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Record W2125917793 · doi:10.1017/s1464793106007068

Human cell type diversity, evolution, development, and classification with special reference to cells derived from the neural crest

2006· review· en· W2125917793 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiological reviews/Biological reviews of the Cambridge Philosophical Society · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCell typeBiologyNeural crestEvolutionary biologyComputational biologyCellGeneticsEmbryo

Abstract

fetched live from OpenAlex

Metazoans are composed of a finite number of recognisable cell types. Similar to the relationship between species and ecosystems, knowledge of cell type diversity contributes to studies of complexity and evolution. However, as with other units of evolution, the cell type often resists definition. This review proposes guidelines for characterising cell types and discusses cell homology and the various developmental pathways by which cell types arise, including germ layers, blastemata (secondary development/neurulation), stem cells, and transdifferentiation. An updated list of cell types is presented for a familiar, albeit overlooked model taxon, adult Homo sapiens, with 411 cell types, including 145 types of neurons, recognised. Two methods for organising these cell types are explored. One is the artificial classification technique, clustering cells using commonly accepted criteria of similarity. The second approach, an empirical method modeled after cladistics, resolves the classification in terms of shared features rather than overall similarity. While the results of each scheme differ, both methods address important questions. The artificial classification provides compelling (and independent) support for the neural crest as the fourth germ layer, while the cladistic approach permits the evaluation of cell type evolution. Using the cladistic approach we observe a correlation between the developmental and evolutionary origin of a cell, suggesting that this method is useful for predicting which cell types share common (multipotential) progenitors. Whereas the current effort is restricted by the availability of phenotypic details for most cell types, the present study demonstrates that a comprehensive cladistic classification is practical, attainable, and warranted. The use of cell types and cell type comparative classification schemes has the potential to offer new and alternative models for therapeutic evaluation.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.154
GPT teacher head0.315
Teacher spread0.161 · 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