Expression of apoptosis regulatory proteins in the skeletal muscle of tumor-bearing rabbits compared with diet-restricted rabbits
Bibliographic record
Abstract
The mechanism of body weight loss in the tumor-bearing state is still unclear. In this study, we investigated expressions of apoptosis regulatory proteins in the skeletal muscle of tumor-bearing and diet-restricted rabbits, and tried to evaluate the differences between the two groups. The apoptotic index (AI) in the tumor-bearing group was 28.1+/-2.84 on day 10. By day 20, many more apoptotic cells were found (AI: 40.5+/-3.20), but then after day 20 their numbers gradually decreased (AI: 9.67+/-2.22 on day 30 and 0.93+/-0.96 on day 40). By contrast, no apoptotic cells were detected in the diet-restricted group at any of the times examined. Bcl-2 immunoreactivity was either not detected at all or only weakly observed in both groups. By contrast, Bax expression increased gradually after implantation in the tumor-bearing group. Bax expression in skeletal muscle cell was graded (moderate) 10 days after tumor implantation, and (high) by day 20, in 2 of the 5 tumor-bearing rabbits. After day 20, however, Bax immunoreactivity decreased continuously in the tumor-bearing group. By contrast, hardly any Bax-immuno-positive cells were detected in the diet-restricted group. These results suggest that loss of body weight in the tumor-bearing group is different from that in the diet-restricted group, and is related to apoptosis of skeletal muscles.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Study of apoptosis regulatory proteins in skeletal muscle of tumor-bearing rabbits; the object is cachexia biology.
The study examines apoptosis in tumor-bearing rabbits, not research practice.
Biomedical study of apoptosis proteins in tumor-bearing rabbits; laboratory biology.
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 | 0.000 |
| 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) | 0.001 | 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".