Glycosylation on proteins of the intestine and perimicrovillar membrane of <i>Triatoma</i> (<i>Meccus</i>) <i>pallidipennis</i>, under different feeding conditions
Bibliographic record
Abstract
Trypanosoma cruzi, the causative agent of Chagas disease, interacts with molecules in the midgut of its insect vector to multiply and reach the infective stage. Many studies suggest that the parasite binds to midgut-specific glycans. We identified several glycoproteins expressed in the intestine and perimicrovillar membrane (PMM) of Triatoma (Meccus) pallidipennis under different feeding conditions. In order to assess changes in protein-linked glycans, we performed lectin and immunoblot analyses on glycoprotein extracts from these intestinal tissues using well-characterized lectins, and an antibody, which collectively recognize a wide range of different glycans epitopes. We observed that the amount and composition of proteins and glycoproteins associated with different glycans structures changed over time in the intestines and PMM under different physiological conditions. PMM extracts contained a wide variety of glycoproteins with different sugar residues, including abundant high-mannose and complex sialylated glycans. We propose that these molecules could be involved in the process of parasite-vector interactions.
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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 | 0.000 | 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) | 0.001 | 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".