Where do <i>Trypanosoma cruzi</i> go? The distribution of parasites in blood components from fractionated infected whole blood
Bibliographic record
Abstract
BACKGROUND: Platelets (PLTs) are the blood component most frequently involved in Trypanosoma cruzi transfusion transmission cases reported in the literature, although whole blood (WB) and red blood cells (RBCs) have also been incriminated. However, there is little knowledge of the parasite distribution among blood components. STUDY DESIGN AND METHODS: The aim of this study was to investigate in which blood component T. cruzi parasites concentrate the most, after fractionating artificially T. cruzi-infected WB. The T. cruzi parasite load was studied by a specific quantitative real-time polymerase chain reaction (qPCR) in WB, buffy coat (BC), PLT concentrates, RBCs before and after leukoreduction, and plasma (PL). RESULTS: The parasite load in WB experimentally infected with 1.5 × 10(6) parasites (2.78 × 10(3) parasite equivalents/mL) was unevenly distributed among the separated blood components. The highest level was found in the BC (6.94 × 10(3) parasite equivalents/mL) and RBCs before leukoreduction by filtration (2.51 × 10(3) parasite equivalents/mL), after which RBCs presented a 99.9% reduction in parasite levels. Both PL and PLTs, partially leukoreduced by centrifugation but nonfiltered, had low parasite levels, the lowest concentration being in PL. CONCLUSIONS: The highest parasite concentration was detected in the BC, followed by RBCs before leukoreduction. There is a notable risk of transfusion-transmitted Chagas disease associated with nonleukoreduced RBCs. Leukoreduction may be an effective prevention strategy for transfusion-transmitted T. cruzi infection, especially in endemic countries and in nonendemic countries with a high rate of immigration from Latin America.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".