Transfer of Inter-α-inhibitor Heavy Chains to Hyaluronan by Surface-linked Hyaluronan-TSG-6 Complexes
Bibliographic record
Abstract
Inter-alpha-inhibitor, TSG-6, and hyaluronan have important functions in fertility and inflammation. Two subunits of inter-alpha-inhibitor, the heavy chains, form covalent bonds with TSG-6 or hyaluronan in vitro. TSG-6-heavy chain complexes serve as intermediates in the transfer of heavy chains from inter-alpha-inhibitor to hyaluronan. In vivo, in addition to these complexes, stable ternary complexes of hyaluronan with both TSG-6 and heavy chains have been demonstrated in the ovulatory cumulus oophorus. In our ongoing efforts to characterize the multiple interactions between hyaluronan, TSG-6 and inter-alpha-inhibitor, we recently characterized the formation of highly stable complexes of TSG-6 with hyaluronan that had been tethered to a solid surface. Here we show that these hyaluronan-TSG-6 complexes are functionally active and transfer heavy chain subunits from inter-alpha-inhibitor to either free or surface-bound hyaluronan. Transitional hyaluronan-TSG-6-heavy chain complexes do not accumulate in vitro. Our data show the capability for heavy chain transfer by both free TSG-6 and preformed hyaluronan-TSG-6 complexes, suggesting that both might contribute to hyaluronan modification in vivo. Transfer of heavy chains to surface-tethered hyaluronan by either free TSG-6 or surface-tethered hyaluronan-TSG-6 complexes did not affect the CD 44-mediated binding of BW 5147 cells in vitro. We show how TSG-6 and hyaluronan together can deplete inter-alpha-inhibitor and generate bikunin, as has been observed in sepsis, and discuss the role of TSG-6 in the generation of hyaluronan-heavy chain complexes associated with ovulation, arthritis, and sepsis.
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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 | 0.001 |
| 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".