Ablation of <i>Bscl2</i>/seipin in hepatocytes does not cause metabolic dysfunction in congenital generalised lipodystrophy
Bibliographic record
Abstract
ABSTRACT Mutations affecting the BSCL2 gene cause the most severe form of congenital generalised lipodystrophy (CGL). Affected individuals develop severe metabolic complications including diabetes and hepatic steatosis. Bscl2-deficient mice almost entirely reproduce the CGL phenotype. Adipose tissue-specific loss of Bscl2 is also sufficient to cause early-onset generalised lipodystrophy in mice. However, these mice do not show severe metabolic dysfunction, even when challenged with a high-fat diet. Germline Bscl2 loss in mice and BSCL2 disruption in humans causes severe hepatic steatosis, and the encoded protein, seipin, has acknowledged roles in lipid accumulation. Given the critical role of the liver in glucose regulation, we speculated that intact hepatic Bscl2 expression may protect adipose tissue-specific Bscl2-deficient mice from metabolic disease. To investigate this, we generated a novel mouse model in which Bscl2 has been deleted in both adipose tissue and hepatocytes simultaneously using an adeno-associated viral vector. Despite achieving efficient disruption of Bscl2 in the liver, hepatic lipid accumulation and metabolic homeostasis was unaffected in mice fed a high-fat diet for 4 weeks. We also investigated the consequences of BSCL2 ablation in the human hepatocyte HepG2 cell line using CRISPR/Cas9 genome editing. No significant increases in lipid accumulation were observed in BSCL2 knockout cell lines. Overall, we reveal that Bscl2/BSCL2 does not appear to play a cell-autonomous role in the regulation of lipid accumulation in the liver. Loss of hepatic BSCL2 is therefore unlikely to contribute significantly to the development of hepatic steatosis or metabolic dysfunction in this form of CGL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.003 | 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".