Search Results (42,851)

With ever-developing analytical capabilities, the protection of the dairy chain from contamination by residues of veterinary drugs is improving. Legislative requirements are an inherent part of this process. Of antibiotics in dairy farming, representatives of the beta-lactams, tetracyclines, sulfonamides, (fluoro)quinolones, aminoglycosides, or polypeptide antibiotics are the most widely used. Due to the typically low levels of antibiotic residues in milk, mass spectrometry is the most commonly used detection technique. However, the interference of the sample matrix is one of its main limiting factors, and therefore, it needs to be eliminated. In the first step, the lipid fraction is removed and proteins are precipitated, followed by solid-phase or liquid–liquid extraction. The current trends include the reduction in the consumption of organic solvents (to reduce occupational hazards and burden to the environment) and automation, eliminating the influence of human error and optimizing the workflow. These trends lead to the development of new microextraction and automated techniques as well as the use of new sorbents and/or (green) solvents of natural origin. To capture the latest developments in the field and the relatively recent aforementioned trends, this review focuses on papers investigating antimicrobial residues in milk that were published between 2015 and 2024, providing an overview of emerging techniques applicable to antibiotic residue detection in milk samples. Full article

To monitor health risks associated with vaping, we introduce a multi-spectral optical sensor powered by machine learning for real-time characterization of electronic cigarette aerosols. The sensor can accurately measure the mass of particulate matter (PM) in specific particle size channels, providing essential information for estimating lung deposition of vaping aerosols. For the sensor’s input, wavelength-specific optical attenuation signals are acquired for three separate wavelengths in the ultraviolet, red, and near-infrared range, and the inhalation pressure is collected from a pressure sensor. The sensor’s outputs are PM mass in three size bins, specified as 100–300 nm, 300–600 nm, and 600–1000 nm. Reference measurements of electronic cigarette aerosols, obtained using a custom vaping machine and a scanning mobility particle sizer, provided the ground truth for size-binned PM mass. A lightweight two-layer feedforward neural network was trained using datasets acquired from a wide range of puffing conditions. The performance of the neural network was tested using unseen data collected using new combinations of puffing conditions. The model-predicted values matched closely with the ground truth, and the accuracy reached 81–87% for PM mass in three size bins. Given the sensor’s straightforward optical configuration and the direct collection of signals from undiluted vaping aerosols, the achieved accuracy is notably significant and sufficiently reliable for point-of-interest sensing of vaping aerosols. To the best of our knowledge, this work represents the first instance where machine learning has been applied to directly characterize high-concentration undiluted electronic cigarette aerosols. Our sensor holds great promise in tracking electronic cigarette users’ puff topography with quantification of size-binned PM mass, to support long-term personalized health and wellness. Full article

Gas washing and oil mixing have been widely studied in the Tazhong area of the Tarim Basin, but their effects on Cambrian subsaltic dolomite reservoirs have not yet been adequately explored. In this study, the influence of gas washing and oil mixing on light oils from these reservoirs was investigated. Using n-alkane mass depletion (Q value) analysis, light oils from wells ZS1 and ZS5 were analyzed to quantify the intensity of gas washing and to identify possible oil mixing in the Cambrian Awataga (Є₂a) and Wusongar (Є₁w) reservoirs. Unaltered light oil was recovered and models of phase behavior were constructed by PVT simulation and basin modeling to compare with altered light oils. The results show that the light oil in well ZS1 experienced medium-strength gas washing (Q value = 40.88%), while the gas washing in well ZS5 was weaker (Q value < 40.88%), providing evidence of oil mixing. Despite these changes, the light oils in the Cambrian reservoirs maintained a single liquid-phase state over geologic time without transitioning to condensate or gas phases. These results improve the understanding of gas washing in the Tazhong area and show that it has significantly altered the Cambrian reservoirs and affected the preservation of hydrocarbons after oil accumulation. Full article

Lithium is an important non-renewable resource, and the study of the tiered separation of rare earths and lithium from rare earth molten salt slag is an important approach to solving the current global resource shortage. This article adopts a sulfuric acid leaching process and a lithium-containing solution iron lithium extraction separation process to recover lithium from rare earth molten salt slag. The method systematically investigates the impact of sulfuric acid concentration, liquid-to-solid ratio, leaching temperature, leaching time, pH, P507 concentration, phase ratio, extraction temperature, and extraction time on the lithium extraction effect and iron lithium separation effect in rare earth molten salt slag. The results show that under the conditions of a sulfuric acid concentration of 0.9 mol/L, a liquid-to-solid ratio of 8:1 mL/g, a leaching temperature of 70 °C, a leaching time of 90 min, a pH of 0.9, a P507 concentration of 50%, a phase ratio of 5:3, an extraction temperature of 30 °C, and an extraction time of 20 min, the lithium leaching rate reaches 97.8%, and the separation of iron and lithium is fully achieved. This method can efficiently recover the valuable element lithium from rare earth molten salt slag, which is of great significance for the subsequent preparation of lithium products and the realization of a closed-loop production of rare earth alloys by molten salt electrolysis. Full article

For decades, fossil fuels have been the backbone of reliable energy systems, offering unmatched energy density and flexibility. However, as the world shifts toward renewable energy, overcoming the limitations of intermittent power sources requires a bold reimagining of energy storage and integration. Power-to-X (PtX) technologies, which convert excess renewable electricity into storable energy carriers, offer a promising solution for long-term energy storage and sector coupling. Recent advancements in machine learning (ML) have revolutionized PtX systems by enhancing efficiency, scalability, and sustainability. This review provides a detailed analysis of how ML techniques, such as deep reinforcement learning, data-driven optimization, and predictive diagnostics, are driving innovation in Power-to-Gas (PtG), Power-to-Liquid (PtL), and Power-to-Heat (PtH) systems. For example, deep reinforcement learning has improved real-time decision-making in PtG systems, reducing operational costs and improving grid stability. Additionally, predictive diagnostics powered by ML have increased system reliability by identifying early failures in critical components such as proton exchange membrane fuel cells (PEMFCs). Despite these advancements, challenges such as data quality, real-time processing, and scalability remain, presenting future research opportunities. These advancements are critical to decarbonizing hard-to-electrify sectors, such as heavy industry, transportation, and aviation, aligning with global sustainability goals. Full article

Background: Voriconazole is an antifungal drug, which is classified under Bio-Classification System-II and has low water solubility (0.71 mg/mL) and high permeability. Hardly any endeavors have been made to increase the bioavailability of voriconazole. Objective: To develop and evaluate a solid SMEDDS (self-microemulsifying drug delivery system) for antifungal activity. Methods: Based on solubility studies of Labrafil-M 1994 CS (oil), Cremophor-RH 40 (a surfactant) and Transcutol-HP (a co-surfactant) were selected as components of the SMEDDS and a pseudo-ternary phase diagram was prepared. Thereafter, the oil, surfactant, and co-surfactant were mixed with altered weight ratios (1:1/1:2/2:1) and evaluated through various in vitro, in vivo analyses. Results: The particle size of the optimized formulation was observed to be 19.04 nm and the polydispersity index (PDI) value was found to be 0.162 with steady-state zeta potential. The optimized liquid SMEDDS was converted into a solid SMEDDS. Various adsorbents, such as Aerosil-200, Avicel-PH101, Neusilin-US2, and Neusilin UFL2 were screened to better detect the oil-absorbing capacity and flow properties of the powder. Neusilin UFL2 was selected as an adsorbent due to its better oil-absorbing capacity. DSC, X-ray diffraction, and dissolution studies were carried out to characterize the formulation. Further, the Pharmacokinetic profile was also studied in Wistar rats and the Cmax, tmax, and AUC0®t were calculated. The Cmax and AUC0®t plasma concentration is considerably better for the SMEDDS than for the pure drug and marketed formulation. Conclusions: This investigation clearly reveals the potential of developing a solid SMEDDS for candidiasis and invasive aspergillosis treatment, with better efficacy as compared to the commercially available marketed formulation. Full article

Optical microresonators supporting whispering-gallery modes (WGMs) have become a versatile platform for achieving electromagnetically induced transparency-like (EIT-like) phenomena. We theoretically and experimentally demonstrated the tunable coupled-mode induced transparency based on the surface nanoscale axial photonics (SNAP) microresonator. Single-EIT-like and double-EIT-like (DEIT-like) effects with one or more transparent windows are achieved due to dense mode families and tunable resonant frequencies. The experimental results can be well-fitted by the coupled mode theory. An automatically adjustable EIT-like effect is discovered by immersing the sensing region of the SNAP microresonator into an aqueous environment. The sharp lineshape and high slope of the transparent window allow us to achieve a liquid refractive index sensitivity of 2058.8 pm/RIU. Furthermore, we investigated a displacement sensing phenomenon by monitoring changes in the slope of the transparent window. We believe that the above results pave the way for multi-channel all-optical switching devices, multi-channel optical communications, and biochemical sensing processing. Full article

For monitoring capillary moisture conduction, the most important parameter is the moisture conductivity coefficient, which is a material characteristic; however, its use in practical calculations is not very common. For further development in the field of liquid moisture propagation, an automated measuring apparatus has been developed and granted a European patent. Its essence lies in detecting the liquid water content based on a well-known physical phenomenon: electromagnetic radiation in the microwave range. The determination of the spatiotemporal moisture field is the first and fundamental step for describing transportation phenomena. The moisture field thus created allows for the viewing of the moisture conductivity coefficient, which is one of the most important parameters in describing transportation phenomena as a function of moisture. The presence of water in building materials can significantly affect their physical properties, such as mechanical or thermal–technical characteristics. This may lead to unacceptable consequences, which might only manifest after a certain period of time. In the case of multi-layered structures, moisture can transfer from one material to another. Therefore, it is essential to address this process. The advantage of the software solution described by the methodology is the use of an open communication protocol in the form of a synchronized array, which is not common in typical applications of this type. The principle of separating hardware modules is also unusual for devices of this type, as it requires the independent communication of each module with the control software. Mutual communication is handled exclusively at the software level, making it possible to modify, optimize, or parameterize the procedures as needed. Upon closer examination of the wetting curves of various materials, anomalies were revealed in some of their structures. This can be advantageously utilized in the research of newly developed composite materials. The assembled system of measuring instruments, their software integration, and control provide a foundation for the practical application of the described procedures and methods for determining the moisture field of building materials. The parameterization of individual processes, as well as the open access to data, allows for the optimization of the methodology, as materials of entirely different characteristics may require an individual approach, which will certainly contribute to the advancement of science and research in this area. Currently, this work is being followed by further extensive studies, not yet published by the authors, focusing on the application of the described moisture field to evaluate the moisture conductivity coefficient as a function dependent on the material’s mass moisture content. Their application requires specific mathematical and programming approaches due to the significant volume of data involved. Full article

Background/Objectives: The importance of fixed-dose combinations (FDCs) for the treatment of hypertension is well established. However, from a stability perspective, FDCs present a challenge since the degradation of one active pharmaceutical ingredient (API) can be affected by the presence of another API. The aim of this study was to compare the degradation behaviors and evaluate the degradation kinetics of three antihypertensive drugs, perindopril tert-butylamine (PER), amlodipine besylate (AML), and indapamide (IND). Methods: The degradation processes were studied using the previously developed reverse phase high-performance liquid chromatographic (RP-HPLC) method after exposing each drug individually, as well as the combinations of two/three drugs, to different stress factors, such as light, oxidation, acidic, basic, or neutral pH values at different temperatures. Results: The results show that PER is most unstable under basic conditions and that AML displays a negative, while IND displays a positive effect, on PER stability when combined. AML is most affected by basic conditions and oxidation, and its stability is affected by both drugs positively; IND undergoes extreme photolysis, which is positively affected by AML but negatively by PER. Conclusions: Great care must be taken when formulating FDCs with these three drugs, as well as solutions or oral suspensions adjusted for geriatric or pediatric populations, since the stability of all three drugs is greatly affected by pH conditions, as well as light or oxidation factors and their interactions. Full article

The bioactive flavonoids pinostrobin (PN) and panduratin A (PA) from Boesenbergia rotunda are essential for research and therapeutic applications. This study introduces an innovative method utilizing ultrasound-assisted extraction with n-hexane pre-treatment, followed by one-step centrifugal partition chromatography (CPC) purification. Extraction efficiency was evaluated using ultra high-performance liquid chromatography (UHPLC), and the isolated compounds were characterized through ¹H-NMR and liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS), adhering to AOAC validation guidelines. Optimal extraction conditions comprised a particle size of 125 μm, a solid-to-liquid ratio of 1:30 g/mL, and a 10 min extraction time, yielding a crude extract of 6.96 ± 0.07%. Using an n-hexane/MeOH/water (5/3.4/1.6, v/v) solvent system in ascending mode, PN (2.16 mg, 98.78% purity) and PA (0.4 mg, 99.69% purity) were isolated from 67 mg of crude extract within 30 min. This streamlined approach enhances purification efficiency, allowing for faster extraction and higher purity, making it a suitable method for commercial applications. Full article

Eschar and slough in wounds serve as a reservoir for microorganisms and biofilms, damaged/devitalised cells, and inflammatory chemokines/cytokines, which work to initiate and prolong persistent inflammation and increase the risk of infection. Biofilm-related inflammation and infections are considered to be highly prevalent in acute wounds and chronic wounds. As slough is known to harbour biofilms, measuring the efficacy of antimicrobials in killing microbes both within and under slough is warranted. This highlights the need for more clinically relevant wound biofilm models to address this significant clinical need. Consequently, in this study, we developed an in vitro artificial wound slough (AWS) biofilm model produced by forming a biofilm below a layer of AWS, the latter of which was composed of the main protein components reported in wound eschar and slough, namely collagen, elastin, and fibrin. The model was employed to investigate the antibiofilm and antibacterial efficacy of a new patented smart next-generation antibiofilm technology composed of silver–zinc EDTA complexes and designed as a family of multifunctional metal complexes referred to as MMCs, in a liquid format, and to determine both the performance and penetration through AWS to control and manage biofilms. The results demonstrated the ability of the AWS–biofilm model to be employed for the evaluation of the efficacy of a new antibiofilm and antimicrobial next-generation smart technology. The results also demonstrated the potential for the proprietary EDTA multifunctional metal complexes to be used for the disruption of biofilms, such as those that form in chronic wounds. Full article

In this study, we designed a molecularly imprinted polymers-dispersive solid-phase extraction-high-performance liquid chromatography (MIPs-DSPE-HPLC) method, as a simple and efficient platform for the sensitive detection of two sulfonamide antibiotics (SAs) of sulfamethoxine (SMM) and sulfamethoxazole (SMZ) in environmental water samples. Using SMM and SMZ as templates, methacrylic acid as the functional monomer, ethylene glycol dimethacrylate as the crosslinking agent, and azodiisobutyronitrile as the catalyst, the dual-template molecularly imprinted polymers (dt-MIPs) were successfully synthesized via surface imprinting technology and multi-template imprinting strategy. The adsorption properties of the prepared MIPs were characterized, and the adsorption capacities of MIPs towards SMZ and SMM were 27.35 mg/g and 30.92 mg/g, respectively. The detection limits of the method in three environmental water samples were in the range of 0.23–1.74 μg/L, and the recoveries were between 82.7 and 110.3%, with relative standard deviations less than 5.93%. The construction process of this MIPs-DSPE-HPLC method is straightforward, exhibits high sensitivity and selectivity, and thus provides a versatile method for the quantification of SAs in complex matrices. Full article

Cynanchum auriculatum Royle ex Wight (CA) is a traditional medicinal and edible plant in China. This study aimed to isolate and characterize the phenolic compounds of C. auriculatum to identify its main antioxidant constituents. Polyphenols were extracted using an ultrasound-assisted ethanol extraction method, followed by partitioning with ethyl acetate. The ethyl acetate extract was then purified through thin-layer chromatography, silica gel column chromatography, and reverse-phase silica gel column chromatography. Three monomeric compounds—cynandione A (I), 2,5-dihydroxyacetophenone (II), and radix piperacanthone (III)—were identified through their physical and chemical properties, UV and IR spectra, and liquid chromatography–mass spectrometry (LC-MS/MS). Vitamin C (VC) and 2,4-dihydroxyacetophenone were used as controls to evaluate the antioxidant potential of the two most abundant monomers. Antioxidant assays demonstrated that 2,5-dihydroxyacetophenone and cynandione A exhibited strong antioxidant activity at lower concentrations, whereas 2,4-dihydroxyacetophenone showed significantly weaker activity. Furthermore, cynandione A displayed superior cellular antioxidant activity compared to 2,5-dihydroxyacetophenone, indicating its potential as a promising bioactive compound. In conclusion, this study provides valuable insights into the phenolic composition of C. auriculatum and highlights cynandione A as a key antioxidant, paving the way for future research on its therapeutic applications. Full article

Certain species of Mucorales have been identified as causative agents of mucormycosis, a rare yet often lethal fungal infection. Notably, these fungi exhibit intrinsic resistance to common azole drugs, which target lipids. Given the pivotal role of lipids in drug resistance and their contribution to innate resistance to azoles, this study provides a comprehensive overview of key lipid classes, including sphingolipids (SLs), glycerophospholipids (GPLs), and sterols, in Rhizopus delemar 99-880, a well-characterized reference strain among Mucorales. Using shotgun lipidomics as well as liquid- and gas-chromatography-based mass spectrometric analyses, we identified the lipid intermediates and elucidated the biosynthetic pathways of SLs, PGLs, and sterols. The acidic SLs were not found, probably because the acidic branch of the SL biosynthesis pathway terminates at α-hydroxy phytoceramides, as evident by their high abundance. Intermediates in the neutral SL pathway incorporated higher levels of 16:0 fatty acid compared to other pathogenic fungi. A strikingly high phosphatidylethanolamine (PE)/phosphatdylcholine (PC) ratio was observed among GPLs. Ergosterol remains the major sterol, similar to other fungi, and our analysis confirms the existence of alternate ergosterol biosynthesis pathways. The total lipidomic profile of R. delemar 99-880 offers insights into its lipid metabolism and potential implications for studying pathogenesis and drug resistance mechanisms. Full article

Differentiated thyroid carcinoma (DTC) is among the most prevalent endocrine cancers. The diagnosis of DTC has witnessed tremendous progress in terms of technological advancement and clinical operational guidelines. DTC diagnostics have evolved significantly over centuries, from early clinical examinations to modern molecular testing and imaging modalities. The diagnosis and management of DTC are currently dependent on the international histological classification and identification of specific genetic abnormalities in tumor tissue, as well as the prognostic implications that can inform treatment decisions. This study goes down the memory lanes of various diagnostic methods for DTCs, highlighting recent advancements in molecular testing and point-of-care (POC) technology. Beginning with conventional methods like fine needle aspiration biopsy (FNAB), fine needle aspiration cytology (FNAC), and ultrasound (US) and moving to contemporary innovative approaches such as POC-thyroglobulin (POC-Tg) and liquid biopsy, this review showcases the current trends in DTC diagnostics. Although considerable progress has been achieved in early malignancy detection, patient stratification, prognosis, and personalized treatment, there is a need to refine the mainstay diagnostic procedures. Finally, future perspectives were provided, and emerging roles of artificial intelligence in DTC diagnostics were explored. Full article