Failure to Improve Parameters of Lactose Maldigestion using the Multiprobiotic Product VSL3 in Lactose Maldigesters: A Pilot Study
Bibliographic record
Abstract
Lactose maldigestion is a common genetic trait in up to 70% of the world's population. In these subjects, the ingestion of lactose may lead to prebiotic effects which can be confirmed by measurement of breath hydrogen. After a period of continuous lactose ingestion, colonic bacterial adaptation is measurable as improved parameters of lactose digestion. There may be inherent benefits in this process of adaptation which may protect against some diseases. We attempt to link therapeutically beneficial probiotics (VSL3, Seaford Pharmaceuticals Inc, Ontario) with improvement in parameters of lactose maldigestion. Two groups of five subjects with maldigestion were fed one or four packets of VSL3 (one packet containing 450 x 10(9) live bacteria) before testing and then 17 days later. A 50 g lactose challenge was carried out before and after feeding. While there was a trend toward increasing rather than reducing of summed breath hydrogen, no statistically significant changes were observed between results from before testing and those from testing 17 days later. The authors conclude that direct consumption of the probiotic VSL3 may not improve parameters of lactose maldigestion without metabolic activation. In its present format, therefore, the test for colonic adaptation cannot be used to demonstrate direct bacterial embedding with VSL3.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".