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Record W4221089794 · doi:10.1016/j.xpro.2022.101233

PDMS hydrogel-coated tissue culture plates for studying the impact of substrate stiffness on dendritic cell function

2022· article· en· W4221089794 on OpenAlexaff
Megan Lee, Kevin Y. Chu, Mainak Chakraborty, Nicholas Konstantine Kotoulas, Masoud Akbari, Cynthia Goh, Xavier Clemente‐Casares, Daniel A. Winer, Annie Shrestha, Sue Tsai

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of TorontoUniversity Health NetworkToronto General HospitalUniversity of Alberta
FundersNational Institute on Aging
KeywordsSelf-healing hydrogelsMechanosensitive channelsPolydimethylsiloxaneSubstrate (aquarium)StiffnessCD11cMaterials scienceFunction (biology)Cell functionNanotechnologyCellCell biologyChemistryComposite materialBiologyPolymer chemistry

Abstract

fetched live from OpenAlex

The mechanical properties of polydimethylsiloxane hydrogels can be tuned to mimic physiological tensions, an underappreciated environmental parameter in immunology studies. We describe a workflow to prepare PDMS-coated tissue culture plates with biologically relevant substrate stiffness, and the use of these hydrogel plates to condition isolated primary splenic CD11c+ dendritic cells (DC). Finally, we suggest downstream applications to study the impact of substrate stiffness on DC function and metabolism. The protocol could be adapted to study other mechanosensitive immune cell subsets. For complete details on the use and execution of this protocol, please refer to Chakraborty et al. (2021).

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.025
GPT teacher head0.319
Teacher spread0.294 · 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
GenreMethods

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

Citations12
Published2022
Admission routes1
Has abstractyes

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