Insect‐Microbe‐Based Laccase: Untapped Natural Resource for Industrial and Biotechnological Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Insects are highly diversified organisms that often form strong relationships with microorganisms. This relationship is driven by the secretion and exchange of various proteins. Among these, laccase (Lac), also known as multicopper oxidoreductase, is notable due to its high redox potential, broad substrate specificity, and reactivity. Many insects that produce Lacs are capable of breaking down various plant materials, including leaf litter, wood, paper, wool, clothes, and leather. As such, Lac is of prime importance in insect‐microbe ecological roles and it is important that Lacs are further explored for a range of beneficial applications. Although some studies already highlight the potential of insect‐microbe‐associated Lacs in biotechnology and bioremediation, they are not as extensively identified, characterized, or explored as those from fungi and bacteria. Lacs are typically produced by various organisms and secreted outside of cells via complex pathways. The biosynthesis of Lac can be enhanced or engineered through bioinformatics, genetic engineering, and synthetic biology tools, which achieve significant success in genome mining over the last decade. This review aims to raise awareness of the untapped potential of insect‐microbe‐associated Lacs and calls for their further exploration for human benefit.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it