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Stem cell‐based cell therapy for Huntington disease: A review

2007· review· en· W2019370476 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.

Bibliographic record

VenueNeuropathology · 2007
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsStem cellNeural stem cellStem-cell therapyEmbryonic stem cellMesenchymal stem cellHuntington's diseaseTransplantationMedicineCell therapyAdult stem cellNeuroscienceDiseasePathologyBiologyInternal medicineCell biology

Abstract

fetched live from OpenAlex

Huntington disease (HD) is a devastating neurodegenerative disorder and no proven medical therapy is currently available to mitigate its clinical manifestations. Although fetal neural transplantation has been tried in both preclinical and clinical investigations, the efficacy is not satisfactory. With the recent explosive progress of stem cell biology, application of stem cell-based therapy in HD is an exciting prospect. Three kinds of stem cells, embryonic stem cells, bone marrow mesenchymal stem cells and neural stem cells, have previously been utilized in cell therapy in animal models of neurological disorders. However, neural stem cells were preferably used by investigators in experimental HD studies, since they have a clear capacity to become neurons or glial cells after intracerebral or intravenous transplantation, and they induce functional recovery. In this review, we summarize the current state of cell therapy utilizing stem cells in experimental HD animal models, and discuss the future considerations for developing new therapeutic strategies using neural stem cells.

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)0.000
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 score0.972
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.369
Teacher spread0.249 · 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