Purinergic Signalling in Immune System Regulation in Health and Disease
Bibliographic record
Abstract
The concept of a purinergic signalling system was first proposed by Professor Geoffrey Burnstock over 30 years ago. This includes the cellular responses to purine nucleotides, such as ATP, and nucleosides, such as adenosine, that act as extracellular messengers playing a role through specific nucleotide and adenosine receptors in all systems. Indeed, in addition to their role in cellular metabolism, nucleotides as well as nucleosides are extracellular mediators that activate biological responses in all cells. Cells subjected to activation or shear or mechanical stress release nucleotides such as ATP, ADP, UTP, and UDP in large amounts. All cells can release nucleotides in a controlled fashion [1]. The mechanisms of nucleotide release have been the focus of intense research activities but are still not fully understood. While activated platelets and neurons release nucleotides by exocytosis, neutrophils, and T lymphocytes use pannexin-1 hemichannels for nucleotide efflux, some cells also constitutively release nucleotides.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".