Ethyl Cinnamate Derivatives as Promising High-Efficient Acaricides against <i>Psoroptes cuniculi</i>: Synthesis, Bioactivity and Structure–Activity Relationship
Bibliographic record
Abstract
This paper reported the synthesis, structure-activity relationship (SAR) and acaricidal activity in vitro against Psoroptes cuniculi, a mange mite, of 25 ethyl cinnamate derivatives. All target compounds were synthesized and elucidated by means of MS, (1)H- and (13)C-NMR analysis. The results showed that 24 out of 25 tested compounds at 1.0 mg/mL demonstrated acaricidal activity in varying degrees. Among them, 6, 15, 26, 27 and 30 showed significant activity with median lethal concentration values (LC50) of 89.3, 119.0, 39.2, 29.8 and 41.2 µg/mL, respectively, which were 2.1- to 8.3-fold the activity of ivermectin (LC50=247.4 µg/mL), a standard drug in the treatment of Psoroptes cuniculi. Compared with ivermectin, with a median lethal time value (LT50) of 8.9 h, 27 and 30 showed smaller LT50 values of 7.9 and 1.3 h, respectively, whereas 6, 15 and 26 showed slightly larger LT50 values of 10.6, 11.0 and 10.4 h at 4.5 µmol/mL. SARs showed that the presence of o-NO2 or m-NO2 on the benzene ring significantly improved the activity, whereas the introduction of a hydroxy, methoxy, acetoxy, methylenedioxy, bromo or chloro group reduced the activity. (E)-Cinnamates were more effective than their (Z)-isomer. Nevertheless, the carbon-carbon double bond in the acrylic ester moiety was proven not to be essential to improve the activity of cinnamic acid esters. Thus, the results strongly indicate that cinnamate derivatives, especially their dihydro derivatives, should be promising candidates or lead compounds for the development of novel acaricides for the effective control of animal or human acariasis.
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 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".