Validation of Apolipoprotein A-1 and Fibronectin Fragments as Markers of Parasitological Cure for Congenital Chagas Disease in Children Treated With Benznidazole
Bibliographic record
Abstract
Abstract Background No reliable tests or validated biomarkers exist to ensure parasitological cure following treatment of Chagas disease (CD) patients chronically infected with Trypanosoma cruzi. As seroreversion, the only marker of cure, happens more quickly in children, we investigated the correlation between previously identified biomarkers and seroreversion in children. Methods Thirty CD children (age 1 month to 10 years) diagnosed as T. cruzi positive (time point S0) were treated with benznidazole (BZ) 5–8 mg/kg/d for 60 days. At least 2 serological tests were used to evaluate treatment efficacy from the end of treatment (S1) until seroreversion (S2). Thirty children (age 1 month to 10 years) and 15 adults were used as healthy controls (HCs). Immunoblot and a proteomic-based assay were used to validate previously identified fragments of apolipoprotein A-1 (ApoA1) and fibronectin (FBN) as CD biomarkers. Results Correlation between seroreversion and absence of ApoA1 and FBN fragments by immunoblot was observed in 30/30 (100%) and 29/30 (96.6%) CD children, respectively. ApoA1 and FBN fragments were absent at the end of BZ treatment in 20/30 (66.6%) and 16/30 (53.3%) children, respectively. Absence of fragments in serum profiles was confirmed by mass spectrometry. Using intact protein analysis, a 28 109-Da protein identified as full-length ApoA1 by tandem mass spectrometry was detected in HC serum samples. Conclusions These data confirm that ApoA1 and FBN fragments can discriminate between healthy and T. cruzi–infected samples. Correlation with seroreversion was shown for the first time; results suggest predictive capacity potentially superior to serology, making them potentially useful as surrogate biomarkers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".