Effect of human very low-density lipoproteins on cardiotrophin-like cytokine factor 1 (CLCF1) activity
Bibliographic record
Abstract
Abstract The cytokines CLCF1 and CNTF are ligands for the CNTF receptor and the apolipoprotein E (ApoE) receptor sortilin. Both share structural similarities with the N-terminal domain of ApoE, known to bind CNTF. We therefore evaluated whether ApoE or ApoE-containing lipoproteins interact with CLCF1 and regulate its activity. We observed that CLCF1 forms complexes with the three major isoforms of ApoE in co-immunoprecipitation and proximity assays. FPLC analysis of mouse and human sera mixed with CLCF1 revealed that CLCF1 co-purifies with plasma lipoproteins. Studies with sera from ApoE−/−mice indicate that ApoE is not required for CLCF1-lipoprotein interactions. VLDL- and LDL-CLCF1 binding was confirmed using proximity and ligand blots assays. CLCF1-induced STAT3 phosphorylation was significantly reduced when the cytokine was complexed with VLDL. Physiological relevance of our findings was asserted in a mouse model of oxygen-induced retinopathy, where the beneficial anti-angiogenic properties of CLCF1 were abrogated when co-administrated with VLDL, indicating, that CLCF1 binds purified lipoproteins or lipoproteins in physiological fluids such as serum and behave as a “lipocytokine”. Albeit it is clear that lipoproteins modulate CLCF1 activity, it remains to be determined whether lipoprotein binding directly contributes to its neurotrophic function and its roles in metabolic regulation.
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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".