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Record W3166129227 · doi:10.1126/sciadv.abf0797

Spatiotemporally confined red light-controlled gene delivery at single-cell resolution using adeno-associated viral vectors

2021· article· en· W3166129227 on OpenAlexfundno aff
Maximilian Hörner, Carolina Jerez‐Longres, Anna Hudek, Sebastian Hook, O. Sascha Yousefi, Wolfgang W. Schamel, Cindy Hörner, Matías D. Zurbriggen, Haifeng Ye, Hanna J. Wagner, Wilfried Weber

Bibliographic record

VenueScience Advances · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
FundersAlbert-Ludwigs-Universität FreiburgCanada's Michael Smith Genome Sciences CentreMedizinischen Hochschule HannoverDeutsche ForschungsgemeinschaftRice University
KeywordsGene deliveryResolution (logic)Adeno-associated virusGeneVirologyCellComputational biologyVector (molecular biology)BiologyGenetic enhancementGeneticsComputer scienceRecombinant DNAArtificial intelligence

Abstract

fetched live from OpenAlex

Methodologies for the controlled delivery of genetic information into target cells are of utmost importance for genetic engineering in both fundamental and applied research. However, available methods for efficient gene transfer into user-selected or even single cells suffer from low throughput, the need for complicated equipment, high invasiveness, or side effects by off-target viral uptake. Here, we engineer an adeno-associated viral (AAV) vector system that transfers genetic information into native target cells upon illumination with cell-compatible red light. This OptoAAV system allows adjustable and spatially resolved gene transfer down to single-cell resolution and is compatible with different cell lines and primary cells. Moreover, the sequential application of multiple OptoAAVs enables spatially resolved transduction with different transgenes. The approach presented is likely extendable to other classes of viral vectors and is expected to foster advances in basic and applied genetic research.

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 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)0.001
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 score0.005
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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 teacher head, 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

Citations27
Published2021
Admission routes1
Has abstractyes

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