Bibliographic record
Abstract
Phagocytosis and innate immune responses to solid structures are topics of interest and debate. Alum, monosodium urate, calcium pyrophosphate dehydrate, silica and by extension all solid entities draw varying degrees of attention from phagocytes, such as antigen presenting cells. For some, innocuous soluble metabolites turn into fierce irritants upon crystallization, pointing to divergent signaling mechanisms of a given substance in its soluble and solid states. Over the years, many mechanisms have been proposed, including phagocytic receptors, toll like receptors, and NACHT-LRRs (NLRs), as well as several other protein structure mediated recognition of the solids. Is there a more general mechanism for sensing solids? In this perspective, I present an alternative view on the topic that membrane lipids can engage solid surfaces, and the binding intensity leads to cellular activation. I argue from the stands of evolution and biological necessity, as well as the progression of our understanding of cellular membranes and phagocytosis. The effort is to invite debate of the topic from a less familiar yet equally thrilling viewing angle.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".