Binding of acellular, native and cross-linked human hemoglobins to haptoglobin: enhanced distribution and clearance in the rat
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is well established that hemoglobin resulting from red cell lysis binds to haptoglobin in plasma to form a complex. The increased molecular size precludes its filtration by the kidneys, redirecting it toward hepatocellular entry. Chemically cross-linked hemoglobins are designed to be resistant to renal excretion, even in the absence of haptoglobin. The manner in which binding to haptoglobin influences the pharmacokinetics of acellular cross-linked and native hemoglobins was investigated after intravenous injection of radiolabeled native human hemoglobin and trimesyl-(Lys82)beta-(Lys82)beta cross-linked human hemoglobin, at trace doses, into rats. Under these conditions, there is sufficient plasma haptoglobin for binding with hemoglobin. In vitro binding assayed by size-exclusion chromatography for bound and free hemoglobin revealed that, at <8 muM hemoglobin, native human hemoglobin was completely bound to rat haptoglobin, whereas only approximately 30% of trimesyl-(Lys82)beta-(Lys82)beta cross-linked hemoglobin was bound. Plasma disappearance of low doses (0.31 mumol/kg) of native and cross-linked hemoglobins was monoexponential (half-life = 23 and 33 min, respectively). The volume of distribution (40 vs. 19 ml/kg) and plasma clearance (1.22 vs. 0.4 ml.min(-1).kg(-1)) were higher for native than for cross-linked hemoglobin. Native and cross-linked human hemoglobins were found primarily in the liver, and not in the kidney, heart, lung, or spleen, mostly as degradation products. These pharmacokinetic findings suggest that the binding of hemoglobin to haptoglobin enhances its hepatocellular entry, clearance, and distribution.
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.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it