Eubiotic Effect of a Dietary Bio-Aqua® and Sodium Diformate (NaDF) on Salmo trutta caspius: Innate Immune System, Biochemical Indices, Antioxidant Defense, and Expression of Immunological and Growth-Related Genes.

The present study investigated the effects of combined and singular oral administration of Bio-Aqua® with different dosages of sodium diformate (NaDF) on biochemical indices, innate immune responses, antioxidant effects, and expressions of immunological related genes of Caspian brown trout (Salmo trutta caspius). Fingerlings Salmo trutta caspius (n = 1800; initial weight 15 ± 3 g) were randomly allocated into five groups (120 fish group-1 in triplicates). Control diet: without any addition, G1, G2, G3, and G4 received diets containing 0.2 g kg-1 commercial probiotic Bio-Aqua® combined with 0, 0.5, 1.0, and 1.5% NaDF to the basal diet for 60 days according to recommended dosages reported in previous studies. Results indicated that serum bactericidal activity (G3 on day 60 and G1 on day 30) and classic complement in all groups (on day 60) (G1 and G2 on day 30) were significantly elevated (P < 0.05). The serum lysozyme, glucose, globulin, and albumin levels showed no significant differences between all groups compared to the control group (P > 0.05). On days 30 and 60 of the sampling, no significant difference was observed in the amount of superoxide disotase (SOD) and catalase (CAT) between the treatments (P > 0.05) but activity of malondialdehyde (MDA) was lower in G1 than the control (P < 0.05). The expression of the immune-regulating genes IL-10, IL-1ß, GTP, FATP, and IGF was significantly improved in all probiotic + acidifier-treated groups (P < 0.05). The current findings showed that mixture of Bio-Aqua® and NaDF (1.5% + pro) is beneficial, as it effectively improves some immune parameters and expression of immunological and growth-related genes in Caspian brown trout.

Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics.

This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works.