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Emerging neuromodulatory molecules for the treatment of neurogenic erectile dysfunction caused by cavernous nerve injury

2008· review· en· W2009928657 on OpenAlexaff
Anthony J Bella, Guiting Lin, Ilias Cagiannos, Tom F. Lue

Bibliographic record

VenueAsian Journal of Andrology · 2008
Typereview
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsGlial cell line-derived neurotrophic factorMedicineErectile dysfunctionNeurotrophic factorsNeurotrophinNeuroprotectionNeuroscienceRegeneration (biology)Prostate cancerBioinformaticsInternal medicineCancerPsychologyBiology

Abstract

fetched live from OpenAlex

Advances in the neurobiology of growth factors, neural development, and prevention of cell death have resulted in a heightened clinical interest for the development of protective and regenerative neuromodulatory strategies for the cavernous nerves (CNs), as therapies for prostate cancer and other pelvic malignancies often result in neuronal damage and debilitating loss of sexual function. Nitric oxide released from the axonal end plates of these nerves within the corpora cavernosa causes relaxation of smooth muscle, initiating the haemodynamic changes of penile erection as well as contributing to maintained tumescence; the loss of CN function is primarily responsible for the development of erectile dysfunction (ED) after pelvic surgery and serves as the primary target for potential neuroprotective or regenerative strategies. Evidence from pre-clinical studies for select neuromodulatory approaches is reviewed, including neurotrophins, glial cell line-derived neurotrophic factors (GDNF), bone morphogenic proteins, immunophilin ligands, erythropoetin (EPO), and stem cells.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.043
GPT teacher head0.328
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations40
Published2008
Admission routes1
Has abstractyes

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