Epithelial Anion Transport as Modulator of Chemokine Signaling
Bibliographic record
Abstract
The pivotal role of epithelial cells is to secrete and absorb ions and water in order to allow the formation of a luminal fluid compartment that is fundamental for the epithelial function as a barrier against environmental factors. Importantly, epithelial cells also take part in the innate immune system. As a first line of defense they detect pathogens and react by secreting and responding to chemokines and cytokines, thus aggravating immune responses or resolving inflammatory states. Loss of epithelial anion transport is well documented in a variety of diseases including cystic fibrosis, chronic obstructive pulmonary disease, asthma, pancreatitis, and cholestatic liver disease. Here we review the effect of aberrant anion secretion with focus on the release of inflammatory mediators by epithelial cells and discuss putative mechanisms linking these transport defects to the augmented epithelial release of chemokines and cytokines. These mechanisms may contribute to the excessive and persistent inflammation in many respiratory and gastrointestinal diseases.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".