Iskanje po katalogu digitalne knjižnice

Opis: This study focuses on the surface and subsurface characterization of a pharmaceutical tablet containing sodium metamizolate (NaMET), with an emphasis on mass spectrometry using time-of-flight secondary ion mass spectrometry (ToF-SIMS). ToF-SIMS enabled the identification of NaMET-specific fragment ions, which served as signals for the determination of the spatial distribution of this active pharmaceutical ingredient (API) within the tablet matrix. A ToF-SIMS fragmentation mechanism for NaMET was proposed based on the ToF-SIMS spectra analysis measured on a NaMET reference standard. 3D ToF-SIMS imaging showed heterogeneous localization of the API across a 5 μm depth. Complementary techniques, including 3D profilometry and atomic force microscopy (AFM), provided surface roughness and morphological data, while X-ray photoelectron spectroscopy (XPS) confirmed the elemental composition and chemical states. Depth profiling by XPS further supported the non-uniform distribution of NaMET.
Ključne besede: matamizole, sodium metamizolate, ToF-SIMS, XPS, surface analysis, API
Objavljeno v DKUM: 10.11.2025; Ogledov: 0; Prenosov: 5
Celotno besedilo (9,03 MB)

Opis: Superparamagnetic iron oxide nanoparticles (SPIONs) with sizes below 10 nm are biocompatible and non-toxic, making them promising for biomedical applications. To prevent their agglomeration and enhance their functionality, the nanoparticles were coated with citric acid (CA), which modifies the surface charge, improves dispersion stability, and facilitates biomedical use. In this work, a modular flow-through microreactor system was employed to synthesize and coat the nanoparticles in a single, continuous two-step process. The system enables precise control over temperature and mixing, ensuring uniform reaction conditions and minimizing hot spots. The synthesized Fe3O4 nanoparticles exhibited an average crystallite size of ~5 nm (XRD) and particle sizes of 4–6 nm (TEM). FTIR analysis confirmed the successful surface functionalization with CA, while TGA indicated a coating mass fraction of approximately 4–20 wt%, increasing with higher CA concentration. Zeta potential measurements revealed strong colloidal stability, with values around −35 mV at pH 6.5. Among the tested CA concentrations, the sample with a molar ratio of Fe3O4:CA = 1:0.25 exhibited the most favorable properties, including narrow size distribution and improved dispersion stability. These findings demonstrate that the continuous modular flow approach enables the reproducible synthesis of highly stable, sub-10 nm CA-coated SPIONs, offering promising potential for biomedical applications, particularly as magnetic resonance imaging (MRI) contrast agents.
Ključne besede: superparamagnetic iron oxide nanoparticles, citric acid, modular flow microreactor system, continuous synthesis, zeta potential measurements
Objavljeno v DKUM: 03.11.2025; Ogledov: 0; Prenosov: 1
Celotno besedilo (1,54 MB)

Opis: The aim of the study was to analyse two small wastewater treatment plants (SWTPs) and compare their treatment performance with the aim of developing a zero-waste strategy. The analyses showed that the second wastewater treatment plant had a problem with an increased phosphorus concentration in the wastewater as well as fluctuations in nitrogen removal. One of the key aspects was the recovery of phosphorus in the form of struvite precipitated on zeolite, which can be used as a fertiliser due to its significant nutrient content. The main benefit of the same SWTP is the separate collection of cellulosic material (labelled as sample RS), which has the potential for reuse as biochar, while from the first SWTP the sludge sample (labelled as sample SS) was taken and torrefied for comparison with RS. Both samples were torrefied at 250 ◦C and 350 ◦C in nitrogen and carbon dioxide atmospheres. The RS products obtained in CO2 atmosphere at 350 ◦C showed the best biochar properties, as they had a higher heating value (HHV) and a higher C content. Elemental analysis showed that the carbon content in RS and SS increased from 43 to 65 % and from 35 to 39 %, respectively. Measurement of the HHV of the torrefied RS product showed an increase from 17 to 26 MJ/kg, while for SS it increased from 15 to 17 MJ/kg. The comprehensive combustion index and the EMCI index show higher values for the RS samples torrefied at 350 ◦C. The H/C and O/C ratios are favourable for these samples, as the high quality of torrefied biomass is associated with the highest prices on the market. According to the TGA and FTIR analysis, the type of torrefaction atmosphere, in contrast to the torrefaction temperature, has little influence on the subsequent use of the torrefied samples in combustion. The results show that the integration of torrefaction for biochar production with phosphorus recovery by struvite precipitation is an efficient solution for waste management in small wastewater treatment plants.
Ključne besede: wastewater treatment plant efficiency, torrefication, N2 atmosphere, CO2 atmosphere, solid biofuels, proximate and ultimate analyses, thermogravimetry
Objavljeno v DKUM: 29.10.2025; Ogledov: 0; Prenosov: 6
Celotno besedilo (7,33 MB)

Ključne besede: farmacevtska kemija, laboratorijske vaje, kemija
Objavljeno v DKUM: 27.10.2025; Ogledov: 0; Prenosov: 9
Celotno besedilo (3,00 MB)

Opis: Viral infections pose a significant health threat worldwide. Due to the high mutation rates of many viruses and their reliance on host cellular machinery, the development of effective antiviral therapies is particularly difficult. As a result, only a limited number of antiviral agents is currently available. In parallel to modern vaccines, traditional antiviral drug development is both time-consuming and costly, underscoring the need for faster, more efficient approaches. In recent years, particularly since the beginning of the COVID-19 pandemic, machine learning (ML) together with broader artificial intelligence (AI), have emerged as powerful methodologies for drug discovery and offer the potential to accelerate the identification and development of antiviral agents. This review examines the application of ML in the early stages of antiviral drug discovery, with a particular focus on recent studies where ML methods have successfully identified hit compounds with experimentally demonstrated activity in biological assays. By highlighting these successful case studies, the review illustrates the growing impact of ML in advancing the discovery of urgently needed novel antivirals.
Ključne besede: machine learning, artificial intelligence, antiviral compounds, biological activity
Objavljeno v DKUM: 17.10.2025; Ogledov: 0; Prenosov: 4
Celotno besedilo (10,88 MB)