3-Benzylidene-4-chromanones: a novel cluster of anti-tubercular agents
Bibliographic record
Abstract
In a quest for developing novel anti-tubercular agents, a series of 3-benzylidene-4-chromanones 1a-l were evaluated for growth inhibition of Mycobacterium tuberculosis H37Rv. Three promising compounds 1d, g, j emerged as the lead compounds with the IC50 and IC90 values of less than 1 µg/mL. Evaluation of the potent compounds 1d, g, j and k against Vero monkey kidney cells revealed that these compounds are far more toxic to M. tuberculosis than to Vero cells. Structure-activity relationships demonstrated that 3-benzylidene-4-chromanones are more potent against M. tuberculosis than the related 2-benzylidene cycloalkanones and the meta substituted chromanone derivatives are more active than their ortho- and para-counterparts. Some guidelines for amplifying the project are presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".