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Record W4402969161 · doi:10.1016/j.omtn.2024.102349

Direct delivery of Cas9 or base editor protein and guide RNA complex enables genome editing in the retina

2024· article· en· W4402969161 on OpenAlexfundno aff
Juliette Pulman, Catherine Botto, Hugo Malki, Duohao Ren, Paul Oudin, Anne De Cian, Marie As, Charlotte Izabelle, Bruno Saubaméa, Valérie Forster, Stéphane Fouquet, Camille Robert, Céline Portal, A. Amraoui, Sylvain Fisson, Jean‐Paul Concordet, Deniz Dalkara

Bibliographic record

VenueMolecular Therapy — Nucleic Acids · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersDomaine d’Intérêt Majeur Logiciels et Systèmes ComplexesSorbonne UniversitéFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleAFM-TéléthonAssociation Française contre les MyopathiesAgence Nationale de la RechercheFondation Voir et EntendreFoundation Fighting Blindness
KeywordsCas9CRISPRGenome editingComputational biologyGuide RNAComputer scienceRNABase (topology)RetinaGenomeBiologyGeneticsGeneNeuroscience

Abstract

fetched live from OpenAlex

. However, the delivery into photoreceptors, the primary focus in retinal dystrophies, has not been achieved. Here, we investigate the feasibility of direct RNP delivery into photoreceptors and retinal pigment epithelium cells. We demonstrate that Cas9 or adenine-base editors complexed with guide RNA, can enter retinal cells without the addition of any carrier compounds. Once in the retinal cells, editing rates vary based on the efficacy of the guide RNA and the specific location edited within the genes. Cas9 RNP delivery at high concentrations, however, leads to outer retinal toxicity. This underscores the importance of improving delivery efficiency for potential therapeutic applications in the future.

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.271
Teacher spread0.261 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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