Heavy Metal Levels in Water, Sediment and Tissues of <i>Sarotherodon melanotheron</i> from the Upper Bonny Estuary, Nigeria and Their Human Health Implications
Bibliographic record
Abstract
Heavy metals in small amounts or in excess of permissible limits in aquatic organisms may pose a health risk to their consumers. The aim of this study was to investigate the levels of heavy metal in water, sediment and tissues of Sarotherodon melanotheron , from the Upper Bonny Estuary in the Niger Delta and to evaluate their human health implications. Water, sediment and S. melanotheron samples were collected from 5 different stations namely; Okochiri Creek (S1), Ekerekana Creek (S2) - Point of industrial effluent discharge (POD), Okari-Ama Creek (S3), Ogoloma Creek (S4) and Bonny Estuary (Control). The levels of Cr, Ni, Zn, V, Cd, Pb, Hg, and As were analysed following Standard Procedures using Atomic Absorption Spectrophotometer (AAS). Metals analysed were below detectable limit (0.001 mg/L) in water while metals such as Pb, Cr, Ni, Zn and V were below permissible limit in sediment. Ecological indices indicated that the sediment of the study area was unpolluted. The levels in the tissues (gill, muscle and liver) showed varying concentrations. Ni concentration in the tissues exceeded FAO/WHO permissible limits, Cr was above permissible limit in most tissues, while Pb was only detected in the muscle of S. melanotheron from Okari-ama Creek (S3). Zn and V were below the FAO/WHO permissible limit. Cd, As, and Hg were not detected in all samples. BSAF showed bio-accumulative potentials in the tissues. Further calculations on the risk associated with consumption of S. melanotheron showed that HQ and HI were <1 which showed no threat to public health. However, more studies on heavy metals and proper monitoring of the creeks should be encouraged by regulatory agencies in Nigeria to give informed decisions from risk assessments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".