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Record W2911496601 · doi:10.1159/000496089

Iron Chelation as Novel Treatment for Interstitial Cystitis

2019· article· en· W2911496601 on OpenAlexaff
Georg Hagn, Robert Westhofen, Ian Burkovskiy, Bruce E. Holbein, Juan Zhou, Christine Lehmann

Bibliographic record

VenuePharmacology · 2019
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsReactive oxygen speciesInterstitial cystitisInflammationChelationMedicineDiseaseChemistryUrinary systemInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Interstitial cystitis (IC) is a highly prevalent debilitating disease, with its cardinal symptoms being severe pain, urinary urgency and frequency. The associated pain may eventually lead as a last resort to removal of the bladder. Though the initial trigger for IC remains largely unknown, we propose novel iron chelators as a possible new treatment for this disease. Iron is a mandatory component for the generation of reactive oxygen species (ROS). A substantial decrease in ROS production and thus inflammation can be achieved by effectively sequestering host iron, which we believe may improve outcome and quality of life in IC patients. Novel iron chelators could be used via the intravesical route to reduce or attenuate inflammation by effectively sequestering host iron, thus preventing the production of ROS via the Fenton and Haber-Weiss reactions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.411
Teacher spread0.362 · 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 designBench or experimental
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

Citations4
Published2019
Admission routes1
Has abstractyes

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