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Record W4406532660 · doi:10.1101/2025.01.15.633258

Stimulus-driven cerebrospinal fluid dynamics is impaired in glaucoma patients

2025· preprint· en· W4406532660 on OpenAlexfundno aff
Ji Won Bang, Carlos Parra, Kevin Yu, Hyun Seo Lee, Gadi Wollstein, Joel S. Schuman, Kevin C. Chan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
FundersNational Institutes of HealthNYU Grossman School of MedicineYork UniversityBrightFocus FoundationResearch to Prevent Blindness
KeywordsGlaucomaCerebrospinal fluidStimulus (psychology)NeuroscienceMedicineStimulationHomeostasisInternal medicinePsychology

Abstract

fetched live from OpenAlex

Abstract Cerebrospinal fluid (CSF) dynamics, driven by sensory stimulation-induced neuronal activity, is crucial for maintaining homeostasis and clearing metabolic waste. However, it remains unclear whether such CSF flow is impaired in age-related neurodegenerative diseases of the visual system. This study addresses this gap by examining CSF flow during visual stimulation in glaucoma patients and healthy older adults using functional magnetic resonance imaging. The findings reveal that in glaucoma, CSF inflow becomes decoupled from visually evoked blood-oxygenation-level-dependent (BOLD) response. Furthermore, stimulus-locked CSF patterns, characterized by decreases following stimulus onset and increases after offset, diminish as glaucoma severity worsens. Mediation analysis suggests that this flattened CSF pattern is driven by a flatter BOLD slope, resulting in a shallower CSF trough and a reduced rebound. These findings unveil a novel pathophysiological mechanism underlying disrupted stimulation-driven CSF dynamics in glaucoma and highlight potential in vivo biomarkers for monitoring CSF in the glaucomatous brain.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicGlaucoma and retinal disorders→French-language works237,207→