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Record W2909519046 · doi:10.1002/slct.201803159

Schiff Bases of Tetrahydrocurcumin as Potential Anticancer Agents

2019· article· en· W2909519046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemistrySelect · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCurcumin's Biomedical Applications
Canadian institutionsLakehead University
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsHeLaCurcuminChemistryIn vitroMetabolitePharmacologyCell cultureStereochemistryA549 cellActive metaboliteCombinatorial chemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

Abstract Tetrahydrocurcumin (THC) is a metabolite of curcumin and a valuable lead structure in medicinal chemistry due to its curcumin‐induced biological effects and its derivatives can be promising antitumor agents. Thirteen Schiff base derivatives of THC ( 1 ‐ 13 ) were synthesized by direct condensation of THC with various primary amines in moderate to very good yield (45‐94%) and their structures confirmed by 1 H NMR, 13 C NMR, HR‐ESI‐MS and IR techniques. Furthermore, these compounds were screened for in vitro anticancer activity against three human cancer cell lines including human epithelial lung carcinoma (A549), human epithelial cervical cancer (HeLa) and human breast adenocarcinoma (MCF‐7). Most compounds exhibit moderate to good anticancer activity against all three tested cell lines and are significantly more active than THC. Compound 12 bears an N ‐(4‐trifluromethyl)phenylethyl group and is the most active compound with IC 50 values ranging from 4.8 to 12.7 μM. The results obtained herein are important for further structure modifications of THC and the exploitation of the therapeutic potential of THC derivatives as anticancer agents.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.003
GPT teacher head0.247
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it