic deformation. The effect of T2D on the viscoelastic behavior of vertebral bone is not well explored yet. In this study, the effects of T2D on the creep and stress relaxation behavior of vertebral bone are investigated. Also, this study established a correlation between T2D associated alteration in macromolecular structure and viscoelastic behavior of vertebra. In this study T2D female rat SD model was used. The obtained results demonstrated a significant reduction in the amount of creep strain (p ≤ 0.05) and stress relaxation (p ≤ 0.01) in T2D specimens than the control. Also, the creep rate was found significantly lower in T2D specimens. On the other hand, molecular structural parameters such as mineral-to-matrix ratio (control vs T2D: 2.93 ± 0.78 vs 3.72 ± 0.53; p = 0.02), and non-enzymatic cross link ratio (NE-xL) (control vs T2D: 1.53 ± 0.07 vs 3.84 ± 0.20; p = 0.01) were found significantly altered in T2D specimens. Pearson linear correlation tests show a significant correlation; between creep rate and NE-xL (r = -0.94, p < 0.01), and between stress relaxation and NE-xL (r = -0.946, p < 0.01). Overall this study explored the understanding about the disease associated alteration in viscoelastic response of vertebra and its correlation with macromolecular composition which can help to understand the disease related impaired functioning of the vertebrae body.

Intertwined synergistic abiotic and biotic degradation of polypropylene pellets in marine mesocosms

The accumulation of plastic waste in the oceans has caused growing concern for its effects on marine life. The interactions of plastics with environmental factors have been linked to fragmentation to micro- and nanoparticles with different properties and consequences, but the mechanism of fragmentation has not been fully understood yet. In this work, we investigate the combined effect of marine communities and ultraviolet (UV) radiation towards the degradation of virgin and artificially weathered polypropylene (PP) pellets after a long-term incubation period in marine mesocosms. The surface chemical alterations and deterioration of the polymer, in conjunction with the attachment and evolution of marine bacterial communities, the development of biofilm and exopolymeric substances (EPS), as well as the colloidal properties (zeta-potential and hydrodynamic diameter) of the mesocosms were studied. The surface area of both types of pellets decreased over time, despite no concrete weight change being observed. Cell growth, EPS production and colloid particle size were correlated to the loss of area. Therefore, we propose that surface area could be effectively monitored, instead of weight loss, as an alternative indicator of polymer degradation in biodegradation experiments. Changes in the chemical structure of the polymer, in addition to the evolution of the biological factors, implied that a complex degradation process alternated between two phases: an abiotic phase, when UV irradiation contributes to the deterioration of the polymer surface layers and a biotic phase, when marine communities degrade the weathered polymer surface to reveal the underlying layer of virgin polymer. Finally, microscopic particles, produced as a result of the decrease in pellet area, promoted the aggregation of colloidal particles. The role and impacts of these colloidal particles in marine ecosystems are yet as unidentified as that of micro- and nano-sized plastic particles and call for further investigation.

Abundance, spatial distribution, and chemical characterization of face masks on the beaches of SE Kanyakumari, India

Personal Protective Equipment (PPE) is a new world of waste during the COVID-19 pandemic. In this baseline study, the occurrence of PPE faces masks were assessed on the eleven beaches of Kanyakumari, India concerning the abundance, spatial distribution, and chemical characterization (ATR-FTIR spectroscopy). A total of 1593 items/m² of PPE face masks and their mean density of 0.16 PPE/m², ranging from 0.02 to 0.54 PPE/m² were determined in the study area. Kanyakumari beach (n = 430 items/m²) has the highest concentration of masks (26.99 %), with a mean density of 0.54 m² due to recreational, sewage disposal, and tourism activities. This is perhaps the most important study describing the scientific data that focuses on the significant effects of communal activities and accessibility on COVID-19 PPE face mask pollution. It also highlights the need for sufficient management facilities to optimize PPE disposal.