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Record W1966928558 · doi:10.1117/12.829981

Cryoprotection from bacterial teichoic acid

2009· article· en· W1966928558 on OpenAlexaff
Charles V. Rice, William T. A. Harrison, Karl Kirkpatrick, Eric D. Brown

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTeichoic acidComputer scienceChemistryBiochemistryCell wall

Abstract

fetched live from OpenAlex

Recent studies from our lab demonstrated that teichoic acid is surrounded by liquid water at -40 °C. The size and shape of the liquid water pockets has been visualized with fluorescence microscopy images of aqueous Rhodamine- B solutions. The long, thin channels surround ice crystals with a size of 5-20 microns. Subsequent studies show that B. subtilis Gram-positive bacteria are sequestered into large pockets without added teichoic acid. Here, the ice crystals are orders of manitude larger. When bacteria are mixed with teichoic acid solutions, the distribution of bacteria changes dramatically. The smaller ice crystals allow the bacteria to align in the thin channels of liquid water seen with teichoic acid only. The role of teichoic acid in the freeze tolerance was examined with live/dead fluorescence assays of bacteria mixed with teichoic acid. These quantitative assays were used to determine if teichoic acid acts in a synergetic fashion to enhance the survivability of E. coli, a gram-negative species which lacks teichoic acid. Additionally, we have obtained B. subtilis mutants lacking wall-associated teichoic acids to evaluate cryoprotection compared to the wild-type strain.

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 head0.008
GPT teacher head0.212
Teacher spread0.203 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE→Same topicMicrobial Community Ecology and Physiology→French-language works237,207→