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Record W2400430568 · doi:10.1139/cjpp-2016-0052

The functional morphology and role of cardiac telocytes in myocardium regeneration

2016· article· en· W2400430568 on OpenAlexvenueno aff
Ivan Varga, Ľuboš Danišovič, Ján Kyselovič, Andrea Gažová, Peter Musil, Michal Miko, Štefan Polák

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2016
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsnot available
FundersAgentúra na Podporu Výskumu a Vývoja
KeywordsStem cellRegeneration (biology)Regenerative medicineCell biologyUltrastructureCardiac muscleBiologyMyocytePathologyNeuroscienceAnatomyMedicine

Abstract

fetched live from OpenAlex

Key morphological discoveries in recent years have included the discovery of new cell populations inside the heart called cardiac telocytes. These newly described cells of the connective tissue have extremely long cytoplasmic processes through which they form functionally connected three-dimensional networks that connect cells of the immune system, nerve fibers, cardiac stem cells, and cardiac muscle cells. Based on their functions, telocytes are also referred to as "connecting cells" or "nurse cells" for cardiac progenitor stem cells. In this critical review, we provide a summary of the latest research on cardiac telocytes localized in all layers of the heart - from the historical background of their discovery, through ultrastructural, immunohistochemical, and functional characterizations, to the application of this knowledge to the fields of cardiology, stem cell research, and regenerative medicine.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations30
Published2016
Admission routes1
Has abstractyes

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