Purpose: To study and compare the immune response and neopterin levels in the blood in experimental autoimmune uveitis (EAU).

Methods: A model of EAU was created in 30 Chinchilla rabbits. Intravenous and intravitreal injections of normal horse serum were administered for this purpose. Clinical examinations and blood tests were conducted on days 3, 7, 10, 14, and 21. The blood investigation included the determination of neopterin (NP) level, white blood cell counts, lymphocytes, CD3+ , CD4+ , CD8+ , and CD16+ .

Results: The peak in white blood cell count was observed on days 7 and 10 (6.4 ± 0.4 g/L and 6.0 ± 0.3 g/L, respectively), lymphocytes on day 3 (68.3% ± 2.4%, 3.0 ± 0.2 g/L), CD3 + on day 7 (64.9% ± 3.1%, 2,032.5 ± 91.2 cells/µL), CD4 + and CD16 + on day 10 (54.6% ± 3.8%, 2,462.3 ± 60.7 cells/µL and 21.8% ± 1.8%, 691.2 ± 37.1 cells/µL, respectively). All these values did not return to the initial ones. There was a gradual decrease in the CD8 + count from day 3 (12.5% ± 1.1%, 142.8 ± 9.1 cells/µL) with a subsequent gradual return towards normal levels by day 21. NP levels incresed on day 3 (5.2 ± 0.7 nmol/L), sustained on day 7 (5.2 ± 0.8 nmol/L), and started to decrease from day 10 (4.25 ± 1.7 nmol/L) to 2.3 ± 0.5 nmol/L on day 21. The highest correlation was observed between clinical manifestations and NP with a correlation coeffient of 0.799 (95% confidence interval, 0.719–0.858), which was significantly stronger (p < 0.05) than the correlations with other immune response markers. Conclusions: During the modeling of EAU, there is an active immune response and a rapid reaction of NP on inflammation. NP is a significantly more sensitive marker of intraocular inflammation than the immune response. It can serve as a predictor of the onset and development of EAU.

Key Words: Animal, Blood, Immunity, Neopterin, Uveitis

Aim: To investigate the dynamics of the T-cell immune response in rabbits with experimental autoimmune uveitis (EAU) of varying severity. Materials and Methods: The experiment involved two groups of Chinchilla rabbits (15 rabbits in each group). The model of EAU was created. The clinical picture of intraocular inflammation of varying severity was assessed. The determination of the level of white blood cells (WBC), lymphocytes (Lymphs), CD3+, CD4+, CD8+, and CD16+ in the blood of rabbits was conducted.

Results: Group I – moderate and severe uveitis, Group II – uveitis of mild severity. WBC, Lymphs, CD3+, CD4+, CD16+ were elevated and statistically significant in both groups of animals compared to control parameters on all days of the experiment (3, 7, 10, 14, 21 days) (p < 0.001). CD8+ level had a significantly lower count than the control one (p < 0.001). When comparing the two groups, the immune response was more active in Group I, and the number of immune cells did not return to normal by the end of the experiment.

Conclusion: In the case of EAU, the immune response is characterized by the activation of the T-cell immune system, with the intensity of this response depending on the severity of the clinical presentation of uveitis. Various degrees of clinical severity in EAU were obtained using an experimental model employed in our study. A rapid response of the immune system helps to establish a diagnosis and predict the severity of autoimmune uveitis.

Key words: T-cells response, experiment, autoimmune uveitis

UDC 616.65-006.6-089-07:616.633-07

At present, the identification of high-risk groups of localized prostate cancer (PCa) is highly relevant. Our previous research demonstrated that prostate cancer antigen 3 (PCA3) scores depend on the tumor zone of origin (TZO) and the tumor growth dominant pattern (TGDP).
The aim: to assess the prognostic value of PCA3 score for identifying postoperative 4–5 grade group according to the International Society of Urological Pathology 2014 (ISUP) classification in patients with localized peripheral zone prostate cancer with posterior TGDP (pPZ-PCa).
Materials and methods. PCA3 scores and correlations were assessed and compared in different PCa patient groups and subgroups based on TZO, TGDP, and ISUP grade. Receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic significance of the model and determine the optimal PCA3 score cutoff for identifying ISUP 4–5.
Results. The PCA3 scores showed a significant (p<0.01) positive correlation (r=0.71) with ISUP grade in pPZPCa. PCA3 scores differed significantly (p<0.01) between ISUP 1–3 and 4–5 pPZ-PCa subgroups. ROC analysis demonstrated excellent performance with an AUC of 0.98 (95% CI: 0.95–0.99) for identifying ISUP 4–5 pPZ-PCa.
Conclusions. PCA3 scores demonstrated prognostic value for identifying postoperative ISUP 4–5 in pPZ-PCa.

Urinary bladder cancer (UBC) is a prevalent malignancy worldwide, exhibiting high recurrence rates and significant morbidity and mortality. Traditional diagnostic and prognostic methods often fall short in providing the precision required for effective patient stratification and personalized treatment. Genomic and transcriptomic studies have revolutionized our understanding of UBC by unveiling molecular alterations that drive tumor initiation, progression, and therapeutic response. This systematic review explores the role and application of genomic and transcriptomic analyses in the diagnostics and survival prediction of non-invasive and invasive UBC. We conducted a comprehensive literature search in MEDLINE, Web of Science, and Scopus up to October 2023, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our search yielded 1,256 records (412 in MEDLINE, 378 in Web of Science, and 466 in Scopus), and 356 duplicates were removed. Our findings highlight key mechanisms of action, including mutations in FGFR3, TP53, and RB1 genes, and alterations in pathways such as PI3K/AKT/mTOR and MAPK/ERK, which are pivotal in UBC pathogenesis. Recent research advances, including liquid biopsies and single-cell sequencing, offer promising non-invasive diagnostic tools and deeper insights into tumor heterogeneity. This review underscores the critical importance of integrating genomic and transcriptomic data into clinical practice to improve diagnostics, prognostic assessments, and personalized treatment strategies for UBC patients. Future research should focus on integrating multi-omics data and validating molecular biomarkers in large clinical trials to further enhance patient outcomes.

Background: Prostate cancer is a leading cause of cancer-related morbidity and mortality among men worldwide. Fusion biopsy, combining magnetic resonance imaging (MRI) with transrectal ultrasound (TRUS) guidance, has enhanced the detection of clinically significant prostate cancer. However, challenges such as inter-operator variability and accurate lesion targeting persist. Artificial intelligence (AI) and machine learning (ML) offer potential improvements in diagnostic accuracy and efficiency. Objective: To systematically review the role and perspectives of AI and ML in improving the efficiency of fusion biopsy in men with prostate cancer. Materials and Methods: Following PRISMA guidelines, a comprehensive literature search was conducted in MEDLINE, Web of Science, and Scopus up to October 2023. Studies assessing the application of AI and ML in fusion biopsy for prostate cancer were included. Results: A total of 1,236 records were identified (MEDLINE: 432; Web of Science: 398; Scopus: 406), with 312 duplicates removed. Titles and abstracts of 924 articles were screened, and 68 qualified for full-text eligibility assessment. Twenty-seven articles met the inclusion criteria and were qualitatively synthesized. Conclusion: AI and ML hold promise in improving the efficiency and accuracy of fusion biopsies in prostate cancer. Large-scale, prospective studies and standardized protocols are necessary to validate these technologies and facilitate their integration into clinical practice.