Unraveling the potential of transcranial photobiomodulation and ultrasound stimulation for brain therapeutics: an introduction
Bibliographic record
Abstract
The human brain is the most sophisticated and the finest processing unit ever designed, but mental and neurological disorders are an imminent threat to its functioning.Indeed, brain disorders comprise one of the most challenging health issues of modern society due to their tremendous health, social, and economic impact.However, pharmacological therapies face a physical obstacle e the blood-brain barrier (BBB) -that impedes most biopharmaceuticals from reaching brain tissues and thus blocks their efficiency.For this reason, researchers have been recently focusing on alternative, non-invasive, and drug-free therapeutic strategies to restore the healthy functionality and mechanobiology of the brain.Among these, non-invasive and natural-based therapeutic strategies such as transcranial photobiomodulation (tPBM, i.e., the application of modulated red/NIR light for therapeutic purposes) and ultrasound stimulation (tUS) are at the forefront of clinical interventions with the potential to improve different neuropathologies and the behavioral decline that typically accompanies neurodegeneration.These therapeutic stimuli have been proven to improve the metabolic activity of brain cells (including neurons and glia), block neuropathological mechanisms, alter the permeability of the BBB, among many others neuroprotective effects.However, these therapeutic solutions face four common barriers that hinder their wide clinical use: (1) limited knowledge of the optimal stimulation pattern; (2) insufficiently personalized stimulation; (3) limited access to deep brain structures; (4) poor stimulation selectively and spatial coverage.These barriers are a consequence of the insufficient understanding on how optical and ultrasonic waves interact with the brain and surrounding tissues and the bioavailability of the stimulus in targeted deep brain regions.For this reason, we believe that the development and optimization of optomechanical tools to mitigate neurodegeneration and stimulate brain activity require a holistic and integrated approach involving experimental, in silico, and in vitro models, from which efficient, customized, and innovative transcranial stimulation therapies may arise.
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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 | 0.001 | 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".