The influence of climate changes on heavy metals accumulation in Alosa immaculata from the Danube River Basin.

This research report provides a comprehensive overview of the historical trends in heavy metal concentrations in the Pontic shad (Alosa immaculata) populations from both the Danube River and the Black Sea, while also exploring the potential influence of global warming on metal accumulation. Through bibliometric modeling analysis, it reveals significant limitations in existing international research, particularly the lack of comprehensive data on the impact of hydroclimatic changes on heavy metal accumulation in Alosa immaculata. Recognizing the critical importance of studies on heavy metal bioaccumulation in Danube shad, this research underscores their significance in defining tolerance thresholds, quantifying the impact of toxic elements along the aquatic food chain, and enhancing the economic sustainability of ichthyofauna monitoring efforts. Furthermore, these studies contribute invaluable insights into the complex dynamics of aquatic ecosystems, offering essential decision-making support for optimizing commercial fishing management practices on the Danube and ensuring robust support systems for industrial fishing endeavors.

Human health risk assessment of potentially toxic elements and microplastics accumulation in products from the Danube River Basin fish market.

The present study aimed to quantify the concentration levels of potentially toxic elements (PTEs) such as aluminum, arsenic, cadmium, chromium, copper, nickel, lead, zinc, and mercury, as well as microplastics occurrence in various tissues of fish and seafood species, commercialized in the Lower Danube River Basin. A health risk assessment analysis was performed based on the PTEs concentration levels in the muscle tissue. Estimated daily intake (EDI), target hazard quotient (THQ), hazard index (HI), and target cancer risk (TR) of PTEs were calculated. It was observed that the species within the seafood category registered the highest levels of PTEs. For instance, in the muscle tissue of bivalve Mytilus galloprovincialis (from the Black Sea), the highest value was observed in the case of Zn (37.693 mg/kg), and the presence of polystyrene polymer was identified. The values associated with EDI, THQ, HI, and TR of PTE exposure were significantly lower than 1.

Effects of cooking methods and co-ingested foods on mercury bioaccessibility in pontic shad (Alosa immaculata).

Human mercury (Hg) exposure is mostly caused by eating fish. However, there are major differences between the measured and predicted mercury concentration on Hg bioavailability. This study investigated the effects of cooking (steaming, baking, frying, marinating, and smoking) and selected components' co-ingestion on Hg bioaccessibility. Baking and frying reduced Hg bioaccessibility compared to the raw sample. The bioaccessible Hg fraction in fish was assessed through in vitro digestion method. Hg bioaccessibility varied from 4.31 to nearly 24.95% and the Hg recovery rate varied from 63.44 to 78.74%. Co-ingested garlic and broccoli with pontic shad had a positive effect on decreasing fish Hg bioaccessibility. The antioxidant activity of co-ingested food items was also calculated and correlated with mercury bioaccessibility. These results highlighted a possible positive role of plant-based foods and other food processing techniques in the bioaccessibility reduction of other chemical contaminants found in food sources.

Effects of Single and Combined Ciprofloxacin and Lead Treatments on Zebrafish Behavior, Oxidative Stress, and Elements Content.

Even though the toxic effects of antibiotics and heavy metals have been extensively studied in the last decades, their combined adverse impact on aquatic organisms is poorly understood. Therefore, the objective of this study was to assess the acute effects of a ciprofloxacin (Cipro) and lead (Pb) mixture on the 3D swimming behavior, acetylcholinesterase (AChE) activity, lipid peroxidation level (MDA-malondialdehyde), activity of some oxidative stress markers (SOD-superoxide dismutase and GPx-glutathione peroxidase), and the essential elements content (Cu-copper, Zn-zinc, Fe-iron, Ca-calcium, Mg-magnesium, Na-sodium and K-potassium) in the body of zebrafish (Danio rerio). For this purpose, zebrafish were exposed to environmentally relevant concentrations of Cipro, Pb, and a mixture for 96 h. The results revealed that acute exposure to Pb alone and in mixture with Cipro impaired zebrafish exploratory behavior by decreasing swimming activity and elevating freezing duration. Moreover, significant deficiencies of Ca, K, Mg, and Na contents, as well as an excess of Zn level, were observed in fish tissues after exposure to the binary mixture. Likewise, the combined treatment with Pb and Cipro inhibited the activity of AChE and increased the GPx activity and MDA level. The mixture produced more damage in all studied endpoints, while Cipro had no significant effect. The findings highlight that the simultaneous presence of antibiotics and heavy metals in the environment can pose a threat to the health of living organisms.

An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production.

Here, we aim to improve the overall sustainability of aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. We implement new AI methods for operational management together with innovative solutions for plant growth bed, consisting of Rapana venosa shells (R), considered wastes in the food processing industry. To this end, the ARIMA-supervised learning method was used to develop solutions for forecasting the growth of both fish and plant biomass, while multi-linear regression (MLR), generalized additive models (GAM), and XGBoost were used for developing black-box virtual sensors for water quality. The efficiency of the new R substrate was evaluated and compared to the consecrated light expended clay aggregate-LECA aquaponics substrate (H). Considering two different technological scenarios (A-high feed input, B-low feed input, respectively), nutrient reduction rates, plant biomass growth performance and additionally plant quality are analysed. The resulting prediction models reveal a good accuracy, with the best metrics for predicting N-NO3 concentration in technological water. Furthermore, PCA analysis reveals a high correlation between water dissolved oxygen and pH. The use of innovative R growth substrate assured better basil growth performance. Indeed, this was in terms of both average fresh weight per basil plant, with 22.59% more at AR compared to AH, 16.45% more at BR compared to BH, respectively, as well as for average leaf area (LA) with 8.36% more at AR compared to AH, 9.49% more at BR compared to BH. However, the use of R substrate revealed a lower N-NH4 and N-NO3 reduction rate in technological water, compared to H-based variants (19.58% at AR and 18.95% at BR, compared to 20.75% at AH and 26.53% at BH for N-NH4; 2.02% at AR and 4.1% at BR, compared to 3.16% at AH and 5.24% at BH for N-NO3). The concentration of Ca, K, Mg and NO3 in the basil leaf area registered the following relationship between the experimental variants: AR > AH > BR > BH. In the root area however, the NO3 were higher in H variants with low feed input. The total phenolic and flavonoid contents in basil roots and aerial parts and the antioxidant activity of the methanolic extracts of experimental variants revealed that the highest total phenolic and flavonoid contents were found in the BH variant (0.348% and 0.169%, respectively in the roots, 0.512% and 0.019%, respectively in the aerial parts), while the methanolic extract obtained from the roots of the same variant showed the most potent antioxidant activity (89.15%). The results revealed that an analytical framework based on supervised learning can be successfully employed in various technological scenarios to optimize operational management in an aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. Also, the R substrate represents a suitable alternative for replacing conventional aquaponic grow beds. This is because it offers better plant growth performance and plant quality, together with a comparable nitrogen compound reduction rate. Future studies should investigate the long-term efficiency of innovative R aquaponic growth bed. Thus, focusing on the application of the developed prediction and forecasting models developed here, on a wider range of technological scenarios.

Vitamin C Mitigates Oxidative Stress and Behavioral Impairments Induced by Deltamethrin and Lead Toxicity in Zebrafish.

Environmental contamination from toxic metals and pesticides is an issue of great concern due to their harmful effects to human health and the ecosystems. In this framework, we assessed the adverse effects when aquatic organisms are exposed to toxicants such as deltamethrin (DM) and lead (Pb), alone or in combination, using zebrafish as a model. Moreover, we likewise evaluated the possible protective effect of vitamin C (VC) supplementation against the combined acute toxic effects of the two toxicants. Juvenile zebrafish were exposed to DM (2 µg L-1) and Pb (60 µg L-1) alone and in combination with VC (100 µg L-1) and responses were assessed by quantifying acetylcholinesterase (AChE) activity, lipid peroxidation (MDA), some antioxidant enzyme activities (SOD and GPx), three-dimension locomotion responses and changes of elements concentrations in the zebrafish body. Our results show that VC has mitigative effects against behavioral and biochemical alterations induced by a mixture of contaminants, demonstrating that it can be used as an effective antioxidant. Moreover, the observations in the study demonstrate zebrafish as a promising in vivo model for assessing the neuroprotective actions of bioactive compounds.

Preliminary investigation of lower Danube pollution caused by potentially toxic metals.

The current study aims to assess the pollution status of the European river-sea system lower Danube River-Danube Delta-North West Black Sea, through an integrated analysis of metal concentrations in water, sediments and fish community. The Danube flows through numerous industrial cities and receives a significant amount of pollutants due to the reception of urban and industrial emissaries, as well as agricultural land runoff. Samples of water, sediments and fish (10 species) were collected from 7 representative sites along Danube River, Danube Delta and Black Sea shore. For the analysed fish species, potentially toxic and essential elements (Pb, Cd, As, Cu, Fe, Zn, Mg, Ca, Na, K) from muscle and liver samples were measured and discussed. Measurement of elements and other environmental quality parameters were determined for water and sediments. The Black Sea area, represented by S6 and S7, received sediments from Danube with the lowest concentrations of Cd (0.05 ± 0.01 µg g-1, respectively 0.01 ± 0.001 µg g-1), Pb (3 ± 0.03 µg g-1, respectively 2 ± 0.03 µg g-1), As (2 ± 0.02 µg g-1, respectively 1.4 ± 0.3 µg g-1), Ni (8.9 ± 0.1 µg g-1, respectively 5.2 ± 0.2 µg g-1), Cr (8 ± 0.7 µg g-1, respectively 5 ± 0.2 µg g-1), Cu (3 ± 0.1 µg g-1, respectively 2 ± 0.04 µg g-1), Fe(6 ± 0.3 µg g-1, respectively 3 ± 0.1 µg g-1) and Zn (0.03 ± 0.003 µg g-1, respectively 0.017 ± 0.001 µg g-1). These results suggest that the Danube Delta system plays an important role in filtering the pollutants. Based on the biota and water analysis, there was no correlation observed between Cd, respectively Pb concentration in the environment and fish body (Person Coef. = -0.02 in muscle tissue and -0.01 in liver tissue, respectively Pearson Coeff. = -0.06 in muscle tissue and 0.1 in liver tissue). Cadmium remained an active element in the pollution of the Danube area (S1 and S2), with high concentration in the water matrix (0.14 ± 0.02 µg L-1, respectively 0.05 ± 0.01 µg L-1) and fish muscle (0.15 ± 0.03 µg g-1f.w. in C. carpio - S2). This fact was confirmed by several other studies.

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues.

Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (Psetta maxima maeotica), are accepted by the scientific communities as suitable bioindicators of heavy metal pollution in the aquatic environment. The present study uses a machine learning approach, which is based on multiple linear and non-linear models, in order to effectively estimate the concentrations of heavy metals in both turbot muscle and liver tissues. For multiple linear regression (MLR) models, the stepwise method was used, while non-linear models were developed by applying random forest (RF) algorithm. The models were based on data that were provided from scientific literature, attributed to 11 heavy metals (As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Ni, Zn) from both muscle and liver tissues of turbot exemplars. Significant MLR models were recorded for Ca, Fe, Mg, and Na in muscle tissue and K, Cu, Zn, and Na in turbot liver tissue. The non-linear tree-based RF prediction models (over 70% prediction accuracy) were identified for As, Cd, Cu, K, Mg, and Zn in muscle tissue and As, Ca, Cd, Mg, and Fe in turbot liver tissue. Both machine learning MLR and non-linear tree-based RF prediction models were identified to be suitable for predicting the heavy metal concentration from both turbot muscle and liver tissues. The models can be used for improving the knowledge and economic efficiency of linked heavy metals food safety and environment pollution studies.