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Record W4391322371 · doi:10.2217/nnm-2023-0267

Nanomedicine-Mediated Drug Delivery for Potential Treatment of Inflammatory Bowel Disease: A Narrative Review

2024· review· en· W4391322371 on OpenAlexaff
Zhina Majdzadeh Ardekani, Ana L Lorenzo-Leal, Horacio Bach

Bibliographic record

VenueNanomedicine · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseUlcerative colitisNanomedicineNarrative reviewDrug deliveryDiseaseCrohn's diseaseIntensive care medicineInflammatory Bowel DiseasesDrugBiological drugsTargeted drug deliveryInternal medicinePharmacologyNanotechnology

Abstract

fetched live from OpenAlex

Background & aims: Inflammatory bowel disease (IBD) is a condition characterized by chronic inflammation of the gastrointestinal tract, manifesting as either Crohn's disease (CrD) or ulcerative colitis (UC). Current treatment options for CrD and UC primarily focus on symptom management. In recent years, advancements in nanotechnology have increased the clinical applicability of nanoparticles (NPs) in treating IBD. This review explores the current research on NP-mediated drug-delivery systems for IBD treatment and assesses its advantages and limitations. Results: The authors examine diverse nanomedicine applications for IBD and address the current challenges and prospects in the field to advance nanomediated therapies in the future. Conclusion: Innovative NP-based treatment strategies promise a reliable and effective approach to IBD management.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.302
Teacher spread0.290 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2024
Admission routes1
Has abstractyes

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