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Record W4406248307 · doi:10.54254/2753-8818/2024.19897

Klotho in Alzheimer's Disease: Evaluating Therapeutic Potential and Addressing Experimental Challenges

2025· article· en· W4406248307 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTheoretical and Natural Science · 2025
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsKlothoNeuroinflammationNeurodegenerationDiseaseNeuroscienceOxidative stressCognitive declineAmyloid (mycology)MedicineCognitionDementiaBioinformaticsPsychologyBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Alzheimer's Disease (AD), the most common neurodegenerative disorder, is characterized by cognitive decline and neurodegeneration. This review explores the intersection of AD pathology and Klotho, a protein linked to aging and cognitive enhancement. Klotho modulates aging-related processes, including amyloid-beta dynamics and neuroinflammation, through mechanisms such as autophagy enhancement, oxidative stress reduction, and amyloid-beta clearance. Research has indicated Klotho's potential in mitigating AD symptoms in murine models, such as APP/PS1. However, methodological challenges, including variability in experimental models and inconsistencies in Klotho administration, complicate the translation of these findings. This review synthesizes current research, highlights experimental limitations, and proposes methodological improvements to enhance the reliability and applicability of Klotho as a therapeutic target for AD, providing a foundation for future investigations that could revolutionize neurodegenerative disease 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.386
Teacher spread0.351 · 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