An association between fibroblast growth factor 21 and cognitive impairment in iron-overload thalassemia
Bibliographic record
Abstract
Abstract Although an increased fibroblast growth factor 21 (FGF21) level was related to mild cognitive impairment (MCI) in metabolic syndrome patients, any association regarding FGF21 and MCI in thalassemia patients as well as mechanistic insight are questionable. Therefore, the objectives of this study were: (1) to investigate the prevalence and associative risk factors of MCI in thalassemia patients, (2) to evaluate the association between levels of FGF21 and MCI in thalassemia patients, and (3) to investigate brain FGF21 signaling in iron-overload thalassemia. Thalassemia patients were enrolled onto the study (n = 131). Montreal cognitive assessment (MoCA) was used to determine cognitive performance. Plasma FGF21 level was determined in all patients. Iron-overload β-thalassemic (HT) mice were used to investigate brain FGF21 level and signaling, the expression of synaptic proteins, and Alzheimer's like pathology. We found that 70% of thalassemia patients developed MCI. FGF21 level was positively correlated with the MCI. Interestingly, brain FGF21 resistance, as indicated by increased brain FGF21 levels with impaired FGF21 signaling, was found in iron-overload HT mice. The reduced synaptic protein expression and increased Alzheimer's like pathology were also observed. These suggest that FGF21 may play a role in MCI in thalassemia patients.
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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 | 0.001 | 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) | 0.002 | 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".