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Record W7000098024

The Effects of PMMA Surface Chemistry and Extracellular Traps on Macrophages, Lens Epithelial Cells and the Wound Healing Response

2018· dissertation· en· W7000098024 on OpenAlexafffund

Bibliographic record

VenueQSpace (Queen's University Library) · 2018
Typedissertation
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsQueen's University
FundersQueen's University
KeywordsImmune systemNeutrophil extracellular trapsWound healingExtracellularLens (geology)CellIn vivoViability assayMonocyteCell culture
DOInot available

Abstract

fetched live from OpenAlex

Posterior capsule opacification (PCO) is a condition that affects 20-40% of patients that undergo cataract lens replacement surgery. The design of the replacement intraocular lens (IOL) (for instance material, shape, and surface chemistry) is thought to be one of the main contributing factors to its development. Following the implantation of a biomaterial, there is a response by the immune system, activating cells and the release of various factors. The neutrophil is one of the first immune cells to respond and consequently has an effect on local cells and downstream immune cells. Also, neutrophils release a meshwork of DNA and proteins termed neutrophil extracellular traps (NETs). NETs are present during the inflammatory response and can affect downstream immune cells (i.e. macrophages) and the local cells. Therefore, it is hypothesized that the lens surface chemistry and the immune response of the neutrophils affect the behaviour of lens epithelial cells (LECs) and macrophages in the wound healing response. In this research, NETs were isolated from an HL60 cell line and used to investigate their effect on macrophages (activated THP1 cells) and LECs in vitro. Cell viability and behaviour of these cell types were assessed to determine the effects that NETs have on local and immune cells involved in PCO and the wound healing response. Poly(methyl methacrylate) (PMMA) disks were functionalized with amine or carboxyl surface groups to explore how the surface chemistry can affect LEC behaviour and viability in vitro. Lastly, in vivo analysis of functionalized PMMA beads investigated the healing response and neutrophil presence to different surface chemistries. When THP1 cells were incubated on tissue cultured polystyrene (TCPS) pre-treated with NETs, the NETs increased monocyte differentiation and TNF-α production when paired with iii activation with phorbol 13-myrstate 12-acetate (PMA) but there was no significant increase in THP1 cells differentiation when they were incubated on NETs only. It was also found that there were paracrine effects on the activated macrophages, leading to increased cell activation when THP1 cells were seeded onto TCPS at a higher cell density. When LEC were incubated on TCPS with pre-adsorbed NETs, the NETs decreased LEC viability but, interestingly, increased the production of alpha smooth muscle actin (α-SMA), a marker of epithelial to mesenchymal transition. When LEC were incubated on PMMA, the PMMA surface chemistry altered the viability of LECs and α-SMA production, with increased viability and α-SMA expression on aminated PMMA. When PMMA beads were injected subcutaneously into C57BL/6J mice, there was increased neutrophil presence and vessel formation 7 days after injection as well as differences in these two measures surrounding the aminated and carboxylated PMMA. Neutrophil presence was increased surrounding PMMA-COOH and vessel structure formation was increased surrounding PMMA-NH2 at 1 day and 7 days after injection.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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
Published2018
Admission routes2
Has abstractyes

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