Vol. 8 No. 06 (2026): Volume 08 Issue 06

The growing complexity of healthcare systems, rapid technological advancement, and increasing demand for patient-centered care have intensified the need for evidence-generation models capable of supporting timely and effective decision-making. Traditional clinical research methods, particularly randomized controlled trials, remain essential for evaluating therapeutic efficacy; however, their limitations in representing diverse patient populations and real-world clinical settings have prompted greater interest in Real-World Evidence (RWE). RWE, generated from routine healthcare data, provides valuable insights into treatment effectiveness, healthcare delivery, and patient outcomes across diverse populations. This research and review article examines the development of a robust RWE framework designed to accelerate healthcare innovation and improve clinical outcomes. Drawing exclusively upon contemporary literature concerning coordinated registry networks, learning health systems, evaluation theory, and translational science, the study synthesizes key conceptual foundations, infrastructure requirements, governance mechanisms, and implementation strategies necessary for effective RWE generation and utilization. The analysis identifies interoperability, stakeholder collaboration, data quality assurance, and translational action mechanisms as critical determinants of framework success. Findings suggest that integrated RWE ecosystems can facilitate continuous learning, support regulatory decision-making, optimize healthcare delivery, and strengthen innovation pathways. The article proposes a comprehensive methodological framework that aligns technological infrastructure, organizational coordination, and outcome-oriented evaluation principles. The study contributes to the evolving discourse on evidence-based healthcare transformation by offering a structured approach for operationalizing RWE systems capable of producing measurable clinical and organizational benefits.

This article discusses the neurophysiological development of the brain in infants who received different types of feeding (breast milk and infant formula). The psychosomatic status, in the form of sleep-wake rhythms, was assessed using electroencephalography, and the average duration of sleep during the day, as well as the progress of both nighttime and daytime sleep according to the norms of age groups, and the number of daytime and nighttime awakenings, was evaluated. The following differences were found between the groups: in groups 1 and 3, the average duration of a sleep episode was 3-4 hours. Whereas infants and group 2 had an average daytime sleep episode duration of 1.5-2 h. The results obtained were significant (p≤0.05).

The study evaluated the association between genetic polymorphisms of the natriuretic peptide system and long-term outcomes after coronary artery stenting. A total of 112 patients with coronary artery disease who underwent drug-eluting stent implantation were examined. Genetic testing included NPPA rs5065, NPPB rs198389, and NPR3 rs2270915 polymorphisms. The follow-up period was 24 months. Major adverse cardiovascular events were observed in 28 patients, recurrent angina in 31 patients, in-stent restenosis in 17 patients, and repeat revascularization in 14 patients. NPPA rs5065 C allele carriage was associated with a higher risk of adverse cardiovascular events, while NPR3 rs2270915 G allele carriage was associated with in-stent restenosis. NPPB rs198389 C allele carriage was associated with increased NT-proBNP levels.The results indicate that polymorphisms of the natriuretic peptide system may be useful markers for risk stratification and personalized follow-up after coronary artery stenting.

Kidney transplantation is widely recognized as the most effective treatment for patients with end-stage renal disease, providing improved survival and quality of life compared to long-term dialysis. Nevertheless, immunologically high-risk recipients remain vulnerable to adverse transplant outcomes due to preexisting sensitization and the presence of donor-specific antibodies. High sensitization is commonly associated with previous blood transfusions, pregnancies, or prior transplantations and is considered a major risk factor for antibody-mediated rejection. The present study aimed to investigate the impact of high sensitization on donor kidney morphology in immunologically high-risk patients undergoing kidney transplantation. Histopathological characteristics of donor kidneys were evaluated and correlated with the immunological status of recipients. Particular attention was given to glomerular, vascular, and tubulointerstitial alterations that may influence graft function and survival. The findings demonstrated that highly sensitized recipients were more likely to receive donor kidneys exhibiting significant morphological changes, including vascular thickening, interstitial fibrosis, tubular injury, and glomerular abnormalities. These structural alterations were associated with an increased incidence of delayed graft function and early post-transplant complications. Furthermore, a strong relationship was observed between elevated sensitization levels and the severity of histological abnormalities, suggesting that immunological factors may contribute to both pre-transplant and post-transplant graft injury. The study highlights the importance of comprehensive immunological assessment and detailed morphological evaluation of donor kidneys before transplantation. Understanding the interaction between recipient sensitization and donor kidney morphology may improve risk stratification, optimize donor-recipient matching, and contribute to the development of individualized therapeutic strategies aimed at enhancing graft survival and long-term transplant success in immunologically high-risk patient populations.

The long-term success of dental implant therapy depends heavily on the establishment and maintenance of a healthy peri-implant soft tissue barrier, which serves as a biological seal protecting the underlying crestal bone from microbiological and mechanical insults. This randomized controlled clinical trial combined with a three-dimensional finite element analysis (FEA) investigated the biological, microbiological, and biomechanical responses of peri-implant mucosa to three distinct implant abutment materials: commercially pure titanium, zirconium oxide (zirconia), and cobalt-chromium (Co-Cr) alloys. Following CONSORT guidelines, a total of ninety patients requiring single-tooth implant restorations were randomly allocated to receive either customized titanium, zirconia, or Co-Cr abutments. Over a twelve-month follow-up period, peri-implant soft tissue responses were quantified using microcirculation monitoring, sulcular fluid volume analysis, and biochemical profiles of pro-inflammatory cytokines and bone metabolism mediators. Microbiome evaluations were conducted using high-throughput sequencing and colony-forming unit quantification to track early bacterial adhesion and mature biofilm colonization. Concurrently, three-dimensional FEA models were generated to map the stress distribution and marginal discrepancy patterns within the implant-abutment interface and the surrounding periodontal and bone support systems under simulated functional loads. The clinical results demonstrated that zirconia abutments exhibited significantly lower initial bacterial adhesion and a more favorable pro-inflammatory cytokine profile compared to Co-Cr and titanium surfaces. Microcirculation monitoring revealed that zirconia achieved superior soft tissue vascularization and blood flow regulation, closely mimicking the values observed around natural teeth. The microbiological data confirmed that zirconia surfaces altered the biofilm composition, reducing the concentration of periodontopathogenic strains. However, the FEA models and mechanical loading simulations indicated that while zirconia possessed adequate load capacity, titanium and Co-Cr alloys provided superior structural stability, exhibiting reduced stress concentrations at the abutment screw joint and lower marginal discrepancies under complex loading angles. Co-Cr alloys demonstrated acceptable mechanical properties but induced higher early inflammatory markers and increased bacterial colonization compared to zirconia. This comprehensive synthesis illustrates the intricate trade-offs between biological mucointegration and mechanical integrity across different biomaterials, establishing an empirical framework for material selection in contemporary implant dentistry.

The study included 126 patients with comorbid conditions and risk factors for chronic kidney disease. The mean age of the patients was 59.3 ± 8.7 years. Arterial hypertension was observed in 96 patients, diabetes mellitus in 62 patients, cardiovascular diseases in 54 patients, and obesity in 47 patients. A decrease in estimated glomerular filtration rate below 60 ml/min/1.73 m² was detected in 39 patients, while albuminuria was found in 58 patients. A high and very high risk of chronic kidney disease progression was identified in 51 patients.The proposed prevention algorithm included regular monitoring of eGFR, albuminuria, blood pressure, glycemic status, lipid profile, body mass index, lifestyle correction, and elimination of nephrotoxic risk factors. The results indicate that patients with arterial hypertension, diabetes mellitus, obesity, and cardiovascular diseases require systematic screening and multidisciplinary follow-up. The use of an integrated risk assessment algorithm may contribute to early detection of renal dysfunction and prevention of chronic kidney disease progression in patients with comorbid pathology.

The ability to diagnose skin disease by using dermatoscopic images is growing due to advancements in AI. despite those developments, the biggest challenges are still related to class imbalance (skin cancer is rare), variable characteristics among lesions, and lack of diversity in available datasets when it comes to people's ethnicities. all of which limit how reliable the models are and limits the amount they can generalize to other populations. therefore, this research developed a hybrid classification system. this system combined a deep learning-based feature extraction method called mobilenetv2 with random forest. this allows for the derivation of highly informative features from the skin lesion images through transfer learning. the ensemble nature of the random forest also increases the classification stability and prevents overfitting.  In addition to the development of the hybrid classification framework; this project also implemented several preprocessing methods. the two most important preprocessing methods include normalizing the data and implementing class balance methods. the purpose was to make sure that the best possible training data existed and ultimately increase the effectiveness of the suggested framework. experimental evaluation on the ham-10k dataset showed that the proposed Mobile-Netv2-random forest model had an average classification accuracy of approximately 97.86%. additionally, precision, recall, and f1 score values were extremely consistent. all three values demonstrate that the proposed hybrid classification framework offers a relatively simple yet effective solution. the simplicity of the proposed solution would be able to compete with some of the more complex hybrid solutions. finally, the results indicate that utilizing lightweight DLmodels with ensemble MLmethods could provide significant improvements in skin lesion classifications.

This article investigates the dynamics of attention in first- and second-year university students throughout the academic year. The study was conducted at Qarshi State University and involved a total of 125 students — 27 male and 98 female — divided into first-year (n=63) and second-year (n=62) groups. Attention was assessed using the Schulte-Gorbov table method on the NS-Psychotest apparatus (ООО Neurosoft), which measures the speed and flexibility of attentional switching; results were recorded in seconds, with shorter completion times indicating higher attentional efficiency.

Measurements were carried out at four stages: at the beginning of the academic year (September), before examinations (January), after examinations (February), and at the end of the academic year (May). This longitudinal design allowed the researchers to track the wave-like pattern of attentional changes across the full academic cycle. All tests were administered during morning hours under standardized conditions.

In first-year male students, the baseline task completion time was 55±2.4 seconds, while in female students it was 48±3.4 seconds, indicating higher attentional efficiency in females at the outset. Before the examination session (January), task completion time increased significantly in both groups — to 62±1.8 s in males and 56.3±2.3 s in females — and these changes were statistically significant (P<0.05). After examinations (February), partial recovery was observed in both groups; however, indicators did not return to baseline levels. By the end of the academic year (May), attention efficiency deteriorated again to 62.8±2.2 s in males and 58±1.2 s in females (P<0.05).

A similar pattern was observed in second-year students. Baseline values were slightly higher (i.e., completion times were longer) than in first-year students, suggesting a degree of residual cognitive strain already present at the start of the academic year. The most pronounced change was recorded in second-year female students, whose completion time increased from 50.3±2 s to 63±4 s before examinations (P<0.05). Recovery after examinations was partial, and by May, values remained significantly higher than baseline in all groups (P<0.05 in males; P<0.01 in females).

The results demonstrate that academic workload and examination stress have a measurable and consistent negative impact on attentional performance in university students. The incomplete recovery of attentional indicators between assessment points reflects the cumulative effect of academic stress across the academic year.