Role of Tumor Necrosis Factor Alpha Induced Protein-8 Like-2 as a Biomarker of Parkinson's Disease
Bibliographic record
Abstract
Background and Aim: Neuroinflammation plays an early and prominent role in the pathology of Parkinson disease. Tumor necrosis factor alpha induced protein-8 like-2 (TIPE2) is a relatively new subtype of tumor necrosis factor which may play a role in pathogenesis of Parkinson disease. Our aim was to evaluate the role of serum level of TIPE2 as a risk factor for Parkinson disease and as a serological biomarker of disease severity. Methods: Forty-seven patients diagnosed as idiopathic PD according to diagnostic criteria of the UK Parkinson Disease Society Brain Bank, and 47 healthy individuals were enrolled. All patients were on medical treatment of PD and were evaluated by Unified Parkinson’s disease Rating Scale (UPDRS), and Modified Hoehn and Yahr staging scale(HY). Cognitive function was assessed using Montreal Cognitive Assessment Scale (MOCA). TIPE2 serum level was measured in all participants. Results: PD patients had significantly higher levels of TIPE2 (P-value <0.001). Also, PD patients with cognitive impairment had significantly higher levels of TIPE2 (P-value= 0.039). TIPE2 level was positively correlated with score of modified HY staging (p-value o.oo1). Also,TIPE2 level was positively correlated with bradykinesia, total motor sub scores of UPDRS and total score of UPDRS (p-value 0.009, 0.019, 0.027 respectively). There was a significant negative correlation between TIPE2 and the scores of executives and visuospatial functions, attention, abstraction and total score of MoCA. Conclusions: TIPE2 serum levels in PD patients are higher than its serum level in healthy controls. Such high level of TIPE2 has a considerable impact on disease severity.
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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 | 0.001 | 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 | 0.001 | 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".