Altered gene expression in slc4a11−/− mouse cornea highlights SLC4A11 roles
Bibliographic record
Abstract
Abstract SLC4A11 is a H+/NH3/water transport protein, of corneal endothelial cells. SLC4A11 mutations cause congenital hereditary endothelial dystrophy and some cases of Fuchs endothelial corneal dystrophy. To probe SLC4A11’s roles, we compared gene expression in RNA from corneas of 17-week-old slc4a11−/− (n = 3) and slc4a11+/+ mice (n = 3) and subjected to RNA sequencing. mRNA levels for a subset of genes were also assessed by quantitative real-time reverse transcription PCR (qRT RT-PCR). Cornea expressed 13,173 genes, which were rank-ordered for their abundance. In slc4a11−/− corneas, 100 genes had significantly altered expression. Abundant slc14a1 expression, encoding the urea transporter UT-A, suggests a significant role in the cornea. The set of genes with altered expression was subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, revealing that alterations clustered into extracellular region, cytoskeleton, cell adhesion and plasma membrane functions. Gene expression changes further clustered into classes (with decreasing numbers of genes): cell fate and development, extracellular matrix and cell adhesion, cytoskeleton, ion homeostasis and energy metabolism. Together these gene changes confirm earlier suggestions of a role of SLC4A11 in ion homeostasis, energy metabolism, cell adhesion, and reveal an unrecognized SLC4A11 role in cytoskeletal organization.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".