ORAL ARTIFICIAL CELLS BIOENCAPSULATED GENETICALLY ENGINEERED CELLS CAN LOWER UNWANTED ELECTROLYTES IN UREMIC RATS
Bibliographic record
Abstract
A) Purpose of study: We have shown earlier that oral administration of genetically engineered cells can lower urea, uric acid, and creatinine in uremic rats. The present study is to see whether this can lower K+, P, Cl−, and P in uremic rats. B) Methods used: Genetically engineered E. coli DH5 cells are encapsulated in artificial cells. The efficacy for the removal of electrolytes was analyzed in-vitro in batch bioreactors and in-vivo in daily oral administration to partially nephrectomized male Wistar rats. C) Results summary: In-vitro: Significant lowering of plasma K+, P, Na+, and Cl− occurs in in-vitro experiments in batch bioreactors. In-vivo experiments in uremic rats show that oral administration also resulted in lowering of plasma electrolytes levels. For example, plasma K+ decreases from 5.66 + 1.15 (mmol/L) to 4.23 ± 0.90 (mmol/L), plasma P from 2.44 ± 0.56 (mmol/L) to 1.54 ± 0.59 (mmol/L), plasma Na+ 146 ± 6.30 (mmol/L) to 131.20 ± 8.60 (mmol/L), plasma Cl− from 206.00 ± 49.70 (mmol/L) to 101.00 ± 15.00 (mmol/L), and alkaline phosphatase from 212.33 ± 63.21 (u/l) to 87.66 ± 24.54 (u/l). On discontinuation of the therapy, electrolyte levels increased again. Ref.: www.artcell.mcgill.ca
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".