Untargeted Metabolomic Approach of <i>Curcuma longa</i> to Neurodegenerative Phytocarrier System Based on Silver Nanoparticles

Curcuma is one of the most famous medicinal and tropical aromatic plants. Its health benefits have been appreciated and exploited in traditional Asian medicine since ancient times. Various studies have investigated its complex chemical composition and demonstrated the remarkable therapeutic properties of curcuma’s phytoconstituents. Oxidative stress is a decisive driving factor triggering numerous pathologies (neurodegenerative, psychiatric and cardiovascular diseases; diabetes; tumors, etc.). Numerous recent studies have focused on the use of natural compounds and nanomaterials as innovative molecular targeting agents as effective therapeutic strategies. In this study, we report, for the first time, the development of a simple target phytocarrier system that capitalizes on the bioactive properties of curcuma and AgNPs. The complete metabolic profile of curcuma was determined based on gas chromatography-mass spectrometry (GC-MS) and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QTOF-MS). A total of 80 metabolites were identified under mass spectra (MS)-positive mode from 10 secondary metabolite categories: terpenoids, amino acids, diarylheptanoids, flavonoids, phenolic acids, steroids, fatty acids, coumarins, alkaloids and miscellaneous. In addition, the biological activity of each class of metabolites was discussed. A comprehensive characterization (FT-IR, UV-Vis, DLS, SEM, TEM, EDS, zeta potential and XRD) was performed to study the morphostructural properties of this new phytocarrier system. Antioxidant activity of the new phytocarrier system was evaluated using a combination of in vitro methods (total phenolic assay, 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and cyclic voltammetric method (Trolox equivalent antioxidant capacity (TEAC) electrochemical assay)). Antioxidants assays showed that the phytocarrier system exhibits superior antioxidant properties to those of its components, i.e., curcuma or citrate-coated-AgNPs. These data confirm the potential to enhance relevant theoretical knowledge in the area of innovative antioxidant agents, with potential application in neurodegenerative therapeutic strategies

Chemical Composition, In Vitro and In Silico Antioxidant Potential of Melissa officinalis subsp. officinalis Essential Oil

The investigation aimed to study the in vitro and in silico antioxidant properties of Melissa officinalis subsp. officinalis essential oil (MOEO). The chemical composition of MOEO was determined using GC–MS analysis. Among 36 compounds identified in MOEO, the main were beta-cubebene (27.66%), beta-caryophyllene (27.41%), alpha-cadinene (4.72%), caryophyllene oxide (4.09%), and alpha-cadinol (4.07%), respectively. In vitro antioxidant properties of MOEO have been studied in 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) free-radical scavenging, and inhibition of β-carotene bleaching assays. The half-maximal inhibitory concentration (IC50) for the radical scavenging abilities of ABTS and DPPH were 1.225 ± 0.011 μg/mL and 14.015 ± 0.027 μg/mL, respectively, demonstrating good antioxidant activity. Moreover, MOEO exhibited a strong inhibitory effect (94.031 ± 0.082%) in the β-carotene bleaching assay by neutralizing hydroperoxides, responsible for the oxidation of highly unsaturated β-carotene. Furthermore, molecular docking showed that the MOEO components could exert an in vitro antioxidant activity through xanthine oxidoreductase inhibition. The most active structures are minor MOEO components (approximately 6%), among which the highest affinity for the target protein belongs to carvacrol

COMPARATIVE STUDY ON THE GUIDANCE OF ORTHODONTIC TREATMENTS THROUGH ARTIFICIAL INTELLIGENCE-BASED SOFTWARE AND CLASSIC SOFTWARE

When it comes to guiding orthodontic treatments, our study aims to evaluate the effectiveness and benefits of software powered by artificial intelligence (AI) compared to traditional software. The software underwent a thorough evaluation to assess its performance, adaptability, and verbal communication. According to the findings, the software showed a remarkable ability to process and analyze information, resulting in more accurate planning of orthodontic treatments. Its adaptability has been found to be noteworthy, enabling it to identify and address individual patient conditions and problems with greater precision. With the help of this software, orthodontic treatments can be modified and improved in real time, considering the progress and alterations of the case throughout the treatment. Verbal communication through “speech recognize” AI algorithms contributes significantly to their long-term use and user satisfaction. Creating a comfortable and pleasant environment, this software improves the user experience and strengthens their relationship with technology. Comparatively, the classic software presented a lower level of performance and adaptability, and it was impossible to communicate verbally with the software interface. It is based on fixed rule settings and cannot individualize the orthodontic treatment. On the other hand, it uses standardized planning that can lead to unsatisfactory results or further adjustments. According to the comparative study, the artificial intelligence-based software improved the performance and adaptability of orthodontic treatments. Additionally, it enabled direct verbal communication, eliminating the need for a keyboard and a mouse. They can provide more precise guidance by collecting data and machine learning capabilities. However, it is crucial to consider the cost and security aspects of implementing and using this software in the orthodontic practice

Prognostic Role of Vascular Endothelial Growth Factor and Correlation with Oxidative Stress Markers in Locally Advanced and Metastatic Ovarian Cancer Patients

Background: Vascular endothelial growth factor (VEGF) plays an important role in tumor progression in ovarian cancer, but the complex mechanism and interaction with oxidative stress are not fully understood. Methods: A prospective study included 52 patients with ovarian adenocarcinoma stage IIIA-IV. Serum VEGF and reactive oxygen species (ROS) such as malondialdehyde and ceruloplasmin were measured. Results: VEGF levels were elevated (mean 1014.7 ± 165 pg/mL), especially in patients with macroscopic residual disease (1058 vs. 810 pg/mL, p = 0.0001). Median progression-free survival (PFS) and overall survival (OS) were 6 and 40 months in patients with a very high VEGF (over 1200 pg/mL), 11 and 48 months in patients with VEGF between 1000–1200 pg/mL, 18 and 84 months in patients with VEGF between 800–1000 pg/mL, and not reached in patients with normal VEGF. Increased VEGF values were associated with a 2.6-fold increased risk of disease progression (HR = 2.60, 95% CI 1.69–3.99), and a 1.4-fold increased risk of death (HR = 1.4, 95% CI 1.15–1.91, p = 0.002). Receiver operator characteristic (ROC) curves were used to validate VEGF as a prognostic factor and the area under the curve (AUC) was 0.814, p = 0.036 for PFS and 0.729, p = 0.043, for OS. There was a positive correlation between VEGF and malondialdehyde, Pearson coefficient of 0.35, p = 0.0001. Conclusions: VEGF and malondialdehyde are important prognostic markers in ovarian cancer, especially in macroscopic residual disease, and there is a positive correlation between angiogenesis and oxidative stress

Prognostic Role of Vascular Endothelial Growth Factor and Correlation with Oxidative Stress Markers in Locally Advanced and Metastatic Ovarian Cancer Patients

Background: Vascular endothelial growth factor (VEGF) plays an important role in tumor progression in ovarian cancer, but the complex mechanism and interaction with oxidative stress are not fully understood. Methods: A prospective study included 52 patients with ovarian adenocarcinoma stage IIIA-IV. Serum VEGF and reactive oxygen species (ROS) such as malondialdehyde and ceruloplasmin were measured. Results: VEGF levels were elevated (mean 1014.7 &plusmn; 165 pg/mL), especially in patients with macroscopic residual disease (1058 vs. 810 pg/mL, p = 0.0001). Median progression-free survival (PFS) and overall survival (OS) were 6 and 40 months in patients with a very high VEGF (over 1200 pg/mL), 11 and 48 months in patients with VEGF between 1000&ndash;1200 pg/mL, 18 and 84 months in patients with VEGF between 800&ndash;1000 pg/mL, and not reached in patients with normal VEGF. Increased VEGF values were associated with a 2.6-fold increased risk of disease progression (HR = 2.60, 95% CI 1.69&ndash;3.99), and a 1.4-fold increased risk of death (HR = 1.4, 95% CI 1.15&ndash;1.91, p = 0.002). Receiver operator characteristic (ROC) curves were used to validate VEGF as a prognostic factor and the area under the curve (AUC) was 0.814, p = 0.036 for PFS and 0.729, p = 0.043, for OS. There was a positive correlation between VEGF and malondialdehyde, Pearson coefficient of 0.35, p = 0.0001. Conclusions: VEGF and malondialdehyde are important prognostic markers in ovarian cancer, especially in macroscopic residual disease, and there is a positive correlation between angiogenesis and oxidative stress