MétaCan
Menu
← Back to cohort
Record W7132987484

Defining a neurotrophic factor concentration gradient to guide neurite outgrowth

2002· dissertation· W7132987484 on OpenAlexfundno aff
Xudong Cao

Bibliographic record

VenueTSpace · 2002
Typedissertation
Language
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersMinistère de l’Éducation, Gouvernement de l’OntarioUniversity of TorontoOntario Neurotrauma Foundation
KeywordsNeuriteAgaroseDorsal root ganglionNeurotrophic factorsNeurotrophinNerve growth factorCell cultureNeural tissue engineering
DOInot available

Abstract

fetched live from OpenAlex

Well-defined neurotrophic factor concentration gradients were prepared using a compartmented diffusion chamber. This model system was employed to study the chemotactic effect of neurotrophic factors to guide neurite outgrowth. The information obtained from this model system may provide insights into the designs of a biomimetic device to enhance nerve regeneration after spinal cord injuries. Specifically, by maintaining the concentrations in both the source and sink compartments constant (and different), a linear NGF concentration profile was achieved within the agarose membrane through which a steady state diffusion was established. The well-defined linear NGF concentration profile enabled the quantification of the minimum concentration gradient required to guide neurite outgrowth using PC12 cells as a model cell line for neurons. Furthermore, multiple concentration gradients of different neurotrophic factors were prepared using similar compartmented diffusion chambers. The synergistic guidance effect of multiple factors observed in this model system suggests that peripheral dorsal root ganglion cell neurite outgrowth can be guided over an extended distance. This result could warrant the incorporation of neurotrophic factor concentration gradient into a nerve regeneration device to guide and augment nerve fiber regeneration. Finally, in an attempt to translate the neurotrophic concentration gradient guidance into an artificial device that may enhance CNS regeneration, efforts were also made immobilize biomolecules in a three-dimensional agarose hydrogel using photoimmobilization. The improved photoimmobilization yield using the photoactive agarose gel approach, as a result of the enhanced interactions between the photoactive moieties and the agarose gel, represented a viable approach to immobilize biomolecules in 3D hydrogel matrices. This approach could also be further advanced to photoimmobilize biomolecule concentration gradients in situ.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.338
Teacher spread0.301 · 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 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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueTSpace→Same topicNerve injury and regeneration→French-language works237,207→