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Record W3130117977 · doi:10.3390/biomedicines9020205

Loss of parla Function Results in Inactivity, Olfactory Impairment, and Dopamine Neuron Loss in Zebrafish

2021· article· en· W3130117977 on OpenAlexafffund
Rawan Merhi, Michael Kalyn, Amanda J. Zhu-Pawlowsky, Marc Ekker

Bibliographic record

VenueBiomedicines · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZebrafishDopamineLoss functionOlfactory systemBiologyNeuroscienceBiochemistry

Abstract

fetched live from OpenAlex

The presenilin-associated rhomboid-like (PARL) gene was found to contribute to mitochondrial morphology and function and was linked to familial Parkinson’s disease (PD). The PARL gene product is a mitochondrial intramembrane cleaving protease that acts on a number of mitochondrial proteins involved in mitochondrial morphology, apoptosis, and mitophagy. To date, functional and genetic studies of PARL have been mainly performed in mammals. However, little is known about PARL function and its role in dopaminergic (DA) neuron development in vertebrates. The zebrafish genome comprises two PARL paralogs: parla and parlb. Here, we established a loss-of-function mutation in parla via CRISPR/Cas9-mediated mutagenesis. We examined DA neuron numbers in the adult brain and expression of genes associated with DA neuron function in larvae and adults. We show that loss of parla function results in loss of DA neurons, mainly in the olfactory bulb. Changes in the levels of tyrosine hydroxylase transcripts supported this neuronal loss. Expression of fis1, a gene involved in mitochondrial fission, was increased in parla mutants. Finally, we showed that loss of parla function translates into impaired olfaction and altered locomotion parameters. These results suggest a role for parla in the development and/or maintenance of DA neuron function in zebrafish.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.018
GPT teacher head0.285
Teacher spread0.267 · 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

Citations17
Published2021
Admission routes2
Has abstractyes

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