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Record W3126695924 · doi:10.1080/02652048.2021.1876175

Bortezomib-loaded lipidic-nano drug delivery systems; formulation, therapeutic efficacy, and pharmacokinetics

2021· review· en· W3126695924 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

VenueJournal of Microencapsulation · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBortezomibDrug deliveryPharmacologyDrugPharmacokineticsLiposomeMedicineMultiple myelomaMaterials scienceNanotechnologyInternal medicine

Abstract

fetched live from OpenAlex

AIM: Nano drug delivery systems can provide the opportunity to reduce side effects and improve the therapeutic aspect of a variety of drugs. Bortezomib (BTZ) is a proteasome inhibitor approved for the treatment of multiple myeloma and mantle cell lymphoma. Severe side effects of BTZ are the major dose-limiting factor. Particulate drug delivery systems for BTZ are polymeric and lipidic drug delivery systems. This review focussed on lipidic-nano drug delivery systems (LNDDSs) for the delivery of BTZ. RESULTS: LNDDSs including liposomes, solid lipid nanoparticles, and self-nanoemulsifying drug delivery systems showed reduce systemic side effects, improved therapeutic efficacy, and increased intestinal absorption. Besides LNDDSs were used to target-delivery of BTZ to cancer. CONCLUSION: Overall, LNDDSs can be considered as a novel delivery system for BTZ to resolve the treatment-associated restrictions.

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 score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.032
GPT teacher head0.304
Teacher spread0.272 · 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