PCSK9 inhibition protects mice from food allergy
Bibliographic record
Abstract
Abstract The Proprotein Convertase Subtilisin Kexin of type 9 (PCSK9) has been identified in 2003 as the third gene involved in familial hypercholesterolemia. PCSK9 binds to the membrane low-density lipoprotein receptor (LDLR) and promotes its cellular internalization and lysosomal degradation. Beyond this canonical role, PCSK9 was recently described to be involved in several immune responses. However, to date, the contribution of PCSK9 in food allergy remains unknown. Here, we showed that Pcsk9 deficiency or pharmacological inhibition of circulating PCSK9 with a specific monoclonal antibody (m-Ab) protected mice against symptoms of gliadin-induced-food allergy, such as increased intestinal transit time and ear oedema. Furthermore, specific PCSK9 inhibition during the elicitation steps of allergic process was sufficient to ensure anti-allergic effects in mice. Interestingly, the protective effect of PCSK9 inhibition against food allergy symptoms was independent of the LDLR as PCSK9 inhibitors remained effective in Ldlr deficient mice. In vitro , we showed that recombinant gain of function PCSK9 (PCSK9 D374Y) increased the percentage of mature bone marrow derived dendritic cells (BMDCs), promoted naïve T cell proliferation and potentiated the gliadin induced basophils degranulation. Altogether, our data demonstrate that PCSK9 inhibition is protective against gliadin induced food allergy in a LDLR-independent manner.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".