Composition of Potential Heavy Metal Contaminants in Selected Liquid and Powdered Herbal Medicines Commonly Sold in Port Harcourt Metropolis, Nigeria
Bibliographic record
Abstract
Four potential heavy metal contaminants (PHMC) were analyzed in nine (9) different brands of liquid and five (5) powdered herbal products commonly sold in Port Harcourt metropolis with a view to ascertaining their levels and comparing them with standard regulatory limits (WHO) in order to establish if they are safe for human consumption.The samples were processed, digested and analyzed in triplicate using flame atomic absorption spectrophotometer (GBC Avanta PM6600 type).Concentration of heavy metals in liquid herbal products ranged from <0.001 -2.541 ppm (copper) and 0.041 -0.982 ppm (manganese), while chromium and cadmium were reportedly below detection limit in all test samples.Mean concentrations of copper and manganese in liquid herbal medicines were 0.38 ± 0.79 ppm and 0.47 ± 0.27 ppm respectively.On the other hand, the powdered herbs depicted heavy metal concentrations ranging from 0.049 -0.143 ppm (chromium), 0.437 -2.587 ppm (cadmium), while copper and manganese were reportedly below instrument detection limit.Mean concentrations of chromium and cadmium in finished powdered herbal products were 0.108 ± 0.045 ppm and 1.245 ± 0.815 ppm respectively.Apart from cadmium that exceeded WHO recommended limit in powdered herbal products, all other heavy metal contaminants were observed to be within recommended WHO limits and levels established by countries like Canada and Singapore.There was marked significant variation (P<0.05) in the concentration of copper and manganese amongst the various liquid herbal medicines that were tested.Similarly, the finished powdered herbal products showed significant variation (P<0.05) in concentrations of chromium and cadmium.Overall, the significant concentration of cadmium found in herbs of powdered form which are sold within the Port Harcourt metropolis is alarming and may be responsible for the high occurrence of kidney and liver health cases.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".