“Seipin mediates Perilipin-1 recruitment to lipid droplets to preserve human adipocyte identity”
Bibliographic record
Abstract
gene, which encodes the protein seipin. However, how seipin loss causes adipose tissue failure remains unclear. Using human adipocyte progenitor cells capable of robust differentiation in vitro and in vivo, we reveal two unexpected findings that redefine CGL2 pathogenesis. First, seipin is dispensable for lipid droplet biogenesis but essential for recruiting the major adipocyte scaffold protein Perilipin 1 (PLIN1) to the lipid droplet surface. Second, we discover that the integrity of the lipid droplet serves as an organelle to nucleus quality control checkpoint enforcing adipocyte identity. Without seipin-dependent PLIN1 recruitment, adipocytes exhibit enhanced lipolysis and ceramide accumulation, triggering an unexpected cellular response of de-differentiation into a progenitor-like state. From this de-differentiated state, cells can undergo additional cycles of differentiation and de-differentiation upon repeated adipogenic stimuli. However, some cells escape de-differentiation, instead forming a single large droplet and displaying severe cellular structural abnormalities. Consistent with this model, we find functional adipose tissue can form in vivo from seipin-deficient cells, yet ultimately fails. These findings resolve conflicting models of CGL2 pathogenesis by reframing seipin as a regulator of PLIN1 recruitment, rather than droplet formation per se, and reveal the fundamental role of lipid droplet integrity in the development of functional human adipocytes.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".