Diverse Species-Specific Phenotypic Consequences of Loss of Function <i>Sorting Nexin 14</i> Mutations
Bibliographic record
Abstract
Abstract Mutations in the SNX14 gene cause spinocerebellar ataxia, autosomal recessive 20 (SCAR20) in both humans and dogs. SCAR20 is understood to involve subcellular disruption to autophagy and lipid metabolism. Previously reported studies on the phenotypic consequences of SNX14 mutations have been limited to in vitro investigation of patient-derived dermal fibroblasts, laboratory engineered cell lines and developmental analysis of zebrafish morphants. In addition, studies have investigated the biochemical roles of SNX14 homologues Snz ( Drosophila ) and Mdm1 (yeast) which have demonstrated an important role during lipid biogenesis. This study investigates the impact of constitutive Snx14 mutations in laboratory species: mice and zebrafish. Loss of SNX14 in mice was found to be embryonic lethal around mid-gestation. This is due to placental pathology that involves severe disruption to syncytiotrophoblast cell differentiation. Zebrafish carrying a homozygous, maternal zygotic snx14 genetic loss-of-function mutation contrasts with other vertebrates, being both viable and anatomically normal. Whilst no obvious behavioural effects were observed, elevated levels of neutral lipids and phospholipids resemble previously reported effects on lipid homeostasis in other species. The biochemical role of SNX14 therefore appears largely conserved through evolution while the overall consequences of loss of function varies considerably between species. New mouse and zebrafish models therefore provide valuable insights into the functional importance of SNX14 with distinct opportunities for investigating its cellular and metabolic function in vivo .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".