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Record W3004195396 · doi:10.1007/s12015-020-09955-y

Thymus Regeneration and Future Challenges

2020· review· en· W3004195396 on OpenAlexfundno aff
Valentin P. Shichkin, Mariastefania Antica

Bibliographic record

VenueStem Cell Reviews and Reports · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
FundersEuropean Regional Development FundConsejo Superior de Investigaciones CientíficasTerry Fox Foundation
KeywordsRegeneration (biology)Stem cellInduced pluripotent stem cellIn vivoBiologyIn vitroCell biologyImmunologyBiotechnologyBiochemistryEmbryonic stem cell

Abstract

fetched live from OpenAlex

Thymus regenerative therapy implementation is severely obstructed by the limited number and expansion capacity in vitro of tissue-specific thymic epithelial stem cells (TESC). Current solutions are mostly based on growth factors that can drive differentiation of pluripotent stem cells toward tissue-specific TESC. Target-specific small chemical compounds represent an alternative solution that could induce and support the clonal expansion of TESC and reversibly block their differentiation into mature cells. These compounds could be used both in the composition of culture media designed for TESC expansion in vitro, and in drugs development for thymic regeneration in vivo. It should allow reaching the ultimate objective - autologous thymic tissue regeneration in paediatric patients who had their thymus removed in the course of cardiac surgery.

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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.043
GPT teacher head0.303
Teacher spread0.261 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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