Hemoglobin Enhances the Biological Activity of Synthetic and Natural Bacterial (Endotoxic) Virulence Factors: A General Principle
Bibliographic record
Abstract
Although hemoglobin (Hb) is mainly present in the cytoplasm of erythrocytes (red blood cells), lower concentrations of pure, cell-free Hb are released permanently into the circulation due to an inherent intravascular hemolytic disruption of erythrocytes. Previously it was shown that the interaction of Hb with bacterial endotoxins (lipopolysaccharides, LPS) results in a significant increase of the biological activity of LPS. There is clear evidence that the enhancement of the biological activity of LPS by Hb is connected with a disaggregation of LPS. From these findings one questions whether the property to enhance the biological activity of endotoxin, in most cases proven by the ability to increase the cytokine (tumor-necrosis-factor-alpha, interleukins) production in human mononuclear cells, is restricted to bacterial endotoxin or is a more general principle in nature. To elucidate this question, we investigated the interaction of various synthetic and natural virulence (pathogenicity) factors with hemoglobin of human or sheep origin. In addition to enterobacterial R-type LPS a synthetic bacterial lipopeptide and synthetic phospholipid-like structures mimicking the lipid A portion of LPS were analysed. Furthermore, we also tested endotoxically inactive LPS and lipid A compounds such as those from Chlamydia trachomatis. We found that the observations made for endotoxically active form of LPS can be generalized for the other synthetic and natural virulence factors: In every case, the cytokine-production induced by them is increased by the addition of Hb. This biological property of Hb is connected with its physical property to convert the aggregate structures of the virulence factors into one with cubic symmetry, accompanied with a considerable reduction of the size and number of the original aggregates.
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 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".