Allosteric Sensing of Fatty Acid Binding by NMR: Application to Human Serum Albumin
Bibliographic record
Abstract
Human serum albumin (HSA) serves not only as a physiological oncotic pressure regulator and a ligand carrier but also as a biomarker for pathologies ranging from ischemia to diabetes. Moreover, HSA is a biopharmaceutical with a growing repertoire of putative clinical applications from hypovolemia to Alzheimer's disease. A key determinant of the physiological, diagnostic, and therapeutic functions of HSA is the amount of long chain fatty acids (LCFAs) bound to HSA. Here, we propose to utilize (13)C-oleic acid for the NMR-based assessment of albumin-bound LCFA concentration (CONFA). (13)C-Oleic acid primes HSA for a LCFA-dependent allosteric transition that modulates the frequency separation between the two main (13)C NMR peaks of HSA-bound oleic acid (ΔνAB). On the basis of ΔνAB, the overall [(12)C-LCFA]Tot/[HSA]Tot ratio is reproducibly estimated in a manner that is only minimally sensitive to glycation, albumin concentration, or redox potential, unlike other methods to quantify HSA-bound LCFAs such as the albumin-cobalt binding assay.
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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 | 0.001 | 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".