Distribution and Bioaccumulation of Essential and Toxic Metals in Tissues of Thaila (Catla catla) from a Natural Lake, Pakistan and Its Possible Health Impact on Consumers

Trace Elements in Stenella coeruleoalba: Assessment of Marine Environmental Pollution and Dolphin Health Status

Heavy metals are environmental contaminants and can easily accumulate and biomagnify in various marine species (fishes and mammalians) at the top of the aquatic food chain. Among marine mammalians, the striped dolphin (Stenella coeruleoalba) is the most abundant cetacean in the Mediterranean Sea and is considered to be a sentinel species to monitor the environmental marine pollution. In this study, the contents of toxic metals and metalloids (Cd, Pb, Hg, and As), micro-elements (Ni, Cr, Cu, Fe, Co, Mn, Se and Zn) and macro-elements (Na, Ca, K, Mg and P) were evaluated by ICP-MS analysis in several organs/tissues (lung, skin, muscle and liver) of Stenella coeruleoalba. The assessment of marine environmental pollution and dolphins health status was carried out through further analysis of the same specific parameters such as the metal pollution index (MPI) and coefficient of condition (K). Finally, the correlation between toxic metals and metalloids and essential micro-elements, expressed as molar ratios, was analyzed to evaluate the detoxifying ability (effectiveness) of Zn, Se and Cu. Data obtained showed the presence of toxic metals and metalloids analyzed in the Stenella coeruleoalba samples but the MPI values suggested a low environmental contamination of the Mediterranean Sea where dolphins lived. The content of micro- and macro-elements was found to be in a normal range for this species and predictive of dolphins good health status, as confirmed by the coefficient of condition K. However, the correlation between toxic and essential metals, expressed as molar ratios, showed that the following toxic metals cannot be detoxified by the essential metals: 66Zn/201Hg, 82Se/201Hg, 63Cu/201Hg and 66Zn/52Cr, 82Se/52Cr, 63Cu/52Cr. Therefore, this study highlights the key role of dolphin Stenella coeruleoalba to assess marine pollution and the importance of analyzing the complete mineral profile to evaluate the animal health status.

Black cardamom (Amomum subulatum) extract improves growth potential, antioxidant status, immune parameters and response to crowding stress in Catla catla

Natural herbs are excellent alternatives to synthetic compounds to enhance the growth performance and health status of fish. This study was conducted to evaluate the efficacy of black cardamom (Amomum subulatum) extract (BCE) as an herbal supplement in improving the growth, antioxidant status, haematology, and serum biochemistry of Catla catla. The acclimatized fish (N = 900; average initial weight = 14.44 ± 0.33 g) were allocated into five groups (60 fish/group in triplicate) in hapas (4 × 2 × 2.5 ft) and provided with feed containing 0 (control), 0.5, 1, 2 and 4 g/kg BCE for 90 days before being subjected to 8 days of crowding stress. After 90 days, significantly higher feed utilization and growth were observed in all BCE-fed treatments compared to the control; however, the maximum values of these parameters were noted in the 2 g/kg BCE-fed treatment. Moreover, the BCE-fed groups exhibited a significant increase in antioxidant indices (glutathione peroxidase, superoxide dismutase and catalase), with a significant reduction in malondialdehyde levels, indicating a higher antioxidant capacity compared to the control. Significant improvements in haematological parameters, such as an increase in haematocrit, haemoglobin and red blood cells and a decrease in white blood cells, were observed in BCE-fed treatments compared to the control. Furthermore, BCE-fed groups showed a significant decrease in serum glucose, cortisol and triglycerides, while total protein, globulin and albumin levels were significantly higher compared with the control. During the feeding trial of 90 days, no mortality was observed; however, the lowest cumulative mortality was noted in the 2 g/kg BCE group after crowding stress of 8 days. In conclusion, the use of BCE in feed can enhance the growth performance, antioxidant status, haematology, and serum biochemistry of C. catla and improve the resistance against crowding stress. The optimum levels of BCE for C. catla were estimated based on weight gain % (1.78 g/kg; R2  = 0.97), feed conversion ratio (1.65 g/kg; R2  = 0.98), MDA content (1.66 g/kg; R2  = 0.93) and serum lysozyme activity (1.72 g/kg; R2  = 1) using broken-line regression analysis.

Intelligent soft computational models integrated for the prediction of potentially toxic elements and groundwater quality indicators: a case study

Reports have shown that potentially toxic elements (PTEs) in air, water, and soil systems expose humans to carcinogenic and non-carcinogenic health risks. In southeastern Nigeria, works that have used data-driven algorithms in predicting PTEs in groundwater are scarce. In addition, only a few works have simulated water quality indices using machine learning modelling methods in the region. Therefore, in this study, physicochemical analyses were carried out on groundwater samples in southeastern Nigeria. The laboratory results were used to compute two water quality indices: pollution index of groundwater (PIG) and the water pollution index (WPI), to ascertain groundwater quality. In addition, the physicochemical parameters served as input variables for multiple linear regression (MLR) and artificial neural network (ANN) modelling and prediction of Cr, Fe, Ni, NO3−, Pb, Zn, WPI, and PIG. The results of WPI and PIG computation showed that about 30–35% of the groundwater samples were unsuitable for human consumption, whereas 65–70% of the samples were deemed suitable. The insights from the PIG and WPI model also revealed that lead (Pb) was the most influential PTE that degraded the quality of groundwater resources in the research area. The findings of the MLR and ANN models indicated strong positive prediction accuracies (R 2 = 0.856–1.000) with low modeling errors. The predictive MLR and ANN models of the PIG and WPI generally outperformed those of the PTEs. The models produced in this study predicted the PTEs better compared to previous studies. Thus, this work provides insights into effective water sustainability, management, and protection.

Investigations of the Polycyclic Aromatic Hydrocarbon and Elemental Profile of Smoked Fish

Fish are vulnerable to environmental pollutants such as polycyclic aromatic hydrocarbon and heavy metals. As one of the most commonly applied processing methods, the smoking of different species has been applied globally. Hence, this study aims to investigate the smoking process on the polycyclic aromatic hydrocarbon and elemental accumulation of the five different species (rainbow trout, Atlantic bonito, horse mackerel, sea bass, and Atlantic bluefin tuna) which are commonly processed and traded in the smoked fish industry. The processing yield, water holding capacity, and pH were also investigated. The results revealed that the proximal differences among fish species influence the water holding capacity, processing yield, and pH which are very important for process sustainability and the quality of the end product. The main finding was the proximal composition impact on the accumulation of both PAHs and heavy metals at different levels. While all of the tested samples were below the maximum permissible limit, some of the heavy metals, especially toxic elements, were found above the acceptable limit. Horse mackerel is determined to be the species most vulnerable to PAHs and heavy metal accumulation.