Regularity of blood transfusion influences the severity of systemic iron burden, cognitive decline, and gut dysbiosis in thalassemia patients
Bibliographic record
Abstract
BACKGROUND: Thalassemia is a hereditary disease with impaired red blood cell production, resulting in cumulative systemic iron burden. The life-long therapeutic blood transfusion with or without iron chelators in those patients leads to the development of early-onset neurocognitive decline. However, the effects of regularity of blood transfusion on the severity of iron burden, cognitive decline, and gut dysbiosis in thalassemia patients are still unclear. METHOD: Sixty participants, including 20 transfusion-dependent (TDT) patients, 20 non-transfusion-dependent (NTDT) patients, and 20 healthy controls, underwent evaluation for neurocognitive function using the Montreal Cognitive Assessment (MoCA). The current systemic iron burden was determined by the levels of serum ferritin. Amplicon-based sequencing of the bacterial 16s rRNA V3-V4 regions of stool DNA was employed to delineate profiles of gut microbiota. RESULT: The TDT patients showed greater severity of systemic iron burden, cognitive decline and gut dysbiosis than the NTDT patients. The TDT group was particularly afflicted with systemic iron burden as indicated by the highest levels of serum ferritin (Fig. 1A). Compared to the controls, the TDT and NTDT groups had significantly lower MoCA scores (Fig. 1B). In addition, there was a negative correlation between MoCA scores and the levels of serum ferritin (Fig. 1C). The thalassemia patients also exhibited gut dysbiosis, with microbial compositions among the three groups being distinct from each other (Fig. 1D and 1E). Interestingly, an increase in abundance of Paraclostridium was associated with cognitive decline. CONCLUSION: These findings suggest that the severity of systemic iron burden, based on the regularity of blood transfusion, impacts on the magnitude of cognitive decline and gut dysbiosis in thalassemia patients. It is possible that systemic iron potentially serves as a dose-dependent factor in the pathogenesis of neurodegeneration through gut dysbiosis. Therefore, therapeutic approaches via well-control of systemic iron levels and balanced gut microbiota could prevent early-onset cognitive decline 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 | 0.001 |
| 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) | 0.002 | 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".