Low-level environmental exposure to lead and renal adverse effects: A cross-sectional study in the population of children bordering the Mbeubeuss landfill near Dakar, Senegal
Bibliographic record
Abstract
This study deals with the health effects within a child population, neighbouring a landfill. After detecting metals in soil and air samples collected in the surroundings of the landfill and in a control site, we have studied: (i) levels of lead (Pb) and exposure biomarkers in blood and urine, (ii) oxidative stress biomarkers and (iii) renal injury by applying a set of early effect biomarkers. Levels of Pb were higher in the exposed site (i.e. 1129 mg/kg and 640 ng/m(3) in soil and air samples, respectively) versus those in the control site (i.e. 14.3 mg/kg and 9.3 ng/m(3) in soil and air samples, respectively). Pb impregnation and levels of delta-aminolevulinic acid in urine were influenced by the living site that shows the prevailingly alarming situation in the Mbeubeuss landfill. Malondialdehyde changes indicated Pb-induced excessive production of reactive oxygen species. Lactate dehydrogenase activities and proteinuria were found to be higher in the children living in the exposed site. These evidences may reveal the usefulness of these two effect biomarkers to monitor the kidney injury entailed by relatively low-environmental exposure to Pb. Overall, these results show that the Mbeubeuss landfill constitutes a real source of environmental and health risk, be it living or working on site, of the surrounding population, predominantly for children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".