Transgenomic Metabolic Interactions in a Mouse Disease Model: Interactions of <i>Trichinella </i><i>s</i><i>piralis</i> Infection with Dietary <i>Lactobacillus </i><i>p</i><i>aracasei </i>Supplementation
Bibliographic record
Abstract
Irritable Bowel Syndrome (IBS) is a common multifactorial intestinal disorder for which the aetiology remains largely undefined. Here, we have used a Trichinella spiralis (T. spiralis)-induced model of post-infective IBS, and the effects of probiotic bacteria on gut dysfunction have been investigated using a metabonomic strategy. A total of 44 mice were divided into four groups: an uninfected control group and three T. spiralis-infected groups, one as infected control and the two other groups subsequently treated with either Lactobacillus paracasei (L. paracasei) NCC2461 in spent culture medium (SCM) or with L. paracasei-free SCM. Plasma, jejunal wall and longitudinal myenteric muscle samples were collected at day 21 post-infection. An NMR-based metabonomic approach characterized that the plasma metabolic profile of T. spiralis-infected mice showed an increased energy metabolism (lactate, citrate, alanine), fat mobilization (acetoacetate, 3-D-hydroxybutyrate, lipoproteins) and a disruption of amino acid metabolism due to increased protein breakdown, which were related to the intestinal hypercontractility. Increased levels of taurine, creatine and glycerophosphorylcholine in the jejunal muscles were associated with the muscular hypertrophy and disrupted jejunal functions. L. paracasei treatment normalized the muscular activity and the disturbed energy metabolism as evidenced by decreased glycogenesis and elevated lipid breakdown in comparison with untreated T. spiralis-infected mice. Changes in the levels of plasma metabolites (glutamine, lysine, methionine) that might relate to a modulation of immunological responses were also observed in the presence of the probiotic treatment. The work presented here suggests that probiotics may be beneficial in patients with IBS.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".