Albumin-mediated Regulation of Cellular Glutathione and Nuclear Factor Kappa B Activation
Bibliographic record
Abstract
Human serum albumin (HSA) is a cystine-rich serum protein taken up by many cells through receptor-mediated and fluid-phase endocytosis. We hypothesized that HSA may play a role in modulating cellular antioxidant redox signaling. Lung epithelial cells (A549), fibroblasts (HFL1), and blood lymphocytes had increased glutathione (GSH) levels after 8 h incubation with HSA. Similar GSH increases were observed with either plasma-derived or recombinant HSA. Serum depleted of HSA had no effect on cellular GSH. The GSH increase was also observed in normal murine lungs upon in vivo airway instillation of HSA. GSH enhancement was not related to the redox state of the free cysteine residue (Cys-34) on HSA, however, reduction of disulfide bonds in HSA inhibited the increase in cellular GSH. In addition, the albumin-mediated increase in GSH was inhibited by the vacuolar (H(+))-ATPase inhibitors, bafilomycin A(1) and concanamycin, as well as by the membrane pH-disrupting ionophore monensin, but not by 20 mM NH(4)Cl. The degree to which albumin increased GSH levels was sufficient to protect cells against H(2)O(2)-mediated cytotoxicity and to decrease TNF-alpha-mediated NF-kappaB activation. We conclude that albumin specifically modulates cellular GSH levels, an effect sufficient to protect cells against oxidant injury and regulate NF-kappaB activation.
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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".