Complement inhibition reduces material‐induced leukocyte activation with PEG modified polystyrene beads (Tentagel™) but not polystyrene beads
Bibliographic record
Abstract
With isolated leukocytes, inhibiting complement reduced material-induced leukocyte activation (CD11b) with polyethylene glycol modified polystyrene beads (PS-PEG), but not with polystyrene beads (PS). The PS-PEG beads (TentaGel) were complement activating as measured by SC5b-9 levels consistent with the sensitivity of these beads to leukocyte inhibition with complement inhibitors. Following contact with PS and PS-PEG beads, isolated leukocytes in plasma and in the absence in platelets were found to significantly upregulate CD11b, while TF expression and exposure of phosphatidylserine remained at background levels. Complement inhibition by means of sCR1 partially reduced CD11b upregulation on PS-PEG beads, but had no effect with PS beads. Pyridoxal-5-phosphate (P5P) was able to significantly reduce both CD11b upregulation and exposure of phosphatidylserine with PS-PEG beads, although it did not appear to inhibit SC5b-9 production. Pentamidine and NAAGA inhibited complement and were effective in reducing CD11b upregulation with both PS and PS-PEG. However, they also had an inhibitory effect on leukocyte signaling mechanisms, precluding their utility for further study in this context. Leukocyte adhesion occurred to similar extents on both PS and PS-PEG beads. While sCR1 and P5P blocked adhesion and activation (for adherent leukocytes) on PS-PEG beads, they had no effect on leukocytes adherent to PS beads. The role of complement in leukocyte activation and adhesion was found to be material-dependent. Thus, leukocyte-material compatibility may be resolved by complement inhibition in some but not all cases. For these other materials (example here was PS), other mechanisms, such as fibrinogen adsorption and direct leukocyte release, may need exploitation to minimize leukocyte activation and adhesion.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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 teacher head, 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".