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Record W7161950492 · doi:10.82308/18343

Multi-Walled Carbon Nanotube Filter for Detaining Immunosuppressive T-Cells and Inducing the Activation of Effector T-Cells

2025· dissertation· en· W7161950492 on OpenAlexaboutno aff
Gemma Di Placido

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon nanotubeEffectorCancer cellContact angleChemical vapor depositionFilter (signal processing)CoatingCancerFiltration (mathematics)

Abstract

fetched live from OpenAlex

Cancer is a major public health concern worldwide and the main cause of death in Canada. It remains challenging to effectively treat cancer given its ability to evade and suppress immune responses. Adoptive T-cell transfer (ACT) has recently gained popularity as a promising cancer immunotherapy. ACT works on the premise of enhancing the effectiveness of autologous white blood cells. T-cells are a type of white blood cell that play a critical role in killing cancer cells. However, regulatory T (Treg) cells are immunosuppressive and prevent the cancer-killing effector T (Teff) cells from eliminating cancer cells. A plasma functionalized MWCNT filter was developed with future intentions of detaining Treg cells and activating Teff cells using mechanical forces and non-biological agonists. Multiwalled carbon nanotubes (MWCNTs) are a network of cylindrically rolled carbon atoms used as the base of the filter material given its attractive material properties. The MWCNT coating was made functional to biological systems by modifying its surface using an ammonia plasma treatment, namely plasma-enhanced chemical vapor deposition. Amine (NH2) functional groups were grafted onto the surface of the MWCNTs which allow for future immobilization of target antibodies. The surfaces of the MWCNT and NH2-MWCNT filters were analyzed by scanning electron microscopy, X-ray photoelectron spectroscopy, water contact angle goniometry, and Raman spectroscopy. High purity superhydrophobic MWCNT filters were synthesized by chemical vapor deposition and contained a carbon content of 98.9 %. The surfaces of NH2-MWCNT filters became hydrophilic after ammonia functionalization. The D band and G band intensity ratios of the MWCNT and NH2-MWCNTfilters were 0.45 and 0.53, respectively, which confirmed the presence of NH2 functional groups on the surface of the MWCNTs. A splenocyte suspension was normally dispensed through the MWCNT and NH2-MWCNT filters. Spleen cell viability experiments were performed using fluorescence microscopy. Probability (p)-values of 0.44 and 0.16 were computed for the spleen cell viability experiments through the MWCNT and NH2-MWCNT filters, respectively. The high p-values suggested that the interaction of the splenocytes with the MWCNT and NH2-MWCNT filters were not statistically significant in influencing the viability of the cells. Mouse interferon (IFN)-γ ELISA assays were performed to measure the quantity of cytokines released in the filtered splenocyte suspension after applied normal stresses through the MWCNT and NH2-MWCNT filters. Low quantities of less than 3 pg/mL of IFN-γ were reported in the supernatant of the filtered suspensions. Mechanical forces alone did not induce the activation of T-cells while passing through the filters. The combination of mechanically dispensing T-cells through NH2-MWCNT filters coated with immobilized target antibodies may lead to the selective enhancement and proliferation of T-cells

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 score0.004

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)0.0010.000

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 head0.015
GPT teacher head0.266
Teacher spread0.252 · 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
Published2025
Admission routes1
Has abstractyes

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