Plasma concentrations of Granulocyte Colony-Stimulating Factor (G-CSF) in Patients with Substance Use Disorders and Comorbid Major Depressive Disorders
Bibliographic record
Abstract
Abstract Aims: Granulocyte colony–stimulating factor (G-CSF) has raised much interest due to its role to cocaine addiction in preclinical models. We analyzed the circulating expression of G-CSF in abstinent chronic users of alcohol and/or cocaine with or without comorbid major depressive disorders to investigate the role of this trophic factor with complicated substance use disorders.Methods: We recruited 176 patients and 136 controls. Patients were divided in 50 patients with major depressive disorder (MDD) and 126 abstinent substance use disorders (SUD) patients undergoing treatments for alcohol (N=66) or cocaine (N=60) addiction according to DSM-IV-TR criteria. A blood sample was collected to examine plasma concentrations of G-CSF.Results: The plasma concentrations of G-CSF were significantly decreased in the cocaine group compared with the SUD control group. There was a sex dimorphism in the alcohol group, with lower G-CSF concentrations in women compared with men. Plasma concentrations of G-CSF were associated with abstinence and with the length of alcohol problems. The decrease in G-CSF was associated with comorbid MDD, a finding specific for SUD patients since there were no alterations of G-CSF primary settings MDD outpatients.Conclusions: Circulating G-CSF is reduced in SUD patients, being associated to comorbid MDD. A sex-dependent effect was observed in female AUD. Plasma G-CSF concentrations might be used as a predictor of length of chronic alcohol use and as a stratification role in the dual diagnosis in SUD. Further investigation is needed to explore the role of G-CSF as potential biomarker of pathogenic/prognosis in SUD population.
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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) | 0.001 | 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".