ATR-FTIR spectroscopy to evaluate serum protein expression in a murine cerebral ischemia model.

Stroke is a prevalent vascular disease that causes disability and death worldwide. Molecular techniques have been developed to assess serum concentrations of biomarkers associated with this disease, such as some proteins. ATR-FTIR was proposed as an alternative technique to determine protein expression during the early stages of stroke. Serum samples from sham, ischemic, and ischemic treated with estradiol benzoate (EB; as a neuroprotective agent) male rats were evaluated at 0, 2-, 4-, 6-, 12-, and 24-hours post-ischemia. The analysis was developed in the mid-infrared region but mainly focused on the protein region (1500-1700 cm-1), where it was possible to observe the modulation in the absorbance intensity. The peaks at 1545, 1645, 1635, and 1650 cm-1 associated with amide II, amide I, ß-sheets, and α-helixes, respectively, were prominent peaks where protein modulation was observed. The results demonstrate that infrared spectroscopy could be a good alternative technique to determine the modulation of protein expression during stroke events.

Hats Off to Modeling! Profiling Early Synthetic Dyes on Historic Woolen Samples with ATR-FTIR Spectroscopy and Multivariate Curve Resolution-Alternating Least Square Algorithm.

This research focuses on analyzing wool samples dyed with synthetic dyes from the early 20th century. A methodology to identify and distinguish wool fibers dyed with azo, triphenylmethane, and xanthene dyes, which are no longer in use, using the ATR-FTIR spectra, is presented. Firstly, the dataset was subjected to PCA, which revealed the similarities and differences among the samples, illustrating a distribution pattern based on dye classes. MCR-ALS was employed to extract the spectral profiles of the dyed fibers, thereby enhancing the efficacy of the analytical techniques and extracting the comprehensive information from a single instrument. The combination of ATR-FTIR spectroscopy with chemometric methods, such as PCA and MCR-ALS, has proven to be an effective strategy for identifying and differentiating wool fibers dyed with early azo, triphenylmethane, and xanthene dyes. This approach has demonstrated particular effectiveness in enabling rapid analysis without requiring sampling or pretreatment. Moreover, the analysis is supported by thorough bibliographic research on these no longer used colorants. In order to maximize the potential of non-destructive spectroscopic techniques, such as ATR-FTIR, the approach used has proven to be crucial. This study underscores how chemometric techniques expand the capabilities of spectroscopy, extracting extensive information from a single instrument and aligning with the goals of cultural heritage analysis.

Occurrence of microplastics in the gastrointestinal tracts of four most consumed fish species in Giresun, the Southeastern Black Sea.

Microplastic studies investigating concentrations in water are numerous, but the majority of microplastics settle and are retained in sediment, and higher concentrations are regularly reported in sediments. Thus, MPs accumulation may be more threatening to benthic fish living in sediments than to pelagic fish. The presence, abundance and diversity of microplastics were investigated by collecting samples from two pelagic, European anchovy, and horse mackerel and two benthic fish species, red mullet, and whiting that are popularly consumed in Giresun province of Türkiye, located on the southern coast of the Black Sea. Visual classification and chemical compositions of microplastics was performed using a light microscope and ATR-FTIR spectrophotometry, consecutively. The overall incidence and mean microplastics abundance in sampled fishes were 17 and 1.7 ± 0.18 MP fish-1, respectively. MPs were within the range of 0.026-5 mm in size. In most of the cases, the MP was black in color with 41%. With the rates of 56%, polypropylene was the predominant polymer type. The most dominant MP type was identified as fiber followed by fragments and pellets. The relationship between MP amounts in fish and Fulton condition factor was not strong enough to establish a cause-effect relationship.

Pilot Study on the Use of Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy for Diagnosing and Characterizing Cardiac Amyloidosis.

Amyloidosis diagnosis relies on Congo red staining with immunohistochemistry and immunofluorescence for subtyping but lacks sensitivity and specificity. Laser-microdissection mass spectroscopy offers better accuracy but is complex and requires extensive sample preparation. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy offers a promising alternative for amyloidosis characterization. Cardiac tissue sections from nine patients with amyloidosis and 20 heart transplant recipients were analyzed using ATR-FTIR spectroscopy. Partial least squares discriminant analysis (PLS-DA), principal component analysis (PCA), and hierarchical cluster analysis (HCA) models were used to differentiate healthy post-transplant cardiac tissue from amyloidosis samples and identify amyloidosis subtypes [κ light chain (n = 1), λ light chain (n = 3), and transthyretin (n = 5)]. Leave-one-out cross-validation (LOOCV) was employed to assess the performance of the PLS-DA model. Significant spectral differences were found in the 1700-1500 cm-1 and 1300-1200 cm-1 regions, primarily related to proteins. The PLS-DA model explained 85.8% of the variance, showing clear clustering between groups. PCA in the 1712-1711 cm-1, 1666-1646 cm-1, and 1385-1383 cm-1 regions also identified two clear clusters. The PCA and the HCA model in the 1646-1642 cm-1 region distinguished κ light chain, λ light chain, and transthyretin cases. This pilot study suggests ATR-FTIR spectroscopy as a novel, non-destructive, rapid, and inexpensive tool for diagnosing and subtyping amyloidosis. This study was limited by a small dataset and variability in measurements across different instruments and laboratories. The PLS-DA model's performance may suffer from overfitting and class imbalance. Larger, more diverse datasets are needed for validation.

Age estimation of Phormia regina pupae based on ATR-FTIR and chemometrics.

Accurate postmortem interval estimation is vital in the investigation of homicides, suicides, and accidental deaths. It is key in narrowing suspect lists, improving crime-solving efficiency, and offering solace to bereaved families. The intra-puparial period, comprising about half of a fly's developmental cycle, presents challenges for morphological age estimation. External changes are limited to color shifts and the appearance of respiratory horns on the puparium only within several hours after pupariation, while detailed internal development analysis often requires invasive methods like removing the puparium, which can be damaging. Additionally, these techniques usually depend on a forensic entomologist's expertise, which lead to subjective biases. This study employed attenuated total reflection-fourier transform infrared spectroscopy, a rapid, non-destructive method for analyzing proteins, chitosan, and chitin in puparia. Data showed a consistent reduction in the concentration of the amide I band within the puparium during the intra-puparial development at five constant temperatures (19 °C, 22 °C, 25 °C, 28 °C and 31 °C). This trend in the spectral data effectively distinguishes pupae at various stages of intra-puparial development, facilitating precise age estimation, which is critical for the estimation of the minimum postmortem interval (PMImin). Finally, this work combined the total reflection-fourier transform infrared spectroscopy with chemometric analysis and successfully developed a partial least squares discriminant analysis model and a random forest model, with accuracies of 88 % and 81 %, respectively. These models enable the non-invasive age estimation of P. regina in its intra-puparial period, a stage traditionally difficult to assess morphologically, thus laying the groundwork for PMImin estimation using fly pupae.

Unveiling the Potential of Vitamin D3 Orodispersible Films: A Comprehensive FTIR and UV-Vis Spectroscopic Study.

Vitamin D3 is a crucial fat-soluble pro-hormone essential for bolstering bone health and fortifying immune responses within the human body. Orodispersible films (ODFs) serve as a noteworthy formulation strategically designed to enhance the rapid dissolution of vitamin D, thereby facilitating efficient absorption in patients. This innovative approach not only streamlines the assimilation process but also plays a pivotal role in optimizing patient compliance and therapeutic outcomes. The judicious utilization of such advancements underscores a paradigm shift in clinical strategies aimed at harnessing the full potential of vitamin D for improved patient well-being. This study aims to examine the vitamin D3 ODF structure using spectroscopic techniques to analyze interactions with excipients like mannitol. Fourier-transform infrared spectroscopy (FTIR) and ultraviolet-visible (UV-Vis) spectroscopy were utilized to assess molecular composition, intermolecular bonding, and vitamin D3 stability. Understanding these interactions is essential for optimizing ODF formulation, ensuring stability, enhancing bioavailability, and facilitating efficient production. Furthermore, this study involves a translational approach to interpreting chemical properties to develop an administration protocol for ODFs, aiming to maximize absorption and minimize waste. In conclusion, understanding the characterized chemical properties is pivotal for translating them into effective self-administration modalities for Vitamin D films.

The utilization of blood serum ATR-FTIR spectroscopy for the identification of gastric cancer.

Gastric cancer represents a significant public health challenge, necessitating advancements in early diagnostic methodologies. This investigation employed attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to conduct a multivariate analysis of human serum. The study encompassed the examination of blood samples from 96 individuals diagnosed with gastric cancer and 96 healthy volunteers. Principal component analysis (PCA) was utilized to interpret the infrared spectral data of the serum samples. Specific spectral bands exhibiting intensity variations between the two groups were identified. The infrared spectral ranges of 3500 ~ 3000 cm⁻1, 1700 ~ 1600 cm⁻1, and 1090 ~ 1070 cm⁻1 demonstrated significant diagnostic value for gastric cancer, likely attributable to differences in protein conformation and nucleic acids. By employing machine learning algorithms to differentiate between gastric cancer patients (n = 96) and healthy controls (n = 96), we achieved a sensitivity of up to 89.7% and a specificity of 87.2%. Receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.901. These findings underscore the potential of our serum-based ATR-FTIR spectroscopy examination method as a straightforward, minimally invasive, and reliable diagnostic test for the detection of gastric cancer.

Classification of idiopathic recurrent spontaneous miscarriage using FTIR and Raman spectroscopic fusion technology.

Recurrent spontaneous miscarriage refers to the repeated loss of two or more clinically detected pregnancies occurring within 24 weeks of gestation. No identifiable cause has been identified for nearly 50% of these cases. This group is referred to as idiopathic recurrent spontaneous miscarriage (IRSM) or miscarriage of unknown origin. Due to lack of robust scientific evidence, guidelines on the diagnosis and management of IRSM are not well defined and often contradictory. This motivates us to explore the vibrational fingerprints of endometrial tissue in these women. Endometrial tissues were collected from women undergoing IRSM (n = 20) and controls (n = 20) corresponding to the window of implantation. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectra were obtained within the range of 400-4000 cm-1 using Agilent Cary 630 FTIR spectrometer. Raman spectra were also generated within the spectral window of 400-4000 cm-1 using Thermo Fisher Scientific, DXR Raman spectrophotometer. Based on the limited molecular information provided by a single spectroscopic tool, fusion strategy combining Raman and ATR-FTIR spectroscopic data of IRSM is proposed. The significant features were extracted applying principal component analysis (PCA) and wavelet threshold denoising (WTD) and fused spectral data used as input into support vector machine (SVM), adaptive boosting (AdaBoost) and decision tree (DT) models. Altered molecular vibrations associated with proteins, glutamate, and lipid metabolism were observed in IRSM using Raman spectroscopy. FTIR analysis indicated changes in the molecular vibrations of lipids and proteins, collagen dysregulation and impaired glucose metabolism. Combination of both spectroscopic data using mid-level fusion (MLF: 92% using AdaBoost and DT models) and high-level fusion (HLF: 92% using SVM models) methods showed improved IRSM classification accuracy as compared to individual spectral models. Our results indicate that spectral fusion technology hold promise in enhancing diagnostic accuracy of IRSM in clinical settings. Validation of these findings in a larger patient population is underway.

Discrimination and analytical profiling of colored printed documents using ATR-FTIR spectroscopy coupled with explorative and predictive statistical analysis: Part I.

Printed documents are a common form of evidence in forensic document examination. The integration of spectroscopy with chemometrics have evolved evidential analytical interpretation of printing inks. However, we report the first ever study that explores the examination of both black and colored printed documents combined with explorative Principal Component Analysis (PCA) and supervised techniques viz. Soft independent modelling of class analogy (SIMCA) and Partial Least Square- Discriminant Analysis (PLS-DA). The study investigated 74 (40 Ink-based and 34 Toner- based) colored printed document samples using ATR-FTIR to discriminate and determine the source of origin of an unknown printed document using a non-destructive approach. Qualitative analysis by ATR- FTIR indicated the presence of polystyrene, bisphenol A and acrylates as the common binder polymers in the samples. The study was also able to obtain pigment information like presence of PR 57 and PR 146 in magenta, Carbon black in black, Copper Phthalocyanine and PB 15 in Cyan and PY 74 in yellow colored printed samples. Further, PCA has been used as an explorative technique that showed a variance of 97 % in the dataset and indicating that the color Cyan contributes to the maximum classification accuracy. SIMCA has been used as a supervised method to classify the known and test samples to their respective defined classes. However, SIMCA could only classify Toner-based samples in their respective class and inconclusive results were obtained in case of Ink-based samples. Finally, PLS-DA was also used to classify the two class of samples which resulted in a discrimination accuracy of 98.6 %. The derived model was also used for validation study on blind test samples which provided 100 % classification results.

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.

Probing the stability and quality of the cellulose-based Pickering emulsion containing sesamolin-enriched sesame oil by chemometrics-assisted ATR-FTIR spectroscopy.

This study presents the employment of Fourier transform infrared (FTIR) spectroscopy with attenuated total reflection and principal component analysis (PCA) to analyze the stability of a Pickering emulsion stabilized by carboxylated-cellulose nanocrystal (cCNC) comprising sesame oil phases with or without sesamolin. FTIR measurements identified an intermolecular hydrogen bond between the ester group of the triglyceride and the carboxyl group of the cCNC to create the emulsion droplet. The spectral bands from the hydroxyl group vibration (3700-3050 cm-1), carbonyl (1744 cm-1), CO groups of the ester triglyceride and cCNC (1160-998 cm-1) markedly discriminated between stabilized and destabilized emulsions. The PCA of FTIR spectra detected the change of molecular interaction during storage according to creaming, aggregation, and coalescence and changes in physicochemical parameters such as droplet size, refractive index, and zeta potential. Hence, PCA enabled the observation of the destabilization of emulsion in real-time.

Species discrimination from hair using ATR-FTIR spectroscopy: Application in wildlife forensics.

Hair is a commonly encountered trace evidence in wildlife crimes involving mammals and can be used for species identification which is essential for subsequent judicial proceedings. This proof of concept study aims, to distinguish the black guard hair of three wild cat species belonging to the genus Panthera i.e. Royal Bengal Tiger (Panthera tigris tigris), Indian Leopard (Panthera pardus fusca), and Snow Leopard (Panthera uncia) using a rapid and non-destructive ATR-FTIR spectroscopic technique in combination with chemometrics. A training dataset including 72 black guard hair samples of three species (24 samples from each species) was used to construct chemometric models. A PLS2-DA model successfully classified these three species into distinct classes with R-Square values of 0.9985 (calibration) and 0.8989 (validation). VIP score was also computed, and a new PLS2DA-V model was constructed using variables with a VIP score ≥ 1. External validation was performed using a validation dataset including 18 black guard hair samples (6 samples per species) to validate the constructed PLS2-DA model. It was observed that PLS2-DA model provides greater accuracy and precision compared to the PLS2DA-V model during cross-validation and external validation. The developed PLS2-DA model was also successful in differentiating human and non-human hair with R-Square values of 0.99 and 0.91 for calibration and validation, respectively. Apart from this, a blind test was also carried out using 10 unknown hair samples which were correctly classified into their respective classes providing 100 % accuracy. This study highlights the advantages of ATR-FTIR spectroscopy associated with PLS-DA for differentiation and identification of the Royal Bengal Tiger, Indian Leopard, and Snow Leopard hairs in a rapid, accurate, eco-friendly, and non-destructive way.

The mysteries of DNA preservation in bone: A comparative study of petrous bones and metacarpal epiphyses using ATR-FTIR spectroscopy.

A comparative analysis of 26 petrous bones and epiphyses of metacarpals from the Second World War era revealed no significant differences in DNA yield or success in STR typing. This unexpected parity in DNA preservation between the petrous bone, a renowned source of endogenous DNA in skeletal remains, and the epiphyses of metacarpals, which are porous and susceptible to taphonomic changes, is surprising. In this study, we introduced ATR-FTIR spectroscopy as an approach to unravel the correlation between bone molecular structure and DNA preservation. Metacarpals and petrous bones with same taphonomic history were sampled and prepared for DNA analyses. While one portion of the sample was used for DNA analysis, the other underwent ATR-FTIR spectroscopic examination. The normalized spectra and FTIR indices between the epiphyses of metacarpals and petrous bones were compared. Because the taphonomic history of the remains used is relatively short and stable, the ATR-FTIR spectroscopy unveiled subtle structural differences between the two bone types. Petrous bones exhibited higher mineralization, whereas epiphyses contained more organic matter. The unexpected preservation of DNA in the epiphyses of metacarpals can likely be attributed to the presence of soft tissue remnants within the trabeculae. Here observed differences in the molecular structure of bones indicate there are different mechanisms enabling DNA preservation in skeletal tissues.

Metallic nanoparticle actions on the outer layer structure and properties of Bacillus cereus and Staphylococcus epidermidis.

Although the antimicrobial activity of nanoparticles (NPs) penetrating inside the cell is widely recognised, the toxicity of large NPs (>10 nm) that cannot be translocated across bacterial membranes remains unclear. Therefore, this study was performed to elucidate the direct effects of Ag-NPs, Cu-NPs, ZnO-NPs and TiO2-NPs on relative membrane potential, permeability, hydrophobicity, structural changes within chemical compounds at the molecular level and the distribution of NPs on the surfaces of the bacteria Bacillus cereus and Staphylococcus epidermidis. Overall analysis of the results indicated the different impacts of individual NPs on the measured parameters in both strains depending on their type and concentration. B. cereus proved to be more resistant to the action of NPs than S. epidermidis. Generally, Cu-NPs showed the most substantial toxic effect on both strains; however, Ag-NPs exhibited negligible toxicity. All NPs had a strong affinity for cell surfaces and showed strain-dependent characteristic dispersion. ATR-FTIR analysis explained the distinctive interactions of NPs with bacterial functional groups, leading to macromolecular structural modifications. The results presented provide new and solid evidence for the current understanding of the interactions of metallic NPs with bacterial membranes.

Can Combining Hyaluronic Acid and Physiotherapy in Knee Osteoarthritis Improve the Physicochemical Properties of Synovial Fluid?

Known as the degenerative disease of the knee with the highest prevalence, knee osteoarthritis (KOA) is characterized by a gradual destructive mechanism that, in severe cases, can provoke the need for total knee substitution. As the disease progresses, various enzymatic, immunological, and inflammatory processes abnormally degrade hyaluronic acid (HA), SF's main component, and affect the concentrations of specific proteins, with the final results seriously endangering synovial fluid (SF)'s rheological and tribological features and characteristics. No effective treatments have been found to stop the progression of KOA, but the injection of HA-based viscoelastic gels has been considered (alone or combined with physiotherapy (PT)) as an alternative to symptomatic therapies. In order to evaluate the effect of viscosupplementation and PT on the characteristics of SF, SF aspirated from groups treated for KOA (HA Kombihylan® and groups that received Kombihylan® and complex PT) was analyzed and compared from analytical, spectrophotometrical, and rheological perspectives. In the patients treated with PT, the SF extracted 6 weeks after viscosupplementation had a superior elastic modulus (G') and viscous moduli (G″), as well as a homogeneous distribution of proteins and polysaccharides. The viscosupplementation fluid improved the bioadhesive properties of the SF, and the use of the viscosupplementation fluid in conjunction with PT was found to be favorable for the distribution of macromolecules and phospholipids, contributing to the lubrication process and the treatment of OA-affected joints.

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.

On the Assessment of Strawberries' Shelf-Life and Quality, Based on Image Analysis, Physicochemical Methods, and Chemometrics.

The aim of the present study was to evaluate Marisol strawberries' (Fragaria × ananassa) physicochemical quality and shelf-life during storage, using an integrated analytical approach. More specifically, the research aimed to assess the strawberries' color, texture, and nutritional quality, over an 11-day storage period, employing physicochemical analyses, spectrophotometric assays, Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy, image analysis, and statistical tools. The results revealed significant changes in the outer surface texture and color characteristics, indicating spoilage progression. Physicochemical parameters such as water activity, moisture content, soluble solids, titratable acidity, and ascorbic acid content exhibited significant alterations, influencing the taste profile and freshness perception. Antioxidant and antiradical activities showed fluctuations, suggesting a potential decrease in phenolic content during storage. Moreover, the ATR-FTIR spectra findings confirmed the results regarding the moisture content, soluble solids, and total phenolic content. The integration of physicochemical and image analysis-derived features through a principal component analysis (PCA) enabled the accurate classification of samples based on storage days. Regression analysis, using these features, successfully predicted the storage day with high accuracy. Overall, this integrated analytical approach provided valuable information on the estimation of Marisol strawberries' shelf-life and the prediction of their quality deterioration, contributing to better fruit management and the minimization of discards.

Structural characterization of DNA amplicons by ATR-FTIR spectroscopy as a guide for screening metainflammatory disorders in blood plasma.

Attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy is a promising rapid, reagent-free, and low-cost technique considered for clinical translation. It allows to characterize biofluids proteome, lipidome, and metabolome at once. Metainflammatory disorders share a constellation of chronic systemic inflammation, oxidative stress, aberrant adipogenesis, and hypoxia, that significantly increased cardiovascular and cancer risk. As a result, these patients have elevated concentration of cfDNA in the bloodstream. Considering this, DNA amplicons were analyzed by ATR-FTIR at 3 concentrations with 1:100 dilution: (IU/mL): 718, 7.18, and 0.0718. The generated IR spectrum was used as a guide for variable selection. The main peaks in the biofingerprint (1800-900 cm-1) give important information about the base, base-sugar, phosphate, and sugar-phosphate transitions of DNA. To validate our method of selecting variables in blood plasma, 38 control subjects and 12 with metabolic syndrome were used. Using the wavenumbers of the peaks in the biofingerprint of the DNA amplicons, was generated a discriminant analysis model with Mahalanobis distance in blood plasma, and 100 % discrimination accuracy was obtained. In addition, the interval 1475-1188 cm-1 showed the greatest sensitivity to variation in the concentration of DNA amplicons, so curve fitting with Gaussian funcion was performed, obtaining adjusted-R2 of 0.993. PCA with Mahalanobis distance in the interval 1475-1188 cm-1 obtained an accuracy of 96 % and PLS-DA modeling in the interval 1475-1088 cm-1 obtained AUC = 0.991 with sensitivity of 95 % and specificity of 100 %. Therefore, ATR-FTIR spectroscopy with variable selection guided by DNA IR peaks is a promising and efficient method to be applied in metainflammatory disorders.

Comparison of ATR-FTIR and NIR spectroscopy for identification of microplastics in biosolids.

Biosolids are considered a potentially major input of microplastics (MPs) to agricultural soils. Our study aims to identify the polymeric origin of MPs extracted from biosolid samples by comparing their Attenuated Total Reflection (ATR) - Fourier-transform infrared (FTIR) spectra with the corresponding near-infrared (NIR) spectra. The reflectance spectra were preprocessed by Savitzky-Golay (SG), first derivative (FD) and compared with analogous spectra acquired on a set of fifty-two selected commercial plastic (SCP) materials collected from readily available products. According to the results portrayed in radar chart and built from both ATR-FTIR and NIR spectral datasets, the MPs showed high correlations with polymers such as polyethylene (LDPE, HDPE), polyethylene terephthalate (PET), polystyrene (PS), polypropylene (PP) and polyamide (PA), determined in SCP samples. Each unknown MP sample had on average three or more links to several types of SCP, according to the correlation coefficients for each polymer ranging from 0.7 up to 1. The comparison analysis classified the majority of MPs as composed mainly by LDPE/HDPE, according to the top correlation coefficients (r > 0.90). PP and PET were better identified with NIR than ATR-FTIR. In contrast to ATR-FTIR analysis, NIR was unable to identify PS. Based on these results, the primary sources of MPs in the biosolids could be identified as discarded consumer packaging (containers, bags, bottles) and fibers from laundry, disposable glove, and cleaning cloth. SYNOPSIS: Microplastics (MPs) are considered contaminants of emerging concern. This study compares two simple and fast spectroscopy techniques to identify microplastics in the biosolid matrix.

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.