This study presents a comparative analysis of molecular docking data, focusing on the binding interactions of the natural compounds apigenin and luteolin with the proteins TP-53, pRb, and APOBEC, in comparison to conventional pharmacological ligands. Advanced bioinformatics techniques were employed to evaluate and contrast binding energies, showing that apigenin and luteolin demonstrate significantly higher affinities for TP-53, pRb, and APOBEC, with binding energies of −6.9 kcal/mol and −6.6 kcal/mol, respectively. These values suggest strong potential for therapeutic intervention against HPV-16. Conventional ligands, by comparison, exhibited lower affinities, with energies ranging from −4.5 to −5.5 kcal/mol. Additionally, protein–protein docking simulations were performed to assess the interaction between HPV-16 E6 oncoprotein and tumor suppressors TP-53 and pRb, which revealed high binding energies around −976.7 kcal/mol, indicative of their complex interaction. A conversion formula was applied to translate these protein–protein interaction energies to a comparable scale for non-protein interactions, further underscoring the superior binding potential of apigenin and luteolin. These findings highlight the therapeutic promise of these natural compounds in preventing HPV-16-induced oncogenesis, warranting further experimental validation for clinical applications.

Background/Objectives: The signs and symptoms of premenstrual syndrome (PMS) can be similar to those of various other illnesses and conditions. To facilitate the detection and categorization of PMS symptoms, specific questionnaires have been developed. The aim of this study was to translate and culturally adapt the Premenstrual Symptoms Screening Tool (PSST) for the Serbian-speaking population and assess its validity and reliability. Material and Methods: Our convenience sample included 350 Serbian-speaking female health sciences students from one of the Serbian universities who had PMS symptoms at least once during the past 12 months. They completed a general socio-epidemiologic questionnaire, the PSST, and the Depression, Anxiety and Stress Scale-21 (DASS-21). The PSST was translated according to the recommended methodology, and its psychometric characteristics (internal consistency, construct, discriminant validity and convergent validity) were tested. Results: There were no major changes in the items during the process of translation or validation. The Cronbach’s alpha coefficient for the whole scale was 0.927, whereas if an item was deleted, it was >0.8 for all the items. The McDonald’s omega coefficient was 0.896, indicating good internal consistency. The CI–TC coefficients were greater than 0.40 for all the items, indicating that all items were significant elements of the PSST. Exploratory factor analysis extracted three factors. Confirmatory factor analysis revealed adequate values for all model fit estimators. The PSST significantly correlated with the DASS-21, which confirmed its adequate convergent validity. Conclusions: The Serbian version of the PSST showed good validity and therefore can be used as a screening tool for PMS in Serbian-speaking young women.

This study investigates the use of artificial intelligence (AI) and ethnobotanical knowledge to identify natural compounds with potent antiviral activity against HPV-16. Through molecular docking simulations, we evaluated the binding affinities of various essential oil components, in-cluding Apigenin, against the key antigenic determinants of HPV-16 (E6, E7 oncoproteins, and L1 major capsid protein). Apigenin exhibited strong binding affinities, particularly to E6 Oncopro-tein. To further enhance these findings, we employed an AI-driven reverse engineering approach to predict a natural compound with superior efficacy. The AI identified Luteolin, a flavonoid with additional hydroxyl groups, as a promising candidate. Comparative docking studies demon-strated that Luteolin possesses significantly stronger binding affinities to all three HPV-16 targets, surpassing the efficacy of Apigenin. This work highlights the potential of AI in accelerating the discovery and optimization of natural antiviral agents, providing a powerful tool for pharmaco-logical and ethnopharmacological screenings. Our findings suggest that AI-guided identification of natural compounds can lead to the development of more effective antiviral therapies, warranting further experimental validation and potential synthesis in laboratory settings.

This article focuses on the sonographic axamination techique for evaluation of intracranial translucencies during the first trimester ultrasound scan. Appropriate knowledge of sonographic landmarks is the most important factor for evaluation normal as well as abnormal brain structure, and this examination may enable detection of open spina bifida and Arnold – Chiari anomaly at an early stage of fetal develpoment.

This study presents a detailed comparative analysis of Molecular Docking data, focusing on the binding interactions of conventional ligands and natural compounds, Apigenin and Luteolin, with TP-53, pRb, and APOBEC. Utilizing advanced bioinformatics techniques, coupled with Ar-tificial Intelligence software and High-Performance Computing (HPC), we measured and con-trasted the binding energies of these interactions. Additionally, we investigated protein-protein interactions between HPV-16 oncoprotein E6 and tumor suppressors TP-53 and pRb. Our findings demonstrate that the natural compounds Apigenin and Luteolin exhibit significantly higher binding affinities to TP-53, pRb, and APOBEC compared to conventional pharmacological ligands. The binding energies for Apigenin and Luteolin were approximately -6.9 kcal/mol and -6.6 kcal/mol, respectively, indicating their strong potential as therapeutic agents in inhibiting the oncogenic functions of HPV-16. In contrast, conventional ligands showed lower binding affinities, with energies around -4.5 to -5.5 kcal/mol. The study further revealed that the protein-protein interactions between E6 and TP-53, and E6 and pRb, exhibited considerably higher binding en-ergies, approximately -976.7 kcal/mol, due to the multiple interaction sites and the complex nature of protein interfaces. A conversion formula was developed to translate these high-energy inter-actions to a comparable scale for non-protein-protein interactions, highlighting the superior binding potential of natural compounds, which, through the same conversion formula, was shown to be higher than that of interaction between E6 with TP-53 and E6 with pRb. These results underscore the therapeutic promise of Apigenin and Luteolin in preventing HPV-16-related on-cogenesis. By demonstrating their higher binding affinities to crucial tumor suppressors, this study supports the development of natural compound-based therapies. The findings also em-phasize the necessity for further experimental validation to explore these compounds' efficacy in clinical settings. This comprehensive analysis provides a robust framework for understanding the comparative binding interactions and lays the groundwork for innovative therapeutic strategies against HPV-16.