Cerebrospinal fluid proteins in idiopathic intracranial hypertension: An exploratory SWATH proteomics analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The pathogenesis of idiopathic intracranial hypertension (IIH) is currently poorly understood. This exploratory study aimed to identify potential cerebrospinal fluid (CSF) biomarkers in IIH cases compared to controls using SWATH-MS proteomics approach. EXPERIMENTAL DESIGN: CSF samples were collected prospectively from IIH cases and control subjects which were subjected to SWATH-MS based untargeted proteomics. Proteins with fold change > 1.5 or < 0.67 and p-value < 0.05 were considered significantly differentially expressed. Data are available via ProteomeXchange with identifier PXD027751. Statistical analysis was conducted in R version 3.6.2. RESULTS: We included CSF samples from 33 subjects, consisting of 13 IIH cases and 20 controls. A total of 262 proteins were identified in Proteinpilot search. Through SWATH analysis, we quantified 232 proteins. We observed 37 differentially expressed proteins between the two groups with 24 upregulated and 13 downregulated proteins. There were two differential proteins among overweight versus non-overweight IIH cases. Network for 23 proteins was highly connected in the interaction analysis. CONCLUSIONS AND CLINICAL RELEVANCE: Neurosecretory, neuroendocrine, and inflammatory proteins were predominantly involved in causing IIH. This exploratory study served as a platform to identify 37 differentially expressed proteins in IIH and also showed significant differences between overweight and non-overweight IIH patients.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it