Association of serum visfatin and its mRNA expression levels with cognitive function and idiopathic intracranial hypertension in obese Egyptian women
Bibliographic record
Abstract
Abstract Background An epidemic of obesity has spread across the globe. Obesity has numerous comorbidities, including airway disease, insulin resistance, type 2 diabetes, cardiovascular disease, atherosclerosis, degenerative neurological disease, cognitive dysfunction, and cancer. Inflammatory cytokine is suggested to play a role in obesity and its complications. The current study aimed to estimate the expression and serum visfatin concentrations in obese Egyptian women. Moreover, we aimed to evaluate the possible association of visfatin gene expression and its serum levels with idiopathic intracranial hypertension (IIH) and cognitive dysfunction Participants and methods This cross-sectional study enrolled 60 obese women and 40 lean healthy women as controls. Obese women were classified according to grades of obesity into three groups. All participants underwent full clinical, neurological, and psychiatric examination. IIH group included patients with intracranial pressure greater than 25 cm H2O (opening pressure measured during lumber puncture in lateral decubitus position). Cognitive function was evaluated by using Montreal Cognitive Assessment scale (MoCA), Arabic version. Estimation of visfatin expression levels was determined by real-time PCR, and serum visfatin concentrations were measured using enzyme-linked immunosorbent assay. Results Our results revealed that obese women had higher values of visfatin expression (1.44±0.29) and serum levels (124.1±) compared with lean women (1.01±0.3 and 46.1±33.8, respectively). The visfatin expression and serum levels were significantly positively correlated with obesity indices, metabolic risks, MoCA, cerebrospinal fluid opening pressure, and cognitive dysfunction. Linear regression test showed that BMI, cerebrospinal fluid opening pressure, and MoCA were the main predictors of both serum and expression levels of visfatin in obese women. The receiver operating characteristic curve analysis revealed that the power of serum visfatin levels was higher than visfatin expression in differentiating obese women from lean ones. Conclusion There was a strong independent association between both higher visfatin expression and serum levels and obesity indices, metabolic risks, IIH, and cognitive dysfunction in obese Egyptian women.
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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".