Circulating Betatrophin and Hepatocyte Growth Factor in Type 2 Diabetic Patients: Their Relationship With Disease Prognosis
Bibliographic record
Abstract
Background: In Saudi Arabia, diabetes established itself as an epidemic that necessitates dissection of its predisposing factors and pathogenesis to set appropriate preventive measures. In a cross-sectional study, relationships between plasma betatrophin (BetaT) and hepatocyte growth factor (HGF) on one side, and, glycemic control, lipogram, anthropometric indices, treatment and prognosis on the other side were assessed in Saudi patients with type 2 diabetes mellitus (T2DM) vs. healthy controls. Methods: The study voluntarily enrolled 202 T2DM patients (44 males and 158 females) and socioeconomically, age- and body mass index (BMI)-matched 106 healthy participants (71 males and 35 females). All participants were subgrouped according to gender and BMI ( = 25) and patients were also subgrouped according to disease duration ( 5 years) and treatment (insulin/non-insulin). Demographic and anthropometric data were anonymously collected. EDTA whole blood for HbA1c and its plasma for bioassays were frozen at -80 °C. Standard procedures and specific immunoassays were employed for biomarkers. Results: Plasma insulin paralleled BMI and disease duration and was highly significantly different comparing patients and healthy controls. As expected glycemic control and lipogram indices were also highly significantly different comparing patients and healthy controls. Because of the massive individual variation in the plasma levels of each of betatrophin (except for a higher level in patients with lower BMI) and HGF (except for a higher level in females and those with higher BMI among controls), there were non-significant differences comparing patients and healthy controls. Males were more inclined to have more insulin treatment. Surprisingly, the later doubled the disease severity complication score and correlated negatively with plasma HDL-cholesterol. Betatrophin did not show much correlation among controls but correlated negatively with age and cholesterol and positively with BMI and HbA1c in patients. HGF showed very clear negative correlation with age and plasma insulin in patients. Conclusion: The massive individual variation in plasma content of betatrophin and HGF did allow specific diagnostic/pathogenetic classification for these two hepato-/adipokines. This may reflect gene polymorphism at their gene regulatory sequences and/or resistance correlating insulin resistance. The former is being pursued in our laboratory for patients with distinctly higher and lower levels. J Endocrinol Metab. 2017;7(1):31-43 doi: https://doi.org/10.14740/jem405w
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".