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Record W7133061292

Discovery and Characterization of Small-molecule CRISPR/Cas13 Inhibitors Using a High Throughput Platform

2023· dissertation· W7133061292 on OpenAlexaff
Ashim Alexander Bhattacharya

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCRISPRPalindromeDNAGeneGenome editingRNAIn vitroCellFluorescence
DOInot available

Abstract

fetched live from OpenAlex

Since being re-purposed for gene editing in mammalian cells, the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas (CRISPR Associated Protein) system has become an indispensable resource in the molecular biologist’s toolbox. This family of RNAguided endonucleases cleaves RNA or DNA sequences in a sequence-specific manner. CRISPR/Cas13 has received attention due to its ability to specifically target ssRNA sequences. The goal of this thesis was to expand the capabilities of this system by enabling small-molecule control of its activity. To do this, we screened a library of 13,120 compounds for the ability to inhibit CRISPR/LwCas13a activity in vitro using a fluorescent assay. Next, we validated the top 20 hits using both fluorescent and native substrate assays. We characterized verified compounds and evaluated their activity in cells. These results identify new cell permeable Cas13 inhibitors that enable its activity to be regulated in cells with unprecedented ease.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.327
Teacher spread0.311 · 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

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