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Record W2170331518 · doi:10.1002/jemt.20247

Two‐photon fluorescent microlithography for live‐cell imaging

2005· article· en· W2170331518 on OpenAlex
Santiago Costantino, Katrin G. Heinze, Oscar E. Martínez, Paul De Koninck, Paul W. Wiseman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicroscopy Research and Technique · 2005
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsUniversité LavalMcGill University
Fundersnot available
KeywordsMicrocontact printingFluorescenceLithographyMaterials scienceFluorescence microscopeMicroscopySoft lithographyNanotechnologyLive cell imagingEtching (microfabrication)OpticsFabricationOptoelectronicsChemistryCell

Abstract

fetched live from OpenAlex

Fluorescent dyes added to UV-cure resins allow the rapid fabrication of fluorescent micropatterns on standard glass coverslips by two-photon optical lithography. We use this lithographic method to tailor fiduciary markers, focal references, and calibration tools, for fluorescence and laser scanning microscopy. Fluorescent microlithography provides spatial landmarks to quantify molecular transport, cell growth and migration, and to compensate for focal drift during time-lapse imaging. We show that the fluorescent patterned microstructures are biocompatible with cultures of mammalian cell lines and hippocampal neurons. Furthermore, the high-relief topology of the lithographed substrates is utilized as a mold for poly(dimethylsiloxane) stamps to create protein patterns by microcontact printing, representing an alternative to the current etching techniques. We present two different applications of such protein patterns for localizing cell adhesion and guidance of neurite outgrowth.

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.

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: none
Teacher disagreement score0.420
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.327
Teacher spread0.312 · 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