Aldolase Isoenzyme Patterns during Human Ontogeny andin Lung, Kidney and Breast Cancer
Bibliographic record
Abstract
Enzyme patterns characteristic of fetal tissue have been noted in some experimental tumor models, particularly in hepatomas. In this study we undertook to determine whether biochemical evidence of a similar reversion could be detected in tumors of other human organs. As marker, we chose to use the aldolase isoenzymes A, B and C, for which distinct adult and fetal tissue patterns have been described. Using monospecific antibodies, we determined the aldolase isoenzyme pattern in a variety of human organs ranging in age from 14 to 40 weeks of gestation, in the 2- to 3-month postnatal period and in adults. In addition, 19 breast cancers, 19 primary lung cancers and 8 kidney cancers were examined. Our studies on breast cancer revealed three apparently distinct groups -- one showing primarily the A isoenzyme type (6 cases), a second containing mainly A with considerable quantities of B and C isoenzymes (9 cases) and a third group (4 cases) which may contain a different isoenzyme altogether since the combined activity of the three known forms was less than 100% in each case. In lung cancer, fetal characteristics could be substantiated since in fetal and adult lung tissue, the isoenzyme pattern is almost identical; 3 out of 19 cases showed substantial quantities of the B isoenzyme. In kidney tumors, a reversion to the A form with an appreciable fraction of the C form was found, which is similar to the fetal pattern.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".