Search Results (744)

Green synthesis of copper oxide (CuO) nanoparticles offers a sustainable alternative to conventional chemical methods that often involve toxic reagents and harsh conditions. This study investigates the use of Tithonia diversifolia, an invasive species in Sri Lanka, as a bioreductant for the eco-friendly fabrication of CuO nanoparticles. Using copper sulfate (CuSO₄·5H₂O) as a precursor, eight treatments were conducted by varying precursor concentration, temperature, and reaction time to determine optimal conditions. A visible color change in the reaction mixture initially indicated nanoparticle formation. Among all the conditions, treatment T4 (5 mM CuSO₄, 80 °C, 2 h) yielded the most favorable results in terms of stability, morphology, and crystallinity. UV-Vis spectroscopic analysis confirmed the synthesis, with absorbance peaks between 265 and 285 nm. FTIR analysis revealed organic functional groups and characteristic metal–oxygen vibrations in the fingerprint region (500–650 cm⁻¹), confirming formation. SEM imaging showed that particles were mainly spherical to polygonal, averaging 125–150 nm. However, dynamic light scattering showed larger diameters (~240 nm) due to surface capping agents. Zeta potential values ranged from −16.0 to −28.0 mV, indicating stability. XRD data revealed partial crystallinity with CuO-specific peaks. These findings support the potential of T. diversifolia in green nanoparticle synthesis, suggesting a low-cost, eco-conscious strategy for future applications. Full article

Background: Drug–drug interactions (DDIs) may occur when two or more drugs are taken together, leading to undesired side effects or potential synergistic effects. Most clinical effects of drug combinations have not been assessed in clinical trials. Therefore, predicting DDIs can provide better patient management, avoid drug combinations that can negatively affect patient care, and exploit potential synergistic combinations to improve current therapies in women’s healthcare. Methods: A DDI prediction model was built to describe relevant drug combinations affecting reproductive treatments. Approved drug features (chemical structure of drugs, side effects, targets, enzymes, carriers and transporters, pathways, protein–protein interactions, and interaction profile fingerprints) were obtained. A unified predictive score revealed unknown DDIs between reproductive and commonly used drugs and their associated clinical effects on reproductive health. The performance of the prediction model was validated using known DDIs. Results: This prediction model accurately predicted known interactions (AUROC = 0.9876) and identified 2991 new DDIs between 192 drugs used in different female reproductive conditions and other drugs used to treat unrelated conditions. These DDIs included 836 between drugs used for in vitro fertilization. Most new DDIs involved estradiol, acetaminophen, bupivacaine, risperidone, and follitropin. Follitropin, bupivacaine, and gonadorelin had the highest discovery rate (42%, 32%, and 25%, respectively). Some were expected to improve current therapies (n = 23), while others would cause harmful effects (n = 11). We also predicted twelve DDIs between oral contraceptives and HIV drugs that could compromise their efficacy. Conclusions: These results show the importance of DDI studies aimed at identifying those that might compromise or improve their efficacy, which could lead to personalizing female reproductive therapies. Full article

Emerging and persistent contaminants (EPCs) were detected at high concentrations in Chiang Mai’s Mae Kha Canal, identifying urban waterways as important sources of pollution in the Ping River system in northern Thailand. Maximum levels of metformin (20,000 ng/L), fexofenadine (15,900 ng/L), gabapentin (12,300 ng/L), sucralose (38,000 ng/L), and acesulfame (23,000 ng/L) point to inadequately treated wastewater as a plausible contributor. Downstream enrichment patterns relative to upstream sites highlight the cumulative impact of urban runoff. Five compounds—acesulfame, gemfibrozil, fexofenadine, TBEP, and caffeine—consistently emerged as reliable tracers of urban wastewater, forming a distinct chemical fingerprint of the riverine exposome. Median EPC concentrations were highest in Mae Kha, lower in other urban canals, and declined with distance from the city, reflecting spatial gradients in urban density and pollution intensity. Although most detected concentrations fell below predicted no-effect thresholds, ibuprofen frequently approached or exceeded ecotoxicological benchmarks and may represent a compound of ecological concern. Non-targeted analysis revealed a broader “chemical cocktail” of unregulated substances—illustrating a witches’ brew of pollution that likely escapes standard monitoring efforts. These findings demonstrate the utility of wide-scope surveillance for identifying key compounds, contamination hotspots, and spatial gradients in mixed-use watersheds. They also highlight the need for integrated, long-term monitoring strategies that address diffuse, compound mixtures to safeguard freshwater ecosystems in rapidly urbanizing regions. Full article

Spruce wood is a natural polymeric material, consisting of cellulose, lignin, hemicelluloses and other secondary components, which gives it a unique chemical footprint and architecture. Varnishes are used in musical instruments to protect the wood against humidity variations, wood being a hygroscopic material, but also to protect the wood from dirt. The varnishes used both to protect the wood from resonance and to ensure a special aesthetic appearance are either polymeric varnishes (nitrocellulose, oil-based) or volatile solvents (spirit). In this study, the color changes, the surface morphology and the chemical spectrum produced by three types of varnishes, applied in 5, 10 and 15 layers, on resonance spruce plates were analyzed. The results revealed significant changes in the color parameters: the lightness decreased by approximately 17% after the first layer, by 50% after 5 layers, by 65% after 10 layers and by 70% after 15 layers. The color parameters are most influenced by the anatomical quality of spruce wood (annual ring width and earlywood/latewood ratio) in the case of oil-based varnishes and least influenced in the case of nitrocellulose varnishes. The chemical fingerprint was determined by FTIR spectrum analysis, which revealed that the most pronounced absorptions were the double band 2926–2858 cm⁻¹, corresponding to aliphatic methylene and methyl groups (asymmetric and symmetrical C-H stretch), and the bands at 1724 cm⁻¹ (oil-based varnish), 1722 cm⁻¹ (nitrocellulose varnish) and 1708 cm⁻¹ (spirit varnish), all assigned to non-conjugated carbonyl groups in either carboxylic acids, esters aldehydes or ketones. The novelty of the study lies in the comparative analysis of three types of varnishes used in the musical instrument industry, applied to samples of spruce resonance wood with different macroscopic characteristics in three different layer thicknesses. Full article

Smokeless powders are a commonly used low explosive within the ammunition industry. Their ease of purchase has allowed criminals to use these products to build improvised explosive devices. Canines have become a vital tool in locating such improvised devices. With differing fabrication processes, one of the most difficult challenges for canine handlers is the optimal selection of training aids to choose as odor targets to allow for broad generalization. Several studies have been underway to understand the chemical odor characterization of smokeless powders, which can help provide canine teams with essential information to understand odor signatures from powder varieties. In this study, a SPME method optimization was conducted using unburned smokeless powders to provide a chemical odor profile assessment. Concurrently, statistical analysis using PCA and Spearman’s rank correlations was performed to explore whether odor volatile composition depicted associations between and within powder brands. The results showed that a longer extraction time (24 h) was optimal across all powders, as this yielded higher compound abundance and number of extracted odor volatiles. The optimal SPME fiber varied per powder, depicting the complexity of powder composition. There were 66 highly frequent compounds among the 18 powders, including 2-ethyl-1-hexanol, diphenylamine (DPA), and dibutyl phthalate. Principal component analysis (PCA) showed that while powders may be of the same type (single/double base), they can still portray clustering differences across and within brands. The Spearman’s rank correlation within powder type suggested that the double-base powders had a slightly higher similarity index when compared with the single-base powder types. Understanding the volatile odor profiles of various smokeless powders can enhance canine training by informing the selection of effective training aids and supporting odor generalization. Full article

In this paper, an in-depth characterization of the composition of extra-virgin olive oil (EVOO) from different cultivars was performed, with the aim of obtaining the fingerprint profile of bioactive constituents and studying the oxidative stability of the samples, both by an accelerated stability test and after four months of storage at room temperature. Among the investigated cultivars, some were typical of Umbria (Central Italy), namely Moraiolo, Frantoio, and Dolce Agogia, others of Apulia (Southern Italy), Coratina, Peranzana, and Bella di Cerignola, and others were typical Spanish cultivars cultivated in Umbria (Arbequina and Arbosana). The comparison of the chemical parameters among oils from the different cultivars allowed for their discrimination by multivariate statistical analysis. Some phenolic compounds were mainly responsible for the sample group’s differentiation, with the oils from the Spanish cultivars clearly distinguished from the Umbrian and Apulian sample groups. The processing of the results by chemometric analysis during oil storage and stability tests again allowed the discrimination of the samples analyzed at different storage times. This study contributes to increasing knowledge on olive oils—chemical and nutraceutical properties from specific cultivars, particularly some less studied so far, such as the Bella di Cerignola cultivar, and their changes in their nutraceutical properties during storage. Full article

In this study, we perform density functional theory (DFT) simulations to investigate the Raman spectra of the bulk and surface phases of β-Li₃PS₄ (LPS) and Li₂S, as well as their interfaces at varying compositional ratios. This analysis is relevant given the widespread application of these materials in Li–S solid-state batteries, where Li₂S functions not only as a cathode material but also as a protective layer for the lithium anode. Understanding the interfacial structure and how compositional variations influence its chemical and mechanical stability is therefore crucial. Our results demonstrate that the LPS/Li₂S interface remains stable regardless of the compositional ratio. However, when the content of both materials is low, the Raman-active vibrational mode associated with the [PS₄]³⁻ tetrahedral cluster dominates the interface spectrum, effectively obscuring the characteristic peaks of Li₂S and other interfacial features. Only when sufficient amounts of both LPS and Li₂S are present does the coupling between their vibrational modes become sufficiently pronounced to alter the Raman profile and reveal distinct interfacial fingerprints. Full article

Inelastic electron tunneling spectroscopy (IETS) has emerged as a powerful vibrational spectroscopy technique for molecular electronic junctions, providing unique insights into molecular vibrations and electron–phonon coupling at the nanoscale. In this review, we present a comprehensive overview of IETS in molecular junctions, tracing its development from foundational principles to the latest advances. We begin with the theoretical background, detailing the mechanisms by which inelastic tunneling processes generate vibrational fingerprints of molecules, and highlighting how IETS complements optical spectroscopies by accessing electrically driven vibrational excitations. We then discuss recent progress in experimental techniques and device architectures that have broadened the applicability of IETS. Central focus is given to emerging applications of IETS over the last decade: molecular sensing (identification of chemical bonds and conformational changes in junctions), thermoelectric energy conversion (probing vibrational contributions to molecular thermopower), molecular switches and functional devices (monitoring bias-driven molecular state changes via vibrational signatures), spintronic molecular junctions (detecting spin excitations and spin–vibration interplay), and advanced data analysis approaches such as machine learning for interpreting complex tunneling spectra. Finally, we discuss current challenges, including sensitivity at room temperature, spectral interpretation, and integration into practical devices. This review aims to serve as a thorough reference for researchers in physics, chemistry, and materials science, consolidating state-of-the-art understanding of IETS in molecular junctions and its growing role in molecular-scale device characterization. Full article

Tomatoes are globally esteemed not only for their nutritional value but also for their complex and appealing aroma, a key determinant of consumer preference. The present study aimed to comprehensively characterise the volatilomic fingerprints of three tomato species—Solanum lycopersicum L., S. lycopersicum var. cerasiforme, and S. betaceum—encompassing six distinct varieties, through the application of headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC-MS). A total of 55 volatile organic compounds (VOCs) spanning multiple chemical classes were identified, of which only 28 were ubiquitously present across all varieties examined. Carbonyl compounds constituted the predominant chemical family, with hexanal and (E)-2-hexenal emerging as putative key contributors to the characteristic green and fresh olfactory notes. Notably, esters were found to dominate the unique volatile fingerprint of cherry tomatoes, particularly methyl 2-hydroxybenzoate, while Kumato and Roma varieties exhibited elevated levels of furanic compounds. Multivariate statistical analyses, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), demonstrated clear varietal discrimination and identified potential aroma-associated biomarkers such as phenylethyl alcohol, 3-methyl-1-butanol, hexanal, (E)-2-octenal, (E)-2-nonenal, and heptanal. Collectively, these findings underscore the utility of volatilomic fingerprint as a robust tool for varietal identification and quality control within the food industry. Full article

With the development of various new types of instrumental aroma sensing technologies, there is a need for methodologies that help developers and users evaluate the performance of the different devices. This study introduces a simple method that uses standard coffee beverages, reproducible worldwide, thus allowing users to compare aroma sensing devices and technologies globally. Eight different variations of commercial coffee capsules were used to brew espresso coffees (40 mL), consisting of either Arabica coffee or a blend of Robusta and Arabica coffee, covering a wide range of sensory attributes. The AlphaMOS Astree electronic tongue (equipped with sensors based on chemically modified field-effect transistor technology) and the AlphaMOS Heracles NEO and the Volatile Scout3 electronic noses (both using separation technology based on gas chromatography) were used to describe the taste and odor profiles of the freshly brewed coffee samples and also to compare them to the various sensory characteristics declared on the original packaging, such as intensity, roasting, acidity, bitterness, and body. Linear discriminant analysis (LDA) results showed that these technologies were able to classify the samples similarly to the pattern of the coffees based on the human sensory characteristics. In general, the arrangement of the different coffee types in the LDA results—i.e., the similarities and dissimilarities in the types based on their taste or smell—was the same in the case of the Astree electronic tongue and the Heracles electronic nose, while slightly different arrangements were found for the Scout3 electronic nose. The results of the Astree electronic tongue and those of the Heracles electronic nose showed the taste and smell profiles of the decaffeinated coffees to be different from their caffeinated counterparts. The Heracles and Scout3 electronic noses provided high accuracies in classifying the samples based on their odor into the sensory classes presented on the coffee capsules’ packaging. Despite the technological differences in the investigated devices, the introduced coffee test could assess the similarities in the taste and odor profiling capacities of the aroma fingerprinting technologies. Since the coffee capsules used for the test can be purchased all over the world in the same quality, these coffees can be used as global standard samples during the comparison of different devices applying different measurement technologies. The test can be used to evaluate instrumentational and data analytical developments worldwide and to assess the potential of novel, cost-effective, accurate, and rapid solutions for quality assessments in the food and beverage industry. Full article

Chemical modifications are the standard for small interfering RNAs (siRNAs) in therapeutic applications, but predicting their off-target effects remains a significant challenge. Current approaches often rely on sequence-based encodings, which fail to fully capture the structural and protein–RNA interaction details critical for off-target prediction. In this study, we developed a framework to generate reproducible structure-based chemical features, incorporating both molecular fingerprints and computationally derived siRNA–hAgo2 complex structures. Using an RNA-Seq off-target study, we generated over 30,000 siRNA–gene data points and systematically compared nine distinct types of feature representation strategies. Among the datasets, the highest predictive performance was achieved by Dataset 3, which used extended connectivity fingerprints (ECFPs) to encode siRNA and mRNA features. An energy-minimized dataset (7R), representing siRNA–hAgo2 structural alignments, was the second-best performer, underscoring the value of incorporating reproducible structural information into feature engineering. Our findings demonstrate that combining detailed structural representations with sequence-based features enables the generation of robust, reproducible chemical features for machine learning models, offering a promising path forward for off-target prediction and siRNA therapeutic design that can be seamlessly extended to include any modification, such as clinically relevant 2′-F or 2′-OMe. Full article

The objective of this study was to analyze the impact of solar and hybrid dryers on the physicochemical characteristics, fingerprints, and cognitive-sensory perceptions of Mexican consumers of traditional tostadas made with corn of different races. Corn tostadas from different native races were evaluated with solar and hybrid (solar-photovoltaic solar panels) dehydration methods. Proximal chemical quantification, instrumental analysis (color, texture), fingerprint by Fourier transform infrared spectroscopy (FTIR), and sensory-cognitive profile (emotions and memories) and its relationship with the level of pleasure were carried out. The data were evaluated using analysis of variance models, Cochran Q, and an external preference map (PREFMAP). The results showed that the drying method and corn race significantly (p < 0.05) affected only moisture content, lipids, carbohydrates, and water activity. Instrumental color was influenced by the corn race effect, and the dehydration type influenced the fracturability effect. FTIR fingerprinting results revealed that hybrid samples exhibited higher intensities, particularly associated with higher lime concentrations, indicating a greater exposure of glycosidic or protein structures. Race and dehydration type effects impacted the intensity of sensory attributes, emotions, and memories. PREFMAP vector model results revealed that consumers preferred tostadas from the Solar-Chiquito, Hybrid-Pepitilla, Hybrid-Cónico, and Hybrid-Chiquito races for their higher protein content, moisture, high fracturability, crunchiness, porousness, sweetness, doughy flavor, corn flavor, and burnt flavor, while images of these tostadas evoked positive emotions (tame, adventurous, free). In contrast, the Solar-Pepitilla tostada had a lower preference because it was perceived as sour and lime-flavored, and its tostada images evoked more negative emotions and memories (worried, accident, hurt, pain, wild) and fewer positive cognitive aspects (joyful, warm, rainy weather, summer, and interested). However, the tostadas of the Solar-Cónico race were the ones that were most rejected due to their high hardness and yellow to blue tones and for evoking negative emotions (nostalgic and bored). Full article

The rapid neutron-capture process (r-process) is responsible for the creation of roughly half of the elements heavier than iron, including precious metals like silver, gold, and platinum, as well as radioactive elements such as thorium and uranium. Despite its importance, the nature of the astrophysical sites where the r-process occurs, and the detailed mechanisms of its formation, remain elusive. The key to resolving these mysteries lies in the study of chemical signatures preserved in ancient, metal-poor stars. These stars, which formed in the early Universe, retain the chemical fingerprints of early nucleosynthetic events and offer a unique opportunity to trace the origins of r-process elements in the early Galaxy. In this review, we explore the state-of-the-art understanding of r-process nucleosynthesis, focusing on the sites, progenitors, and formation mechanisms. We discuss the role of potential astrophysical sites such as neutron star mergers, core-collapse supernovae, magneto-rotational supernovae, and collapsars, that can play a key role in producing the heavy elements. We also highlight the importance of studying these signatures through high-resolution spectroscopic surveys, stellar archaeology, and multi-messenger astronomy. Recent advancements, such as the gravitational wave event GW170817 and detection of the r-process in the ejecta of its associated kilonovae, have established neutron star mergers as one of the confirmed sites. However, questions remain regarding whether they are the only sites that could have contributed in early epochs or if additional sources are needed to explain the signatures of r-process found in the oldest stars. Additionally, there are strong indications pointing towards additional sources of r-process-rich nuclei in the context of Galactic evolutionary timescales. These are several of the outstanding questions that led to the formation of collaborative efforts such as the R-Process Alliance, which aims to consolidate observational data, modeling techniques, and theoretical frameworks to derive better constraints on deciphering the astrophysical sites and timescales of r-process enrichment in the Galaxy. This review summarizes what has been learned so far, the challenges that remain, and the exciting prospects for future discoveries. The increasing synergy between observational facilities, computational models, and large-scale surveys is poised to transform our understanding of r-process nucleosynthesis in the coming years. Full article

The garden Nasturtium (Tropaeolum majus L.) is increasingly consumed worldwide due to its culinary appeal and perceived health benefits. However, the chemical markers underlying its functional properties remain insufficiently characterized. Building on evidence from a recent human pilot study confirming both high acceptability and dietary safety, we conducted a comprehensive volatilomic and phytochemical analysis of T. majus flowers and their juice. Headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC-MS) was employed to establish the volatilomic fingerprint of floral tissues and juice. Our analysis revealed a striking dominance of benzyl isothiocyanate and benzonitrile, which together accounted for 88% of the total volatile organic metabolites (VOMs) in the juice, 67% and 21%, respectively. In the floral tissues, benzyl isothiocyanate was even more prevalent, representing 95% of the total volatile profile. Complementary in vitro assays confirmed a substantial total phenolic content and strong antioxidant activity in the flowers. These findings provide a robust chemical rationale for the potential health-promoting attributes of T. majus, while identifying key volatilomic markers that could support future functional and safety claims. In parallel, a benefit–risk assessment framework is discussed in accordance with the European Food Safety Authority (EFSA) guidelines for the Qualified Presumption of Safety (QPS) of edible flowers. Given that both benzyl isothiocyanate and benzonitrile are classified as Cramer Class III substances, a conservative intake threshold of 1.5 μg/kg body weight per day is proposed. To enable quantitative exposure modeling and support the derivation of a tolerable daily intake (TDI), future studies should integrate organic solvent-based extraction methodologies to estimate the total volatile load per gram of floral biomass. This would align risk–benefit assessments with the EFSA’s evolving framework for novel foods and functional ingredients. Full article

Background/Objectives: The industrial extraction and purification processes of Cannabis sativa L. compounds are critical steps in creating formulations with reliable and reproducible therapeutic and sensorial attributes. Methods: For this study, standardized preparations of chemotype I were chemically analyzed, and the sensory attributes were studied to characterize the extraction and purification processes, ensuring the maximum retention of cannabinoids and minimization of other secondary metabolites. The industrial process used deep-cooled ethanol for selective extraction. Results: Taking into consideration that decarboxylation occurs in the process, the cannabinoid profile composition was preserved from the herbal substance to the herbal preparations, with wiped-film distillation under deep vacuum conditions below 0.2 mbar, as a final purification step. The profiles of the terpenes and cannabinoids in crude and purified Full-spectrum Extract Cannabis Oil (FECO) were analyzed at different stages to evaluate compositional changes that occurred throughout processing. Subjective intensity and acceptance ratings were received for taste, color, overall appearance, smell, and mouthfeel of FECO preparations. Conclusions: According to sensory analysis, purified FECO was more accepted than crude FECO, which had a stronger and more polarizing taste, and received higher ratings for color and overall acceptance. In contrast, a full cannabis extract in the market resulted in lower acceptance due to taste imbalance. The purification process effectively removed non-cannabinoids, improving sensory quality while maintaining therapeutic potency. Terpene markers of the flower were remarkably preserved in SOMAÍ’s preparations’ fingerprint, highlighting a major qualitative profile reproducibility and the opportunity for their previous separation and/or controlled reintroduction. The study underscores the importance of monitoring the extraction and purification processes to optimize the cannabinoid content and sensory characteristics in cannabis preparations. Full article