Synergism in aluminum and mercury neurotoxicity
Bibliographic record
Abstract
] to human neuronal-glial (HNG) cells in primary co-culture using the evolution of the pro-inflammatory transcription factor NF-kB (p50/p65) complex as a critical indicator for the onset of inflammatory neurodegeneration and pathogenic inflammatory signaling. As indexed by significant induction of the NF-kB (p50/p65) complex the results indicate: (i) a notable increase in pro-inflammatory signaling imparted by each of these two environmental neurotoxins toward HNG cells in the ambient 20-200 nM range; and (ii) a significant synergism in the neurotoxicity when aluminum (sulfate) and mercury (sulfate) were added together. This is the first report on the neurotoxic effects of aluminum sulfate and/or mercury sulfate on the initiation of inflammatory signaling in human brain cells in primary culture. The effects aluminum+mercury together on other neurologically important signaling molecules or the effects of other combinations of common environmental metallic neurotoxins to human neurobiology currently remain not well understood but certainly warrant additional investigation and further study in laboratory animals, in human primary tissue cultures of CNS cells, and in other neurobiologically realistic experimental test systems.
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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 | 0.000 | 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) | 0.004 | 0.001 |
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".