Role of Ghrelin Polymorphisms in Obesity Based on Three Different Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Associations between preproghrelin DNA variants and obesity-related phenotypes were studied in 3004 subjects from the Québec Family Study (QFS), the HERITAGE Family Study (HERITAGE), and the Swedish Obese Subjects (SOS) Study. RESEARCH METHODS AND PROCEDURES: Body mass index (BMI), fat mass (FM) from underwater weighing, and abdominal fat from computerized tomography were measured. The ghrelin polymorphisms were identified by polymerase chain reaction. RESULTS: Arg51Gln QFS subjects (n = 6) had lower ghrelin concentrations (p = 0.007) than Arg51Arg subjects (n = 14). White preproghrelin Met72Met subjects in HERITAGE had the lowest BMI (p = 0.020), and those in the QFS cohort had the lowest FM (p < 0.001). Met72 carrier status (Met72+) was associated with lower FM (p = 0.026) and higher insulin-like growth factor-1 levels (p = 0.019) among blacks. Met72Met QFS subjects had less visceral fat (p = 0.002) and a lower fasting respiratory quotient (p = 0.037). HERITAGE Met72+ white subjects also showed lower exercise respiratory quotient (p = 0.030) and higher maximal oxygen uptake (p = 0.023). Furthermore, the prevalence of Met72+ was higher (19.2%; p < 0.05) in SOS subjects whose BMI was < or =25 kg/m(2) than in those with BMI >25 kg/m(2) (14.8%). SOS Met72+ obese women had a lower (11.4%; p = 0.032) prevalence of hypertension than noncarriers (23.9%). DISCUSSION: Arg51Gln mutation was associated with lower plasma ghrelin levels but not with obesity. The preproghrelin Met72 carrier status seems to be protective against fat accumulation and associated metabolic comorbidities.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it