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Record W4408674214 · doi:10.3389/fragi.2025.1547883

Rock inhibitors in Alzheimer’s disease

2025· review· en· W4408674214 on OpenAlex
Chao Zheng, Weiming Xia, Jianhua Zhang

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

VenueFrontiers in Aging · 2025
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute on Aging
KeywordsAstrocytosisNeuroinflammationGliosisNeuroscienceTauopathySenile plaquesDiseaseDementiaMicrogliaAlzheimer's diseasePathologyBiologyMedicineInflammationNeurodegenerationImmunologyCentral nervous system

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is the most common age-related neurodegenerative disease and cause of dementia. AD pathology primarily involves the formation of amyloid β (Aβ) plaques and neurofibrillary tangles containing hyperphosphorylated tau (p-tau). While Aβ targeted treatments have shown clinical promise, other aspects of AD pathology such as microgliosis, astrocytosis, synaptic loss, and hypometabolism may be viable targets for treatment. Among notable novel therapeutic approaches, the Ras homolog (Rho)-associated kinases (ROCKs) are being investigated as targets for AD treatment, based on the observations that ROCK1/2 levels are elevated in AD, and activation or inhibition of ROCKs changes dendritic/synaptic structures, protein aggregate accumulation, inflammation, and gliosis. This review will highlight key findings on the effects of ROCK inhibition in Aβ and ptau pathologies, as well as its effects on neuroinflammation, synaptic density, and potentially metabolism and bioenergetics.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.360
Teacher spread0.320 · 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