Bioactive proteins in bovine colostrum and effects of heating, drying and irradiation
Bibliographic record
Abstract
Bovine colostrum (BC) contains bioactive proteins, such as immunoglobulin G (IgG), lactoferrin (LF) and lactoperoxidase (LP). BC was subjected to low-temperature, long-time pasteurization (LTLT, 63 °C, 30 min) or high-temperature, short-time pasteurization (HTST, 72 °C, 15 s) and spray-drying (SD), with or without γ-irradiation (GI, ∼14 kGy) to remove microbial contamination. Relative to unpasteurized liquid BC, SD plus GI increased protein denaturation by 6 and 11%, respectively, increasing to 19 and 27% after LTLT and to 48% after HTST, with no further effects after GI (all P < 0.05). LTLT, without or with GI, resulted in 15 or 29% denaturation of IgG, compared with non-pasteurized BC, and 34 or 58% for HTST treatment (all P < 0.05, except LTLT without GI). For IgG, only GI, not SD or LTLT, increased denaturation (30-38%, P < 0.05) but HTST increased denaturation to 40%, with further increases after GI (60%, P < 0.05). LTLT and HTST reduced LP levels (56 and 81% respectively) and LTLT reduced LF levels (21%), especially together with GI (47%, P < 0.05). Denaturation of BSA, β-LgA, β-LgB and α-La were similar to IgG. Methionine, a protective amino acid against free oxygen radicals, was oxidised by LTLT + GI (P < 0.05) while LTLT and HTST had no effect. Many anti-inflammatory proteins, including serpin anti-proteinases were highly sensitive to HTST and GI but preserved after LTLT pasteurization. LTLT, followed by SD is an optimal processing technique preserving bioactive proteins when powdered BC is used as a diet supplement for sensitive patients.
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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".