A cell-based assay for rapid assessment of ACE2 catalytic function
Bibliographic record
Abstract
Abstract Angiotensin-converting enzyme II (ACE2) is a monocarboxypeptidase expressed throughout multiple tissues and its catalysis of bioactive peptides regulates the renin-angiotensin system mediating blood pressure homeostasis. ACE2 is implicated in a variety of diseases, including obesity, diabetes, and cardiovascular diseases, and is the obligate entry receptor for SARS-CoV-2 infection. Disease-associated genetic variants of ACE2 are increasingly being identified but are poorly characterized. To aid this problem, we introduce a fluorometric cell-based assay for evaluating surface-expressed ACE2 catalytic activity that preserves the native glycosylation of the host environment and is amenable to high-throughput analysis of ACE2 variants in multi-well plates. We demonstrate sensitivity to detecting catalysis of the key ACE2 substrates, Angiotensin II, Apelin-13, and des-Arg9-bradykinin, and impact of a catalytically-deficient ACE2 variant. Normalizing catalytic measures to surface ACE2 expression accounts for variability in ACE2 variant transfection, surface delivery or stability. This assay provides a convenient and powerful approach for investigating the catalytic characteristics of ACE2 variants involved in cardiovascular peptide cascades and homeostasis of multiple organs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".