Immunolocalization of skeletal matrix proteins in tissue and mineral of the coral <i>Stylophora pistillata</i>
Bibliographic record
Abstract
The precipitation and assembly of calcium carbonate skeletons by stony corals is a precisely controlled process regulated by the secretion of an ECM. Recently, it has been reported that the proteome of the skeletal organic matrix (SOM) contains a group of coral acid-rich proteins as well as an assemblage of adhesion and structural proteins, which together, create a framework for the precipitation of aragonite. To date, we are aware of no report that has investigated the localization of individual SOM proteins in the skeleton. In particular, no data are available on the ultrastructural mapping of these proteins in the calcification site or the skeleton. This information is crucial to assessing the role of these proteins in biomineralization. Immunological techniques represent a valuable approach to localize a single component within a calcified skeleton. By using immunogold labeling and immunohistochemical assays, here we show the spatial arrangement of key matrix proteins in tissue and skeleton of the common zooxanthellate coral, Stylophora pistillata. To our knowledge, our results reveal for the first time that, at the nanoscale, skeletal proteins are embedded within the aragonite crystals in a highly ordered arrangement consistent with a diel calcification pattern. In the tissue, these proteins are not restricted to the calcifying epithelium, suggesting that they also play other roles in the coral's metabolic pathways.
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 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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".