Real-Time Polymerase Chain Reaction Monitoring of Recombinant DNA Entry into Soil from Decomposing Roundup Ready Leaf Biomass
Bibliographic record
Abstract
Glyphosate-tolerant, Roundup Ready (RR) soybeans account for about 57% of all genetically modified (GM) crops grown worldwide. The entry of recombinant DNA into soil from GM crops has been identified as an environmental concern due to the possibility of their horizontal transfer to soil microorganisms. RR soybeans contain recombinant gene sequences that can be differentiated from wild-type plant and microbial genes in soil by using a sequence-specific molecular beacon and real-time polymerase chain reaction (PCR). A molecular beacon-based real-time PCR system to quantify a wild-type soybean lectin ( le1) gene was designed to compare amounts of endogenous soybean genes to recombinant DNA in soil. Microcosm studies were carried out to develop methodologies for the detection of recombinant DNA from RR soybeans in soil. RR soybean leaf litterbags were imbedded in the soil under controlled environmental conditions (60% water holding capacity, 10/15 degrees C, and 8/16 h day/night) for 30 days. The soybean biomass decomposition was described using a single-phase exponential equation, and the DNA concentration in planta and in soil was quantified using real-time PCR using sequence-specific molecular beacons for the recombinant cp4 epsps and endogenous soybean lectin ( le1) genes. The biomass of RR soybean leaves was 8.6% less than nontransgenic (NT) soybean leaves after 30 days. The pooled half-disappearance time for cp4 epsps and le1 in RR and of le1 in NT soybean leaves was 1.4 days. All genes from leaves were detected in soil after 30 days. This study provides a methodology for monitoring the entry of RR and NT soybean DNA into soil from decomposing plant residues.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".