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Record W1992533162 · doi:10.1128/jb.00528-09

In Situ Characterization of Differences in the Viscoelastic Response of Individual Gram-Negative and Gram-Positive Bacterial Cells

2009· article· en· W1992533162 on OpenAlexafffund
Virginia Vadillo‐Rodríguez, Sarah R. Schooling, John Dutcher

Bibliographic record

VenueJournal of Bacteriology · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsViscoelasticityCell envelopePeptidoglycanBiologyBacillus subtilisGramEscherichia coliGram-negative bacteriaBacterial cell structureBiophysicsBacterial outer membraneGram-positive bacteriaMembraneEnvelope (radar)Cell wallAtomic force microscopyBacteriaBiochemistryMaterials scienceGeneticsNanotechnologyComposite material

Abstract

fetched live from OpenAlex

We used a novel atomic force microscopy (AFM)-based technique to compare the local viscoelastic properties of individual gram-negative (Escherichia coli) and gram-positive (Bacillus subtilis) bacterial cells. We found that the viscoelastic properties of the bacterial cells are well described by a three-component mechanical model that combines an instantaneous elastic response and a delayed elastic response. These experiments have allowed us to investigate the relationship between the viscoelastic properties and the structure and composition of the cell envelope. In addition, this is the first report in which the mechanical role of Lpp, the major peptidoglycan-associated lipoprotein and one of the most abundant outer membrane proteins in E. coli cells, has been quantified. We expect that our findings will be helpful in increasing the understanding of the structure-property relationships of bacterial cell envelopes.

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 score0.002

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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

Citations79
Published2009
Admission routes2
Has abstractyes

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