Lamprini Tzioga

Skeletal deformities remain a major challenge in marine fish hatcheries, affecting larval quality, animal welfare, production efficiency, and market value. In European seabass (Dicentrarchus labrax), saddleback syndrome (SBS) is a relevant skeletal abnormality that develops during larval ontogeny and has been associated with defects of the primordial marginal finfold around the flexion stage. This study investigated whether gene expression markers, combined with machine learning, could provide a stage-specific molecular approach for assessing SBS-associated larval batch quality. Larval populations from commercial hatcheries were classified as GOOD or POOR according to SBS incidence at mid-metamorphosis. Gene expression was analyzed at first feeding, flexion, post-flexion, and mid-metamorphosis, targeting genes involved in osteogenesis, myogenesis, metabolism, oxidative phosphorylation, and stress response. Stage-specific random forest models were used to classify gene expression profiles derived from larval populations with contrasting SBS incidence and to identify candidate informative genes. The models showed cross-validated area under the receiver operating characteristic curve (ROC AUC) values ranging from 0.83 to 0.962, with the highest performance at flexion. Reduced models based on the three most informative genes retained comparable internal cross-validation performance. Key candidate genes were mainly related to mitochondrial energy production, iron metabolism, stress response, muscle development, and extracellular matrix formation. These findings suggest that gene expression profiling combined with machine learning may support stage-aware discrimination of larval populations with contrasting SBS incidence, although validation in larger independent datasets is required before hatchery application.

Background/Objectives: Persistent infection with high-risk (HR) HPV genotypes is the main risk factor for the development of cervical cancer. The present analysis provides recent trends on HR-HPV infection rates and the distribution of HR-HPV genotypes among 3500 Greek women between 2021 and 2023. Methods: The detection of HR-HPVs and the specific identification of HPV16 and HPV18 were conducted using the Roche Cobas 4800 HPV assay. The genotyping of 12 other HR-HPV genotypes was performed through the Nested Multiplex PCR methodology (NMPCR). Results: The overall infection rate was 8.8% with the most prevalent HR-HPV genotype being HPV16 followed by HPV31, HPV66, HPV56, HPV51, HPV58, HPV45, HPV18, HPV68, HPV59, HPV52, HPV35, HPV39, and HPV33. Among HR-HPV-positive cases the prevalence of single, double, triple, and quadruple infections was 73.9%, 19.9%, 5.5%, and 0.7%, respectively. Age-specific analysis showed that the HR-HPV infection rate was higher in the age group of 31–35 years (25.5%) and it was estimated that multiple infections occur more often in younger women. Notably, the distribution of HR-HPV genotypes varies among different age groups. It is proposed that HPV16, HPV31, HPV56, and HPV66 may show an increased possibility of establishing long-term infections in Greek women over 36 years old. Conclusions: The high rates of specific HR-HPVs which are not included in the prophylactic vaccines underlines the significance of constant surveillance of circulating HPVs in the Greek population.

The causal relationship between HPV and cervical cancer in association with the high prevalence of high risk HPV genotypes led to the design of HPV vaccines based on the major capsid L1 protein. In recent years, capsid protein L2 has also become a focal point in the field of vaccine research. The present review focuses on the variability of HPV16 L1 and L2 genes, emphasizing the distribution of specific amino acid changes in the epitopes of capsid proteins. Moreover, a substantial bioinformatics analysis was conducted to describe the worldwide distribution of amino acid substitutions throughout HPV16 L1, L2 proteins. Five amino acid changes (T176N, N181T; EF loop), (T266A; FG loop), (T353P, T389S; HI loop) are frequently observed in the L1 hypervariable surface loops, while two amino acid substitutions (D43E, S122P) are adjacent to L2 specific epitopes. These changes have a high prevalence in certain geographic regions. The present review suggests that the extensive analysis of the amino acid substitutions in the HPV16 L1 immunodominant loops may provide insights concerning the ability of the virus in evading host immune response in certain populations. The genetic variability of the HPV16 L1 and L2 epitopes should be extensively analyzed in a given population.

Angiopoietin-2 (Ang-2) has been implicated in the development of several types of cancer, including lung malignancy. In the present study, we examined the impact of Ang-2 serum concentration on the development, dissemination, and 5-year overall survival of NSCLC and SCLC. A total of 99 patients with lung cancer were tested. The OS of NSCLC and SCLC patients was estimated using Kaplan–Meier curves and compared through log-rank test. The median serum level of Ang-2 at baseline in both NSCLC and SCLC patients was significantly higher than that of controls (p < 0.0001). The Ang-2 serum concentration was not related to metastasis, neither in NSCLC nor in SCLC cases. The OS was found to be significantly shorter for stage IIIβ NSCLC patients with a high baseline Ang-2 serum concentration (p = 0.012), while Cox regression analysis showed that Ang-2 is a significant independent factor for poor prognosis for stage IIIβ NSCLC (hazard ratio = 2.97, 95% CI: 1.05–8.40, p = 0.04). The concentration of Ang-2 has no impact on the prognosis of SCLC. Ang-2 could be considered as a significant molecular marker that enables the prediction of NSCLC and SCLC development, and is involved in the poor prognosis of stage IIIβ NSCLC.