Measurement of GLP-1 in Impaired Glucose Tolerance Subjects in Comparison to Type 2 Diabetes Patients and Healthy Subjects
Bibliographic record
Abstract
Background: Incretin therapy of type 2 diabetes patients is based on the fact that Incretin Effect is diminished in those patients. The objective is to measure glucagon-like peptide-1 (GLP-1) levels in impaired oral glucose tolerance (IGT) subjects and compare them to those of type 2 diabetes patients and healthy subjects. If the incretin hormone (GLP-1) is established to be diminished in IGT subjects, future study may assess effectiveness of incretin therapy to prevent or delay diabetes in IGT subjects. Patients and methods: GLP-1 was measured by ELISA test at 0, 30 and 120 minutes in accordance with OGTT in three groups: type 2 diabetes groups including 24 patient, impaired glucose tolerance group including 24 subject and healthy control group including 24 subject as control. Patients were classified according to the WHO criteria for diabetes diagnosis. Results: Fasting GLP-1 levels were none significantly different between the studied groups. One the other hand, GLP-1 response at 30' was significantly diminished in diabetics when compared with IGT and controls. GLP-1 levels at 120' were significantly reduced in type 2 diabetes patients when compared with IGT and controls and significantly diminished in IGT when compared with controls. Conclusions: The study indicates that the GLP-1 levels are diminished in impaired glucose tolerance subjects when it’s compared to normal subjects.
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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 | 0.001 | 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) | 0.002 | 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".