The paper aims to introduce user-friendly modelling approaches to analyze how abiotic factors influence various trophic levels within the marine ecosystem, both naturally and through human impact. It specifically investigates the connections between environmental parameters (like temperature, salinity, and nutrients) and plankton along the Romanian Black Sea coast during the warm season (May-September) over a decade. Utilizing machine learning (ML) algorithms and data collected during this period, models were developed to project the proliferation of zooplankton. During the warm season, water temperature emerged as a significant factor affecting copepods and “other groups” zooplankton densities, while no discernible impact was noted on Noctiluca scintillans blooms. Salinity fluctuations notably influenced typical phytoplankton proliferation, with phosphate concentrations primarily driving widespread blooms. Two scenarios were explored for forecasting zooplankton growth: Business as Usual, predicting modest increases in temperature, salinity, and constant nutrient levels, and the Mild scenario, anticipating more substantial temperature and salinity increases while nutrients decrease significantly by 2042. The findings highlight that under both scenarios, Noctiluca scintillans displays notably high densities, with the second scenario projecting even higher values, surpassing the first by around 70%. These densities indicate characteristics of a eutrophic ecosystem, suggesting the potential implications of altered abiotic factors on ecosystem health.

The oral cavity is environment to a diverse range of organisms that make up an essential element of the human microbiota. There are 50-1000 kinds of microorganisms capable of colonizing the mouth. The entamoeba parasites have at minimum 7 species (E. histolytica, E. dispar, E. moshkovskii, E. coli, E. polecki E. hartmann, E. gingivalis). These parasites are parasitic single-celled organisms and Entamoeba gingivalis was the first amoeba to be described in 1849 that was capable of existing in humans. It was shown that only Entamoeba gingivalis is able to colonize the oral cavity. The aim of this study was to evaluate prevalence of E. Gingivalis in periodontal disease using two electronic database search engines. In order to have a broader view of the subject, a comprehensive manual search was conducted on these content aggregators and the initial search resulted in 277 articles using the keywords „Entamoeba gingivalis”, „periodontitis”, „E. gingivalis”, „periodontal disease”, „prevalence”, and „incidence”, in different combinations. The results showed that 755 cases were infected with Entamoeba gingivalis out of a total number of 1,729 patients diagnosed with periodontal disease indicating a global prevalence of 43%. When comparing different stages of periodontal diseases results revealed that the prevalence in patients with gingivitis was 58% while in periodontitis group the prevalence was 44%. Overall prevalence of Entamoeba Gingivalis based on gender was 43 % in female patients whilst in male patients was 47%. Based on the results it can be concluded that the higher incidence of Entamoeba Gingivalis in people with periodontal disease compared to healthy people is more than just a sign of the disease; it may also be linked to the severity of the condition and its propensity to progress.