Search Results (1,219)

Clinical manifestations of salmonellosis in humans typically include acute gastroenteritis, abdominal pain, diarrhea, nausea, and fever. Diarrhea and anorexia may persist for several days. In some cases, the organisms may invade the intestinal mucosa and cause septicemia, even in the absence of significant gastrointestinal symptoms. Most clinical signs are attributed to hematogenous dissemination of the pathogen. As with other microbial infections, disease severity is influenced by the serotype of the organism, bacterial load, and host susceptibility. Serotyping analysis of Salmonella spp. using the White–Kauffmann–Le Minor scheme remains the gold standard for strain typing. However, this method is expensive, time-consuming, and requires significant expertise and visual interpretation by trained personnel, which is why it is typically restricted to regional or national reference laboratories. In this study, we evaluated a spectroscopic technique coupled with chemometrics and multivariate machine learning algorithms for its ability to discriminate the main Salmonella spp. serogroups in a clinical routine setting. We analyzed 95 isolates of Salmonella that were randomly selected, including four strains of S. Typhi. The I-dOne Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) system (Alifax S.r.l., Polverara, Italy) also shows promising potential for distinguishing Salmonella Typhi within the D serogroup. The I-dOne system enables simultaneous identification of both species and subspecies using the same workflow and instrumentation, thus streamlining the diagnostic process. Full article

The extremophilic strain Vreelandella titanicae Zn11_249 was isolated from Salar de Uyuni, an environment with high salinity, among other extreme factors. This study researched the optimised production, characterisation, antioxidant activity, and cytotoxicity of exopolysaccharides (EPS) produced by this strain under different ionic stresses. Zn11_249 was cultured in a minimal medium with glucose as the sole carbon source as a control, and under kosmotropic (NaCl, 1 M) and chaotropic (LiCl, 0.3 M) conditions, yielding EPS_U1, EPS_U2, and EPS_U3, respectively. Maximum EPS production (336 mg/L) occurred under chaotropic conditions after 96 h. EPSs were characterised using the following techniques: Gas chromatography (GC-MS); Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR); Thermogravimetric Analysis (TGA); and Differential Scanning Calorimetry, (DSC). The results showed differences between the molecular weights for EPS_U1 (3.9 × 10⁴ Da), EPS_U2 (3.9 × 10⁴ Da), and EPS_U3 (5.85 × 10⁴ Da). Their monosaccharide molar ratios (%) were 40/25/25/10 in EPS_U1, 10/30/30/30 in EPS_U2, and 25/25/25/25 in EPS_U3, composed of mannose, galactose, rhamnose, and glucose, respectively. Functional group analysis confirmed their heteropolysaccharide nature. Thermal profiles suggest the potential of these exopolysaccharides as biomaterials. Antioxidant tests demonstrated significant activity against DPPH, OH, and O₂ radicals, while cytotoxicity assays showed no toxicity. These results highlight the biotechnological potential of EPSs from Veelandella titanicae Zn11_249 for biomedical and cosmetic uses. Full article

Glass ionomers are utilized extensively within the domain of dentistry, for instance, as provisional restorations, liners, or bases, in addition to their application as pit and fissure sealers. It is imperative that this type of material exhibits favorable physico-chemical and biological properties. The primary objective of the presented study is to modify commercial resin-modified glass ionomer (Riva Light Cure, RMGIC) by doping it with copper particles (RMGIC + Cu) and to evaluate its properties in terms of potential beneficial clinical applications. Susceptibility to adhesion of microbial species and potential antimicrobial activity was evaluated against the Candida albicans, Streptococcus mutans, and Lactobacillus rhamnosus strains. Antiviral properties were evaluated against two viruses: Herpes simplex virus type 1 and human Adenovirus 5. Cytotoxicity of the materials was assessed using Balb/3T3 mouse fibroblast cell line. Temporal fluoride release up to 168 h in water and artificial saliva of different pH levels were also measured and assessed using statistical analysis. Samples were also subjected to Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy and Fourier-Transform Raman Spectroscopy. The findings of the present study demonstrate that RMGIC + Cu displays reduced biofilm formation against the tested strains when compared to non-modified material. The influence of the Cu presence on fluoride release is most pronounced in artificial saliva with a low pH (4.5), where the difference is significantly higher in samples with Cu than in samples without it. No reduction in herpes simplex 1 titers under the influence of either material was observed, whereas both materials exhibited virucidal properties against human adenovirus 5. Commercial glass ionomer presented no cytotoxicity, while the modified biomaterial caused changes in the fibroblast culture only under the sample (slight cytotoxicity, grade 1). Considering all the acquired results, doping glass ionomer with copper may be an interesting modification enhancing antimicrobial properties of the biomaterial, but it requires further evaluation in terms of long-term cytotoxicity before further in vivo studies. Full article

The preservation of archaeological bone is of great importance for both archaeological and conservation science studies. Traditional methods of preservation assessment, such as attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), are minimally invasive and destructive. Neutron and X-ray tomography offer a totally non-invasive novel analysis method for the state of preservation of archaeological bones. Seven archaeological animal bones were selected for analysis based on animal maturity, species, visual factors, and ATR-FTIR analysis results. Archaeological bone is a hierarchical composite material constructed from both organic and mineral components; therefore, neutron tomography and synchrotron X-ray tomography have been combined in this novel approach to assess the state of preservation of animal archaeological bone. The neutron data demonstrated that the organic distribution along the diaphysis of archaeological bones varied significantly both within bones and between different animal bones. There is minimal consistency between the samples, emphasizing the inhomogeneity in archaeological bone collections. X-ray tomography revealed unseen physical details, including cracks and substantial damage. The collection of this information via non-invasive methods is highly valuable for cultural heritage, providing a deeper understanding of the observed inhomogeneity in ATR-FTIR analysis data and revealing obscured physical details. Full article

The aim of this study is to identify the textile materials used to make Bulgarian folk costumes and to support the process of conservation and restoration of ethnographic objects. In the 18th and 19th centuries, folk costumes were made almost exclusively of natural materials, while in the first half and middle of the 20th century, they included contemporary synthetic and regenerated cellulose materials, as well as blends of these materials with natural fibers. A series of historical textiles and contemporary industrial fabrics were studied using a variety of analytical approaches, including micro-chemical staining and solubility tests, optical microscopy, scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS), and infrared (IR) spectroscopy. IR measurements were carried out in attenuated total reflectance (ATR) and external reflectance (ER) modes using a portable IR spectrometer, which enabled non-invasive analysis. The analysis revealed that the composition of the industrial fabrics and historical textiles encompassed synthetic fibers, such as polyester and polyamide, while others were made of regenerated cellulose fibers like viscose. Additionally, some textiles had a mixed composition of cotton and polyester or silk and viscose. The combined analytical approach provided reliable identification of both the synthetic and natural textile materials. Full article

In order to enhance the corrosion resistance of aluminum alloys, mussel adhesive protein (MAP) was intercalated into layered double hydroxide (LDH) grown onto an Al substrate. The results from X-ray diffraction (XRD), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and energy dispersive spectroscopy (EDS) measurements all confirmed that part of the positively charged MAP can be successfully intercalated into the LDH based on the strong second reactivity. MAP is able to form complexes with the metal cations and hydroxides, leading to less positive charges on the hydroxide layers of the LDH. The intercalation results in the removal of the previously intercalated anions from the interlayer space of the LDH, which maintains the charge balance and lamellar structure. The MAP intercalated LDH film can provide effective corrosion protection to the Al substrate. Full article

Introduction: Amoxicillin and Ampicillin are among the most widely used antibiotics for treating bacterial infections. While traditional drug monitoring methods often face challenges relative to accuracy and analysis speed, optical-based techniques offer a promising alternative. Fourier Transform Infrared Spectroscopy (FTIR), a well-established tool, is particularly suited for this purpose. As their molecular structures and characteristic infrared absorption features are very similar, they could be difficult to differentiate using FTIR spectroscopy. Hence, chemometric analysis is important to overcome this challenge. This study introduces a novel approach to the standard methods of antibiotic detection and monitoring, leveraging the capabilities of vibrational spectroscopy and helping in antimicrobial stewardship. Attenuated Total Reflection (ATR)–FTIR is carried out with chemometric tools to investigate Amoxicillin and Ampicillin over different degradation processes. Principal Component Analysis (PCA) was used in the fingerprint region to detect differences between the studied antibiotics. Additionally, absorbance intensity in the fingerprint region was monitored to assess the degradation of each antibiotic over time. To achieve this, the area under the curve was calculated and subjected to inferential statistical tests for both intragroup (the degradation of the same antibiotic) and intergroup (degradation within the same time interval, comparing the two antibiotics) comparisons. All analyses were performed in OriginLab and using Python in the Google Colab and Orange environments. For the calculations of the limit of detection (LoD), the method based on the calibration curve was used. Through the experiments, it was possible to identify the fingerprints of each antibiotic and statistically separate them, despite both belonging to the same class of antibiotics, where the spectral peaks appear in the same region. For degradation, all tests were conducted with a significance level of α = 5%. In this investigation, our results show several quantification characteristics with a detection limit of 96.76 mM for Ampicillin and 66.01 mM for Amoxicillin using the peak intensity. This research demonstrates that FTIR spectroscopy is effective for antibiotic detection and has the potential to be further developed into a monitoring protocol. Full article

This study investigated the potential of Thymus serpyllum L. and Mentha × piperita L. essential oils (EOs), known for their bioactive properties, as adjunctive treatments targeting Basal cell carcinoma cancer stem cells (BCC CSCs). Primary cultures were established from ten BCC tumor samples and their distant resection margins as controls. The chemical composition of the EOs was analyzed by gas chromatography–mass spectroscopy (GC-MS) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). The biological effects were evaluated via colony and spheroid formation, scratch assays, MTT and neutral red cytotoxicity assays, and qRT-PCR for Hh (SHH, PTCH1, SMO, and GLI1) and Notch (Notch1 and JAG1) gene expression. GC analysis identified thymol, p-cymene, and linalool as the main components of the EO of T. serpyllum L., and menthone and menthol in the EO of M. × piperita L. IC50 values were 262 µg/mL for T. serpyllum L. and 556 µg/mL for M. × piperita L. and were applied in all experiments. Both EOs significantly reduced CSC clonogenicity and migration (p < 0.05). The EO of T. serpyllum L. downregulated SMO and GLI1, while the EO of M. × piperita L. upregulated PTCH1, Notch1, and JAG1 (p < 0.05). These findings suggest that both EOs exhibit anticancer effects in BCC CSCs by modulating key oncogenic pathways, supporting their potential in BCC therapy. Full article

The acid number evaluates the degree of deterioration of lubricating oil. Existing methods for evaluating the performance degradation of lubricating oils are mostly based on the detection of traditional physical and chemical indicators, which often only reflect a single dimension of the degradation process, thus affecting the accuracy and repeatability of the results. Integrating multi-dimensional information can more comprehensively reflect the essence of degradation, which can improve the accuracy and reliability of the evaluation results. Mid-infrared spectroscopy is an effective means of monitoring the acid number. In this study, a combination of infrared spectroscopy quantitative analysis and chemometrics was used. The oil sample data was divided into training set and validation set by the Kennard–Stone method. In the experiment, a Fourier transform infrared spectrometer equipped with an attenuated total reflection accessory (ATR-FTIR) was used to collect spectral data of the samples in the wavenumber range of 1750–1700 cm⁻¹ (this range corresponds to the characteristic absorption of carboxyl groups and is directly related to the acid number). Meanwhile, a G20S automatic potentiometric titrator was used to determine the acid number as a reference value in accordance with GB/T 7304. The study compared various preprocessing methods. A regression prediction model between the spectra and acid number was established using partial least squares regression (PLSR) within the selected wavenumber range, with the root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), and coefficient of determination (R) as evaluation indicators. The experimental results showed that the PLSR model established after preprocessing with second derivative combined with seven-point smoothing exhibited the optimal performance, with an RMSECV of 0.00505, an RMSEP of 0.14%, and an R of 0.9820. Compared with the traditional titration method, this prediction method is more suitable for real-time monitoring of production lines or rapid on-site screening of equipment. It can in a timely manner warn of the deterioration trend of lubricating oil, reduce the risk of equipment wear caused by oil failure, and provide efficient technical support for lubricating oil life management. Full article

The authenticity of Protected Designation of Origin (PDO) Feta cheese is critical for consumer confidence and market integrity, particularly in light of widespread concerns over economically motivated adulteration. This study evaluated the potential of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with chemometric modeling to differentiate authentic Feta from non-Feta white brined cheeses. A total of 90 cheese samples, consisting of verified Feta and cow milk cheeses, were analyzed in both freeze-dried and fresh forms. Spectral data from raw, first derivative, and second derivative spectra were analyzed using principal component analysis–linear discriminant analysis (PCA-LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) to distinguish authentic Feta from non-Feta cheese samples. Derivative processing significantly improved classification accuracy. All classification models performed relatively well, but the PLS-DA model applied to second derivative spectra of freeze-dried samples achieved the best results, with 95.8% accuracy, 100% sensitivity, and 90.9% specificity. The most consistently highlighted discriminatory regions across models included ~2920 cm⁻¹ (C–H stretching in lipids), ~1650 cm⁻¹ (Amide I band, corresponding to C=O stretching in proteins), and the 1300–900 cm⁻¹ range, which is associated with carbohydrate-related bands. These findings support ATR-FTIR spectroscopy as a rapid, non-destructive tool for routine Feta authentication. The approach offers promise for enhancing traceability and quality assurance in high-value dairy products. Full article

Calendula officinalis L. is a widely used medicinal plant whose secondary metabolism and morphology are influenced by light. This study evaluated the effects of 2 and 4 h end-of-day (EOD) red/far-red (R:FR) and green (G) light on the growth, physiology, and phytochemical profile of hydroponically grown C. officinalis under a constant red/blue light background, compared with a red/blue control without EOD treatment. Morphological, physiological (gas exchange, chlorophyll fluorescence), biochemical (chlorophyll, anthocyanin), and chemical composition (attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and Gas Chromatography-Mass Spectrometry (GC-MS)) were evaluated. EOD G 2 h enhanced photosynthetic pigments, anthocyanins, and biomass, while control plants showed higher phenolic content. EOD R:FR induced stem elongation but reduced pigment and metabolite accumulation. GC-MS revealed organ-specific metabolic specialization, with flowers displaying greater chemical diversity than leaves. EOD G favored sesquiterpene diversity in flowers, while EOD R:FR increased nitrogen-containing compounds and unsaturated fatty acids. Vibrational data supported these shifts, with spectral signatures of esters, phenolics, and lipid-related structures. Bioactive compounds, including α-cadinol and carboxylic acids, were identified across treatments. These findings demonstrate that EOD light modulates physiological and metabolic traits in C. officinalis, highlighting EOD G as an enhancer of biomass and phytochemical richness for pharmaceutical applications under controlled conditions. Full article

Background/Objectives: The work presented herein focused on the development and characterization of a transdermal caffeine platform fabricated from ultrathin micro- and submicron fibers produced via electrospinning. Methods: The formulations incorporated caffeine encapsulated in a polyethylene oxide (PEO) matrix, combined with various permeation enhancers. A backing layer made of annealed electrospun polycaprolactone (PCL) facilitated the lamination of the two layers to form the final multilayer patch. Comprehensive characterization was conducted, utilizing scanning electron microscopy (SEM) to assess the fiber morphology, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) for chemical detection and to assess the stability of the caffeine, and differential scanning calorimetry (DSC) along with wide-angle X-ray scattering (WAXS) to analyze the physical state of the caffeine within the fibers of the active layer. Additionally, Franz cell permeation studies were performed using both synthetic membranes (Strat-M) and ex vivo human stratum corneum (SC) to evaluate and model the permeation kinetics. Results: These experiments demonstrated the significant role of enhancers in modulating the caffeine permeation rates provided by the patch, achieving permeation rates of up to 0.73 mg/cm² within 24 h. Conclusions: This work highlights the potential of using electro-hydrodynamic processing technology to develop innovative transdermal delivery systems for drugs, offering a promising strategy for enhancing efficacy and innovative therapeutic direct plasma administration. Full article

The quality and freshness of fruits and vegetables are critical factors in consumer acceptance and are significantly affected during transport and storage. This study aimed to evaluate the quality of greenhouse-grown tomatoes stored for 24 days by combining non-destructive image analysis, spectrophotometric assays (including total phenolic content and antioxidant and antiradical activity assessments), and attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy. Additionally, water activity, moisture content, total soluble solids, texture, and color were evaluated. Most physicochemical changes occurred between days 14 and 17, without major impact on overall fruit quality. A progressive transition in peel hue from orange to dark orange, and increased surface irregularity of their textural image were noted. Moreover, the combined use of instrumental and image analyses results via multivariate analysis allowed the clear discrimination of tomatoes according to storage days. In this sense, tomato samples were effectively classified by ATR-FTIR spectral bands, linked to carotenoids, phenolics, and polysaccharides. Machine learning (ML) models, including Random Forest and Gradient Boosting, were trained on image-derived features and accurately predicted shelf life and quality traits, achieving R² values exceeding 0.9. The findings demonstrate the effectiveness of combining imaging, spectroscopy, and ML for non-invasive tomato quality monitoring and support the development of predictive tools to improve postharvest handling and reduce food waste. Full article

As demand for plant-based beverages grows, analytical tools are needed to classify and understand their structural and compositional diversity. This study applied a multi-analytical approach to characterize 41 commercial almond-, oat-, rice- and soy-based beverages, evaluating attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, protein secondary structure proportions, colorimetry, and microscopic image texture analysis. A total of 26 variables, derived from ATR-FTIR and protein secondary structure assessment, were employed in multivariate models, using partial least squares discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA) to evaluate classification performance. The results indicated clear group separation, with soy and rice beverages forming distinct clusters while almond and oat samples showing partial overlap. Variable importance in projection (VIP) scores revealed that β-turn and α-helix protein structures, along with carbohydrate-associated spectral bands, were the key features for beverages’ classification. Textural features derived from microscopy images correlated with sugar and carbohydrate content and color parameters were also employed to describe beverages’ differences related to sugar content and visual appearance in terms of homogeneity. These findings demonstrate that combining ATR-FTIR spectral data with protein secondary structure data enables the effective classification of plant-based beverages, while microscopic image textural and color parameters offer additional extended product characterization. Full article

In food processing, non-destructive and non-invasive characterization is a powerful tool for monitoring processes and controlling quality. Cheeses consist of a large variety of products whose nutritional and sensory properties depend on the source materials, cheesemaking procedures, and biochemical transformations occurring during maturation and storage. In this study, proton magnetic resonance relaxation time correlation maps (2D ¹H-NMR T₁–T₂) are used to investigate the effect of the ripening degree on Pecorino cheese and evaluate its evolution during storage in a refrigerator under vacuum-packaging conditions. NMR relaxometry has allowed for non-invasive monitoring of packaged Pecorino cheese slices, and the results were compared with those obtained with the two widely used techniques, i.e., Differential Scanning Calorimetry (DSC) and Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy (ATR-FTIR). The analysis of variance and simultaneous component analysis (ASCA), separately applied to 2D ¹H-NMR T₁–T₂ correlation maps, DSC, and ATR-FTIR data, suggests that the results obtained with the NMR approach are consistent with those obtained using the two benchmark techniques. In addition, it can distinguish cheeses stored for different durations (storage time) irrespective of their original moisture content (ripening degree), and vice versa, without opening the vacuum-package, which could compromise the integrity of the samples. Full article