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Record W7028906713

High throughput Detection of Molecular Targets in Cancer Using Nanoparticles: Application in Diagnostics

2008· dissertation· en· W7028906713 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2008
Typedissertation
Languageen
FieldArts and Humanities
TopicTechnology, Environment, Urban Planning
Canadian institutionsnot available
Fundersnot available
KeywordsFluorescenceFörster resonance energy transferCancer biomarkersCancerFluorometerCancer cellEosinMicroscopyAdenocarcinoma
DOInot available

Abstract

fetched live from OpenAlex

In light of cancer as a multi-parameter disease, technological advancements are being developed to obtain automated and high throughput assessment of molecular targets in diagnostics, with the aim to reduce subjective analytical assessment of tumours and/or to integrate molecular data obtained from different tests on given tumour samples. Towards this goal, a multi-disciplinary approach is presented in this dissertation using nanotechnology. First, by combining quantum dot (QD) nanocrystals, tissue microarray, optical spectroscopy, and algorithm design, an automated and high throughput quantitative approach in the assessment of biomarker surrogates in neoplastic tissue is introduced. The validation study was performed using epidermal growth factor (EGFR) in 8 formalin-fixed paraffin-embedded (FFPE) xenografts of lung adenocarcinoma (r2=0.9) (chapter 2). Furthermore, in chapter 3 a novel design of QD-based fluorescent probes, nanobeads, was presented by encapsulation of QDs in polystyrene in an emulsion polymerization reaction. Nanobeads exhibited resistance to fluorescent quenchers such as solutions of extreme pH and colorimetric dyes of hematoxylin & eosin (H&E) and Giemsa, key standard dyes used in cancer diagnostic. Comparative studies with organic dye, phycoerythrin (PE), and QDs demonstrated significant (P<0.001) fluorescent quenching in H&E and Giemsa using Kruskal Wallis test. The design allowed a simultaneous consolidation of fluorescent immunoassaying, using nanobeads, and morphologic and parametric visualization of cellular features, using colorimetric stains, in a given biopsy. Sten-volmer analysis demonstrated a reduction of fluorescence resonance energy transfer among nanobead610nm and nanobead560nm. The application of the QD-based methods bears potential significance in cancer diagnosis and in tumor management, especially human core biopsies of limited quantity. In chapter 4, cellular endocytosis of gold particles was shown to be size dependence, with gold particles of 50 nm demonstrating the highest uptake. The cellular response subsequent to gold uptake was assessed using 10k cDNA microarrays. Significant analysis of microarray (SAM) showed the gene expression of treated and non-treated particles to be 99.65% similar. The remaining 35 genes however, demonstrated down regulation of apoptosis, cell proliferation and cell adhesion responses in treated cells. While promising, future research and development are required to adopt nanoparticles in diagnostics.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.472
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.161
Teacher spread0.155 · 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