Alzheimer's disease: A case study involving EEG-based fE/I ratio and pTau-181 protein analysis through nasal administration of <i>Saraswata Ghrita</i>
Bibliographic record
Abstract
Background: (SG), a traditional Ayurvedic remedy administered nasally, offers a holistic approach and is believed to directly affect brain functions through its unique delivery route. Objective: This study aimed to evaluate the effectiveness of SG in improving cognitive function and neurochemical biomarkers in a patient with AD. Key outcomes included electroencephalography-based excitation/inhibition (fE/I) ratio, and levels of phosphorylated Tau-181 (pTau-181), serotonin, dopamine, acetylcholine, and dehydroepiandrosterone (DHEA). Methods: A 90-day proof-of-concept clinical trial was conducted with one AD patient. Nasal administration of SG was performed twice daily. Measurements included EEG spectral power analysis across 1-48 Hz, cognitive function assessed by Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Quality of Life in Alzheimer's Disease (QoL-AD) scales, and biochemical analyses of pTau-181, serotonin, dopamine, acetylcholine, and DHEA. Results: Notable improvements were observed: ADAS-Cog score decreased from 40 to 36, QoL-AD score increased from 23 to 31, MMSE score improved from 13 to 18, and MoCA score increased from 8 to 13. Biochemical markers showed a decrease in pTau-181 (12.50 pg/ml to 6.28 pg/ml), an increase in acetylcholine (13.73 pg/ml to 31.83 pg/ml), while serotonin and DHEA levels rose, and dopamine levels decreased (39.14 pg/ml to 36.21 pg/ml). Conclusions: SG demonstrated potential in enhancing cognitive functions and neurochemical markers in AD, with the nasal route proving safe and effective. These findings suggest the value of traditional Ayurvedic treatments in contemporary AD management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".