A Fish Leukocyte Immune-Type Receptor Uses a Novel Intracytoplasmic Tail Networking Mechanism to Cross-Inhibit the Phagocytic Response
Bibliographic record
Abstract
) leukocyte immune-type receptors (IpLITRs) are a family of immunoregulatory proteins shown to regulate several innate immune cell effector responses, including phagocytosis. The precise mechanisms of IpLITR-mediated regulation of the phagocytic process are not entirely understood, but we have previously shown that different IpLITR-types use classical as well as novel pathways for controlling immune cell-mediated target engulfment. To date, all functional assessments of IpLITR-mediated regulatory actions have focused on the independent characterization of select IpLITR-types in transfected cells. As members of the immunoglobulin superfamily, many IpLITRs share similar extracellular Ig-like domains, thus it is possible that various IpLITR actions are influenced by cross-talk mechanisms between different IpLITR-types; analogous to the paired innate receptor paradigm in mammals. Here, we describe in detail the co-expression of different IpLITR-types in the human embryonic AD293 cell line and examination of their receptor cross-talk mechanisms during the regulation of the phagocytic response using imaging flow cytometry, confocal microscopy, and immunoprecipitation protocols. Overall, our data provides interesting new insights into the integrated control of phagocytosis via the antagonistic networking of independent IpLITR-types that requires the selective recruitment of inhibitory signaling molecules for the initiation and sustained cross-inhibition of phagocytosis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".