Effect of charge on interstitial distribution of albumin in rat dermis <i>in vitro</i>
Bibliographic record
Abstract
At physiological pH, negatively charged glycosaminoglycans in the extracellular matrix may influence distribution volume of a probe. We hypothesized that by varying the probe charge we would be able to observe a graded response of available volume fraction. Human serum albumin (HSA) (isoelectric point (pI) 5.0) was made more positive by cationization. Using reaction times of 10, 45 and 60 min, cationized HSA (cHSA) with respective pIs of 6.5, 7.3 and 8.0 were made. After eight days of equilibration in a buffer containing labelled native HSA and cHSA, the distribution volumes were calculated relative to that of 51Cr-EDTA, an extracellular tracer. The available volume in fully swollen dermis for native albumin relative to that of the extracellular tracer averaged 0.485+/-0.008 (n=49), with corresponding volumes for cHSA-10 min, cHSA-45 min and cHSA-60 min of 0.554+/-0.012 (n=17), 0.647+/-0.026 (n=17) and 0.718+/-0.021 (n=12), respectively. Increasing the ionic strength of the bathing solution to 1 M NaCl, thereby screening the fixed charges of tissue elements and probes alike, resulted in similar available and thereby excluded volumes of native HSA and neutral cHSA-45 min. These experiments suggest that fixed negative charges, most likely glycosaminoglycans, contribute significantly to interstitial exclusion of charged macromolecules, a phenomenon of importance for hydration of the interstitial fluid phase and therefore for body fluid balance. Moreover, the data indicate that previous findings of similar excluded volumes for the two differently sized major plasma proteins albumin (molecular mass 66 kDa) and IgG (molecular mass 160 kDa) may be explained by a more pronounced electrostatic repulsion of the former by the extracellular matrix.
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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".