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Record W4409974014 · doi:10.1002/adhm.202501006

β‐1,3 Glucan Microparticles & Nanoparticles: Fabrication Methods & Applications in Immunomodulation & Targeted Drug Delivery

2025· review· en· W4409974014 on OpenAlexafffund
Nate Dowdall, Todd Hoare

Bibliographic record

VenueAdvanced Healthcare Materials · 2025
Typereview
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsImmune systemDrug deliveryNanotechnologyInnate immune systemMaterials scienceCell biologyBiologyImmunology

Abstract

fetched live from OpenAlex

Innate immune cells such as macrophages and dendritic cells play major roles in the progression of many cancerous, fibrotic, and autoimmune diseases, often due to environmental cues that skew these cells toward a phenotype that progresses or exacerbates the disease state. As such, a growing focus in treating such diseases is placed on exploiting the high plasticity of these cells to modify or reverse their pro-disease phenotypes using immunomodulatory materials. β-1,3 glucans are one such type of material that has exhibited diverse immunomodulatory effects on immune cells, including the mitigation or reversal of the adverse effects of dysregulated immune cells. In this review, we outline various fabrication techniques to produce β-1,3 glucan-derived microparticles and nanoparticles and discuss the diverse particle properties that can be obtained by tuning glucan chemistry, fabrication method, and formulation components. Furthermore, the immunomodulatory applications of β-1,3 glucan particles are highlighted with a focus on immune cell targeting, modulation, and the delivery of small molecule and macromolecular therapeutics.

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 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 score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.034
GPT teacher head0.366
Teacher spread0.332 · 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 teacher head, not a consensus.

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

Citations8
Published2025
Admission routes2
Has abstractyes

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