Labeling DNA Damage with Terminal Transferase
Bibliographic record
Abstract
Apoptotic and programmed cell death are characterized by, and indeed were first discovered from observations of, remarkable morphological changes that occur in the nucleus ( see 1 for a comprehensive review of apoptosis and programmed cell death). Thus, light and electron microscopy were the first tools for the detection of apoptosis. This characteristic collapse of chromatin and ultimately the structural organization of the nucleus is triggered by the degradation of DNA, which is an active process and occurs prior to death of the cell. The degradation of DNA was subsequently found to be mediated by endonucleolytic activity that generated a specific pattern of fragments ( 2 ). The fragment sizes were multiples of approx 200 bp, the amount of DNA wound around a single nucleosome, and the pattern became known as the DNA ladder ( Fig. 1A ). Later it became apparent that DNA fragmentation is quite variable within cells and some cell types produce only high molecular weight (HMW) fragments ( Fig. 1B , 3 ). The latter observations formed the basis of a convenient in vitro biochemical technique for the routine detection of apoptosis by resolving the fragmented DNA by conventional or pulsed field agarose gel electrophoresis. However, this technique requires relatively large amounts of material and DNA extraction. Subsequently, a variety of techniques have emerged to detect apoptotic DNA fragmentation in situ by exploiting the fact that the hydroxyl group at the 5′ or 3′ ends of the small DNA fragments becomes exposed. Nucleotide analogues can be attached to the ends by several enzymes, with T erminal d eoxynucleotide T ransferase (TdT) being the most popular ( 4 , 5 ). The assays are typically fluorescence-based, either by the direct incorporation of a nucleotide to which a fluorochrome has been conjugated, or indirectly using fluorescent dye conjugated antibodies that recognize biotin- or digoxigenin-tagged nucleotides. Radioactively labeled nucleotides can also be used. Since several million fragments are generated during complete DNA fragmentation and low levels of fluorescence can be readily detected by photo-multipliers and CCD arrays, the assays are extremely sensitive. The assays have been formatted for light and confocal microscopy as well as flow cytometry, thereby greatly facilitating the detection and quantitation of apoptosis in situ . In addition, endlabeling techniques are employed in studies of the actual mechanism of DNA fragmentation, as well as the detection and characterization of endonucleases. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".