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Record W3081007665 · doi:10.1210/jendso/bvaa120

Androgen Therapy in Neurodegenerative Diseases

2020· review· en· W3081007665 on OpenAlex
Vittorio Emanuele Bianchi, Laura Rizzi, Elena Bresciani, Robert J. Omeljaniuk, Antonio Torsello

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

VenueJournal of the Endocrine Society · 2020
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsLakehead University
Fundersnot available
KeywordsNeuroscienceMedicinePsychology

Abstract

fetched live from OpenAlex

Abstract Neurodegenerative diseases, including Alzheimer disease (AD), Parkinson disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and Huntington disease, are characterized by the loss of neurons as well as neuronal function in multiple regions of the central and peripheral nervous systems. Several studies in animal models have shown that androgens have neuroprotective effects in the brain and stimulate axonal regeneration. The presence of neuronal androgen receptors in the peripheral and central nervous system suggests that androgen therapy might be useful in the treatment of neurodegenerative diseases. To illustrate, androgen therapy reduced inflammation, amyloid-β deposition, and cognitive impairment in patients with AD. As well, improvements in remyelination in MS have been reported; by comparison, only variable results are observed in androgen treatment of PD. In ALS, androgen administration stimulated motoneuron recovery from progressive damage and regenerated both axons and dendrites. Only a few clinical studies are available in human individuals despite the safety and low cost of androgen therapy. Clinical evaluations of the effects of androgen therapy on these devastating diseases using large populations of patients are strongly needed.

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)0.001
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 score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.069
GPT teacher head0.340
Teacher spread0.271 · 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