Microencapsulation protected <i>Lactobacillus</i> viability and its activity in modulating the intestinal microbiota in newly weaned piglets
Bibliographic record
Abstract
Lactobacilli are sensitive to heat, which limits their application as probiotics in livestock production. Lactobacillus rhamnosus LB1 was previously shown to reduce enterotoxigenic Escherichia coli (ETEC) and Salmonella infections in pigs. To investigate its potential in the application, the bacterium was microencapsulated and examined for its survival from feed pelleting and long-term storage as well as its function in modulating pig intestinal microbiota. The in vitro studies showed that freshly microencapsulated Lactobacillus rhamnosus LB1 had viable counts of 9.03 ± 0.049 log10 colony-forming units/g, of which only 0.06 and 0.87 Log of viable counts were reduced after storage at 4 and 22 °C for 427 d. The viable counts of encapsulated Lactobacillus rhamnosus LB1 were 1.06 and 1.54 Log higher in the pelleted and mash feed, respectively, than the non-encapsulated form stored at 22 °C for 30 d. In the in vivo studies, 80 piglets (weaned at 21 d of age) were allocated to five dietary treatments for a 10-d growth trial. The dietary treatments were the basal diet (CTL) and basal diet combined with either non-encapsulated LB1 (NEP), encapsulated LB1 (EP), bovine colostrum (BC), or a combination of encapsulated LB1 and bovine colostrum (EP-BC). The results demonstrated that weaning depressed feed intake and reduced growth rates in pigs of all the treatments during 21 to 25 d of age; however, the body weight gain was improved during 25 to 31 d of age in all groups with the numerically highest increase in the EP-BC-fed pigs during 21 to 31 d of age. Dietary treatments with EP, particularly in combination with BC, modulated pig intestinal microbiota, including an increase in Lactobacillus relative abundance. These results suggest that microencapsulation can protect Lactobacillus rhamnosus LB1 against cell damage from a high temperature during processing and storage and there are possible complementary effects between EP and BC.
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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".