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Record W2615014982 · doi:10.1177/0885328217708458

Nanoformulated water-soluble paclitaxel to enhance drug efficacy and reduce hemolysis side effect

2017· article· en· W2615014982 on OpenAlexaff
Weiting Gu, Jie Chen, Prabir K. Patra, Xiaoyan Yang, Quanrong Gu, Lingxuan Wei, Jason P. Acker, Beihua Kong

Bibliographic record

VenueJournal of Biomaterials Applications · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsCanadian Blood ServicesUniversity of Alberta
Fundersnot available
KeywordsPaclitaxelHemolysisDrugNanocarriersPharmacologyIn vivoChemotherapyPoloxamerMedicineChemistrySurgeryBiologyInternal medicineBiotechnology

Abstract

fetched live from OpenAlex

Surgery, chemotherapy, and radiotherapy are the three top cancer treatment modalities. Paclitaxel (PTX) is one of the most widely used chemotherapy drugs. However, its clinical applications have been significantly limited due to: (i) serious hemolysis effect of currently available commercial paclitaxel formulations and (ii) its water insolubility. An easy way to deliver paclitaxel by a new nanocarrier system using pluronic copolymers of P123/F68 and Sorbitan monopalmitate (Span 40) was reported in our previous research article. The characterization of the formulation and analysis of drug release and cellular uptake were also presented. In this article, we reported discoveries of our follow-up in vivo antitumor and in vitro hemolytic study discoveries. The experimental results showed that the nanoformulated PTX achieved much better tumor suppression performance while reducing hemolysis side effects. This newly formulated drug can significantly improve patient outcomes in cancer chemotherapy.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.299
Teacher spread0.289 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2017
Admission routes1
Has abstractyes

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