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Record W7126286788

Development of near infrared semiconductor quantum dots for in vivo imaging

2021· other· en· W7126286788 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueOpenBU (Boston University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBioconjugationQuantum dotPreclinical imagingAbsorption (acoustics)Biological imagingSurface modificationMolecular imagingFolate receptor
DOInot available

Abstract

fetched live from OpenAlex

Quantum dots (QDs) are semiconductor nanoparticle fluorophores with size tunable emission wavelengths and large absorption cross sections, making QDs ideal optical imaging agents. Optical imaging has seen considerable academic and commercial interest, particularly for preclinical imaging. This interest stems from the capacity to multiplex, i.e., the detection of multiple independent imaging probes simultaneously, the accessibility of optical imaging equipment, and the absence of ionizing radiation. Since multiple in vivo targets can be imaged simultaneously, multiplexing is particularly appealing for targeted molecular imaging. In oncology, where a myriad of receptors can be used as targets for personalized medicine, multiplexed imaging would improve rapid receptor status profiling. Given their flexible design, QDs can be engineered for use as targeted contrast agents. To meet the needs of this application, the QDs must 1) emit in the near or short wavelength infrared (NIR/SWIR) wavelength regime to mitigate absorption of light by tissues, 2) be biocompatible, and 3) enable functionalization with targeting agents, such as antibodies or small molecules. In this thesis, the first requirement was addressed by synthesizing an inverted Type-I ZnSe/InP/ZnS system, which is the first InP based system with tunable emission past 750 nm. Biocompatibility of the InP system was confirmed with in vivo toxicity studies of the ZnSe/InP/ZnS QDs. The third requirement was addressed by the development of bioconjugation and functionalization schemes resulting in active QD targeting to the biologically interesting cellular targets human epidermal growth factor receptor 2 (HER2) and folic acid receptor alpha. In addition to developing the new contrast agent, the imaging approach was also refined to address concerns of non-specific labeling of the tumor. To discern between targeted and untargeted binding in vivo, a dual tracer approach using both an untargeted and targeted imaging probe, paired with a corresponding image processing algorithm, was implemented and validated. Identifying the limitations of this approach in NIR-I imaging, resulting from tissue auto fluorescence and light attenuation, laid the groundwork for future imaging work in the SWIR. In order to explore the utility of SWIR for dual tracer approaches, PbS/CdS QDs emitting throughout the SWIR wavelength regime were synthesized. The PbS/CdS QDs were used to generate pilot in vivo SWIR imaging data in collaboration with the National Research Council of Canada. The pilot data demonstrate that tissue attenuation and autofluorescence will not be an issue in the SWIR wavelength regime. By pairing SWIR emitting QDs with dual tracer imaging principles, future studies may be able to discern tumor biomarker status at tissue depth. Such an approach would allow researchers to determine how tumors respond to targeted therapies, furthering the development of personalized medicine.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.243
Teacher spread0.217 · 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

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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