Impact of operating conditions on chromatographic column performance: experimental studies on adsorption of high-value minor whey proteins
Bibliographic record
Abstract
Over the last decade, ion-exchange chromatography (IEC) has been extensively explored for protein purification at both small and large scales. Despite several IEC columns are commercialized, the physical phenomena underlying the adsorption of proteins on ion-exchange columns performance has not been thoroughly investigated. In this work, the influence of operating conditions on the adsorption of lactoperoxidase (LP) and lactoferrin (LF) on cation exchange chromatography adsorbent is experimentally studied in order to understand fundamental pertaining to underlying mechanism. Analysis was carried out in columns with different IDs (7.7 and 16 mm), packed for 100 mm with 90 μm particle size polymer-grafted cation exchanger. The flow distribution was measured using acetone as a non-binding tracer. An evaluation of van Deemter plots was done as well as LP breakthrough curves at different flow rates and LP loading concentrations. The results were compared with two columns in terms of efficiency and the LP binding capacity. The dynamic binding capacity at 10% breakthrough was found to be independent of the applied flow rate. Surprisingly for both systems, LP breakthrough takes place later at higher loading concentrations, which is in contrast to IEC. The results propose a major presence of non-ideal effects as steric shielding and charge repulsion of protein in the adsorption. In addition, the accessibility of binding sites for protein at higher concentrations seems more available than sodium counter-ions in buffer.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".