Efficacy of Lycium Barbarum Polysaccharide on Cytokine Response in Youths with Subthreshold Depression
Bibliographic record
Abstract
Abstract Background: Elevated levels of inflammatory cytokines such as Interleukin (IL)-17A have been repeatedly linked with major depression in both animals and humans. Our recent double-blinded Randomized Placebo-controlled Trial (RCT) discovered significant efficacy of a traditional Chinese medicine substance, namely the Lycium barbarum polysaccharide (LBP), on reducing depressive symptoms among adolescents with subthreshold depression. Here, we further investigated whether the antidepressant property of LBP was associated with its anti-inflammatory effect on adolescents with subthreshold depression. Methods: In this 6-week RCT, we measured common cytokine levels from participants’ peripheral blood samples, both at baseline and at the end of the 6-week intervention with either LBP (intervention group, N=14) or placebo (control group, N=10). Independent t-tests were used to compare the change of cytokine levels between groups.Network-based analysis was applied to evaluate the systemic immune responses to the interventions. Results: The intervention and control groups were matched on demographic and clinical characteristics. As expected, the LBP group exhibited a greater reduction in IL-17A compared to the placebo group (t = -2.25, P = 0.04) after the 6-week interventions. Moreover, network-level analysis showed that LBP reduced the correlations and connectivity among cytokines (Z = 3.34, P < 0.01), which was in turn associated with improvement of depressive symptoms. Conclusions: Our findings demonstrated that 6-week repeated LBP administrations downregulated immune responses in adolescents with StD, which could be a key mechanistic pathway underpinning the antidepressant effect of LBP.
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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 | 0.000 | 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".