Endothelin and bradykinin: ‘brothers‐in‐arms’ in Chagas vasculopathies?
Bibliographic record
Abstract
Reports of Chagas disease are increasing in non-endemic populations across the globe. Apart from vector eradication and prevention efforts by public health organizations, current pharmacological interventions are sparse and show important side effects. In this issue of the BJP, Andrade et al. elegantly demonstrate a new pharmacological paradigm whereby Trypanosoma cruzi host cell invasion requires significant cross-talk between receptors for kinins and endothelins. It is shown, for example, that acting via both ET(A) and ET(B) receptors, endothelin-1 (ET-1) cooperates with the (TLR2/CXCR2/B(2) kinin receptor) complex to activate inflammatory processes in response to invading trypomastigotes. This study by Andrade et al. prompts, however, several important questions, summarized in this Commentary, such as the putative role of chymase-dependent production of ET-1, the contentious protective role of ACE inhibitors in Chagasic patients, the unexplored role of de novo formed B(1) receptors for kinins triggered by cytokines and the putative role of compartmentalized calcium pools in host cell invasion by trypomastigotes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.024 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".