Heavy Metal Levels and Risk Assessment from Consumption of Marine Fish in Peninsular Malaysia
Bibliographic record
Abstract
Fish consumption is one of the primary sources of protein in Malaysia. However, harmful substances, including heavy metals released from anthropogenic sources may accumulate in marine organisms through the food chain. Hence, human health risks may occur through the consumption of fish contaminated by heavy metals. This study was conducted to determine the concentrations of heavy metals and to assess health risks in edible tissues of 296 commonly consumed marine fish throughout Peninsular Malaysia. The marine fish samples were collected from selected major fish landing ports throughout Peninsular Malaysia. This paper focused on nine heavy metals concentrations namely selenium (Se), cadmium (Cd), lead (Pb), copper (Cu), zinc (Zn), antimony (Sb), tin (Sn), chromium (Cr) and manganese (Mn) in 46 species of marine fish. The fish samples were digested using a microwave digestion system (Multiwave 3000, Anton Paar). Heavy metals concentrations were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) ELAN 9000 (Perkin Elmer, Sciex, Canada). The heavy metals concentrations in marine fish samples were found to be dominated by Zn followed by Sn, Se, Cu, Mn, Cr, Pb, Cd and Sb which ranged between 15.9612 mg/kg (Zn) and 0.0002 mg/kg (Sb) wet weight. Among the investigated fish species, Otolithoides biauritus demonstrated the lowest concentration for all heavy metal except for Pb. The estimated weekly intakes (EWI) for all samples in this study were below the established PTWI by JECFA of FAO/WHO. Risk assessment results showed that the hazard quotient (HQ) and hazard index (HI) values were lower than 1 in all fish species. The results indicate that exposure to the studied metals poses a low non-carcinogenic risk and considered safe for human consumption.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".