Search Results (3,314)

Plastics are very versatile materials that have contributed to the development of society since the 19th century; however, their mismanagement has led to an accumulation of plastic waste in almost every ecosystem, affecting the fauna of the planet. However, recently, some studies have shown that some insects might be able to adapt, consuming a wide range of hydrocarbon base polymers. In this work, the adaptive capacity of Zophobas morio larvae when feeding on different synthetic polymers derived from petroleum was studied. Four different thirty-day larval feeding treatments were carried out with synthetic polymers, including expanded polystyrene (PS), low-density polyethylene (LDPE), polyisoprene (PI), and butyl rubber (BR); in addition, a positive control of organic diet was included. Intestinal bacteria were isolated from the treatments and identified by Sanger sequencing. To analyze the chemical composition and physical form of the frass produced, Fourier transform infrared spectroscopy (FITR) was performed, and images of the feces’ surfaces were taken with scanning electron microscopy (SEM), respectively. Zophobas morio larvae were able to consume 54% of PS in 30 days, equivalent to 3.2 mg/d/larva. Nine culturable bacterial strains associated with the decomposition of synthetic polymers were identified in the intestine of the larvae. As for the physicochemical analysis of the feces, FTIR spectra showed the scission of bands corresponding to functional groups of the synthetic polymers in the comparison of the plastic diet treatments versus the feces of antibiotic-treated and plastic-fed larvae, while the comparison of spectra of the plastic and control treatments also identified differences in the absorption peaks. SEM imaging demonstrated that superworm feces differed in dependence on the substrate consumed. The findings demonstrated that Zophobas morio larvae possess a gut biological complex that allows them to feed and survive by consuming various petroleum-derived polymers. Full article

Mycotoxin contamination of foods is a major concern for food safety and public health worldwide. The contamination of agricultural commodities employed by humankind with mycotoxins (toxic secondary metabolites of fungi) is a major risk to the health of the human population. Common methods for mycotoxin detection include chromatographic separation, often combined with mass spectrometry (accurate but time-consuming to prepare the sample and requiring skilled technicians). Artificial intelligence (AI) has been introduced as a new technique for mycotoxin detection in food, providing high credibility and accuracy. This review article provides an overview of recent studies on the use of AI methods for the discovery of mycotoxins in food. The new approach demonstrated that a variety of AI technologies could be correlated. Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. In addition, this review focuses on the advancement of AI to work concomitantly with smart sensing technologies or other non-conventional techniques such as spectroscopy, biosensors, and imaging techniques for rapid and less damaging mycotoxin detection. We question the requirement for large and diverse datasets to train AI models, discuss the standardization of analytical methodologies, and discuss avenues for regulatory approval of AI-based approaches, among other top-of-mind issues in this domain. In addition, this research provides some interesting use cases and real commercial applications where AI has been able to outperform other traditional methods in terms of sensitivity, specificity, and time required. This review aims to provide insights for future directions in AI-enabled mycotoxin detection by incorporating the latest research results and stressing the necessity of multidisciplinary collaboration among food scientists, engineers, and computer scientists. Ultimately, the use of AI could revolutionize systems monitoring mycotoxins, improving food safety and safeguarding global public health. Full article

Thermochromic textiles possess the capability to indicate ambient temperature through color changes, enabling real-time temperature monitoring and providing temperature warnings for body heat management. In this study, three thermochromic dyes—blue, red, and yellow—were synthesized using crystalline violet lactone (CVL), 6′-(diethylamino)-1′,3′-dimethyl-fluoran (DDF), and 3′,6′-dimethoxyfluoran (DOF) as leuco dyes, respectively, with biomass tea polyphenol serving as the color developer and tetradecanol as the phase change material. The chemical structures of these dyes were characterized using UV spectroscopy, infrared spectroscopy, Raman spectroscopy and ¹H NMR. The thermochromic mechanisms were investigated, revealing that the binding bonds between the leuco dyes and the color developer broke and reorganized with temperature changes, imparting reversible thermochromic property. Polyester fabrics were dyed using an impregnation method to produce three reversible thermochromic fabrics in blue, red, and yellow. The structure and properties of these fabrics were analyzed, showing a significant increase in the UPF value from 26.3 to approximately 100, indicating enhanced UV resistance. Water contact angle measurements revealed that the contact angle of undyed polyester fabrics was 139°, while that of dyed polyester fabrics decreased by about 40°, indicating improved hydrophilicity. Additionally, the fabric inductive static tester showed that the static voltage half-life of dyed polyester fabric was less than 1 s, demonstrating a significant antistatic effect. Infrared thermal imaging results indicated that during the warming and cooling process, the thermochromic polyester fabric exhibited specific energy storage and insulation effects at 38 °C, close to the human body temperature. This study presented a novel approach to developing smart color-changing textiles using biomass-derived thermochromic dyes, offering diverse materials for personal thermal management, and intelligent insulation applications. Full article

The ancient Roman town of Turris Libisonis was located on the northern coast of Sardinia and was known in the past as an important naval port. Located in the Gulf of Asinara, it was a Roman colony from the 1st century BCE and became one of the richest towns on the island. Among the archaeological finds in the area, the cippus exhibited in the Antiquarium Turritano is of great interest for its well-preserved traces of polychromy. The artefact dates back to the early Imperial Age and could have had a funerary or votive function. The artefact was first examined using a portable and non-invasive protocol involving multi-band imaging (MBI), portable X-ray fluorescence (p-XRF), portable FT-IR in external reflectance mode (ER FT-IR) and Raman spectroscopy. After this initial examination, a few microfragments were collected and investigated by optical microscopy (OM), X-ray powder diffraction (XRPD), Fourier-transform infrared spectroscopy in ATR mode (ATR FT-IR) and micro-ATR mode (μATR FT-IR) and Scanning Electron Microscopy/Energy Dispersive Spectroscopy (SEM-EDS) to improve our knowledge and characterize the materials and to determine their provenience. The results contribute to a better understanding of the provenance of materials and shed light on pigments on stone and their use outside the Italian peninsula and, in particular, Roman Sardinia. Full article

Fluorescence lifetime imaging microscopy is sensitive to molecular interactions and environments. In homo-dyne frequency-domain fluorescence lifetime imaging microscopy, images of fluorescence objects are acquired at different phase settings of the detector. The detected intensity as a function of detector phase is a sinusoidal function that is sensitive to the lifetime of the fluorescent species. In this paper, the theory of phase-sensitive fluorescence image correlation spectroscopy is described. In this version of lifetime imaging, image correlation spectroscopy analysis (i.e., spatial autocorrelation) is applied to successive fluorescence images acquired at different phase settings of the detector. Simulations of different types of lifetime distributions reveal that the phase-dependent density of fluorescent objects is dependent on the heterogeneity of lifetimes present in the objects. We provide an example of this analysis workflow to a cervical cancer cell stained with a fluorescent membrane probe. Full article

Geophysical monitoring of CO₂ geological sequestration represents a critical technology for ensuring the long-term safe storage of CO₂ while verifying its characteristics and dynamic changes. Currently, the primary geophysical monitoring methods employed in CO₂ geological sequestration include seismic, fiber optic, and logging technologies. Among these methods, seismic monitoring techniques encompass high-resolution P-Cable three-dimensional seismic systems, delayed vertical seismic profiling technology, and four-dimensional distributed acoustic sensing (DAS). These methods are utilized to monitor interlayer strain induced by CO₂ injection, thereby indirectly determining the injection volume, distribution range, and potential diffusion pathways of the CO₂ plume. In contrast, fiber optic monitoring primarily involves distributed fiber optic sensing (DFOS), which can be further classified into distributed acoustic sensing (DAS) and distributed temperature sensing (DTS). This technology serves to complement seismic monitoring in observing interlayer strain resulting from CO₂ injection. The logging techniques utilized for monitoring CO₂ geological sequestration include neutron logging methods, such as thermal neutron imaging and pulsed neutron gamma-ray spectroscopy, which are primarily employed to assess the sequestration volume and state of CO₂ plumes within a reservoir. Seismic monitoring technology provides a broader monitoring scale (ranging from dozens of meters to kilometers), while logging techniques operate at centimeter to meter scales; however, their results can be significantly affected by the heterogeneity of a reservoir. Full article

Background: Neurosurgery demands exceptional precision due to the brain’s complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon’s ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as a promising innovation, offering real-time, in vivo non-invasive biochemical tissue characterization. This literature review evaluates the current research on RS applications in intraoperative neurosurgery, emphasizing its potential to enhance surgical precision and patient outcomes. Methods: Following PRISMA guidelines, a comprehensive systematic review was conducted using PubMed to extract relevant peer-reviewed articles. The inclusion criteria focused on original research discussing real-time RS applications with human tissue samples in or near the operating room, excluding retrospective studies, reviews, non-human research, and other non-relevant publications. Results: Our findings demonstrate that RS significantly improves tumor margin delineation, with handheld devices achieving high sensitivity and specificity. Stimulated Raman Histology (SRH) provides rapid, high-resolution tissue images comparable to traditional histopathology but with reduced time to diagnosis. Additionally, RS shows promise in identifying tumor types and grades, aiding precise surgical decision-making. RS techniques have been particularly beneficial in enhancing the accuracy of glioma surgeries, where distinguishing between tumor and healthy tissue is critical. By providing real-time molecular data, RS aids neurosurgeons in maximizing the extent of resection (EOR) while minimizing damage to normal brain tissue, potentially improving patient outcomes and reducing recurrence rates. Conclusions: This review underscores the transformative potential of RS in neurosurgery, advocating for continued innovation and research to fully realize its benefits. Despite its substantial potential, further research is needed to validate RS’s clinical utility and cost-effectiveness. Full article

Background: Due to the ongoing organ shortage, marginal grafts with steatosis are more frequently used in liver transplantation, leading to higher occurrences of graft dysfunction. A histological analysis is the gold standard for the quantification of liver steatosis (LS), but has its drawbacks: it is an invasive method that varies from one pathologist to another and is not available in every hospital at the time of organ procurement. This study aimed to compare non-invasive diagnostic tools to a histological analysis for the quantification of liver steatosis. Methods: Male C57BL6J mice were fed with a methioninecholine-deficient (MCD) diet for 14 days or 28 days to induce LS, and were compared to a control group of animals fed with a normal diet. The following non-invasive techniques were performed and compared to the histological quantification of liver steatosis: magnetic resonance spectroscopy (MRS), CARS microscopy, ^99mTc MIBI SPECT imaging, and a new near-infrared spectrometer (NIR-SG1). Results: After 28 days on the MCD diet, an evaluation of LS showed ≥30% macrovesicular steatosis. High correlations were found between the NIR-SG1 and the blinded pathologist analysis (R² = 0.945) (p = 0.001), and between the CARS microscopy (R² = 0.801 (p < 0.001); MRS, R² = 0.898 (p < 0.001)) and the blinded pathologist analysis. The ROC curve analysis showed that the area under the curve (AUC) was 1 for both the NIR-SG1 and MRS (p = 0.021 and p < 0.001, respectively), while the AUC = 0.910 for the Oil Red O stain (p < 0.001) and the AUC = 0.865 for the CARS microscopy (p < 0.001). The AUC for the ^99mTc MIBI SPECT was 0.640 (p = 0.013), and this was a less discriminating technique for LS quantification. Conclusions: The best-performing non-invasive methods for LS quantification are MRS, CARS microscopy, and the NIR-SG1. The NIR-SG1 is particularly appropriate for clinical practice and needs to be validated by clinical studies on liver grafts. Full article

Background: Recent years have seen a surge of interest in dual-modality imaging systems that integrate functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to probe brain function. This review aims to explore the advancements and clinical applications of this technology, emphasizing the synergistic integration of fNIRS and EEG. Methods: The review begins with a detailed examination of the fundamental principles and distinctive features of fNIRS and EEG techniques. It includes critical technical specifications, data-processing methodologies, and analysis techniques, alongside an exhaustive evaluation of 30 seminal studies that highlight the strengths and weaknesses of the fNIRS-EEG bimodal system. Results: The paper presents multiple case studies across various clinical domains—such as attention-deficit hyperactivity disorder, infantile spasms, depth of anesthesia, intelligence quotient estimation, and epilepsy—demonstrating the fNIRS-EEG system’s potential in uncovering disease mechanisms, evaluating treatment efficacy, and providing precise diagnostic options. Noteworthy research findings and pivotal breakthroughs further reinforce the developmental trajectory of this interdisciplinary field. Conclusions: The review addresses challenges and anticipates future directions for the fNIRS-EEG dual-modal imaging system, including improvements in hardware and software, enhanced system performance, cost reduction, real-time monitoring capabilities, and broader clinical applications. It offers researchers a comprehensive understanding of the field, highlighting the potential applications of fNIRS-EEG systems in neuroscience and clinical medicine. Full article

Background/Objectives: Despite the role of metabolism in breast cancer metastasis, we still cannot predict which breast tumors will progress to distal metastatic lesions or remain dormant. This work uses metabolic imaging to study breast cancer cell lines (4T1, 4T07, and 67NR) with differing metastatic potential in a 3D collagen gel bioreactor system. Methods: Within the bioreactor, hyperpolarized magnetic resonance spectroscopy (HP-MRS) is used to image lactate/pyruvate ratios, while fluorescence lifetime imaging microscopy (FLIM) of endogenous metabolites measures metabolism at the cellular scale. Results: HP-MRS results showed no lactate peak for 67NR and a comparatively large lactate/pyruvate ratio for both 4T1 and 4T07 cell lines, suggestive of greater pyruvate utilization with greater metastatic potential. Similar patterns were observed using FLIM with significant increases in FAD intensity, redox ratio, and NAD(P)H lifetime. The lactate/pyruvate ratio was strongly correlated to NAD(P)H lifetime, consistent with the role of NADH as an electron donor for the glycolytic pathway, suggestive of an overall upregulation of metabolism (both glycolytic and oxidative), for the 4T07 and 4T1 cell lines compared to the non-metastatic 67NR cell line. Conclusions: These findings support a complementary role for HP-MRS and FLIM enabled by a novel collagen gel bioreactor system to investigate metastatic potential and cancer metabolism. Full article

Background and Purpose. Gentamicin (GEN) is a broad-spectrum antibiotic that cannot be prescribed freely because of its toxicity. Thymoquinone (THQ), a phytochemical, has antibacterial, antioxidant, and toxicity-reducing properties. However, its hydrophobicity and light sensitivity make it challenging to utilize. This incited the idea of co-encapsulating GEN and THQ in liposomes (Lipo-GEN-THQ). Method. Lipo-GEN-THQ were characterized using the zeta-potential, dynamic light scattering, Fourier transform infrared spectroscopy, and transmission electron microscope (TEM). The liposomes’ stability was evaluated under different storage and biological conditions. Lipo-GEN-THQ’s efficacy was investigated by the minimum inhibitory/bactericidal concentrations (MICs-MBCs), time–kill curves, and antibiofilm and antiadhesion assays. Bacterial interactions with the empty and GEN-THQ-loaded liposomes were evaluated using TEM. Results. The Lipo-GEN-THQ were spherical, monodispersed, and negatively charged. The Lipo-GEN-THQ were relatively stable and released GEN sustainably over 24 h. The liposomes exhibited significantly higher antibacterial activity than free GEN, as evidenced by the four-fold lower MIC and biofilm eradication in resistant E. coli strain (EC-219). TEM images display how the empty liposomes fused closely to the tested bacteria and how the loaded liposomes caused ultrastructure damage and intracellular component release. An antiadhesion assay showed that the Lipo-GEN-THQ and free GEN (0.125 mg/L) similarly inhibited Escherichia coli (EC-157) adhesion to the A549 cells (68% vs. 64%). Conclusions. The Lipo-THQ-GEN enhanced GEN by combining it with THQ within the liposomes, reducing the effective dose. The reduction in the GEN dose after adding THQ may indirectly reduce the toxicity and aid in developing an enhanced and safer form of GEN. Full article

This paper presents the authentication analysis of a bronze bust of Napoleon I, attributed to the Italian artist Renzo Colombo (1856–1885) based on his signature and other casting and molding inscriptions. The bust was made using the lost wax technique and artificially patinated in the Pinédo variant workshop. This study combined historiographical research (using the specialized literature) with data from auction catalogs. These were compared with photographs of the entire bust and close-up images of key areas, including anthropomorphic features, clothing, inscriptions, and structural and ornamental details. The condition of the bust and its historical and chemical characteristics were assessed through direct analysis with magnifying tools and indirect analysis using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX). Full article

Two forms of flower-like ZnO nanostructures were synthesized using hydrothermal methods at various growth times/temperatures and zinc precursors. The morphology, structure, chemical composition, and optical properties of these ZnO nanoflowers were studied using a scanning electron microscope (SEM), X-ray diffraction spectroscopy (XRD), X-ray photoelectrons spectroscopy (XPS), Raman spectroscopy, and UV–Vis spectroscopy. The SEM images revealed two forms of flower-like nanostructures, namely lotus- and tulip-like flower ZnO nanostructures. The XPS analysis revealed the oxidation state of the Zn and O elements, as well as the presence of OH groups on the surface of the lotus-like flower ZnO nanostructure. The XRD results revealed less crystallinity of the lotus-like ZnO nanoflowers (NFs) compared with the tulip-like ZnO NFs. The XRD results revealed the presence of Zn (OH)₂ in the ZnO NFs. The Raman results confirmed less crystallinity of the lotus-like ZnO NFs. The estimated optical bandgap was 2.92 and 3.0 eV for the tulip- and lotus-like ZnO NFs, respectively. The tulip-like ZnO NFs showed superior photocatalytic degradation of methylene blue dye, verified via UV–Vis radiation, compared with the lotus-like ZnO NFs, which show the impact of the structure defects and OH- impurities on the photocatalytic performance of ZnO nanoflowers. Full article

The synthesis and characterization of iron oxide nanostructures, specifically snowflake architecture, are investigated for their potential applications in electrochemical sensing systems. A Raman spectroscopy analysis reveals phase diversity in the synthesized powders. The pH of the synthesis affects the formation of the hematite (α-Fe₂O₃) and goethite (α-FeOOH). Scanning electron microscopy (SEM) images confirm the distinct morphologies of the particles, which are selectively obtained through recrystallization during the elongated reaction time. An electrochemical analysis demonstrates the differing behaviors of the particles, with synthesis pH affecting the electrochemical activity and surface area differently for each shape. Cyclic voltammetry measurements reveal reversible dopamine detection processes, with snowflake iron oxide showing lower detection limits than a mixture of snowflakes and cube-like particles. This research contributes to understanding the relationship between iron oxide nanomaterials’ structural, morphological, and electrochemical properties. It offers practical insights into their potential applications in sensor technology, particularly dopamine detection, with implications for biomedical and environmental monitoring. Full article

Four novel Pseudomonas strains with record resistance to copper (Cu²⁺) previously isolated from ecologically diverse samples (P. lactis UKR1, P. panacis UKR2, P. veronii UKR3, and P. veronii UKR4) were tested against sonochemically synthesised copper-oxide (I) (Cu₂O) and copper-oxide (II) (CuO) nanoparticles (NPs). Nanomaterials characterisation by X-ray diffractometry (XRD), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), and High-Resolution Transmission Electron Microscopy (HRTEM) confirmed the synthesis of CuO and Cu₂O NPs. CuO NPs exhibited better performance in inhibiting bacterial growth due to their heightened capacity to induce oxidative stress. The greater stability and geometrical shape of CuO NPs were disclosed as important features associated with bacterial cell toxicity. SEM and TEM images confirmed that both NPs caused membrane disruption, altered cell morphology, and pronounced membrane vesiculation, a distinctive feature of bacteria dealing with stressor factors. Finally, Cu₂O and CuO NPs effectively decreased the biofilm-forming ability of the Cu²⁺-resistant UKR strains as well as degraded pre-established biofilm, matching NPs’ antimicrobial performance. Despite the similarities in the mechanisms of action revealed by both NPs, distinctive behaviours were also detected for the different species of wild-type Pseudomonas analysed. In summary, these findings underscore the efficacy of nanotechnology-driven strategies for combating metal tolerance in bacteria. Full article