Assessment of the immune-modulatory activity of sialylated fraction of IVIg in a murine model of allergic asthma
Bibliographic record
Abstract
Intravenous immunoglobulin (IVIg) has potent immune-modulating properties. In OVA-challenged mice, we demonstrated that IVIg markedly attenuates airway hyperresponsiveness (AHR) and abrogates airways inflammation, accompanied by substantial induction of antigen-specific Foxp3 Treg from non-Treg precursors. Mice were sensitized (i.n.) with OVA and then received IVIg or sialic acid enriched IVIg (SA-IVIg) fragments (i.p.), and then underwent challenge (i.n.). The induction of CD4 CD25 Foxp3 Treg was determined by flow-cytometry. AHR was measured, using a flexiVent small animal ventilator. Phenotypic properties of dendritic cells (DC) from various experimental groups were assessed by flow-cytometry. Expression of DCIR on DC was evaluated by flowcytometry and ICC. Adoptive transfer of DC was carried out to show the tolerogenic activity of IVIg-primed DC. IVIg and the SA-IVIg fraction induced Treg and abrogated AHR in OVA-challenged mice comparably. It followed by tolerogenic predisposition of DC (decrease of CD80/CD86 expression and IFN-γ production and increased level of IL-10). Adoptive transfer of DC from IVIg treated mice to OVA-challenged WT syngeneic mice has the similar anti-inflammatory activity of IVIg/SA-IVIg. Expression of DCIR (Inhibitory C-type lectin receptors) on DC of IVIg and SA-IVIg treated mice increased significantly. IVIg induces Treg likely via conferring tolerogenic activities to DC. This mechanism is dependent on sialylated fraction of IVIg. DCIR is an inhibitory C-type lectin receptor that can be targeted by SA-IVIg and induce an inhibitory signal into the ligated cells. More dissection is required to confirming the role of DCIR in this model.
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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) | 0.001 | 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 | 0.002 |
| 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".