Effect of hydration on interstitial distribution of charged 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 macromolecular probes, a phenomenon of importance for hydration of the interstitium and therefore for body fluid balance. We hypothesized that such charge effect was dependent on hydration. Human serum albumin (HSA) (the pH value for the isoelectric point (pI) = 4.9) was made neutral by cationization (cHSA) (pI = 7.6). Rat dermis was studied in vitro in a specially designed equilibration cell allowing control of hydration. Using a buffer containing labelled native HSA and cHSA, the distribution volumes were calculated relative to that of 51Cr-EDTA, an extracellular tracer. During changes in hydration (H), defined as (wet weight - dry weight) (dry weight)(-1)), the slope of the equation describing the relationship between extracellular fluid volume (V(x)) (in g H2O (g dry weight)(-1)) and H (V(x) = 0.925 H + 0.105) differed significantly from that for available volumes of cHSA (V(a,cHSA) = 0.624 H - 0.538) and HSA (V(a,HSA) = 0.518 H - 0.518). A gradual reduction in H led to a reduction in difference between available volumes for the two albumin species. Screening the fixed charges by 1 m NaCl resulted in similar available and excluded volumes of native HSA and neutral cHSA. We conclude that during gradual dehydration, there is a reduced effect of fixed negative charges on interstitial exclusion of charged macromolecules. This effect may be explained by a reduced hydration domain surrounding tissue and probe macromolecules in conditions of increased electrostatic interactions. Furthermore, screening of negative charges suggested that hyaluronan associated with collagen may influence intrafibrillar volume of collagen and thereby available and excluded volume fraction.
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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) | 0.000 | 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 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".