Altered proteome of high-density lipoproteins from paediatric acute lymphoblastic leukemia survivors
Bibliographic record
Abstract
Acute lymphoblastic leukemia (ALL) is the most frequent malignancy in children. With the use of more modern, efficient treatments, 5-year survival has reached more than 90% in this population. However, this achievement comes with many secondary and long-term effects since more than 65% of the survivors experience at least one severe complication, including the metabolic syndrome and cardiovascular diseases. The main objective of the present work was to characterize the composition of HDL particles isolated from pediatric ALL survivors. HDLs from 8 metabolically healthy ALL survivors, 8 metabolically unhealthy ALL survivors and 8 age- and gender-matched controls were analyzed. The HDL fraction from the survivors contained less cholesterol than the controls. In addition, proteomic analyses revealed an enrichment of pro-thrombotic (e.g., fibrinogen) and pro-inflammatory (e.g., amyloid A) proteins in the HDLs deriving from metabolically unhealthy survivors. These results indicate an alteration in the composition of lipid and protein content of HDL from childhood ALL survivors with metabolic disorders. Although more work is needed to validate the functionality of these HDLs, the data seem relevant for survivor health given the detection of potential biomarkers related to HDL metabolism and functionality in cancer.
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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) | 0.001 | 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".