Putative kallikrein substrates and their (patho)biological functions
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.
Bibliographic record
Abstract
Human tissue kallikreins (KLKs) represent the largest contiguous group of protease genes within our genome. All 15 KLK genes co-localize within approximately 260 kb in human chromosome 19q13.3-13.4 (14 640 kb→274 990 kb). They are widely expressed in several tissues and mediate a wide range of critical physiological and pathological processes. Despite the recent developments in KLK research, elucidation of their physiological substrate repertoires remains a largely unfulfilled goal. Phage display, positional scanning and combinatorial peptide library screens have provided some valuable insights into the preferred specificities of these powerful enzymes. More recently, advances in proteomic technologies have enabled more systemic approaches towards identification of KLK substrates in a physiological setting. The advent of degradomic technologies has brought to light several putative physiological substrates and has allowed a deeper appreciation of the in vivo functional roles of KLKs. The aim of this review is to provide an overview of the different techniques that have been utilized towards the elucidation of the substrate specificities of these enzymes and elaborate on their emerging in vivo substrates.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it