Bibliographic record
Abstract
Methods to microencapsulate enzymes and cells including recombinant enzymes, stem cells, and genetically engineered cells have been described in this chapter. More specific examples of enzyme encapsulation include the microencapsulation of xanthine oxidase for Lesch Nyhan disease, phenylalanine ammonia lyase for phenylketonuria, and microencapsulation of multienzyme systems with cofactor recycling for multistep enzyme conversions. Methods for cell encapsulation include the details for encapsulating hepatocytes for liver failure and for gene therapy. This also includes the details of a novel two-step method for encapsulation of high concentrations of smaller cells. The recent co-encapsulation of bone marrow stem cells with hepatocytes is also included. Another new approach is the detailed method for encapsulation of genetically engineered Escherichia coli DH5 cells and other microorganisms for the removal or conversion metabolites. Another new approach is the nanoencapsulation of hemoglobin and enzymes to form 150-nm diameter nanocapsules; the details are available elsewhere.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".