The gastrointestinal-brain axis in humans as an evolutionary advance of the root-leaf axis in plants: A hypothesis linking quantum effects of light to serotonin and auxin
Bibliographic record
Abstract
Living organisms tend to find viable strategies under ambient conditions that optimize their search for, and utilization of, life-sustaining resources. For plants, a leading role in this process is performed by auxin, a plant hormone that drives morphological development, dynamics, and movement to optimize the absorption of light (through branches and leaves) and chemical “food” (through roots). Similarly to auxin in plants, serotonin seems to play an important role in higher animals, especially humans. Here, it is proposed that morphological and functional similarities between (i) plant leaves and the animal/human brain and (ii) plant roots and the animal/human gastro-intestinal tract have general features in common. Plants interact with light and use it for biological energy, whereas, neurons in the central nervous system seem to interact with biophotons and use them for proper brain function. Further, as auxin drives the “arborescence” of roots within the soil, similarly serotonin seems to facilitate enteric nervous system connectivity within the human gastrointestinal tract. This auxin/serotonin parallel suggests the root-branch axis in plants may be an evolutionary precursor to the gastrointestinal-brain axis in humans. Finally, it is hypothesized that light might be an important factor, both in gastrointestinal dynamics and brain function. Such a comparison may indicate a key role for the interaction of light and serotonin in neuronal physiology (possibly in both the central nervous system and the enteric nervous system), and according to recent work, mind and consciousness.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".