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Abstract 15534: Identification of Narciclasine, a Potential Drug to Treat PAH by Unbiased Pharmaco-Transcriptomic Study

2023· article· en· W4389958884 on OpenAlexaff
ANTONELLA ABI SLEIMAN, EL-Kabbout Reem, Mabrouka Salem, Sandra Breuils Bonnet, Sandra Martineau, Alice Bourgeois, Charlie Théberge, Charlotte Romanet, Sarah‐Eve Lemay, Yann Grobs, Olivier Boucherat, Sébastien Bonnet, Steeve Provencher, François Potus

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineTranscriptomePharmacologyIn vivoTreprostinilInflammationCancer researchPathologyPulmonary hypertensionInternal medicineGene expressionBiologyBiochemistryGene

Abstract

fetched live from OpenAlex

Introduction: Pulmonary arterial hypertension (PAH) is a life-threatening vascular disorder characterized by persistent vasoconstriction and detrimental remodeling of the pulmonary blood vessels. This incurable disease is marked by a complex gene expression reprogramming that triggers, among other, metabolic disorders, heightened by inflammation, and the development of a pro-survival phenotype in pulmonary arterial smooth muscle cells (PASMC).We conducted an unbiased transcriptomic study using lung samples from 16 PAH patients and 12 non-PAH controls and identified 4013 differentially expressed genes. Leveraging in silico pharmaco-transcriptomic analysis (utilizing the Lincs and Sigcom databases), we identified narciclasine as a potential drug. Hypothesis: Consequently, we hypothesized that narciclasine could offer improvements in PAH. Methods and Results: In vivo , we administered narciclasine treatment (1 mg/kg, 2 weeks, gavage) in a murine model of PH (monocrotaline model, 60 mg/kg, sc.) and observed improved PH hemodynamics (RVSP, PAAT, TPR), reduced inflammation (CD68 immunofluorescence (IF)), decreased PASMC survival (PCNA and cleaved caspase 3 IF), and alleviated adverse vascular remodeling (Elastic van Gieson Stain Kit). In vitro , narciclasine exhibited a dose-dependent reduction of cell proliferation (IF: ki67; Western blot Survivin, PCNA and PLK1) and increased apoptosis PAH-PASMC (IF: cleaved caspase 3; Wb: Bax and Bcl2). Transcriptomic study (conducted in treated PASMCs) reveals that the therapeutic effects of narciclasine in PAH may be attributed to decreased glycosylation (Gene Ontology analysis). We further observed increased glycosylation in remodeled arteries from PAH lungs, PH preclinical models, and cultured PASMC (Periodic Acid Schiff Kit). Subsequently, we validated that narciclasine reduced glycosylation and downregulated the expression of glycosylation enzymes (by wb: GFAT, NGT, OGT) both in vitro and in vivo. Statistical tests used: unpaired t (2 groups), ANOVA (> 2 groups). Conclusions: In conclusion, our unbiased pharmaco-transcriptomic study identifies narciclasine as a potential therapeutic drug for PAH. Notably, its efficacy appears to be mediated by the reduction of glycosylation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.325
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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