Primary Biliary Cholangitis Alters Functional Connections of the Brain's Deep Gray Matter
Bibliographic record
Abstract
OBJECTIVES: Fatigue, itch, depressed mood, and cognitive impairment significantly impact the quality of life of many patients with primary biliary cholangitis (PBC). Previous neuroimaging studies of non-hepatic diseases suggest that these symptoms are often associated with dysfunction of deep gray matter brain regions. We used resting-state functional magnetic resonance imaging (rsfMRI) to determine whether PBC patients exhibit altered functional connections of deep gray matter. METHODS: Twenty female non-cirrhotic PBC patients and 21 age/gender-matched controls underwent rsfMRI. Resting-state functional connectivity (rsFC) of deep gray matter brain structures (putamen, thalamus, amygdala, hippocampus) was compared between groups. Fatigue, itch, mood, cognitive performance, and clinical response to ursodeoxycholic acid (UDCA) were assessed, and their association with rsFC was determined. RESULTS: Relative to controls, PBC patients exhibited significantly increased rsFC between the putamen, thalamus, amygdala, and hippocampus, as well as with frontal and parietal regions. Reduced rsFC of the putamen and hippocampus with motor and sensory regions of the brain were also observed. Fatigue, itch, complete response to UDCA, and verbal working memory performance were also associated with altered rsFC of deep gray matter. These rsFC changes were independent of biochemical disease severity. CONCLUSIONS: PBC patients have objective evidence of altered rsFC of the brain's deep gray matter that is in part linked to fatigue severity, itch, response to UDCA therapy, and cognitive performance. These results may guide future approaches to define how PBC leads to altered brain connectivity and provide insight into novel targets for treating PBC-associated brain dysfunction and behavioral symptoms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".