Edar and Troy signalling pathways act redundantly to regulate initiation of hair follicle development
Bibliographic record
Abstract
The development of ectodermal organs requires signalling by ectodysplasin (Eda), a tumor necrosis factor (TNF) family member, its receptor Edar and downstream activation of the nuclear factor kappaB (NF-kappaB) transcription factor. In humans, mutations in the Eda pathway components cause hypohidrotic ectodermal dysplasia, a syndrome characterized by missing teeth, sparse hair and defects in sweat glands. It has been postulated that Eda acts redundantly with another TNF pathway to regulate ectodermal organogenesis. A potential candidate is Troy (or TNFRSF19 or Taj), a TNF receptor which is homologous with Edar in its ligand-binding domain, and is expressed in an overlapping pattern. We have characterized Troy null mice and crossed them with Eda-deficient mice. Single Troy mutants had no defects in ectodermal organs. Analysis of the double mutants revealed an essential role for Troy in hair follicle development. In mice, hair follicles develop in three different waves. Only primary hair follicles are missing in Eda single mutants, whereas the compound mutants lacked also the follicles of the second wave, as well as all hair follicles in the middle of crown leading to focal alopecia. Assessment of NF-kappaB activity with a transgenic reporter construct indicated that Eda is the main activator of NF-kappaB signalling in developing skin appendages and surprisingly that the functional overlap of Troy and Eda signalling pathways is mediated by NF-kappaB independent pathways.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".