MYOCARDIAL DEFECTS IN HYPERACUTE CARDIAC REJECTION
Bibliographic record
Abstract
Dr. Beranek’s interest in our work in xenograft heart transplantation is most appreciated. His concern regarding the histopathology in the graft treated with anti-C5mAb (Fig 1B) is acknowledged. We believe, however, that Dr. Beranek may have over-interpreted a single shot of a black and white representative photograph of that study group. This exemplifies the limitations that authors often have because of the restrictions of space available for illustrations. There are various factors in the photograph that might have prompted his concern. First, the photograph shows myocardial fibers arranged longitudinally. This often causes some minor degree of compression of fibers in a section, giving the impression of crowding of nuclei and thinning of fibers. Second, some artifact present in the section with separation of some of the fibers is often unavoidable. We have seen this also in normal nontransplanted rat hearts. Third, in contrast with adult human and large mammalian hearts, the apparent crowding of nuclei is not an uncommon phenomenon in normal rat hearts. Fourth, we did not see evidence of apoptosis or vacuolization of myocytes in the group in question. Dr. Beranek has identified several provocative explanations for our data presented in Figure 1B. We agree that cardiac damage during hyperacute rejection may be the result of multiple mechanisms and warrants future investigation into the contributions of apoptosis, hemorrhage, and lymphatic overflow. Only after careful examination in testable models will we be able to definitively rule in or rule out what mechanisms are major contributors to cardiomyocyte damage in hyperacute rejection. Hao Wang Bertha Garcia Robert Zhong1
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".