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Potential for Application of Lignin Based Micro/Nanostructures as aMicro/Nanocarrier in the Controlled Release Systems: A Review

2022· review· en· W4223632579 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Nanoscience · 2022
Typereview
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNanocarriersNanotechnologyBiocompatibilityNanocapsulesMaterials scienceControlled releaseNanoparticleCoatingLigninChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Background: A promising strategy is to apply biodegradable and biocompatibility lignin micro/nanoparticles (LMPs/LNPs) as carriers or coating materials for biological active agent delivery in agriculture medicine and pharmaceuticals. Controlled release systems (CRSs) based on LMPs/LNPs are suitable systems to target specific tissues, cells, or plant roots by taking advantage of the unique properties of LMPs/LNPs. Methods: This review discusses changes in the properties of LNPs caused by different parameters in the synthesis method, such as the type of biologically active agent, loading/release method, modification method, encapsulation efficiency, and release rate of the CRSs based on LMPs/LNPs. Results: Research shows that during the LMPs/LNPs synthesis, nanospheres with a porous surface, nanocapsules, or hollow nanospheres with excellent stability and chemical properties are produced, which causes high loading capacity and reduced release rates of active agents. Moreover, the advantages and technical challenges of lignin application as a micro/ nanocarrier were investigated. Conclusion: Finally, several suggestions for the future trend of research and development were recommended.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.301
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it