A Deep Survey of Fish Health for the Recognition of Useful Biomarkers to Monitor Water Pollution
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sampling Sites
2.2. Animals and Biological Indices
2.3. Histopathological Analysis
2.4. Immunohistochemical Analysis
2.5. Blood Smear and Staining
2.6. Statistical Analyses
3. Results
3.1. Chemical Pollution in the Tusciano and Picentino Rivers
3.2. Biological Indices
3.3. Liver Histopathology
3.4. Liver Immunohistochemistry
3.4.1. Inflammatory Biomarkers
3.4.2. Antioxidant Biomarkers
3.5. Spleen Histopathology
3.6. Spleen Immunohistochemistry
3.6.1. Inflammatory Biomarkers
3.6.2. Antioxidant Biomarkers
3.7. Correlation Analysis
3.8. Erythrocyte Abnormalities
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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General Description | Alterations | Importance Factor (ω) |
---|---|---|
Alterations result from a pathological condition of blood and tissue fluid flow | Blood sinusoid dilation | 1 |
Hemorrhage | 1 | |
Alterations result in functional redution or loss of the organ. | Cytoplasmic vacuolization | 1 |
Hemosideriosis | 1 | |
Irregular arrangement of hepatocytes | 1 | |
Lipid accumulation | 2 | |
Necrosis | 3 | |
Cellular hyperplasia | 2 | |
Alterations result from increased presence of cells used in tissue repair; response to damaged tissue | Leukocytes infiltration | 2 |
Melanomacrophage aggregates | 1 | |
Free melanomacroph ages | 1 |
Picentino River | Tusciano River | ||
---|---|---|---|
Physicochemical parameters | Conductivity (µS/cm) | 387 | 1680 |
Oxygen (mg/L) | 9.4 | 7.8 | |
pH | 7.2 | 8.2 | |
Temperature (°C) | 14.8 | 15.3 | |
Total Inorganic Carbon mg/L | 45 | 86 | |
Chlorides mg/L | 7.4 | 22 | |
Bromine mg/L | <0.1 | 0.2 | |
Nitrates mg/L | 2.8 | 39 | |
PTEs | As (µg/L) | <1 | 3.13 |
Cd (µg/L) | <0.1 | 0.17 | |
Co (µg/L) | <0.5 | 0.8 | |
Hg (µg/L) | <0.1 | 0.23 | |
Ni (µg/L) | <0.5 | 0.77 | |
Pb (µg/L) | <1 | 1.22 | |
Pesticides | Boscalid (µg/L) | <0.01 | 0.44 |
Glifosate (µg/L) | <0.01 | 0.32 | |
AMPA (µg/L) | <0.01 | 0.85 | |
Propizamide (µg/L) | <0.01 | 0.02 | |
Terbutryn (µg/L) | <0.01 | 0.05 | |
Fungicide | Metalaxil (µg/L) | <0.01 | 0.04 |
Other contaminants | Tetrachlorethylene (µg/L) | <0.01 | 0.17 |
Toluene (µg/L) | <0.01 | 0.15 | |
Trichloroethylene (µg/L) | <0.01 | 0.11 | |
Trichloromethane (µg/L) | <0.01 | 0.14 |
PTEs (mg/kg) | PI | TU | PAHs (mg/kg) | PI | TU | PCBs (µg /kg) | PI | TU | OCPs (µg /kg) | PI | TU |
---|---|---|---|---|---|---|---|---|---|---|---|
As | 8.7 | 12.5 | Total PAHs | 0.0155 | 0.0182 | PCB 77 | 0.003 | <0.003 | Hexachlorobenzene | 0.005 | 0.113 |
Be | 3.3 | 5.8 | Dibenzo(a,i)pyrene | <0.005 | 0.0051 | PCB 118 | <0.003 | 0.032 | α-Chlordane | <0.005 | 0.078 |
Cd | 0.32 | 0.21 | PCB 105 | <0.003 | 0.02 | Chlordane | 0.005 | 0.081 | |||
Co | 5.7 | 11.2 | PCB 167 | <0.003 | 0.004 | o,p′-DDE | <0.005 | 0.059 | |||
Cu | 38.8 | 35.8 | PCB 156 | 0.004 | 0.007 | p,p′-DDE | 0.02 | 7.591 | |||
Cr | 10.4 | 18.3 | PCB 157 | 0.006 | <0.003 | o,p′-DDD | <0.005 | 0.019 | |||
Hg (µg /kg) | 23 | 23 | PCB 189 | 0.004 | <0.003 | p,p′-DDD | <0.005 | 0.109 | |||
Ni | 10.5 | 12.6 | PCB-28 | <0.003 | 0.005 | o,p′-DDT | <0.005 | 0.292 | |||
Pb | 36.1 | 39.9 | PCB-52 | <0.003 | 0.006 | p,p′-DDT | <0.005 | 1.771 | |||
Sn | 2.5 | 2.7 | PCB-101 | <0.003 | 0.012 | Dieldrin | <0.005 | 0.191 | |||
Tl | 0.8 | 1.36 | PCB-153 | 0.135 | 0.042 | Endosulphan sulphat | 0.128 | <0.005 | |||
V | 45 | 80 | PCB-138 | 0.065 | 0.043 | DDD, DDT, DDE | 0.0325 | 9.84 | |||
Zn | 77.1 | 75.6 | PCB-180 | 0.063 | 0.055 | ||||||
Trichlorobiphenyls | <0.01 | 0.012 | |||||||||
Tetrachlorobiphenyls | <0.01 | 0.036 | |||||||||
Pentachlorobiphenyls | <0.01 | 0.121 | |||||||||
Hexachlorobiphenyls | <0.01 | 0.16 | |||||||||
Heptachlorobiphenyls | 0.227 | 0.098 | |||||||||
Octachlorobiphenyls | 0.081 | 0.013 | |||||||||
Nonachlorobiphenyls | 0.059 | 0.032 | |||||||||
Decachlorobiphenyls | 0.051 | 0.064 | |||||||||
Total PCB | 0.418 | 0.536 |
Species | River | BW (g) | TL (cm) | K | HSI (%) |
---|---|---|---|---|---|
European eel (A. anguilla) | Picentino | ||||
Tusciano | |||||
Brown trout (S. trutta fario) | Picentino | ||||
Tusciano |
Alterations | European Eel (A. anguilla) | Brown Trout (S. trutta fario) | ||
---|---|---|---|---|
Picentino River | Tusciano River | Picentino River | Tusciano River | |
Blood sinusoid dilation | ||||
Hemorrhage | ||||
Cytoplasmic vacuolization | ||||
Hemosideriosis | ||||
Irregular arrangement of hepatocytes | ||||
Lipid accumulation | ||||
Necrosis | ||||
Cellular hyperplasia | ||||
Leukocytes infiltration | ||||
melanomacrophages centers (MMCs) |
Alteration | European Eel (A. anguilla) | Brown Trout (S. trutta fario) | ||
---|---|---|---|---|
Picentino River | Tusciano River | Picentino River | Tusciano River | |
Free melanomacrophages | ||||
Hemosideriosis | ||||
Melanomacrophage aggregates | ||||
Necrosis |
Water Pollutants | Soil Pollutants | |||||
---|---|---|---|---|---|---|
Alterations | Pearson r | p Value (Two-Tailed) | Statistical Significance | Pearson r | p Value (Two-Tailed) | Statistical Significance |
Blood sinusoid dilation | 0.9417 | 0.0583 | ns | 0.9417 | 0.0583 | ns |
Hemorrhage | 0.9886 | 0.0114 | * | 0.9886 | 0.0114 | * |
Cytoplasmic vacuolization | 0.9939 | 0.0061 | ** | 0.9939 | 0.0061 | ** |
Hemosiderosis | 0.9874 | 0.0126 | * | 0.9874 | 0.0126 | * |
Irregular arrangement of hepatocytes | 0.9962 | 0.0038 | ** | 0.9962 | 0.0038 | ** |
Lipid accumulation | 0.9611 | 0.0389 | * | 0.9611 | 0.0389 | * |
Necrosis | 0.9921 | 0.0079 | ** | 0.9921 | 0.0079 | ** |
Cellular hyperplasia | 0.9831 | 0.0169 | * | 0.9831 | 0.0169 | * |
Leukocytes infiltration | 0.9923 | 0.0077 | ** | 0.9923 | 0.0077 | ** |
MMC | 0.9925 | 0.0075 | ** | 0.9925 | 0.0075 | ** |
Water Pollutants | Soil Pollutants | |||||
---|---|---|---|---|---|---|
Alterations | Pearson r | p Value (Two-Tailed) | Statistical Significance | Pearson r | p Value (Two-Tailed) | Statistical Significance |
Free melanomacrophages | 0.9258 | 0.0742 | ns | 0.9258 | 0.0742 | ns |
Hemosiderosis | 0.9874 | 0.0126 | * | 0.9874 | 0.0126 | * |
Melanomacrophage aggregates | 0.7432 | 0.2568 | ns | 0.7432 | 0.2568 | ns |
Necrosis | 0.7675 | 0.2325 | ns | 0.7675 | 0.2325 | ns |
ECA | EF | ENA | ||
---|---|---|---|---|
European eel (A. anguilla) | Picentino River | 12.7 ± 2 | 1.18 ± 0.3 | 7.7 ± 2.1 |
Tusciano River | 27.15 ± 2 *** | 2.8 ± 0.3 | 20.3 ± 0.9 ** | |
Brown trout (S. trutta fario) | Picentino River | 16.3 ± 0.9 | 16.3 ± 0.9 | 9.1 ± 1.6 |
Tusciano River | 28.6 ± 1.9 ** | 28.6 ± 1.9 *** | 21.1 ± 2.8 ** |
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Orso, G.; Imperatore, R.; Coccia, E.; Rinaldi, G.; Cicchella, D.; Paolucci, M. A Deep Survey of Fish Health for the Recognition of Useful Biomarkers to Monitor Water Pollution. Environments 2023, 10, 219. https://doi.org/10.3390/environments10120219
Orso G, Imperatore R, Coccia E, Rinaldi G, Cicchella D, Paolucci M. A Deep Survey of Fish Health for the Recognition of Useful Biomarkers to Monitor Water Pollution. Environments. 2023; 10(12):219. https://doi.org/10.3390/environments10120219
Chicago/Turabian StyleOrso, Graziella, Roberta Imperatore, Elena Coccia, Gianluca Rinaldi, Domenico Cicchella, and Marina Paolucci. 2023. "A Deep Survey of Fish Health for the Recognition of Useful Biomarkers to Monitor Water Pollution" Environments 10, no. 12: 219. https://doi.org/10.3390/environments10120219
APA StyleOrso, G., Imperatore, R., Coccia, E., Rinaldi, G., Cicchella, D., & Paolucci, M. (2023). A Deep Survey of Fish Health for the Recognition of Useful Biomarkers to Monitor Water Pollution. Environments, 10(12), 219. https://doi.org/10.3390/environments10120219