Uvod: Adenomi hipofize su benigni tumori prednjeg režnja hipofize i čine 10% svih intrakranijalnih tumora. Metoda izbora za njihovu evaluaciju i dijagnostiku je magnetna rezonanca. Pruža korisne informacije o odnosu hipofize sa susjednim anatomskim strukturama i temelj je dijagnoze, nadzora, planiranja medicinske ili hirurške strategije i procjene odgovora na liječenje. Metode: U ovom istraživanju uključeno je 14 randomiziranih prospektivnih i retrospektivnih studija, sistemskim odabirom na internet bazama: PubMed, Google Scholar, Crossref i Researchgate. Ispitanici su različite starosne i spolne strukture. Razmotrene su studije koje su uključivale magnetnu rezonancu hipofize i njen značaj i senzitivnost prilikom dijagnostike adneoma hipofize. Ciljevi: Utvrditi značaj magnetne rezonance u dijagnostici adenoma hipofize. Komparirati magnetnu rezonancu sa ostalim radiološkim modalitetima snimanja hipotalamo-hipofizne regije te utvrditi senzitivnost magnetne rezonance prilikom dijagnosticiranja mikroadenoma. Rezultati: Na osnovu sistemskog pregleda literature ustanovljeno je da MRI ima visoku detekciju prilikom dijagnostike adenoma hipofize. Kompjuterizirana tomografija ostaje metoda izbora kada magnetna rezonanca nije dostupna i u slučajevima kada se ona ne može uraditi. Korištenjem dinamskog CT-a poboljšava se detekcija mikroadenoma u odnosu na protokol snimanja hipofize magnetnom rezonancom.

In the last decade, there have been many reports on the negative impact of wildfires on various ecosystems. Unfortunately, wildfires have been intensifying as global temperatures, droughts, and other instances of extreme weather events rise around the world. These circumstances are forcing communities to vigorously address the uncontrolled spread of wildfires, where the ultimate goal is the protection of wildlife. At the same time, many disaster prevention and monitoring methods, based on image processing and computer vision, have been developed. In this paper, we present a new unsupervised method based on RGB color space for the early detection of wildfires from still images. From the analysis of existing state-of-the-art methods, it is evident that different methods explore different color spaces for the extraction of flame features. Our motivation was to use only RGB color space and thus eliminate the time-consuming task of color space conversion. The proposed method consists of several new image processing techniques used to efficiently extract flame features. It outperforms the existing methods, where an increase of 3% and 2% is recorded in the F1 score and Matthews correlation coefficient, respectively. Such performance demonstrates the merits of the proposed method for flame segmentation and detection.

The traditional concept of drug discovery is based on the occupancy-driven pharmacology model. It implies the development of inhibitors occupying binding sites that directly affect protein functions. Therefore, proteins that do not have such binding sites are generally considered as pharmacologically intractable. Furthermore, drugs that act in this way must be administered in dosage regimens that often result in high systemic drug exposures in order to maintain sufficient protein inhibition. Thus, there is a risk of off-target binding and side effects onset. The landscape of drug discovery has been markedly changed since PROTAC (PROteolysis TArgeting Chimera) molecules emerged twenty years ago as a part of event-driven pharmacology model. These are bifunctional molecules that harness the ubiquitin-proteasome system, and are composed of a ligand that binds protein of interest (POI), a ligand that recruits E3 ubiquitin ligase and a linker that connects these two parts. Pharmacologically, PROTAC s bring POI and E3 ubiquitin ligase into the close proximity, which triggers the formation of a functional ternary complex POI-PROTAC -E3 ubiquitin ligase. This event drives POI polyubiquitination and subsequent degradation by the 26S proteasome. The development and exceptional properties of PROTAC molecules that brought them to clinical studies will be discussed in this paper.

The challenges of the COVID-19 pandemic are important and relevant for sustainable development. The aim of this chapter is to review the existing model of economic development, because the COVID-19 pandemic has called into question the effects of structural changes in the economy and manufacturing industry in Serbia. The main contribution of this chapter is the review of development results which show that Serbia is in the process of economic recovery, but that it has not yet embarked on the path of sustainable economic development due to numerous structural problems. Serbia has experience with unsustainable economic development, and this is a strong argument in favor of sustainable concept implementation. In addition, this chapter provides empirical research on structural and technological changes. The obtained results can be used by economic and industrial policy makers to influence the consequences of COVID-19 and to avoid the slowdown of structural reforms. There will be numerous economic, environmental, social, and especially health challenges whose solutions must be sustainable.

For applications as an engineering material, the ability to design properties is of special importance, ie. structuring materials that can be achieved on several levels and in different ways. One of the goals of this research is the development of procedures that would enable the production of silicone polymer nets with improved mechanical, elastic and thermal properties. These materials mainly relate to the dimethylsiloxane structure, which is known for its biocompatibility, in polymeric states. FTIR spectroscopy was used to confirm the presumed mechanism of the siloxane crosslinking reaction. The aim was to further elucidate the mechanism of interaction of silicone materials based on the obtained results of the analysis of mechanical properties of silicone nanocomposites.