MétaCan
Menu
Back to cohort
Record W3132922739 · doi:10.3390/cells10020450

A Glucuronic Acid-Palmitoylethanolamide Conjugate (GLUPEA) Is an Innovative Drug Delivery System and a Potential Bioregulator

2021· article· en· W3132922739 on OpenAlexaff
Emiliano Manzo, Aniello Schiano Moriello, Francesco Tinto, Roberta Verde, Marco Allarà, Luciano De Petrocellis, Ester Pagano, Angelo A. Izzo, Vincenzo Di Marzo, Stefania Petrosino

Bibliographic record

VenueCells · 2021
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPalmitoylethanolamideChemistryPharmacologyGlucuronic acidTRPV1ConjugateEndocannabinoid systemBiochemistryDrug deliveryCapsaicinIn vivoCannabinoidCannabinoid receptorReceptorTransient receptor potential channelBiologyPolysaccharideAgonist

Abstract

fetched live from OpenAlex

Palmitoylethanolamide (PEA) is an endogenous anti-inflammatory lipid mediator and a widely used nutraceutical. In this study, we designed, realized, and tested a drug-carrier conjugate between PEA (the active drug) and glucuronic acid (the carrier). The conjugate, named GLUPEA, was characterized for its capability of increasing PEA levels and exerting anti-inflammatory activity both in vitro and in vivo. GLUPEA treatment, compared to the same concentration of PEA, resulted in higher cellular amounts of PEA and the endocannabinoid 2-arachidonoyl glycerol (2-AG), and increased 2-AG-induced transient receptor potential vanilloid type 1 (TRPV1) channel desensitization to capsaicin. GLUPEA inhibited pro-inflammatory monocyte chemoattractant protein 2 (MCP-2) release from stimulated keratinocytes, and it was almost as efficacious as ultra-micronized PEA at reducing colitis in dinitrobenzene sulfonic acid (DNBS)-injected mice when using the same dose. GLUPEA is a novel pro-drug able to efficiently mimic the anti-inflammatory and endocannabinoid enhancing actions of PEA.

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)0.000
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 score0.015
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.252
Teacher spread0.241 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCellsSame topicCannabis and Cannabinoid ResearchFrench-language works237,207