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Record W2771852644 · doi:10.1073/pnas.1720676115

Biofilm Lithography enables high-resolution cell patterning via optogenetic adhesin expression

2018· article· en· W2771852644 on OpenAlexfundno aff
Xiaofan Jin, Ingmar H. Riedel‐Kruse

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesStanford Bio-XNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaAmerican Cancer Society
KeywordsBiofilmBacterial adhesinSynthetic biologyCell biologyNanotechnologyEscherichia coliMicrobiologyBiologyBiophysicsChemistryGeneBacteriaMaterials scienceComputational biologyGenetics

Abstract

fetched live from OpenAlex

with a light-activated transcriptional promoter (pDawn) to optically regulate expression of an adhesin gene (Ag43). When illuminated with patterned blue light, long-term viable biofilms with spatial resolution down to 25 μm can be formed on a variety of substrates and inside enclosed culture chambers without the need for surface pretreatment. A biophysical model suggests that the patterning mechanism involves stimulation of transiently surface-adsorbed cells, lending evidence to a previously proposed role of adhesin expression during natural biofilm maturation. Overall, this tool-termed "Biofilm Lithography"-has distinct advantages over existing cell-depositing/patterning methods and provides the ability to grow structured biofilms, with applications toward an improved understanding of natural biofilm communities, as well as the engineering of living biomaterials and bottom-up approaches to microbial consortia design.

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)0.000
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 score0.025
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.258
Teacher spread0.239 · 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

Citations126
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicBacterial biofilms and quorum sensingFrench-language works237,207