Differential Display Polymerase Chain Reaction and Gene Expression in Copper-Exposed <i>Daphnia magna</i>
Bibliographic record
Abstract
Contamination of aquatic systems by metals and polycyclic aromatic hydrocarbons (PAHs) is a prevalent environmental problem. These contaminants are known to impact populations, organismal health, and survival negatively. Most of the organism and ecosystem level changes are a consequence of underlying molecular and subcellular damage. Therefore, molecular bioindicators are likely to be a sensitive tool for environmental assessment. We have demonstrated that both copper and phenanthrenequinone (PHEQ) alter protein expression in Daphnia magna. To investigate altered gene expression in Daphnia magna exposed to copper, PHEQ, and other contaminants, a technique based on the differential display polymerase chain reaction (ddPCR) is being developed for D. magna. This technique promises numerous applications as it permits a survey of the genes being expressed in any given organism. Furthermore, ddPCR allows one to monitor the changes in gene expression that result from any toxicant exposure. This paper reviews the applications of ddPCR and describes our development of ddPCR as a bioindicator of gene expression in D. magna in response to toxicant exposure. This is the first step in the development of a novel gene fingerprinting technique that can be applied to any compound and organism of interest.
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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 | 0.001 |
| 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) | 0.001 | 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".