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Record W4390909491 · doi:10.1139/cjpp-2023-0202

Stem cell therapy for cardiac regeneration: past, present, and future

2024· article· en· W4390909491 on OpenAlexafffundvenue
Jaideep Kaur Gill, Sargun Kaur Rehsia, Elika Verma, Niketa Sareen, Sanjiv Dhingra

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2024
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health Research
KeywordsStem cellRegenerative medicineStem-cell therapyInduced pluripotent stem cellMedicineEmbryonic stem cellRegeneration (biology)Cell therapyIntensive care medicineTransplantationNeuroscienceBioinformaticsBiologySurgeryCell biology

Abstract

fetched live from OpenAlex

Cardiac disorders remain the leading cause of mortality worldwide. Current clinical strategies, including drug therapy, surgical interventions, and organ transplantation offer limited benefits to patients without regenerating the damaged myocardium. Over the past decade, stem cell therapy has generated a keen interest owing to its unique self-renewal and immune privileged characteristics. Furthermore, the ability of stem cells to differentiate into specialized cell types, has made them a popular therapeutic tool against various diseases. This comprehensive review provides an overview of therapeutic potential of different types of stem cells in reference to cardiovascular diseases. Furthermore, it sheds light on the advantages and limitations associated with each cell type. An in-depth analysis of the challenges associated with stem cell research and the hurdles for its clinical translation and their possible solutions have also been elaborated upon. It examines the controversies surrounding embryonic stem cells and the emergence of alternative approaches, such as the use of induced pluripotent stem cells for cardiac therapeutic applications. Overall, this review serves as a valuable resource for researchers, clinicians, and policymakers involved in the field of regenerative medicine, guiding the development of safe and effective stem cell-based therapies to revolutionize patient care.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.267

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 head0.015
GPT teacher head0.281
Teacher spread0.266 · 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 designNot applicable
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

Citations18
Published2024
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Physiology and PharmacologySame topicTissue Engineering and Regenerative MedicineFrench-language works237,207