This article presents the results of a study on the determination of polyphenols in Black tea by high-performance liquid chromatography (HPLC). Polyphenols are bioactive compounds in plants, whose antioxidant properties have a therapeutic effect against various diseases. During the study, the main polyphenols (e.g. flavonoids and phenolic acids) in Black tea were identified and their quantitative indicators were determined. The effective effect of these compounds on eye diseases, in particular, age-related macular degeneration, glaucoma, and dry eye syndrome, was studied. The results showed that polyphenols in Karachay play an important role in protecting eye tissues from oxidative stress and reducing inflammatory processes. The results of this study serve to increase the pharmacological value of Karachay and expand the possibilities of its application in the healthcare sector.

Petiveria alliacea, a plant traditionally used in folk medicine, has shown significant potential for antimicrobial activity. This study investigates the antimicrobial properties and mechanisms of action of the stem extract of Petiveria alliacea against a range of pathogenic microorganisms. The extract was tested against both Gram-positive and Gram-negative bacteria, as well as fungi, using standard microbiological assays. The results demonstrated strong antimicrobial efficacy, with notable inhibition zones against several bacterial and fungal strains. Additionally, the study explores the mechanisms underlying these effects, including the disruption of microbial cell walls, membrane integrity, and enzyme inhibition. These findings suggest that Petiveria alliacea stem extract could serve as a promising natural antimicrobial agent, contributing to the development of alternative therapies for combating infections.

It is known and proven that the degree of damage to the left main coronary artery (LMCA), along with the indicators of  the left ventricle (LV) myocardium’s contractile function, are the main factors determining the survival of patients with coronary artery disease (CAD). Therefore, the effectiveness of the chosen management strategy for such patients determines not only the quality of life, i.e relief from angina symptoms, but also long-term prognosis [1,2].

Objective: The aim of this study is to summarize the treatment of De Quervain's tenosynovitis, from a conservative point of view, by means of corticosteroid injection versus corticosteroid injection with immobilization of the thumb, establishing criteria for prognostic evaluation and a systematic review with meta-analysis.

Methodology: Systematic review with meta-analysis registered under the prolific ID CRD42024557767. The research questions were defined using the PICOS model in accordance with the PRISMA guidelines.

Results: 207 patients were included, of whom 103 underwent corticosteroid injection and 104 corticosteroid injection with immobilization. The studies analyzed in this systematic review showed better results in the Disabilities of Arm, Shoulder and Hand (DASH) assessment in the corticosteroid injection with immobilization group.

Conclusion: Even though corticosteroid injections alone are considered a promising choice of conservative treatment, current evidence points to a multimodal approach, employing various non-surgical modalities associated with better results, studies show that the combination of thumb immobilization with corticosteroid injection is a first-line treatment for patients with De Quervain's tenosynovitis.

This study evaluates the effectiveness of machine learning models in predicting the outcomes of laser therapy for periodontal diseases. Various algorithms, including Neural Networks, Gradient Boosting, Random Forest, and Support Vector Machine, were applied to a dataset containing clinical variables such as pocket depth and gingival inflammation. The Neural Network model achieved the highest predictive accuracy with an AUC-ROC score of 0.91, followed by Gradient Boosting at 0.90. These models outperformed traditional techniques, demonstrating that machine learning can accurately predict treatment success. The findings suggest that machine learning can aid clinicians in personalizing laser therapy, optimizing treatment, and improving patient outcomes. Further research with diverse datasets is recommended to refine these models.

This article provides a comprehensive overview of the clinical course, diagnosis, effective treatment methods, and prevention strategies for acute suppurative otitis media (ASOM). The discussion includes an analysis of the disease's progression and potential complications across different age groups, highlighting the importance of timely and appropriate management. Key treatment approaches, such as antibiotic therapy, pain management, and surgical interventions when necessary, are reviewed. Additionally, preventive measures, including vaccination and lifestyle modifications, are emphasized to reduce the incidence and severity of ASOM. This article aims to equip healthcare professionals with updated knowledge to improve patient outcomes and mitigate the risks associated with this common yet potentially serious condition.

Ionizing Radiation (IR) crucial to both therapeutic and diagnostic methods. However, it has hazardous exposure effects on patients and workers in radiation environment personnel. This study aimed to assess the level of knowledge among radiographers working in the private and public hospitals in Palestine about radiation safety and cancer risks of radiation exposure. Online questionnaires were distributed to 74 radiographers at seven private and public hospitals in Palestine. Four demographic characteristics and 17 several options questions about radiation protection were included in the survey. This study revealed that the mean of correct scores was (7.20) out of 17 enquiries from Palestinian radiographers on radiation safety. The current investigation revealed a inadequate knowledge of radiation protection and safety. (40.5%) of the radiographers admitted seldom received any training about radiation protection. While only (2.7%) of them reported that they regularly attended such training. and (27.0%) they never attended it. The knowledge score according to work experience, hospital type, and gender did not have statistical significance. In terms of academic level showed significant differences (P< 0.05), postgraduates’ level of knowledge score was (10.2±2.13), higher than undergraduates (6.88±1.51). The results show that the radiographers involved in this study lacked sufficient understanding on radiation protection and safety. Therefore, the most crucial topic is the administrations of the foundations using radiation have to exercise prudence by supplying staff or the essential infrastructure in the form of equipment and training.

Vaccination is a highly effective public health strategy for reducing child mortality from vaccine-preventable diseases (VPDs) such as measles, polio, tuberculosis, and Haemophilus influenzae. Despite the provision of free routine immunizations for children up to two years old in Nigeria, challenges in vaccine uptake persist, especially for vaccines needed beyond early childhood. These challenges are not merely due to vaccine access but are significantly influenced by maternal attitudes towards immunization. Socio-demographic factors such as ethnicity, education, and employment status are crucial in shaping these attitudes, yet their specific impacts are not well understood. This study aims to explore how these socio-demographic variables affect maternal attitudes towards childhood immunization, with a focus on immunization beyond the age of two in Ughelli North Local Government Area (LGA) of Delta State, Nigeria.

A cross-sectional study was conducted with 321 mothers in Ughelli North LGA, utilizing a modified, pre-tested questionnaire to evaluate maternal attitudes towards childhood immunization. Data were collected through an online survey and analysed using descriptive and inferential statistics, with Chi-square tests used to assess the relationships between socio-demographic factors and attitudes. The majority of participants were Urhobo (60.7%), semi-employed (53.6%), and had tertiary education (92.1%). The findings showed that 79.4% of mothers had positive attitudes towards childhood immunization. Significant associations were found between maternal attitudes and ethnicity (p = 0.026), employment status (p = 0.016), and educational level (p < 0.001), indicating that these factors are pivotal in shaping maternal views on the importance and necessity of immunization.

Unexpectedly, even mothers with high educational levels showed variability in their attitudes based on ethnic background and employment status, suggesting that public health interventions must consider the complex interplay of these factors. The study's results provide valuable insights into the socio-cultural and economic determinants of maternal attitudes towards immunization in Ughelli, underscoring the need for targeted health promotion strategies that address specific demographic groups. Efforts should focus on community-based interventions and media campaigns that highlight the importance of continuing vaccination beyond infancy. Additionally, enhancing access to immunization services and addressing barriers related to employment and ethnicity will be crucial for improving vaccine uptake in the region.

Lateral epicondylitis, popularly known as tennis elbow, has a high incidence in athletes, around 50%, with a high prevalence in beginners learning the one-handed backhand. It is a clinical orthopaedic condition with a major impact on public health due to its high frequency in manual workers, 10.5% of whom may have lateral elbow pain and 2.4% of whom have a confirmed diagnosis. The aim of this study is to compare the effectiveness of arthroscopic versus non-arthroscopic techniques (open and percutaneous). This is a systematic review with meta-analysis. There is no need for approval by the ethics committee or institutional scientific review board. The reference lists of the included and previously published articles were searched for more relevant studies that met the eligibility criteria. Based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Five articles were selected containing patients diagnosed with lateral epicondylitis who underwent surgical treatment by arthroscopy, open surgery and/or percutaneous surgery. A total of 544 patients were included, with a mean age of 46 years. Of these, 347 were treated by arthroscopy, 81 by open surgery and 42 by percutaneous surgery. The results were analyzed using the DASH (Disabilities of the arm, shoulder and hand) score, which assesses dysfunctions of the arm, shoulder and hand. In addition, some studies analyzed the VAS (Visual Analogue Scale) index, patient satisfaction, complications and other clinical assessment scales.Arthroscopic, open and percutaneous surgeries proved to be effective methods for treating lateral epicondylitis.However, because arthroscopy is a method that allows a complete intra-articular evaluation and adequate release of the tendons without ligament involvement, it was associated with a better prognosis in terms of pain, limb mobility and consequent patient satisfaction when compared to open and percutaneous procedures.

Objectives: to analyze surgical approaches for the treatment of idiopathic scoliosis and the prognosis achieved. Methodology: A systematic review with meta-analysis was carried out using the electronic databases PubMed/MEDLINE and Cochrane Library. Results: The sample consisted of 217 patients with a mean age of 15 years diagnosed with idiopathic scoliosis. In all the studies included, the pathological curvature was reduced by more than 49%. Conclusion: The pathological curvature was reduced in all surgical interventions, and the short- and long-term post-operative results were satisfactory.

This article presents the results of the study of the peculiarities of the course and diagnosis of rheumatoid arthritis (RA) in elderly people. In our work we studied 56 RA patients. Of these, 25 (44.6%) of the patients first fell ill in old age, 16 (28.5%) of patients became ill for more than 15 years and 15 (26.7%) of patients younger than 45 years made up a control group.

Skin cancer detection remains a critical challenge in dermatology, with early diagnosis significantly improving patient outcomes. This study presents a comparative analysis of machine learning models for automated skin cancer detection, highlighting the superior performance of Convolutional Neural Networks (CNNs). The CNN model achieved the highest accuracy (92.5%), sensitivity (91.8%), and specificity (93.1%) compared to other algorithms such as Support Vector Machines (SVMs) and Random Forests. The use of advanced preprocessing techniques and diverse datasets ensured the model's robustness and generalizability. While the findings demonstrate the potential of deep learning in dermatological diagnostics, limitations such as model interpretability and dataset diversity were identified. This research underscores the transformative role of AI in improving diagnostic accuracy, enabling early detection, and addressing healthcare disparities, particularly in resource-constrained settings. Future work aims to enhance model explainability and expand its applicability across diverse populations.