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Record W3135118388 · doi:10.3390/molecules26051272

Synthesis of Highly Potent Anti-Inflammatory Compounds (ROS Inhibitors) from Isonicotinic Acid

2021· article· en· W3135118388 on OpenAlex
Sana Yaqoob, Nourina Nasim, Rahila Khanam, Yan Wang, Almas Jabeen, Urooj Qureshi, Zaheer Ul‐Haq, Hesham R. El‐Seedi, Zi‐Hua Jiang, Farooq‐Ahmad Khan

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

VenueMolecules · 2021
Typearticle
Languageen
FieldChemistry
TopicSynthesis and biological activity
Canadian institutionsLakehead University
FundersVetenskapsrådet
KeywordsIsonicotinic acidChemistryIbuprofenIn vitroCombinatorial chemistryIC50Docking (animal)Anti-inflammatoryDrugStereochemistryPharmacologyBiochemistryOrganic chemistryBiologyMedicineHydrazide

Abstract

fetched live from OpenAlex

In search of anti-inflammatory compounds, novel scaffolds containing isonicotinoyl motif were synthesized via an efficient strategy. The compounds were screened for their in vitro anti-inflammatory activity. Remarkably high activities were observed for isonicotinates 5–6 and 8a–8b. The compound 5 exhibits an exceptional IC50 value (1.42 ± 0.1 µg/mL) with 95.9% inhibition at 25 µg/mL, which is eight folds better than the standard drug ibuprofen (11.2 ± 1.9 µg/mL). To gain an insight into the mode of action of anti-inflammatory compounds, molecular docking studies were also performed. Decisively, further development and fine tuning of these isonicotinates based scaffolds for the treatment of various aberrations is still a wide-open field of research.

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 score0.010
Threshold uncertainty score0.890

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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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