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Record W7161985929 · doi:10.82308/34540

Biomimetic nanoparticles and resveratrol as therapeutic interventions in ischemic stroke

2024· dissertation· en· W7161985929 on OpenAlexaboutno aff
Patrick‐Brian Bielawski

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsTissue plasminogen activatorThrombolysisHMGB1ResveratrolNeuroprotectionStroke (engine)IschemiaPlasminogen activatorBrain damage

Abstract

fetched live from OpenAlex

Ischemic stroke is a leading killer worldwide and the primary cause of disability in Canada caused by vessel occlusion from clots. Recombinant tissue plasminogen activator (rtPA) thrombolysis remains the only available effective treatment option and is limited by a short half-life of 4.5 minutes. With a therapeutic time window post-stroke of only 3 hours and its several contraindications, rtPA is limited to a select subpopulation of stroke patients. We investigated a novel nanocarrier fabricated from platelet membranes which were reassembled into monodisperse biomimetic nanoparticles (called cellsomes) loaded with rtPA as a potential treatment alternative. Leveraging the inherent interaction between platelet membrane proteins with clots causing ischemic stroke, we expect to increase rtPA localisation to the occlusion site. The inclusion of rtPA as cargo within the cellsome may protect rtPA from being degraded by plasminogen activator inhibitor 1, improving the therapeutic time window and increasing the ratio of patients achieving reperfusion and improved functional outcomes. Pursuant to stroke, a multiplicity of molecular pathways and cellular reactions are engaged to help protect the brain from damage but can lead to further damage themselves through a vicious pro-inflammatory cycle. In response to stress, cells release damage-associated molecular patterns including High-Mobility Group Box 1 (HMGB1) and Heat Shock protein 70 kDa family (HSP72). HMGB1 can activate pro-inflammatory cytokine production when it is acetylated (AcHMGB1). AcHMGB1 is mainly localised in the cytosol. This study shows HMGB1 and HSP72 modulation following treatment with rtPA-cellsomes and an anti-inflammatory agent (resveratrol) in a stroke model in vitro. We demonstrate that rtPA-cellsomes are not cytotoxic within clinically relevant concentrations and that they retain the thrombolytic activity of free-rtPA, without exerting a hemolytic effect. Under an oxygen-glucose deprivation (OGD) in vitro model of stroke, nuclear abundance of HMGB1 and AcHMGB1 in human microglia and macrophages decreased, whereas treatment with rtPA-cellsomes did not alter nuclear nor cytosolic abundance. Treatment with resveratrol increased HSP72 cytosolic abundance in microglia. Using a proximity ligation assay, HSP72 interacted with HMGB1 and with AcHMGB1, but to different extents. Treatment with resveratrol under OGD conditions further decreased HSP72-HMGB1 interactions. In contrast, resveratrol increased HSP72-AcHMGB1 interactions in microglia, normalising their state similar to controls. This study lends credence to the use of a novel platelet membrane-derived biomimetic nanocarrier as a platform for the effective delivery of rtPA. These findings also point out a salient molecular interaction suited for a two-pronged nanotherapeutic intervention in stroke by enhancing rtPA delivery and by normalising interactions between HMGB1 and HSP72 with resveratrol. Collectively, results from this study suggest that combination therapy using cellsomes and neuroprotective agents merits further investigations in vivo

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 score0.003

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.290
Teacher spread0.270 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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