Hippocampal Subfields Related to Cognitive Decline and Peripheral TIM-3 Levels in Elderly with Knee Osteoarthritis
Bibliographic record
Abstract
Purpose: Knee osteoarthritis (KOA) has been linked to increased cognitive decline risk, but the specific mechanisms underlying this phenomenon remain unclear. Research suggests neuroimaging changes and chronic low-grade inflammation may play key roles as common pathways linking osteoarthritis (OA) to cognitive decline. Patients and Methods: This cross-sectional study recruited 36 individuals diagnosed with KOA and 25 healthy controls (HCs). Cognition was assessed using the Montreal Cognitive Assessment (MoCA) and the Digit Cancellation Test (DCT). The gray matter volume of 12 hippocampal subfields and the serum TIM-3 levels were also measured. Results: KOA patients had significantly lower MoCA scores ( P < 0.01) and fewer correct responses on the DCT ( P < 0.01). They also exhibited a larger volume of the right hippocampal tail (FDR-corrected P = 0.010) and a smaller volume of the right hippocampal fissure (FDR-corrected P = 0.036). Correlation analysis revealed that the volume of the right hippocampal tail was associated with the number of correct responses on the DCT (r = − 0.356, P = 0.049). Additionally, a smaller volume of the left hippocampal fissure was linked to higher serum TIM-3 levels (r = − 0.404, P = 0.030) in KOA patients. Conclusion: The hippocampal tail and hippocampal fissure exhibited reduced volume in KOA patients, and these changes were associated with alterations in attention and serum TIM-3 levels, respectively. These findings suggest a potential link between KOA and cognitive decline through inflammation and neuroscience, offering a theoretical basis for further study. Meanwhile, serum TIM-3 and right hippocampal fissure/tail volume might be potential biomarkers for detecting cognitive decline in KOA patients. Further studies are necessary for the investigation of this possibility. Keywords: cognitive decline, knee osteoarthritis, hippocampal subfields, TIM-3
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".