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Record W4200409800 · doi:10.1139/cjpp-2021-0077

Effect of fluoxetine treatment on neurotoxicity induced by lysolecithin in male rats

2021· article· en· W4200409800 on OpenAlexvenueno aff
Elham Gholami, Mohammadreza Gholami, A Tavakoli, Mahdie Ahmadi, Jafar Rezaian, Maryam Alipour, Farzaneh Chehelcheraghi, Mojtaba Khaksarian

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsFluoxetineCorpus callosumLuxol fast blue stainRemyelinationNeurotoxicityMedicineMultiple sclerosisH&E stainInternal medicineCentral nervous systemWhite matterStainingEndocrinologyPathologyAnesthesiaPharmacologyToxicityMyelinImmunologyMagnetic resonance imagingSerotonin

Abstract

fetched live from OpenAlex

Demyelination disorder is an unusual pathologic event, which occurs in the central nervous system (CNS). Multiple sclerosis (MS) is an inflammatory demyelinating disease that affects the CNS, and it is the leading cause of disability in young adults. Lysolecithin (LPC) is one of the best toxin-induced demyelination models. In this study, a suitable model is created, and the effect of fluoxetine treatment is examined on this model. In this case, it was assumed that daily fluoxetine treatment had increased the endogenous remyelination in the LPC model. This study was focused on investigating the influence of the fluoxetine dose of 5 or 10 mg/kg per day for 1 and 4 weeks on LPC-induced neurotoxicity in the corpus callosum region. It was performed as a demyelinating model in male Wistar rats. After 3 days, fluoxetine was injected intraperitoneally (5 or 10 mg/kg per day) for 1 and 4 weeks in each group. After completing the treatment course, the corpus callosum was removed to examine the gene expression and histological analysis was performed. The results of the histopathological study of hematoxylin and eosin staining of the corpus callosum showed that in 1 and 4-week treatment groups, fluoxetine has reduced the level of inflammation at the LPC injection site (5 and 10 mg/kg per day). Fluoxetine treatment in the luxol fast blue (LFB) staining of the corpus callosum has been led to an increase in myelination capacity in all doses and times. The results of the genetic study showed that the fluoxetine has significantly reduced the expression level of tumor necrosis factor-α, nuclear factor κβ, and induced nitric oxide synthase in comparison with the untreated LPC group. Also, the fluoxetine treatment has enhanced the expression level of the forkhead box P3 (FOXP3) gene in comparison with the untreated group. Fluoxetine has increased the expression level of myelination and neurotrophic genes such as myelin basic protein (MBP), oligodendrocyte transcription factor 2 (OLIG2), and brain-derived neurotrophic factor (BDNF). The outcomes demonstrated that fluoxetine reduces inflammation and strengthens the endogenous myelination in the LPC-induced demyelination model; however, supplementary studies are required for specifying the details of its mechanisms.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.294
Teacher spread0.269 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

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