Study on correlation of signal molecule genes and their receptor-associated genes with rat liver regeneration
Bibliographic record
Abstract
To investigate the effect of signal molecules and their receptor-associated genes on rat liver regeneration (LR) at the transcriptional level, the associated genes were originally obtained by retrieving the databases and related scientific publications; their expression profiles in rat LR were then checked using the Rat Genome 230 2.0 microarray. The LR-associated genes were identified by comparing gene expression difference between partial hepatectomy groups and operation-control groups. A total of 454 genes were proved to be LR related. The genes associated with the seven kinds of signal molecules (steroid hormones, fatty acid derivatives, protein and polypeptide hormones, amino acids and their derivatives, choline, cytokines, and gas signal molecules) were detected to be enriched in a cluster characterized by upregulated expression in LR. The number of genes related to the seven kinds of signal molecules was, in sequence, 63, 27, 100, 102, 16, 166, and 18. The 1027 frequencies of upregulation and 823 frequencies of downregulation in total as well as 42 types of different expression patterns suggest the complex and diverse gene expression changes in LR. It is presumed that signal molecules played an important role in metabolism, inflammation, cell proliferation, growth and differentiation, etc., during rat LR.
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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".