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Record W4385758421 · doi:10.4103/1673-5374.380873

Soluble p75 neurotrophic receptor as a reliable biomarker in neurodegenerative diseases: what is the evidence?

2023· review· en· W4385758421 on OpenAlexaff
Georges Jourdi, Samuel Fleury, Imane Boukhatem, Marie Lordkipanidzé

Bibliographic record

VenueNeural Regeneration Research · 2023
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsAmyotrophic lateral sclerosisBiomarkerMedicineContext (archaeology)DementiaDiseaseNeuroscienceNeurodegenerationFrontotemporal dementiaNeurotrophinSchizophrenia (object-oriented programming)BioinformaticsPathologyReceptorPsychiatryInternal medicinePsychologyBiology

Abstract

fetched live from OpenAlex

Abstract Neurodegenerative diseases are often misdiagnosed, especially when the diagnosis is based solely on clinical symptoms. The p75 neurotrophic receptor (p75 NTR ) has been studied as an index of sensory and motor nerve development and maturation. Its cleavable extracellular domain (ECD) is readily detectable in various biological fluids including plasma, serum and urine. There is evidence for increased p75 NTR ECD levels in neurodegenerative diseases such as Alzheimer’s disease, amyotrophic lateral sclerosis, age-related dementia, schizophrenia, and diabetic neuropathy. Whether p75 NTR ECD could be used as a biomarker for diagnosis and/or prognosis in these disorders, and whether it could potentially lead to the development of targeted therapies, remains an open question. In this review, we present and discuss published studies that have evaluated the relevance of this emerging biomarker in the context of various neurodegenerative diseases. We also highlight areas that require further investigation to better understand the role of p75 NTR ECD in the clinical diagnosis and management of neurodegenerative disorders.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.006
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.003

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 head0.428
GPT teacher head0.490
Teacher spread0.062 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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