Homeobox genes in vertebrate forebrain development and disease
Bibliographic record
Abstract
Homeobox genes are an evolutionarily conserved class of transcription factors that are key regulators of developmental processes such as regional specification, patterning, migration and differentiation. In both mouse and humans, the developing forebrain is marked by distinct boundaries of homeobox gene expression at different developmental time points. These genes regulate the patterning of the forebrain along the dorsal/ventral and rostral/caudal axes and are also essential for the differentiation of specific neuronal subtypes. Inhibitory interneurons that arise from the ganglionic eminences and migrate tangentially to the neocortex and hippocampus are dramatically affected by mutations in several homeobox genes. In this review, we discuss the identification, expression patterns, loss- and/or gain-of-function models, and confirmed transcriptional targets for a set of homeobox genes required for the correct development of the forebrain in the mouse. In humans, mutations of homeobox genes expressed in the forebrain have been shown to result in mental retardation, epilepsy or movement disorders. The number of homeobox genes currently linked to human nervous system disease is surprisingly low, perhaps reflecting the essential functions of these genes throughout embryogenesis or the degree of functional redundancy during central nervous system development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".