Interplay between intestinal alkaline phosphatase, diet, gut microbes and immunity
Bibliographic record
Abstract
Intestinal alkaline phosphatase (IAP) plays an essential role in intestinal homeostasis and health through interactions with the resident microbiota, diet and the gut. IAP's role in the intestine is to dephosphorylate toxic microbial ligands such as lipopolysaccharides, unmethylated cytosine-guanosine dinucleotides and flagellin as well as extracellular nucleotides such as uridine diphosphate. IAP's ability to detoxify these ligands is essential in protecting the host from sepsis during acute inflammation and chronic inflammatory conditions such as inflammatory bowel disease. Also important in these complications is IAP's ability to regulate the microbial ecosystem by forming a complex relationship between microbiota, diet and the intestinal mucosal surface. Evidence reveals that diet alters IAP expression and activity and this in turn can influence the gut microbiota and homeostasis. IAP's ability to maintain a healthy gastrointestinal tract has accelerated research on its potential use as a therapeutic agent against a multitude of diseases. Exogenous IAP has been shown to have beneficial effects when administered during ulcerative colitis, coronary bypass surgery and sepsis. There are currently a handful of human clinical trials underway investigating the effects of exogenous IAP during sepsis, rheumatoid arthritis and heart surgery. In light of these findings IAP has been marked as a novel agent to help treat a variety of other inflammatory and infectious diseases. The purpose of this review is to highlight the essential characteristics of IAP in protection and maintenance of intestinal homeostasis while addressing the intricate interplay between IAP, diet, microbiota and the intestinal epithelium.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".