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Record W4393507463 · doi:10.1007/s12264-024-01193-3

The Neurovascular Unit Dysfunction in the Molecular Mechanisms of Epileptogenesis and Targeted Therapy

2024· article· en· W4393507463 on OpenAlexaff
Xiuxiu Liu, Ying Zhang, Yanming Zhao, Qian Zhang, Feng Han

Bibliographic record

VenueNeuroscience Bulletin · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Jiangsu ProvinceGovernment of Jiangsu Province
KeywordsEpileptogenesisEpilepsyNeurovascular bundleNeuroscienceMedicineIntervention (counseling)BioinformaticsPsychologyPsychiatryPathologyBiology

Abstract

fetched live from OpenAlex

Epilepsy is a multifaceted neurological syndrome characterized by recurrent, spontaneous, and synchronous seizures. The pathogenesis of epilepsy, known as epileptogenesis, involves intricate changes in neurons, neuroglia, and endothelium, leading to structural and functional disorders within neurovascular units and culminating in the development of spontaneous epilepsy. Although current research on epilepsy treatments primarily centers around anti-seizure drugs, it is imperative to seek effective interventions capable of disrupting epileptogenesis. To this end, a comprehensive exploration of the changes and the molecular mechanisms underlying epileptogenesis holds the promise of identifying vital biomarkers for accurate diagnosis and potential therapeutic targets. Emphasizing early diagnosis and timely intervention is paramount, as it stands to significantly improve patient prognosis and alleviate the socioeconomic burden. In this review, we highlight the changes and molecular mechanisms of the neurovascular unit in epileptogenesis and provide a theoretical basis for identifying biomarkers and drug targets.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.039
GPT teacher head0.304
Teacher spread0.265 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations20
Published2024
Admission routes1
Has abstractyes

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