Tissue-Specific Host Recognition by Complement Factor H Is Mediated by Differential Activities of Its Glycosaminoglycan-Binding Regions
Bibliographic record
Abstract
Complement factor H (CFH) regulates complement activation in host tissues through its recognition of polyanions, which mediate CFH binding to host cell surfaces and extracellular matrix, promoting the deactivation of deposited C3b. These polyanions include heparan sulfate (HS), a glycosaminoglycan with a highly diverse range of structures, for which two regions of CFH (CCP6-8 and CCP19-20) have been implicated in HS binding. Mutations/polymorphisms within these glycosaminoglycan-binding sites have been associated with age-related macular degeneration (AMD) and atypical hemolytic uremic syndrome. In this study, we demonstrate that CFH has tissue-specific binding properties mediated through its two HS-binding regions. Our data show that the CCP6-8 region of CFH binds more strongly to heparin (a highly sulfated form of HS) than CCP19-20, and that their sulfate specificities are different. Furthermore, the HS binding site in CCP6-8, which is affected by the AMD-associated Y402H polymorphism, plays the principal role in host tissue recognition in the human eye, whereas the CCP19-20 region makes the major contribution to the binding of CFH in the human kidney. This helps provide a biochemical explanation for the genetic basis of tissue-specific diseases such as AMD and atypical hemolytic uremic syndrome, and leads to a better understanding of the pathogenic mechanisms for these diseases of complement dysregulation.
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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 | 0.000 |
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".