Construction of a Genomic Map of H. pylori by Pulsed-Field Gel Electrophoresis (PFGE)
Bibliographic record
Abstract
The inability of conventional gel electrophoresis to separate DNA molecules exceeding 50 kb in size led to the development of pulsed-field gel electrophoresis (PFGE) by Schwartz et al, (1)in 1982. He introduced the concept of applying two alternating electric fields (i.e., pulsed-field) to separate DNA molecules greater than 50 kb embedded in an agarose gel matrix. Since then, many instruments based on this principle have been developed. For a discussion of various pulsed-field applications, see review articles by Lai et al. (2) and Crété et al. (3). It was shown that, under the influence of an electric field, a DNA molecule embedded in a gel matrix undergoes reorientation, elongation, and migration along the field toward the anode. When a second field is applied in an alternate direction, the DNA molecule must reorientate, elongate, and migrate along the direction of the new field. Larger DNA molecules will take longer to reorientate than smaller molecules; therefore the larger ones spend less time migrating down the gel than the smaller per pulse time. Consequently, larger DNA molecules will appear near the origin while the smaller molecules will migrate furthest. This principle becomes important when different fragment sizes of DNA are to be separated. PFGE has become an important tool for determining genome sizes, physical mapping of the chromosome, and localization of genes on the chromosome of prokaryotic micro-organisms.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".