Modulation of Glutamatergic Burst Activity by Hydrolysed Arabinoxylan Rice Bran: A Multielectrode Array Study in Human-Induced Pluripotent Stem Cell-Derived Neurones and Astrocytes
Bibliographic record
Abstract
The natural product MGN-3 (Biobran) is a defatted, partially hydrolysed rice bran-derived hemicellulose enzymatically modified with an extract of Lentinus edodes. It has a high proportion of arabinoxylan. It has a protective action against intracerebroventricular streptozotocin-induced murine sporadic Alzheimer’s disease and reverses spatial memory deficit in this disease model. The aim was to test the hypothesis that MGN-3 increases glutamatergic burst activity in human neuronal and glial cells by conducting an in vitro multielectrode array-based micro-electrophysiological study in a cultured mixture of human glutamatergic neurones, GABAergic neurones and astrocytes. The effects of MGN-3 at two concentrations, 0.750 g L-1 and 0.375 g L-1, and vehicle (control), on glutamatergic burst activity in a triculture of human-induced pluripotent stem cell (hiPSC)-derived GABAergic neurones, glutamatergic neurones and astrocytes were studied. The change in the number of glutamatergic bursts normalised to the vehicle control was analysed using a normal or Gaussian generalised linear model. This statistical model was highly significant (p = 1.468 × 10-17). Both MGN-3 concentrations were associated with highly significant main effects. These results provide strong evidence to reject the null hypothesis that MGN-3 does not affect glutamatergic burst activity in human neuronal and astrocytic cells. The study's strengths include the novel use of hiPSC-derived neurones and astrocytes and the robust statistical significance of the findings. Limitations include in vitro conditions that may not fully replicate in vivo conditions, potential variability in hiPSC-derived cell preparations, and the need to test other neuronal subtypes or additional doses to assess dose-dependent effects. These should be addressed in future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".