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Record W4298080306 · doi:10.1101/2022.09.28.509973

<i>kcna1a</i> mutant zebrafish as a model of episodic ataxia type 1 and epilepsy

2022· preprint· en· W4298080306 on OpenAlexafffund
Deepika Dogra, Paola L. Meza‐Santoscoy, Renata Rehak, Cristiane Lucia Rodriguez de la Hoz, Cezar Gavrilovici, Kingsley Ibhazehiebo, Jong M. Rho, Deborah M. Kurrasch

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersFondation Brain CanadaCreighton University
KeywordsZebrafishEpilepsyAtaxiaNeuroscienceBiologyCarbamazepineGeneticsGene

Abstract

fetched live from OpenAlex

ABSTRACT Objective KCNA1 mutations are associated with a rare neurological movement disorder known as episodic ataxia type 1 (EA1), with epilepsy as a common comorbidity. Current medications only provide partial relief to ataxia and/or seizures, making new drugs needed. Here, we investigate the utility of zebrafish kcna1a −/− as a model of EA1 with epilepsy by characterizing its phenotype and comparing the efficacy of the first-line therapy carbamazepine in kcna1a −/− zebrafish to Kcna1 −/− rodents. Methods We used CRISPR/Cas9 mutagenesis to introduce a mutation in the sixth segment of the zebrafish Kcna1 protein. Behavioral and electrophysiological assays were performed on kcna1a −/− larvae to assess ataxia- and epilepsy-related phenotypes. We also carried out real-time qPCRs to measure the transcript levels of brain hyperexcitability markers and bioenergetic profiling of kcna1a −/− larvae to evaluate their metabolic health. Carbamazepine efficacy was tested using behavioral assessments in kcna1a −/− zebrafish and seizure frequency in Kcna1 −/− mice. Results kcna1a −/− zebrafish showed uncoordinated movements and locomotor deficits. The mutants also exhibited impaired startle responses when exposed to light-dark flashes and acoustic stimulation. Extracellular field recordings and upregulated fosab transcript levels showed hyperexcitability of the kcna1a −/− brain. Further, vglut2a and gad1b transcript levels were altered, indicative of neuronal excitatory/inhibitory imbalance in the kcna1a −/− brain. Metabolic health was also compromised in kcna1a −/− as seen by a significant reduction in measures of cellular respiration. Notably, carbamazepine reduced the impaired startle response in kcna1a −/− zebrafish but had no effect on the seizure frequency in Kcna1 −/− mice, suggesting that this EA1 zebrafish model might better translate to human efficacy compared to rodents. Significance We conclude that zebrafish kcna1a −/− larvae show ataxia and epilepsy-related phenotypes and that they are responsive to carbamazepine treatment, consistent with EA1 patients. This study supports the notion that these zebrafish disease models can be useful for drug screening as well as studying the underlying disease biology. KEY POINTS Zebrafish kcna1a −/− larvae display dynamic behavioral changes, along with ataxia-like uncoordinated movements and brain hyperexcitability kcna1a −/− larvae have dysfunctional neuronal excitatory/inhibitory balance and perturbed metabolic health Similar to its effectiveness in patients, carbamazepine treatment improves behavioral deficits in kcna1a −/− larvae

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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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