The Relation of Serum Adipocytokines Levels and Haematological Malignancy
Bibliographic record
Abstract
Obesity is a global health problem. Adipocytes produce adipocytokines, which participate in carcinogenesis of many solid tumours. However, reports on the effects in haematological malignancies are limited. We studied this feature in haematological malignancies. The body mass index (BMI), waist:hip ratio and serum adipocytokines levels (leptin and adiponectin) were measured in subjects (n=29) and healthy control (n=18). There was no significant difference in the mean BMI of control and subjects. However, the mean waist:hip ratio in subjects were significantly higher (0.91) compared to control (0.82); p=0.04. The mean level of leptin was raised in subjects compared to control (1.80 vs 17.41); p=0.00. The mean adiponectin level was suppressed in subjects (6.54 vs 0.15); p=0.00. The leptin:adiponectin ratio was also suppressed (0.01 vs 3.93); p=0.000. Subjects with good and poor initial clinical outcome did not show any significant difference in the adiposity index and the serum adipocytokines levels. This study supports the evidence that adiposity and adipocytokines are related to haematological malignancy similar to that reported in solid tumours. Leptin:adiponectin ratio may have the potential as a biomarker of obesity related malignancy. We also concluded that waist:hip ratio is a better index of adiposity compared to BMI. However, there is no significant relation of these parameters with the prognosis.
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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 | 0.001 |
| 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".