MétaCan
Menu
← Back to cohort
Record W7061255135

Redirecting nucleic acid-based nanostructures for immunotherapy and imaging

2023· other· en· W7061255135 on OpenAlexaff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsiNano Medical (Canada)
Fundersnot available
KeywordsBiomarkerImmunotherapyNucleic acidPrecision medicineCancerCancer immunotherapyPersonalized medicine
DOInot available

Abstract

fetched live from OpenAlex

In the pursuit of addressing the complexity and heterogeneity of cancer, cancer therapy and diagnostics have experienced a transition in the fundamental concept of "one-size-fits-all" approach toward precision medicine in which each individual is treated according to the display of specific molecular or cellular biomarker features. By detecting, monitoring, and correlating biomarker expression with disease progression, the treatment can be tailored to target specific tumor associated antigens (TAA)s to maximize patient benefit, minimize adverse events, and deliver personalized cancer therapy on an ongoing basis. In the desire to improve the affinity and specificity for TAA targeting, the accumulative strength of multivalent and multispecific interactions has become recognized as a central principle of targeting. Several factors must be considered when designing efficient multivalent and multispecific systems, highlighting the complexity involved and the pivotal role played by the delivery platform. Nucleic acids serve as ideal platforms for multimerizing targeting ligands. This attribute stems from their modular, flexible, and programmable nature that enables the design of nanostructures in nearly any desired shape, with nanoscale precision and unmatched spatial control of ligand distribution and stoichiometry. The incorporation of dynamic mechanisms to undergo controlled reconfiguration of the nanostructures can drastically broaden their potential. In this dissertation, three projects are presented that all take advantage of the versatility and programmability of nucleic acids to construct tailored nanostructures for targeted therapy and diagnostics in precision medicine. The first project describes the establishment of a method for tightly controlling the circulatory half-life of imaging agents in vivo. For this purpose, we developed a DNA-based, PEGylated, near-infrared imaging agent that, through external actuated toehold-mediated strand displacement reactions, was cleared from circulation. In the second project, a biocompatible nucleic acid-based nanostructure, referred to as the Holliday Junction (HJ), was applied to create a multispecific T cell engager and modulator for T cell redirected cancer immunotherapy which led to efficient tumor cell killing. Finally, the third project applies the HJ to create a multivalent nuclear imaging agent that efficiently improved HER2-positive tumor cell targeting in vitro. Collectively, these projects demonstrate the utility of nucleic acids as building blocks for constructing modular and self-assembled nanostructures tailored to address the challenges of precision 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.

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.271
Teacher spread0.262 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicMagnetic confinement fusion research→French-language works237,207→