Dimethyl 2,2&prime;-[2,2&prime;-(ethane-1,1-diyl)bis(1<em>H</em>-indole-3,2-diyl)]-diacetate: a small molecule capable of nano-scale assembly, inhibiting venous thrombosis and inducing no bleeding side effect
Bibliographic record
Abstract
BACKGROUND: -indole-3,2-diyl)]-diacetate (DEBIC), a recently reported antitumor agent, is worthy of characterization. MATERIALS AND METHODS: One-pot reaction was used to prepare DEBIC. Electrospray Ionization (+/-)-Fourier Transform-Ion Cyclotron Resonance-Mass Spectrometer (ESI(+/-)-FT-ICR-MS), quadrupole Collision Induced Dissociation (qCID) and nuclear overhauser effect spectroscopy spectra were used to present the assembly of DEBIC. Transmission electron microscopy, scanning electron microscopy, atomic force microscopy and Faraday-Tyndall effect were used to visualize the nano-property of DEBIC. Rat models were used to evaluate DVT inhibition and the bleeding reaction of DEBIC. RESULTS: One-pot reaction can provide DEBIC in acceptable yield and high purity. In water, rat plasma and lyophilized powders of DEBIC existed as particles of small nano-size. In vivo DEBIC inhibited DVT in a dose-dependent manner. The minimal effective dose of DEBIC was 1.7 μmol/kg. Even the dose of 36 μmol/kg/day DEBIC did not induce bleeding side effect in DVT rats like in warfarin (0.82 μmol/kg/day). CONCLUSION: DEBIC is a small molecule capable of nano-scale assembly, inhibiting venous thrombosis and inducing no bleeding side effect.
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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) | 0.002 | 0.001 |
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".