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Record W2003119816 · doi:10.2217/14796678.4.4.399

Drawbacks to Stem Cell Therapy in Cardiovascular Diseases

2008· article· en· W2003119816 on OpenAlexaff
Chao‐Hung Wang, Wen‐Jin Cherng, Subodh Verma

Bibliographic record

VenueFuture Cardiology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineStem cellStem-cell therapyMesenchymal stem cellCell therapyEmbryonic stem cellCancer researchGenetic enhancementBioinformaticsPathologyCell biologyBiology

Abstract

fetched live from OpenAlex

Stem cells seem to have unlimited potential for repairing injured tissues derived from cardiovascular diseases. Much as the initial euphoria over preclinical models has ushered in some skepticism, several reports have advised caution against over exuberance, as cellular therapy has both theoretical and reported safety concerns. Embryonic stem cells, skeletal myoblasts, bone marrow-derived stem cells and mesenchymal stem cells are current candidates for cell therapy in end-stage cardiovascular diseases. However, before large-scale clinical trials can take place, a few safety concerns have to be clarified, such as atherogenesis, postangioplasty or stenting restenosis, tumorigenesis, stem cell metastasis, stem cell-mobilized cytokine-related complications and arrhythmogenesis. In this review, potential ways to overcome these issues are discussed, including medical and gene manipulations, dedicated cell-purification techniques, antiarrhythmic cell therapy design, and new concepts such as using natural constructs. With these safety issues under control, stem cell therapy still has a promising future in the next decade.

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 score0.742
Threshold uncertainty score0.786

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 head0.241
Teacher spread0.232 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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