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Spatial Patterning of Scleral Papillae in the Embryonic Chicken Eye

2018· article· en· W3175004230 on OpenAlexafffundabout
Jennifer L. Giffin, Molly G. Hayes, Daniel D. T. Andrews, Nicholas W. Zinck, Tamara A. Franz‐Odendaal

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsDalhousie UniversityMount Saint Vincent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScleraAnatomyBiologyHedgehogEmbryoEmbryogenesisCell biologyGenetics

Abstract

fetched live from OpenAlex

The anterior portion of the eye in birds is supported by a ring of bony elements within the sclera, constituting the scleral ossicles. These intramembranous bones are induced by a series of transient papillae in the overlying conjunctival epithelium during embryonic development. A well‐defined spatiotemporal pattern of formation is followed, resulting in a complete circle of 13–16 evenly‐spaced papillae per eye in the chicken embryo. The regular distribution and variable number of papillae in this system give it a strong similarity to other reaction‐diffusion models of patterning, such as feather and carapace formation, in which short‐range activation is coupled with long‐range inhibition. Therefore, the objective of this study is to investigate whether scleral papillae are formed through a reaction‐diffusion mechanism in the embryonic chicken eye. To carry out this study, chicken embryos at Hamburger and Hamilton stages 28–34 (5.5–8 days post fertilization) were collected, corresponding to the induction and formation of a complete set of scleral papillae. Quantitative morphometrical analyses were performed on dissected eyes, confirming that while eye size increases throughout development, the spacing between the papillae does not. Computer modelling using the Meinhardt‐Gierer equation indicates that scleral papillae development likely follows the typical Turing mechanism of reaction‐diffusion pattern formation. Quantitative PCR on discrete papillary and interpapillary regions will enable us to study the interactions of known signalling molecules including Hedgehog (Hh), Bone Morphogenic Proteins (BMPs), Fibroblast Growth Factors (FGFs) and Wingless (Wnt). The results of this study provide considerable insight into the spacing pattern of scleral papillae. A reaction‐diffusion mechanism explains the ability of scleral papillae to maintain their even distribution regardless of differences in numbers among species or between left and right eyes in the same individual. Identifying the signalling pathways implicated in scleral papillae spacing would further enhance our understanding of not only the position, but also the size and shape of the scleral ossicles as compensation for gaps in the sclerotic ring is known to occur. Support or Funding Information This research was funded by the Natural Sciences and Engineering Research Council of Canada. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.279
Teacher spread0.253 · 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 designObservational
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".

Quick stats

Citations1
Published2018
Admission routes3
Has abstractyes

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