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Record W1603824390 · doi:10.1089/jcr.2014.0027

Caffeine as Treatment for Alzheimer's Disease: A Review

2015· review· en· W1603824390 on OpenAlexaff
Abhishek Mohan, Aaron J. Roberto, Akansha Mohan, Luis Liogier-Weyback, Rahul Guha, Nidhi Ravishankar, Clinton Rebello, Ashish Kumar, Ravinder Mohan

Bibliographic record

VenueJournal of Caffeine Research · 2015
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAmyloid precursor proteinCaffeineContext (archaeology)DiseaseEndosomeMechanism (biology)NeuroscienceAlzheimer's diseasePsychologyMedicineBiologyCell biologyInternal medicineIntracellular

Abstract

fetched live from OpenAlex

In current research, amyloid peptide (βA) remains characteristic in the histopathology of Alzheimer's disease (AD). As a major component in the amyloid precursor protein (APP), the entire βA sequence is thought to be involved in the processing of APP through two major pathways where APP-related membrane-bound fragments are generated from an endosomal/lysosomal pathway. Although it is generally believed APP/βA has a consequence in AD, the mechanism through which βA influences the biology and vulnerability of neural cells remains tenuous. In addition, it has been postulated that caffeine may have an attenuating effect on both accumulation of βA plaques, as well as symptomatic presentation. This review focuses on the hypothesized correlation between the biochemistry and pathology of APP and βA deposition in the context of AD. In addition, this review aims to identify the hypothesized role of caffeine in reducing βA levels and its link with AD.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.382
GPT teacher head0.567
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations17
Published2015
Admission routes1
Has abstractyes

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