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Phenylbenzohydrazides Obtained from Isatoic Anhydride Present Anti-Inflammatory Activity <em>in Vivo</em> and <em>in Vitro</em>

2022· preprint· en· W4307763943 on OpenAlexaff
João Pedro Barros Paiva, Millena Santos Cordeiro, Patricia Ribeiro de Carvalho França, Luiz Octavio Pereira Branco, Isabela Souza dos Santos, Nanashara Figueiredo Reis, Patrick Pedro Pimentel, Thaís Biondino Sardella Giorno, E.C.D. Lima, Patrícia Dias Fernandes

Bibliographic record

VenuePreprints.org · 2022
Typepreprint
Languageen
FieldChemistry
TopicSynthesis and biological activity
Canadian institutionsDiscovery Air (Canada)
FundersFundação Oswaldo Cruz
KeywordsIn vivoIn vitroExtravasationNitric oxidePharmacologyChemistryDexamethasoneInflammationNitric oxide synthaseTumor necrosis factor alphaBiochemistryImmunologyMedicineBiologyInternal medicineBiotechnology

Abstract

fetched live from OpenAlex

Background: Despite the existence of a wide variety of anti-inflammatory drugs, the vast majority are classified as steroidal or non-steroidal. Both classes with many side effects that limit usage. Thus, the search for new molecules with anti-inflammatory potential is still important. Methods: Five phenylbenzohydrazides were synthetized and evaluated in pre-clinical models of acute inflammation in vivo and in vitro. Results: Substances significantly reduced cell migration induced by carrageenan. It was also observed an intense inhibition in protein extravasation and cytokines (IL-6, IL-1β, and TNF-α) production as well as nitric oxide reduction. INL-11 demonstrated to be the most potent since the reduction was significant even when compared with dexamethasone. In vitro INLs also reduced cytokines and NO production and iNOS activity. INL-11 was the most effective in reducing cell migration in vitro. Conclusions: our data suggest that these substances are suitable for further development to new series of compounds that could lead to new hits and future drug prototypes for anti-inflammatory conditions.

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 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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
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 score0.176
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0040.011
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0150.000

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 head0.045
GPT teacher head0.280
Teacher spread0.235 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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