Detection of exon polymorphisms in the human lactoferrin gene
Bibliographic record
Abstract
We previously demonstrated that lactoferrin gene polymorphisms occur in cancer cells of patients with leukemia and breast cancer. In this study, we established a non-radioactive polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) analysis, one of the most sensitive and simplest methods to detect polymorphisms and mutations of the human lactoferrin gene. We optimized the PCR conditions for nine different DNA templates and 16 pairs of exon primers for SSCP analysis. The DNA templates used in the analyses were prepared from a cosmid clone (CT6-1) that contains the human lactoferrin gene, human placental tissue, leukocytes from 10 normal volunteers, leukemic cells of two patients, and previously established three breast and two leukemic cell lines. With the appropriate exon-primer sets, PCR products from exon I to exon 16 of the lactoferrin gene were generated from the DNA templates and analyzed by SSCP. Compared with the homogenous cloned DNA, lactoferrin gene polymorphisms were detected within exons 2, 5, 7, 9, 13, 14, and 15 of the normal placental and leukocyte DNA. In addition, abnormal migration patterns of the lactoferrin gene in cancer cells were detected in exons 4, 5, 13, 14, and 15. The PCR-SSCP band migration patterns can be attributed either to gene polymorphism in normal cells or to DNA mutations in cancer cells and the employed method cannot distinguish between them. Nonetheless, the present analysis suggests that genetic polymorphisms of the lactoferrin gene exist in selected exons and additional mutations of the lactoferrin gene do occur in the cancer cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".