Bibliographic record
Abstract
Two decades ago a class of ion channels, hitherto unsuspected, was discovered. In mammals these Transient Receptor Potential channels (TRPs) have not only expanded in number (to 26 functional channels) but also expanded the view of our interface with the physical and chemical environment. Some are heat and cold sensors while others monitor endogenous and/or exogenous chemical signals. Some TRP channels monitor osmotic potential, and others measure cell movement, stretching, and fluid flow. Many TRP channels are major players in nociception and integration of pain signals. One member of the vanilloid sub-family of channels is TRPV6. This channel is highly selective for divalent cations, particularly calcium, and plays a part in general whole-body calcium homeostasis, capturing calcium in the gut from the diet. TRPV6 can be greatly elevated in a number of cancers deriving from epithelia and considerable study has been made of its role in the cancer phenotype where calcium control is dysfunctional. This review compiles and updates recent published work on TRPV6 as a promising drug target in a number of cancers including those afflicting breast, ovarian, prostate and pancreatic tissues.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
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".