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Record W1983868412 · doi:10.1093/brain/awh570

Histological analysis of fetal dopamine cell suspension grafts in two patients with Parkinson's disease gives promising results

2005· letter· en· W1983868412 on OpenAlexaboutno aff
Deniz Kirik, Anders Björklund

Bibliographic record

VenueBrain · 2005
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
Fundersnot available
KeywordsParkinson's diseaseDopamineSuspension cultureDiseaseMedicineFetusFetal Tissue TransplantationPathologyCellNeuroscienceInternal medicineBiologyCell culturePregnancyBiochemistry

Abstract

fetched live from OpenAlex

In this issue of Brain (pages 1498–1510), Mendez and collaborators report the postmortem analysis of brains from two patients with Parkinson's disease who had received grafts of brain tissue dissected from the developing ventral mesencephalic region, obtained from 6- to 9-week-old aborted fetuses, which is known to contain the appropriate type of dopamine neurones lost in these patients as a result of their disease. The most important aspect of this report is the fact that this is the first time we have been able to evaluate the outcome of so-called cell suspension grafts, a more refined cell preparation technique than has been used in the previously reported autopsy cases. Since 1987, when the first clinical neural transplantation trials were initiated, some 350 Parkinson's disease patients have received intrastriatal grafts of human fetal mesencephalic tissue (Lindvall and Bjorklund, 2004; Winkler et al ., 2005). However, there has so far been no attempt to standardize the way in which the transplantation is carried out at different centres. Almost all aspects of tissue handling and storage, and of graft preparation, have differed from one centre to another (Winkler et al ., 2005). In several open-label trials, such as those performed in Lund, Paris and Halifax, grafts prepared as cell suspensions have been used, whereas other centres …

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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.

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

Citations11
Published2005
Admission routes1
Has abstractyes

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