Highlighting the relevance of proBDNF/mBDNF ratio and matrix metalloproteinase-9 activity in an aging female cohort with overactive bladder syndrome
Bibliographic record
Abstract
Brain derived neurotrophic factor (BDNF) is the most abundant neurotrophin in the human brain and is widely expressed in both the developing and adult mammalian brain.It is involved in various neural processes and is present also in peripheral tissues, such as bladder.Changes in neurotrophin levels, such as BDNF, and their precursor molecules have been associated with several physiological and pathological conditions including voiding dysfunction.By analyzing small metabolites found in urine along with the levels of neurotrophins, it may be possible to identify specific metabolic signatures and profiles associated with different types of voiding dysfunction such as overactive bladder syndrome (OAB).Nerve growth factor (NGF) and BDNF have been previously associated to OAB, with hypothesized mechanisms of their pathological involvement, specifically in the aging population.Herein, we study urinary BDNF in both its precursor and mature form and associated molecules as reliable biomarkers for OAB.Additionally, we use an in vitro model to further understand the mechanism of these molecular imbalance in the urine of OAB patients when compared to non-OAB controls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".