Analysis of Xenopus laevis RECK and Its Relationship to Other Vertebrate RECK Sequences
Bibliographic record
Abstract
Aims: Reversion-inducing cysteine-rich protein with Kazal motifs (RECK) is a membrane-anchored protein that regulates cell migration by both inhibiting matrix metalloproteinases and modulating cellular pathways. Our study is the first to clone and examine the expression pattern of reck during early Xenopus laevis development.Study Design: Expression and sequence analysis.Place and Duration of Study: Department of Biology, University of Western Ontario, 2 years.Methodology: Xenopus laevis RECK cDNA was sequenced and used to make probes to analyze RECK temporal and spatial expression using PCR and in situ hybridization respectively. The X. laevis sequence was also compared to a breadth of vertebrate and a few invertebrate RECK amino acid sequences to ascertain conserved regions and domains that may be present in all vertebrate and other animal species.Results: Semi-quantitative PCR, whole mount in situ hybridization, and immunohistochemistry were used to examine the expression pattern of reck during early X. laevis development. reck expression is low during gastrulation but increases during neurulation and throughout organogenesis. RECK is also present in neural and vascular structures of the X. laevis embryo, consistent with its role in other vertebrates. The predicted full-length X. laevis RECK amino acid sequence was found to be highly conserved with other RECK proteins. All RECK proteins are found to have 3 inhibitory Kazal motifs, where the first is the most conserved in all animals. Furthermore, all RECK proteins contain 6 conserved cysteines in each of 5 knot motifs, with the 3rdknot being the most highly conserved. Knot domains were more conserved amongst birds, than amongst herptiles and mammalians.Conclusion: The conservation of expression and sequence suggest that RECK has a very conserved function in vertebrates and possibly all animals.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".