Bibliographic record
Abstract
Fanconi anemia (FA) is an inherited chromosomal recessive syndrome characterized by cellular hypersensitivity to DNA crosslinking agents and bone marrow failure, which cause aplastic anemia, and an increased incidence of malignancy. 13 complementation groups are currently discovered, and 13 distinct genes have been cloned (FANCA, FANCB, FANCC, FANCD1, FANCD2, FANCE, FANCF, FANCG, FNACI, FANCJ, FANCL, FANCM, FANCN). Stem cells can theoretically divide to other cells without limit as long as a person is still alive. The stem cells that form blood and immune cells are known as hematopoietic stem cells. Hematopoietic stem cells can be acquired from a Fanconi anemia patient, whereas genomic DNA can be obtained easily from blood cells of a normal person. Normal genes also can be synthesised by PCR method. Normal genomic DNA will be delivered into a patient's stem cells via microinjection or transfection after enzyme digestion; the defective genes might be repaired by homologous genetic recombination. The gene-corrected stem cells can be transplanted into the same patient finally. It is possible that human genomic DNA to be considered as materials for homologous genetic recombination to repair defective genes in vivo. This might be an efficient method for gene therapy, which has no or less immunological rejection for Fanconi anemia and some genetic diseases. Several related observations and experiments are discussed to support this possible means of stem cell gene therapy of Fanconi anemia.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".