Search Results (29)

This study investigates the influence of specific surface area (SSA) and aluminum hydroxide particle size on sodium aluminate’s purification efficiency in the Bayer process. This research examines how variations in SSA affect the adsorption and incorporation of contaminants such as Cu, Fe, and Zn, as well as the optimal balance between effective purification and excessive Al₂O₃ loss. Different SSA values and purification durations are analyzed to optimize the purification process and determine conditions that maximize impurity removal while maintaining system stability. Additionally, solid residue characterization using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS) provides insights into impurity incorporation mechanisms, including isomorphic replacement, surface adsorption, and co-crystallization. This study highlights key process parameters that influence impurity behavior and crystallization dynamics, offering valuable guidance for refining industrial purification strategies and improving aluminum hydroxide quality. Full article

Autoimmune liver diseases involve a heterogeneous group of chronic inflammatory disorders, including autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis. Sometimes presented consistently as an overlapping syndrome, their pathogenesis is rather complex and has yet to be fully elucidated, despite extensive research efforts. This review article corroborates the molecular mechanisms of autoimmune liver diseases, as well as existing and potential therapeutic modalities. Full article

The aim of our study was to investigate the role of ABCB1 polymorphism in the pharmacokinetics of carbamazepine (CBZ) in children. The study enrolled 47 Serbian pediatric epileptic patients on CBZ treatment. Genotyping for ABCB1 1236C<T (rs1128503), 2677G<A/T (rs2032582) and 3435C<T (rs1045642) was carried out using the TaqMan method. Steady-state CBZ serum concentrations were available from our previous study, determined by high pressure liquid chromatography (HPLC). The NONMEM software and one-compartment model were used for pharmacokinetic analysis. ABCB1 1236C<T, 2677G<A/T and 3435C<T variations were found at the frequencies of 47.9%, 48.9% and 52.1%, respectively. The equation that described population clearance (CL) was CL (L/h) = 0.175 + 0.0403 × SEX + 0.0332 × ABCB1 + 0.0176 × CYP1A2 + 0.000151 × DD where SEX has a value of 1 if male and 0 if female, ABCB1 has a value of 1 if C-G-C/T-T-T and 0 if any other ABCB1 diplotype, CYP1A2 has a value of 1 if −163A/A and 0 if −163C/C or C/A, and DD is the total CBZ daily dose (mg/day). The presence of the ABCB1 1236T-2677T-3435T haplotype is associated with an increased clearance of CBZ in pediatric epileptic patients. Full article

The c-Fos as a marker of cell activation is used to identify brain regions involved in stimuli processing. This review summarizes a pattern of c-Fos immunoreactivity and the overlapping brain sub/regions which may provide hints for the identification of neural circuits that underlie depressive- and anxiety-like behaviors of adult male rats following three and six weeks of chronic social isolation (CSIS), relative to controls, as well as the antipsychotic-like effects of olanzapine (Olz), and clozapine (Clz), and the antidepressant-like effect of fluoxetine (Flx) in CSIS relative to CSIS alone. Additionally, drug-treated controls relative to control rats were also characterized. The overlapping rat brain sub/regions with increased expression of c-Fos immunoreactivity following three or six weeks of CSIS were the retrosplenial granular cortex, c subregion, retrosplenial dysgranular cortex, dorsal dentate gyrus, paraventricular nucleus of the thalamus (posterior part, PVP), lateral/basolateral (LA/BL) complex of the amygdala, caudate putamen, and nucleus accumbens shell. Increased activity of the nucleus accumbens core following exposure of CSIS rats either to Olz, Clz, and Flx treatments was found, whereas these treatments in controls activated the LA/BL complex of the amygdala and PVP. We also outline sub/regions that might represent potential neuroanatomical targets for the aforementioned antipsychotics or antidepressant treatments. Full article

Metabolic perturbation has been associated with depression. An untargeted metabolomics approach using liquid chromatography-high resolution mass spectrometry was employed to detect and measure the rat serum metabolic changes following chronic social isolation (CSIS), an animal model of depression, and effective antidepressant fluoxetine (Flx) treatment. Univariate and multivariate statistics were used for metabolic data analysis and differentially expressed metabolites (DEMs) determination. Potential markers and predictive metabolites of CSIS-induced depressive-like behavior and Flx efficacy in CSIS were evaluated by the receiver operating characteristic (ROC) curve, and machine learning (ML) algorithms, such as support vector machine with linear kernel (SVM–LK) and random forest (RF). Upregulated choline following CSIS may represent a potential marker of depressive-like behavior. Succinate, stachydrine, guanidinoacetate, kynurenic acid, and 7-methylguanine were revealed as potential markers of effective Flx treatment in CSIS rats. RF yielded better accuracy than SVM–LK (98.50% vs. 85.70%, respectively) in predicting Flx efficacy in CSIS vs. CSIS, however, it performed almost identically in classifying CSIS vs. control (75.83% and 75%, respectively). Obtained DEMs combined with ROC curve and ML algorithms provide a research strategy for assessing potential markers or predictive metabolites for the designation or classification of stress-induced depressive phenotype and mode of drug action. Full article

Nepeta nuda L., a notable medicinal species in the tradition of the Balkan region, is a rich source of bioactive iridoids and phenolics previously described as high-resolution taxonomical classifiers for the genus Nepeta. However, their potential in investigating intra-species differentiation is here described for the first time. The aim was to recognize the sources of natural chemical diversity and their association with the genetic variability both within and among N. nuda populations in the Central Balkans. Chemical diversity was assessed from methanol extracts and essential oils through untargeted and targeted metabolomics using state-of-the-art analytical tools, covering a broad spectrum of compounds that represent the N. nuda metabolome. We found that chemodiversity primarily resides within populations of N. nuda, and similar results were obtained at the DNA level using microsatellite markers. The low genetic and chemical differentiation of the studied N. nuda populations implies that their metabolomic profiles may be less influenced by geographic distance and variable environmental conditions within the Central Balkans, as they are under the pivotal control of their genetic backgrounds. Screening the distribution of the major bioactive compounds belonging to phenolics (phenolic acids and flavonoids) and iridoids (both aglycones and glycosylated forms), within and among N. nuda populations, is able to guarantee mass spectrometry-based tools for the selection of elite representative genotypes with practical importance. The knowledge acquired will allow us to delve deeper into the molecular background of N. nuda chemical diversity, which is the course of our further work. Full article

This study aimed to assess the antioxidant capacity of lemon flavonoid extract Eriomin^® (LE) and its impact on cholesterol metabolism in the context of healthy aging. We orally treated 24-month-old male Wistar rats with an LE (40 mg/kg) suspended in 0.3 mL of sunflower oil. At the same time, control groups received an equal volume of sunflower oil (CON) or remained untreated (ICON) daily for 4 weeks. We examined LE’s effects on superoxide dismutase and catalase- and glutathione-related enzyme activities, the concentration of lipid peroxides and protein carbonyls, total oxidant status (TOS) and antioxidant status (TAS), and oxidative stress index (OSI) in the liver, jejunum, and ileum. We also measured total cholesterol, its biosynthetic precursors (lanosterol, lathosterol, desmosterol), its degradation products (bile acid precursors) in the serum, liver, jejunum, and ileum, and serum phytosterols (intestinal absorption markers). LE reduced TOS, TAS, and OSI (p < 0.05) compared with control values, indicating its consistent antioxidant action in all examined organs. LE lowered hepatic desmosterol (p < 0.05) while also reducing 7α- and 24-hydroxycholesterol levels in the liver and ileum (p < 0.01). Serum cholesterol, hepatic gene expression, and the immunostaining intensity of CYP7A1 were unchanged. In conclusion, LE exerted non-enzymatic antioxidant effects and reduced cholesterol degradation, reducing its biosynthesis products, thereby maintaining serum cholesterol levels. Full article

Chronic social isolation (CSIS) generates two stress-related phenotypes: resilience and susceptibility. However, the molecular mechanisms underlying CSIS resilience remain unclear. We identified altered proteome components and biochemical pathways and processes in the prefrontal cortex cytosolic fraction in CSIS-resilient rats compared to CSIS-susceptible and control rats using liquid chromatography coupled with tandem mass spectrometry followed by label-free quantification and STRING bioinformatics. A sucrose preference test was performed to distinguish rat phenotypes. Potential predictive proteins discriminating between the CSIS-resilient and CSIS-susceptible groups were identified using machine learning (ML) algorithms: support vector machine-based sequential feature selection and random forest-based feature importance scores. Predominantly, decreased levels of some glycolytic enzymes, G protein-coupled receptor proteins, the Ras subfamily of GTPases proteins, and antioxidant proteins were found in the CSIS-resilient vs. CSIS-susceptible groups. Altered levels of Gapdh, microtubular, cytoskeletal, and calcium-binding proteins were identified between the two phenotypes. Increased levels of proteins involved in GABA synthesis, the proteasome system, nitrogen metabolism, and chaperone-mediated protein folding were identified. Predictive proteins make CSIS-resilient vs. CSIS-susceptible groups linearly separable, whereby a 100% validation accuracy was achieved by ML models. The overall ratio of significantly up- and downregulated cytosolic proteins suggests adaptive cellular alterations as part of the stress-coping process specific for the CSIS-resilient phenotype. Full article

(1) Background: Cancer stem cells (CSCs) are a subpopulation of cells in a tumor that can self-regenerate and produce different types of cells with the ability to initiate tumor growth and dissemination. Chemotherapy resistance, caused by numerous mechanisms by which tumor tissue manages to overcome the effects of drugs, remains the main problem in cancer treatment. The identification of markers on the cell surface specific to CSCs is important for understanding this phenomenon. (2) Methods: The expression of markers CD24, CD44, ALDH1, and ABCG2 was analyzed on the surface of CSCs in two cancer cell lines, MDA-MB-231 and HCT-116, after treatment with 5-fluorouracil (5-FU) using flow cytometry analysis. A machine learning model (ML)–genetic algorithm (GA) was used for the in silico simulation of drug resistance. (3) Results: As evaluated through the use of flow cytometry, the percentage of CD24-CD44+ MDA-MB-231 and CD44, ALDH1 and ABCG2 HCT-116 in a group treated with 5-FU was significantly increased compared to untreated cells. The CSC population was enriched after treatment with chemotherapy, suggesting that these cells have enhanced drug resistance mechanisms. (4) Conclusions: Each individual GA prediction model achieved high accuracy in estimating the expression rate of CSC markers on cancer cells treated with 5-FU. Artificial intelligence can be used as a powerful tool for predicting drug resistance. Full article

In this work, we synthesized a new composite material comprised of previously formulated resveratrol nanobelt-like particles (ResNPs) and selenium nanoparticles (SeNPs), namely ResSeNPs. Characterization was provided by FESEM and optical microscopy, as well as by UV-Vis and FTIR spectroscopy, the last showing hydrogen bonds between ResNPs and SeNPs. DPPH, TBA, and FRAP assays showed excellent antioxidative abilities with ResNPs and SeNPs contributing mainly to lipid peroxidation inhibition and reducing/scavenging activity, respectively. The antibacterial effect against common medicinal implant colonizers pointed to notably higher activity against Staphylococcus isolates (minimal inhibitory concentrations 0.75–1.5%) compared to tested gram-negative species (Escherichia coli and Pseudomonas aeruginosa). Antibiofilm activity against S. aureus, S. epidermidis, and P. aeruginosa determined in a crystal violet assay was promising (up to 69%), but monitoring of selected biofilm-related gene expression (pelA and algD) indicated the necessity of the involvement of a larger number of genes in the analysis in order to further establish the underlying mechanism. Although biocompatibility screening showed some cytotoxicity and genotoxicity in MTT and alkaline comet assays, respectively, it is important to note that active antioxidative and antibacterial/antibiofilm concentrations were non-cytotoxic and non-genotoxic in normal MRC-5 cells. These results encourage further composite improvements and investigation in order to adapt it for specific biomedical purposes. Full article

The coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), includes a clinical spectrum of diseases from mild to severe progressive pneumonia, which has affected and still affects the human population worldwide. Most commonly, it is presented by respiratory symptoms, but studies have shown that about 50% of patients with SARS-CoV-2 infection have at least one gastrointestinal symptom (GI), predominantly nausea, diarrhea, vomiting, or loss of appetite. In addition, abnormal liver functional tests are commonly present in the SARS-CoV-2 virus. The aim of our study was to examine the GI and hepatic manifestations of COVID-19 in patients hospitalized due to COVID-19 pneumonia in “COVID hospital Batajnica”, University Clinical Center of Serbia in Belgrade. The study included 498 consecutive patients, and the data was obtained from the patient’s electronic medical history. GI symptoms included nausea, vomiting, diarrhea, and anorexia. Collected laboratory values included baseline and peak values of blood count, inflammatory parameters, liver function tests, renal function tests, and cardiac enzyme tests. The results have shown that GI symptoms occurred in 26% of cases at diagnosis, which indicates the great susceptibility of the GI system to SARS-CoV-2. There was a high risk of liver injury in patients with COVID-19 pneumonia (>60%). The level of AST is more often increased compared to ALT, which is different from other virus-induced liver lesions and may be a useful indicator of SARS-CoV-2 infection. Further research should focus on the causes of liver damage in SARS-CoV-2 virus and the impact on treatment and outcome of COVID-19 disease. Full article

Depression is linked to changes in GABAergic inhibitory neurons, especially parvalbumin (PV) interneurons, which are susceptible to redox dysregulation. Olanzapine (Olz) is an atypical antipsychotic whose mode of action remains unclear. We determined the effect of Olz on PV-positive (+) and glutamate decarboxylase 67 (GAD67) + cell numbers in the layers of dorsal hippocampus (dHIPP) cornu ammonis (CA1–CA3) and dentate gyrus (DG) subregions in rats exposed to chronic social isolation (CSIS), which is an animal model of depression. Antioxidative enzymes and proinflammatory cytokine levels were also examined. CSIS decreased the PV+ cell numbers in the Stratum Oriens (SO) and Stratum Pyramidale (SP) of dCA1 and dDG. It increased interleukin-6 (IL-6), suppressor of cytokine signaling 3 (SOCS3), and copper–zinc superoxide dismutase (CuZnSOD) levels, and it decreased catalase (CAT) protein levels. Olz in CSIS increased the number of GAD67+ cells in the SO and SP layers of dCA1 with no effect on PV+ cells. It reduced the PV+ and GAD67+ cell numbers in the Stratum Radiatum of dCA3 in CSIS. Olz antagonizes the CSIS-induced increase in CuZnSOD, CAT and SOCS3 protein levels with no effect on IL-6. Data suggest that the protective Olz effects in CSIS may be mediated by altering the number of PV+ and GAD67+ cells in dHIPP subregional layers. Full article

Plants have developed a variety of defense mechanisms that allow them to recognize and respond to specific stressors by triggering complex signaling networks that cause appropriate biochemical changes to overcome the stress. In this study, we subjected in vitro grown N. nervosa plants to PEG-induced dehydration stress for 1 day (1DPT), 3 days (3DPT) and 6 days (6DPT). Our study investigated antioxidant enzyme activities, including catalase (CAT), peroxidase (POX) and superoxide dismutase (SOD), unveiling dynamic responses to PEG-induced water stress. CAT levels increased initially (1DPT) but declined with prolonged treatment; while POX activity significantly increased at 3DPT and 6DPT; and SOD, particularly the Mn-SOD3 isoform, demonstrated a substantial increase, emphasizing its role in the enzymatic free-radical scavenging activity. Furthermore, examination of the phenolic acid content revealed that rosmarinic acid (RA) was the predominant phenolic compound, followed by chlorogenic acid (CHLA), while ferulic acid (FA) and caffeic acid (CAFFA) were present in lower concentrations. Notably, PEG-induced dehydration significantly boosted RA content in N. nervosa plants at 3DPT. This increase highlights the plant’s response to oxidative stress conditions and its role in non-enzymatic antioxidant defense mechanisms. These findings significantly contribute to our comprehension of N. nervosa’s adaptive strategies under PEG-induced dehydration stress, offering valuable insights into plant stress physiology within industrial and agricultural contexts. Full article

Metabolic-associated liver disease (MAFLD) affects up to 70% of overweight and more than 90% of morbidly obese people, and its pathogenesis is rather complex and multifactorial. The criteria for MAFLD include the presence of hepatic steatosis in addition to one of the following three criteria: overweight or obesity, presence of type 2 diabetes mellitus (T2DM), or evidence of metabolic dysregulation. If the specific criteria are present, the diagnosis of MAFLD can be made regardless of alcohol consumption and previous liver disease. The pathophysiological mechanisms of MAFLD, including inflammation, lipotoxicity, mitochondrial disfunction, and oxidative stress, as well as the impact of intestinal gut microbiota, are constantly being elucidated. Treatment strategies that are continually emerging are based on different key points in MAFLD pathogenesis. Yet, the ideal therapeutic option has still not been found and future research is of great importance, as MAFLD represents a multisystemic disease with numerous complications. Full article

Recently, there has been a growing interest in the application of artificial intelligence (AI) in medicine, especially in specialties where visualization methods are applied. AI is defined as a computer’s ability to achieve human cognitive performance, which is accomplished through enabling computer “learning”. This can be conducted in two ways, as machine learning and deep learning. Deep learning is a complex learning system involving the application of artificial neural networks, whose algorithms imitate the human form of learning. Upper gastrointestinal endoscopy allows examination of the esophagus, stomach and duodenum. In addition to the quality of endoscopic equipment and patient preparation, the performance of upper endoscopy depends on the experience and knowledge of the endoscopist. The application of artificial intelligence in endoscopy refers to computer-aided detection and the more complex computer-aided diagnosis. The application of AI in upper endoscopy is aimed at improving the detection of premalignant and malignant lesions, with special attention on the early detection of dysplasia in Barrett’s esophagus, the early detection of esophageal and stomach cancer and the detection of H. pylori infection. Artificial intelligence reduces the workload of endoscopists, is not influenced by human factors and increases the diagnostic accuracy and quality of endoscopic methods. Full article