Complement Receptors C5aR and C5L2 Are Associated with Metabolic Profile, Sex Hormones, and Liver Enzymes in Obese Women Pre- and Postbariatric Surgery
Bibliographic record
Abstract
OBJECTIVE: Obesity is associated with metabolic dysfunction with sex differences and chronic, low-grade inflammation.We proposed that hepatic expression of immune complement C3 related receptors (C3aR, C5aR, and C5L2) would be associated with pre- or postmenopausal status and metabolic profile in severely obese women. We hypothesized that C5L2/C5aR ratio, potentially influencing the ASP/C5L2 metabolic versus C5a/C5aR immune response, would predict metabolic profiles after weight loss surgery. MATERIALS AND METHODS: Fasting plasma (hormone, lipid, and enzyme analysis) and liver biopsies (RT-PCR gene expression) were obtained from 91 women during surgery. RESULTS: Hepatic C5L2 mRNA expression was elevated in pre- versus postmenopausal women (P < 0.01) and correlated positively with circulating estradiol, estrone, ApoB, ApoA1, ApoA1/B, waist circumference, age, and LDL-C (all P < 0.05).While plasma ASP was lower in pre- versus postmenopausal women (P < 0.01), the hepatic C5L2/C5aR mRNA ratio was increased (P < 0.001) and correlated positively with estrone (P < 0.01) and estradiol (P < 0.001) and negatively with circulating ApoB and liver enzymes ALT, AST, and GGT (all P < 0.05). Over 12 months postoperatively, liver enzymes in low C5L2/C5aR mRNA ratio group remained higher (ALP and ALT, P < 0.05, AST and GGT, P < 0.001 2-way-ANOVA). CONCLUSION: C5L2-C5aR association with other mediators including estrogens may contribute to hepatic metabolic and inflammatory function.
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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".