Bacopa monnieri supplementation has no effect on serum brain-derived neurotrophic factor (BDNF) levels but beneficially modulates NF-kB and CREB levels in healthy elderly subjects
Bibliographic record
Abstract
Background and Aim: Bacopa monnieri is an Ayurvedic herb that has been used for multiple conditions, most notably to augment cognition, particularly memory and attention.Multiple mechanisms, including raising brain-derived neurotrophic factor (BDNF), have been proposed and investigated in animal models that require translational studies in humans.Methods: Bacopa was administered in an open-labeled study to cognitively healthy controls over a 3-month period.Cognition and mood were assessed using the Montreal Cognitive Assessment (MoCA) and geriatric depression scale (GDS) at the baseline and 3-month visit.Laboratories were assessed for safety and serum levels of mature (mBDNF) and proBDNF were quantified.In a subset of subjects, intracellular signaling processes were assessed using western blot analysis.Results: Bacopa was provided to 35 subjects and was well-tolerated except for 4 (11%) subjects who early terminated due to known, reversible, and gastrointestinal side effects (i.e., nausea, diarrhea).Over the 3 months, the GDS and the total MoCA did not significantly change; however, the delayedrecall subscale significantly improved (baseline: 3.8 ± 1.2, 3-months: 4.3 ± 0.9; P = 0.032).Serum mBDNF and proBDNF levels did not significantly change.Cyclic AMP response element-binding protein (CREB) phosphorylation significantly increased (P = 0.028) and p65 nuclear factor kappa B (NF-κB) phosphorylation significantly decreased (P = 0.030). Conclusion:These results suggest that Bacopa may exert an anti-inflammatory effect through NF-κB and improve intracellular signaling processes associated with synaptogenesis (CREB).The future placebo-controlled studies are recommended.Relevance for Patients: B. monnieri will require larger, blinded trials to better understand potential mechanisms, interactions, and utilization.
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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) | 0.001 | 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) | 0.002 | 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".