Galectin-3 interacts with naïve and primed neutrophils, inducing innate immune responses
Bibliographic record
Abstract
The neutrophil is the first line of defense against infection. As a part of the innate immune response, neutrophils start to emigrate from blood to an affected site and their state is altered from passively circulating naïve to primed, and then to fully activated. The extent of neutrophil activation and their subsequent response varies depending on the stimuli and environment that neutrophils encounter. Because neutrophils can also induce deleterious effects on host tissues, tight regulation of recruitment and functions of neutrophils is required for efficient recovery. Galectin-3, a soluble beta-galactoside binding protein, of which expression is up-regulated during inflammation/infection, is suggested to be involved in various inflammatory responses. However, the precise roles of this lectin in innate immunity remain unknown, while it has been demonstrated that galectin-3 binds to naïve and primed neutrophils. Here we report that galectin-3 can induce L-selectin shedding and interleukin-8 production in naïve and primed neutrophils. These activities were shown to be dependent on the presence of the C-terminal lectin domain and the N-terminal nonlectin domain of galectin-3, which is involved in oligomerization of this lectin. We also found that, after galectin-3 binds to neutrophils, primed but not naïve neutrophils can cleave galectin-3, mainly through elastase, which results in the formation of truncated galectin-3 lacking the N-terminal domain. Together, these results suggest that galectin-3 activates naïve and primed neutrophils, and galectin-3-activated primed neutrophils have an ability to inactivate galectin-3.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".