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Record W1990055281 · doi:10.2174/092986712803833218

Non-Viral Engineering of Skin Precursor-Derived Schwann Cells for Enhanced NT-3 Production in Adherent and Microcarrier Culture

2012· article· en· W1990055281 on OpenAlexafffund
Antos Shakhbazau, Dzmitry Shcharbin, Maria Bryszewska, Ranjan Kumar, Holly Wobma, Michael S. Kallos, Н. В. Гончарова, Ihar Seviaryn, С. М. Космачева, М. П. Потапнев, Rajiv Midha

Bibliographic record

VenueCurrent Medicinal Chemistry · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta InnovatesIntegra LifeSciencesHotchkiss Brain Institute, University of CalgaryUniversity of Calgary
KeywordsMicrocarrierCell cultureCell biologyRecombinant DNAVirologyChemistryMolecular biologyBiologyBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

Genetic engineering of stem cells and their derivatives has the potential to enhance their regenerative capabilities. Here, dendrimer- and lipofection-based approaches were used for non-viral neurotrophin-3 (NT-3) over-expression in Schwann cells differentiated from skin precursors (SKP-SCs). A variety of dendrimers were first tested for transfection efficiency on HEK 293T cells, with PAMAMNH2 G4 found most effective and used subsequently for SKP-SCs transfection. Plasmid-based expression resulted in increased NT-3 release from SKP-SCs in both adherent and microcarrier-based culture. In a proof-of-concept study, the microcarrier/SKP-SCs were implanted into the injured nerve, and transfected cells were shown to detach, integrate into the nerve tissue and associate with regenerating axons. Virus-free systems for transient neurotrophin expression are a feasible and biologically safe option to increase the therapeutic value of stem cells and stem cell-derived cells in nerve repair strategies. Further work to develop bioprocesses for expansion of SKP-SCs on microcarriers in bioreactors is still needed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.457

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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 designBench or experimental
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

Citations23
Published2012
Admission routes2
Has abstractyes

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