Kinetic and thermodynamic parameters for heat denaturation of human recombinant lactoferrin from rice<sup>1</sup>This article is part of a Special Issue entitled Lactoferrin and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Heat denaturation of recombinant human lactoferrin (rhLf) from rice with 3 different iron-saturation degrees, holo rhLf (iron-saturated), AsIs rhLf (60% iron saturation), and apo rhLf (iron-depleted), was studied. The 3 forms of rhLf were subjected to heat treatment, and the kinetic and thermodynamic parameters of the denaturation process were determined. Thermal denaturation of rhLf was assessed by measuring the loss of reactivity against specific antibodies. D(t) values (time to reduce 90% of immunoreactivity) decreased with increasing temperature of treatment for apo and holo rhLf, those values being higher for the iron-saturated form, which indicates that iron confers thermal stability to rhLf. However, AsIs rhLf showed a different behaviour with an increase in resistance to heat between 79 °C and 84 °C, so that the kinetic parameters could not be calculated. The heat denaturation process for apo and holo rhLf was best described assuming a reaction order of 1.5. The activation energy of the denaturation process was 648.20 kJ/mol for holo rhLf and 406.94 kJ/mol for apo rhLf, confirming that iron-depleted rhLf is more sensitive to heat treatment than iron-saturated rhLf.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".