Intercommunity and temporal variation of eleven essential and five toxic elements in human placentas from deliveries in thirteen arctic and sub-arctic areas of Russia and Norway
Bibliographic record
Abstract
Research is described that constitutes an extension of an earlier paper (J. Environ. Monit., 2001, 3, 177-184), in which concentrations were measured in 263 human placentas of 11 essential elements (P, Ca, Mg, Cu, S, Na, Fe, Zn, K, Se, Mn) and 5 toxic elements (Ba, Sr, Pb, Ni, Cd). The additional data considered derive from earlier visits to 4 of the original 6 communities and 3 others, all but one of which are located in northern Norway and neighbouring areas of Russia. This more than doubled the number of placental samples available (263 to 571). Unfortunately, the personal, life-style and morphometric information obtained for the first study group was not available for the additional mothers. Country differences were evident for all elements except Ba, Fe and Zn; Cd, Cu, Mn, Na, Se, Ni, Pb, Sr and S were higher and K, P, Ca and Mg were lower in Russia (p < 0.03). Not unexpectedly, the highest median lead concentration was observed for the largest city in the western arctic region of Russia, namely Murmansk. Similarly, the higher median nickel level observed for Russia reflects the established observation that urinary nickel concentrations are higher in the Russian than in the Norwegian communities. Even though sampling was performed at different times of the year and before and after a 3-year interval in four centres, inter-collection differences were of relatively small magnitude and appear not to be linked to seasonal or temporal changes. Principal component analysis (PCA) confirmed the prominence of Factor 1, which grouped those metals that are known to form insoluble phosphate complexes and whose concentrations showed a dependence on gestational age and maternal smoking in the earlier study. It is concluded that PCA is a powerful statistical tool for exploring and identifying fundamental pathways and processes involved in governing the inorganic elemental composition of placental tissue. It also has the potential of identifying study limitations and quality assurance shortfalls. Further our findings show promise that placental concentrations of toxic elements may serve as an index of exposure and of nutritional intake for selected essential micro-elements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".