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Controlled Release of Tramadol from Mixed Matrix Membranes

2012· article· en· W2096942702 on OpenAlexvenueno aff
Laura Donato, G. Barbaro, Enrico Drioli, Catia Algieri

Bibliographic record

VenueJournal of Membrane and Separation Technology · 2012
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsnot available
FundersUniversità della Calabria
KeywordsPolydimethylsiloxaneMembraneTramadol HydrochlorideTransdermalMatrix (chemical analysis)PolymerChemistryTramadolChemical engineeringChromatographyAnalgesicOrganic chemistryPharmacology

Abstract

fetched live from OpenAlex

In this work mixed matrix membranes (zeolite loaded) were prepared and tested as potential devices for the controlled release of tramadol hydrochloride. Due to the hydrophilic nature of the drug, a hydrophobic polymer (polydimethylsiloxane) was chosen for the membrane preparation. NaX zeolites was added to PDMS matrix as modulating agent with the aim to obtain a linear and adequate delivery of the drug in the time as required by the therapeutic needs of this opioid. About the different investigated systems, the PDMS membrane containing 17 wt% of zeolite and 0.2 wt% of drug seems to be the most promising for application as transdermal device. Different mathematical models (Zero order, First order, Higuchi, Bhaskar, and Korsemeyer-Peppas) were used to interpret the drug release mechanism from the different Mixed matrix membranes. The experimental data showed good fit with three different models: Higuchi, Bhaskar and Korsemeyer-Peppas.

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 score0.000
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 head0.008
GPT teacher head0.266
Teacher spread0.258 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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