Deglycosylation Differentially Regulates Weaned Porcine Gut Alkaline Phosphatase Isoform Functionality along the Longitudinal Axis
Bibliographic record
Abstract
Gut alkaline phosphatases (AP) dephosphorylate the lipid moiety of endotoxin and other pathogen-associated-molecular patterns members, thus maintaining gut eubiosis and preventing metabolic endotoxemia. Early weaned pigs experience gut dysbiosis, enteric diseases and growth retardation in association with decreased intestinal AP functionality. However, the role of glycosylation in modulation of the weaned porcine gut AP functionality is unclear. Herein three different research approaches were taken to investigate how deglycosylation affected weaned porcine gut AP activity kinetics. In the first approach, weaned porcine jejunal AP isoform (IAP) was fractionated by the fast protein-liquid chromatography and purified IAP fractions were kinetically characterized to be the higher-affinity and lower-capacity glycosylated mature IAP (p < 0.05) in comparison with the lower-affinity and higher-capacity non-glycosylated pre-mature IAP. The second approach enzyme activity kinetic analyses showed that N-deglycosylation of AP by the peptide N-glycosidase-F enzyme reduced (p < 0.05) the IAP maximal activity in the jejunum and ileum and decreased AP affinity (p < 0.05) in the large intestine. In the third approach, the porcine IAP isoform-X1 (IAPX1) gene was overexpressed in the prokaryotic ClearColiBL21 (DE3) cell and the recombinant porcine IAPX1 was associated with reduced (p < 0.05) enzyme affinity and maximal enzyme activity. Therefore, levels of glycosylation can modulate plasticity of weaned porcine gut AP functionality towards maintaining gut microbiome and the whole-body physiological status.
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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 | 0.001 |
| 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".