Assessment of Potential Targets for Deep Brain Stimulation in Patients With Alzheimer’s Disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting 36 million people worldwide and 5.2 million in the United States. The pathogenesis of AD is still elusive. Accumulations of abnormal proteins (beta amyloid and tau protein), inflammatory cascades, abnormal responses to oxidative stress and alteration in oxidative metabolism have been implicated in AD. There are few effective therapeutic options available for this disorder at present. Neuromodulation offers a novel treatment modality for patients with AD. The databases of Medline and PubMed were searched for various studies in English literature describing the deep brain stimulation (DBS) in patients with AD. Various animal and human clinical studies have shown promising initial results with bilateral DBS targeting various anatomical nodes. In this review, we attempt to highlight the pathophysiology, neural circuitry and potential neuromodulation options in patients with AD. In appropriately selected patients, DBS can potentially delay the cognitive decline, enhance memory functions and can improve the overall quality of life. However, further randomized controlled trials are required to validate the efficacy of neuromodulation and to determine the most optimal target for AD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".