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Record W2927424015 · doi:10.21037/qims.2019.02.13

Differences in functional brain alterations driven by right or left facial nerve efferent dysfunction: Evidence from early Bell’s palsy

2019· article· en· W2927424015 on OpenAlexaboutno aff
Xiaowei Han, Haimei Li, Lei Du, Xiaochun Wang, Yijiang Zhu, Hongwei Yu, Tianbin Song, Shilong Sun, Runcai Guo, Jing Liu, Sumin Shi, Chao Fu, Wenwen Gao, Lu Zhang, Ran Yan, Guolin Ma

Bibliographic record

VenueQuantitative Imaging in Medicine and Surgery · 2019
Typearticle
Languageen
FieldMedicine
TopicFacial Nerve Paralysis Treatment and Research
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsBell's palsyEfferentFacial nervePalsyMedicineLeft and rightNeurosciencePsychologyAnatomyPathologyAfferent

Abstract

fetched live from OpenAlex

BACKGROUND: Bell's palsy is defined as idiopathic unilateral facial nerve palsy. Early Bell's palsy is characterized by emerging asymmetric motor conduction of the facial nerve and obvious imbalance of facial muscle movement, which can result in a substantial psychological impact on patients and trigger brain cortical functional reorganization. However, the differences between the brain functional alterations were driven by right or left facial nerve efferent dysfunction in patients with early Bell's palsy are not fully understood. The neuroimage study in patients with different-sided Bell's palsy in the early stage will help to understand the different mechanisms involved in functional integration driven by unilateral facial efferent nerve dysfunction and to provide the theoretical foundation for the choice of suitable treatment strategy. METHODS: Sixty-seven patients and 37 age- and sex-matched healthy controls were recruited to undergo resting-state functional magnetic resonance imaging (R-fMRI). Regional brain activity was analyzed by comparing the fractional amplitude of low-frequency fluctuations (fALFF) between right palsy and healthy control, left palsy and healthy control, and right and left palsy groups. The altered brain regions were further selected as seeds in subsequent functional connectivity (FC) analysis, and the correlations between the Toronto Facial Grading System (TFGS) scores and the connectivity alterations were also analyzed. RESULTS: The right and left Bell's palsy groups showed fALFF alterations compared with the healthy control group, and several brain regions with different fALFF values between the right and left palsy groups were identified. In the right palsy group, overall inter-regional FC increased in the right supramarginal gyrus (SMG), bilateral superior frontal gyrus (SFG), and left precentral gyrus (PreCG), compared with the left palsy group. Furthermore, the brain region pairs with higher FC in the right palsy group were left temporal pole of the superior temporal gyrus (TPOsup) and right SMG, left TPOsup and middle cingulate cortex (MCC), left TPOsup and left PreCG, right SMG and SFG, MCC and left PreCG, left and right SFG, and right SFG and left PreCG. In the right palsy group, the left TPOsup and PreCG showed a negative correlation with the TFGS score, while the right SFG and left PreCG showed a positive correlation with the TFGS scores. In the left palsy group, the left TPOsup and right SMG, and the right SMG and SFG region pairs showed a negative correlation with the TFGS score. CONCLUSIONS: The fALFF and FC analyses revealed the remodeling of different brain functional networks driven by right or left facial nerve efferent dysfunction in patients with early Bell's palsy. The reintegration mechanisms differed between patients with right and left Bell's palsy. Additionally, the severity of the disease showed different associations with altered FC.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.017
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.085
GPT teacher head0.352
Teacher spread0.267 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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