Live bacterial cells as orally delivered therapeutics
Bibliographic record
Abstract
Despite the swift escalation in research regarding the use of live bacterial cells for therapeutic purposes, the prophylactic and curative use of probiotic microorganisms still remains a wide and controversial field. In addition, the acknowledgement that live bacterial cells can be genetically engineered to synthesise products that have therapeutic potential has generated substantial interest among clinicians and health professionals. Clinical trials have increasingly provided an insightful scientific derivation for the use of live bacterial cells in medicinal practice in diseases such as diarrhoea, cancer, Crohn's disease, enhancement of the host's immune response, and numerous other diseases. A key constraint in the use of live bacterial cells, however, is the complexity of delivering them to the correct target sites. Oral delivery of free live cells, lyophilised cells and immobilised cells has been attempted, but with restricted success, chiefly because bacterial cells are unable to survive passage through the gastrointestinal tract in sufficient dosage. On many occasions, when given orally, these cells have been found to provoke immunogenic responses that are undesirable. Recent studies show that these problems can be overcome by delivering live bacterial cells using artificial cell microcapsules. This review abridges recent developments in the therapeutic use of live bacterial cells, addresses the potential and restrictions for their application in therapy, and provides insights into the future course of this emerging therapy.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".