Free and Microencapsulated<i>Lactobacillus</i>and Effects of Metabolic Induction on Urea Removal
Bibliographic record
Abstract
We have previously reported the experimental use of genetically engineered Escherichia coli with microencapsulation to lower nitrogenous waste. Concern has surfaced, nonetheless, about safety of genetically engineered product. The purpose of this study is to explore the alternative use of probiotics in removal of plasma urea. After repeated cycles of exposure of Lactobacillus delbrueckii in urea-rich medium under anaerobic environment, the organisms were demonstrated to lower plasma urea concentration in vitro. Suspension of Lactobacillus in uremic plasma reduced the urea nitrogen levels from 51.5 +/- 5.2 mg/dL to 44.3 +/- 3.9 mg/dL (P = 0.02) after 24 hours. With microencapsulation of Lactobacillus (inside semipermeable alginate-polylysine-alginate polymeric membrane), further lowering of urea nitrogen levels was achieved (35.4 +/- 0.8 mg/dL, P = 0.03) at 24 hours. These preliminary data show that expression of certain enzymes could be induced in Lactobacillus delbrueckii and thus capable of lowering plasma urea. Further studies and molecular analysis would be indicated to explore and refine the techniques.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".