Differential mechanisms of neutrophil and monocyte adhesion on neuroblastoma cells: CD18 and VLA-4 integrins mediate adhesion to SK-N-SH, but not to SK-n-MC cell line
Bibliographic record
Abstract
We examined the adhesion of monocytes and polymorphonuclear leukocytes (PMNLs) to the neuroblastoma (NB) cell lines SK-N-SH and SK-N-MC, which have some distinct differentiation characteristics. Monocytes adhered to SK-N-SH and SK-N-MC to the same extent (20 +/- 1.4% and 24 +/- 0.8% of monocytes added). Monocyte adhesion to SK-N-SH but not SK-N-MC was partially inhibited by treating monocytes with a mAb to the CD18 (beta2) integrin chain. The adhesion was further inhibited when monocytes were treated with a combination of mAb to CD18 and VLA-4. Treatment of both NB cell lines with interleukin-1alpha (0.5 ng/ml), tumor necrosis factor alpha (100 U/ml), interferon gamma (200 U/ml), or their combinations increased monocyte adhesion to SK-N-SH and SK-N-MC. With each condition, monocyte adhesion to SK-N-SH was partially blocked by mAb to CD18. The inhibition of adhesion to IL-1alpha- or TNFalpha-treated SK-N-SH cells was greater when the monocytes were treated with mAb to both CD18 and VLA-4. In contrast, monocyte adhesion to IL-1alpha or IFNgamma treated SK-N-MC was only slightly inhibited with a combination of mAb to CD18 + VLA-4 and there was no inhibition at all to TNFalpha-treated SK-N-MC. Spontaneous PMNL adhesion to SK-N-SH was almost negligible but increased by treating the cell line with IL-1alpha, TNFalpha, IFNgamma or their combinations. A mAb to CD18 blocked this increase in each case. The pattern of adhesion of PMNLs to SK-N-MC was totally different. PMNL adhesion to unstimulated SK-N-MC was very high (24 +/- 1.3%), was not inhibited by mAb to CD18, and did not increase by stimulating the cell line with IL-1alpha, TNFalpha, IFNgamma or their combinations. Overall, these results suggest two distinct patterns of monocyte and PMNL interaction with neural cells, such as the SK-N-SH and MC cell lines. While monocyte and PMNL adhesion to SK-N-SH is mainly via CD18/VLA-4 or the CD18 mechanisms, respectively, leukocyte adhesion to SK-N-MC is CD18- and VLA-4-independent. Thus, leukocyte-neural cell interactions share some mechanisms common also to leukocyte-endothelium interaction, but there are also unique mechanisms which may be neural cell and differentiation specific.
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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 | 0.000 | 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".