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Record W2922318829 · doi:10.1002/mus.26464

Impaired short‐ and long‐latency afferent inhibition in amyotrophic lateral sclerosis

2019· article· en· W2922318829 on OpenAlexaboutno aff
Bülent Çengiz, Halit Fidancı, Yeliz Kıyak Keçeli, Hande Baltacı, Reha Kuruoğlu

Bibliographic record

VenueMuscle & Nerve · 2019
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsnot available
FundersGazi Üniversitesi
KeywordsAmyotrophic lateral sclerosisTranscranial magnetic stimulationMedicineNeuroscienceMultiple sclerosisStimulationWristMontreal Cognitive AssessmentCognitionPhysical medicine and rehabilitationInternal medicinePsychologyCognitive impairmentAnatomyDisease

Abstract

fetched live from OpenAlex

INTRODUCTION: To test the hypothesis of impaired cholinergic activity in amyotrophic lateral sclerosis (ALS), we studied short- and long-latency afferent inhibition (SAI and LAI). METHODS: The ulnar nerve was stimulated at the wrist preceding transcranial magnetic stimulation (TMS), 21 ms for SAI and 200 ms for LAI, in 21 patients and 17 control subjects. Short-interval intracortical inhibition (SICI) and cognitive function was assessed in ALS patients using automatic threshold tracking and the Montreal Cognitive Assessment (MoCA). RESULTS: The SAI paradigm resulted in inhibition in all control subjects, whereas inhibition was observed in 13 of 21 (62%) patients. Mean SAI and LAI values were significantly reduced in ALS. No significant correlation existed between afferent inhibition and other neurophysiological data. The MoCA was normal in all but 1 patient. DISCUSSION: LAI and SAI are both impaired in ALS, probably unrelated to increased cortical excitability or cognitive dysfunction. Muscle Nerve 59:699-704, 2019.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score1.000

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)0.0010.000

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 head0.271
Teacher spread0.235 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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