A Multimodal Evaluation of Transcranial Photobiomodulation in Mild Cognitive Impairment: Cognitive, Metabolic, and Neuroimaging Outcomes of a Pilot Randomized Control Trial
Bibliographic record
Abstract
INTRODUCTION: Mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease and related dementias (ADRD), offers a critical window for early intervention. Mitochondrial dysfunction is increasingly recognized as a driver of neurodegeneration, yet most therapies target downstream protein aggregation. Transcranial photobiomodulation (tPBM) delivery of near infrared (NIR) light to stimulate mitochondrial respiration, offers a non-invasive, metabolism-based therapeutic strategy. METHODS: In a single-blinded, randomized, sham-controlled pilot trial ( NCT05563298 ), we evaluated the safety, feasibility, and biological effects of home-based tPBM in individuals aged over 50 with MCI. Participants received either active (n = 10) or sham (n = 10) treatment using visually identical NIR devices targeting default mode network regions and the olfactory bulb. Active devices emitted pulsed 810 nm light for 20 minutes per session, six days per week for six weeks; sham devices emitted light for only 2 seconds per session. No serious adverse events occurred; four mild to moderate events were reported, and adherence exceeded 98%. RESULTS: Active tPBM led to greater improvements in global cognition, as measured by the Mini Mental State Examination (MMSE), and in episodic memory, as measured by the delayed recognition test of the California Verbal Learning Test-Second Edition (CVLT-II). Blood analyses showed increased serum pyruvate and lactate, a reduced lactate to pyruvate ratio, and lower plasma IL-6. Neuroimaging revealed enhanced default mode network connectivity and focal cortical volume and thickness gains. DISCUSSION: These data demonstrate safety, preliminary efficacy, and support future definitive clinical studies.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.006 | 0.001 |
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".