MétaCan
Menu
Back to cohort
Record W1910742191 · doi:10.1139/cjpp-2014-0468

Stem cell therapy for cardiac regeneration: hits and misses

2015· review· en· W1910742191 on OpenAlexafffundvenue
Jagjit Padda, Glen Lester Sequiera, Niketa Sareen, Sanjiv Dhingra

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsSt. Boniface Hospital
FundersH2020 Marie Skłodowska-Curie ActionsHospital Research FoundationManitoba Medical Service Foundation
KeywordsReprogrammingRegeneration (biology)MedicineEmbryonic stem cellStem cellStem-cell therapyRegenerative medicineClinical trialBioinformaticsIntensive care medicineNeuroscienceCellPathologySurgeryTransplantationBiologyCell biologyGenetics

Abstract

fetched live from OpenAlex

Cardiac injury and loss of cardiomyocytes is a causative as well as a resultant condition of cardiovascular disorders, which are the leading cause of death throughout the world. This loss of cardiomyocytes cannot be completely addressed through the currently available drugs being administered, which mainly function only in relieving the symptoms. There is a huge potential being investigated for regenerative and cell replacement therapies through recruiting stem cells of various origins namely embryonic, reprogramming/induction, and adult tissue. These sources are being actively studied for translation to clinical scenarios. In this review, we attempt to discuss some of these promising scenarios, including the clinical trials and the obstacles that need to be overcome, and hope to address the direction in which stem cell therapy is heading.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.052
GPT teacher head0.346
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicPluripotent Stem Cells ResearchFrench-language works237,207