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Redefining the Role of <i>psr</i> in β-Lactam Resistance and Cell Autolysis of <i>Enterococcus hirae</i>

2003· article· en· W2148918797 on OpenAlexaff
Frédéric Sapunaric, Christine Franssen, Patrick Stefanic, Ana Amoroso, Olivier Dardenne, Jacques Coyette

Bibliographic record

VenueJournal of Bacteriology · 2003
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsShriners Hospitals for Children - Canada
FundersUniversidad de Buenos AiresFonds pour la Formation à la Recherche dans l’Industrie et dans l’AgricultureFonds De La Recherche Scientifique - FNRS
KeywordsEnterococcus hiraeBiologyAutolysis (biology)ComplementationGenePenicillin binding proteinsGeneticsMicrobiologyMutantMolecular biologyEnterococcusBiochemistryBacteriaEscherichia coliEnzyme

Abstract

fetched live from OpenAlex

The contribution of penicillin-binding protein 5 (PBP5) and the PBP5 synthesis repressor (Psr) to the beta-lactam resistance, growth, and cell autolysis of wild-type strain ATCC 9790 and resistant strain R40 of Enterococcus hirae was investigated by disruption or substitution of the corresponding pbp5 and psr genes by Campbell-type recombination. The resulting modifications were confirmed by hybridization and PCR. The low susceptibility of E. hirae to beta-lactams was confirmed to be largely dependent on the presence of PBP5. However, against all expectations, inactivation of psr in ATCC 9790 or complementation of R40 cells with psr did not modify the susceptibility to benzylpenicillin or the growth and cell autolysis rates. These results indicated that the psr gene does not seem to be involved in the regulation of PBP5 synthesis and consequently in beta-lactam resistance or in the regulation of cell autolysis in E. hirae.

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 score0.004

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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

Citations14
Published2003
Admission routes1
Has abstractyes

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