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Plasticity of enteric nerve functions in the inflamed and postinflamed gut

2009· review· en· W2021282396 on OpenAlexaff
Gary M. Mawe, Derek S. Strong, Keith A. Sharkey

Bibliographic record

VenueNeurogastroenterology & Motility · 2009
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsNeuroscienceEnteric nervous systemInflammationNeuroplasticityIrritable bowel syndromeSensationAfferentNeurophysiologyMedicineBiologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Inflammation of the gut alters the properties of the intrinsic and extrinsic neurons that innervate it. While the mechanisms of neuroplasticity differ amongst the inflammatory models that have been used, amongst various regions of the gut, and between intrinsic vs extrinsic neurons, a number of consistent features have been observed. For example, intrinsic and extrinsic primary afferent neurons become hyperexcitable in response to inflammation, and interneuronal synaptic transmission is facilitated in the enteric circuitry. These changes contribute to alterations in gut function and sensation in the inflamed bowel as well as functional disorders, and these changes persist for weeks beyond the point at which detectable inflammation has subsided. Thus, gaining a more thorough understanding of the mechanisms responsible for inflammation-induced neuroplasticity, and strategies to reverse these changes are clinically relevant goals. The purpose of this review is to summarize our current knowledge regarding neurophysiological changes that occur during and following intestinal inflammation, and to identify and address gaps in our knowledge regarding the role of enteric neuroplasticity in inflammatory and functional gastrointestinal disorders.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.036
GPT teacher head0.309
Teacher spread0.273 · 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 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

Citations90
Published2009
Admission routes1
Has abstractyes

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