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Record W2330956224 · doi:10.1093/jnen/63.6.641

Increased proNGF Levels in Subjects with Mild Cognitive Impairment and Mild Alzheimer Disease

2004· article· en· W2330956224 on OpenAlexaff
Shiyong Peng, Joanne Wuu, Elliott J. Mufson, Margaret Fahnestock

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2004
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcMaster University
FundersNational Institute on Aging
KeywordsNerve growth factorBasal forebrainPsychologyInternal medicineAlzheimer's diseaseCognitionMini–Mental State ExaminationCognitive declineCholinergicEndocrinologyCognitive impairmentDiseaseDementiaMedicineNeuroscienceReceptor

Abstract

fetched live from OpenAlex

Nerve growth factor (NGF) is critical for the regulation, differentiation, and survival of basal forebrain cholinergic neurons that degenerate in the late stage of Alzheimer disease (AD). The precursor of NGF (proNGF) is the predominant form of NGF in brain and is increased in end stage AD. To determine whether this increase in proNGF is an early or late change during the progression of cognitive decline, we used Western blotting to measure the relative amounts of proNGF protein in the parietal cortex from subjects clinically classified with no cognitive impairment (NCI; n = 20), mild cognitive impairment (MCI; n = 20), or mild to moderate AD (n = 19). We found that proNGF increased during the prodromal stage of AD. The amount of proNGF protein was 1.4-fold greater in the MCI group as compared to NCI, and was 1.6-fold greater in mild-moderate AD as compared to NCI, similar to our previous findings of a 2-fold increase in end stage AD. There was a negative correlation between proNGF levels and Mini Mental Status Examination (MMSE) score, demonstrating that the accumulation of proNGF is correlated with loss of cognitive function. These findings demonstrate that proNGF levels increase during the preclinical stage of AD and may reflect an early biological marker for the onset of 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.034
GPT teacher head0.324
Teacher spread0.290 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations235
Published2004
Admission routes1
Has abstractyes

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