Bibliographic record
Abstract
In a previous work published 4 years ago, an arrest of tumor cell proliferation was obtained with dichloroacetate, an inhibitor of pyruvate dehydrogenase kinase, aiming to dephosphorylate and activate pyruvate dehydrogenase (PDH) [1]. This observation indicates that it may be useful to act as well, on other tumor cell enzymes that change in parallel to PDH, since this leads to a “rewiring of metabolic pathways” that is specific for tumor cells. Altered signaling controls that inhibit, or activate, enzymes in tumor cells were recently reviewed [2, 3]. Schematically, in tumor cells, enzymes such as PDH and pyruvate kinase (PK) are phosphorylated and inhibited as observed for catabolism and gluconeogenesis, while other enzymes (for example, glycogen synthase) are dephosphorylated, in their anabolic configuration, associated to glycolysis. This hybrid situation rewires metabolic pathways in tumor cells and gives them a metabolic advantage, enabling them to plunder tissue reserves mobilized by catabolic hormones [4, 5]. Normally, pancreatic beta cells secrete in parallel to insulin, the transmitter GABA, which switches off neighboring alpha and delta cells releasing respectively glucagon and somatostatin. In this way, when anabolic insulin is released, catabolic glucagon is switched off by GABA [2]. A failure of this GABA mediated mechanism probably explains the hybrid catabolic/anabolic response of tumor cell; however, we also have to consider that differentiated cells in cancer, respond preferentially to catabolic hormones; this is discussed in this letter.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.016 | 0.022 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".