<i>In vitro</i> and <i>in vivo</i> biological characterization of the anti-proliferative potential of a cyclic trinuclear organotin( <scp>iv</scp> ) complex
Bibliographic record
Abstract
Identification of novel molecules that can selectively inhibit the growth of tumor cells, avoid causing side effects to patients and/or intrinsic or acquired resistance, usually associated with common chemotherapeutic agents, is of utmost importance. Organometallic compounds have gained importance in oncologic chemotherapy, such as organotin(iv) complexes. In this study, we assessed the anti-tumor activity of the cyclic trinuclear organotin(iv) complex with an aromatic oximehydroxamic acid group [nBu2Sn(L)]3(H2L = N,2-dihydroxy-5-[N-hydroxyethanimidoyl]benzamide) - MG85 - and provided further characterization of its biological targets. We have previously shown the high anti-proliferative activity of this complex against human colorectal and hepatocellular carcinoma cell lines and lower cytotoxicity in neonatal non-tumor fibroblasts. MG85 induces tumor cell apoptosis and down-regulation of proteins related to tubulin dynamics (TCTP and COF1). Further characterization included the: (i) evaluation of interference in the cell cycle progression, including the expression of critical genes; (ii) affinity to DNA and the corresponding mode of binding; (iii) genotoxic potential in cells with deficient DNA repair pathways; and (iv) in vivo tumor reduction efficiency using mouse colorectal carcinoma xenografts.
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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 | 0.000 | 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".