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Record W2072040433 · doi:10.1210/en.2005-1133

Increased Levels of Acylation-Stimulating Protein in Interleukin-6-Deficient (IL-6−/−) Mice

2006· article· en· W2072040433 on OpenAlexaff
Bob Olsson, Margareta Jernås, Sabina Paglialunga, Lena Carlsson, Ulf Smith, Katherine Cianflone, Kristina Wallenius, Ville Wallenius

Bibliographic record

VenueEndocrinology · 2006
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversité Laval
FundersSahlgrenska UniversitetssjukhusetVetenskapsrådetSvenska Sällskapet för Medicinsk Forskning
KeywordsInternal medicineEndocrinologyProperdinAdipose tissueWhite adipose tissueInterleukinTransthyretinChemistryBiologyMedicineComplement systemImmune systemCytokineImmunology

Abstract

fetched live from OpenAlex

IL-6-deficient (IL-6(-/-)) mice develop obesity at 6-7 months of age. To elucidate the mechanisms of this mature-onset obesity, global gene expression profiles of 3-month-old preobese IL-6(-/-) were compared with those of IL-6(+/+) mice using DNA arrays. Genes that were up-regulated in IL-6(-/-) mice included the factors transthyretin and properdin in white adipose tissue and adipsin in muscle. These factors have been shown to influence the formation of acylation-stimulating protein (ASP), a cleavage product of complement C3. ASP stimulates the synthesis of triacylglycerol in adipocytes, and ASP-deficient mice are resistant to diet-induced obesity. In line with the increases in transthyretin, properdin, and adipsin, ASP levels in serum were increased by 31-54% in IL-6(-/-) compared with IL-6(+/+) mice. Furthermore, IL-6 replacement treatment in IL-6(-/-) mice decreased ASP levels significantly by 25-60%. In conclusion, ASP levels are increased in preobese IL-6(-/-) mice. This increase may result in increased triacylglycerol formation and uptake in IL-6(-/-) adipocytes and thereby contribute to the development of obesity in IL-6(-/-) mice.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.020
GPT teacher head0.277
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2006
Admission routes1
Has abstractyes

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