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Record W2626471464 · doi:10.15173/m.v1i22.817

Human Enteric Glial Cells Alleviate Damaged Adult Sensory Neurons in Rats

2013· article· en· W2626471464 on OpenAlexaffvenue
Dhara Shah, Cai Jiang, Kiran Reddy, Caixin Su, Shucui Jiang

Bibliographic record

VenueThe Meducator · 2013
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSensory systemNeuroscienceBiologyMedicine

Abstract

fetched live from OpenAlex

Spinal cord injury affects millions across the globe. Little is known regarding the cellular mechanism of injury and, unfortunately, there are few viable treatment options. One potential option is the transplantation of peripheral nerves into the site of injury. The complicating factor is that the peripheral nervous system is not readily accessible, and thus the procedure introduces the risk of disrupting the function of other areas. However, this risk is minimized if the nerves are extracted from the enteric system, which is embedded in the lining of the gastrointestinal tract. This system bears similarities to the central nervous system, has remarkable plasticity, and releases growth factors that not only facilitate regeneration of neurons but also protect the enteric nervous system from damage. Previous research shows that rat enteric glial cells induce regeneration in rodent neurons in vivo with a crushed spinal cord, and in vitro to dorsal root ganglia treated with semaphorin-3A to mimic spinal cord injury. We examined whether human enteric glia demonstrate similar effects in vitro on rodent dorsal root ganglia. Our experiments to date show that this treatment is viable, emphasizing its use in clinical trials. The success of this technique is largely due to the fact that the donor cells originate from the host, which minimizes the chance of rejection.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.897

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)0.0010.001

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 head0.020
GPT teacher head0.267
Teacher spread0.247 · 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 designObservational
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
Published2013
Admission routes2
Has abstractyes

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