Kinetic and Thermodynamic Analysis of Two Carboxymethylcellulases from Macrotermes subhyalinus Little Soldier
Bibliographic record
Abstract
Optimization of thermal processes relies on adequate degradation kinetic models to warrant food safety and quality. The knowledge on thermal inactivation of enzymes is necessary to allow their proper utilization in food industry and technology applications, enabling the reduction of heating times and optimization of heating temperatures. In this work, the kinetic of thermal inactivation was studied for the previously characterized carboxylmethylcellulases Ab-CX1 and Ab-CX2 from Macrotermes subhyalinus little soldier. Samples of carboxymethylcellulases were treated at different time-temperature combinations in the range of 5-60 min at 50-65°C and the kinetic and thermodynamic parameters for carboxymethylcellulases were calculated. Results showed that inactivation followed a first-order reaction with k-values between 0.0103 ± 0.0003 to 0.1217 ± 0.0005 and 0.0149 ± 0.0007 to 0.0416 ± 0.0003 min-1 for Ab-CX1 and Ab-CX2, respectively. At high temperatures, Ab-CX2 was less resistant, with a significant decrease in residual activity compared to Ab-CX1. The D- and k-values decreased and increased, respectively, with increasing temperature, indicating faster inactivation of carboxymethylcellulases. Activation energy (Ea) and Z-values were estimated to 76.74 ± 1.98 kJ.mol-1 and 24.21 ± 1.92 °C for Ab-CX1, 62.80 ± 2.05 kJ.mol-1 and 33.33 ± 2.78 °C for Ab-CX2. Thermodynamic parameters (ΔH#, ΔS# and ΔG#) were also calculated. The high value obtained for the variation in enthalpy of activation indicates that a high amount of energy is required to initiate denaturation, probably due to the molecular conformation of carboxymethylcellulases. All results suggest that both carboxymethylcellulases are relatively resistant to long heat treatments up to 50°C.
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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 | 0.001 |
| 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 | 0.001 |
| 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".