The biomedical and bioengineering potential of protein nanocompartments
Bibliographic record
Abstract
Protein nanocompartments (PNCs) are self-assembling biological nanocages that can be harnessed as platforms for a wide range of nanobiotechnology applications. The most widely studied examples of PNCs include virus-like particles, bacterial microcompartments, encapsulin nanocompartments, enzyme-derived nanocages (such as lumazine synthase and the E2 component of the pyruvate dehydrogenase complex), ferritins and ferritin homologues, small heat shock proteins, and vault ribonucleoproteins. Structural PNC shell proteins are stable, biocompatible, and tolerant of both interior and exterior chemical or genetic functionalization for use as vaccines, therapeutic delivery vehicles, medical imaging aids, bioreactors, biological control agents, emulsion stabilizers, or scaffolds for biomimetic materials synthesis. This review provides an overview of the recent biomedical and bioengineering advances achieved with PNCs with a particular focus on recombinant PNC derivatives.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".