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Record W2964546573 · doi:10.1128/aac.01186-19

Regulatory Mechanisms of the LuxS/AI-2 System and Bacterial Resistance

2019· review· en· W2964546573 on OpenAlexaff
Yang Wang, Baobao Liu, Daniel Grenier, Li Yi

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversité Laval
FundersNational Natural Science Foundation of China
KeywordsAntibiotic resistanceMicrobiologyResistance (ecology)BiologyComputational biologyAntibioticsEcology

Abstract

fetched live from OpenAlex

The quorum-sensing (QS) system is an intercellular cell-cell communication mechanism that controls the expression of genes involved in a variety of cellular processes and that plays critical roles in the adaption and survival of bacteria in their environment. The LuxS/AI-2 QS system, which uses AI-2 (autoinducer-2) as a signal molecule, has been identified in both Gram-negative and Gram-positive bacteria. As one of the important global regulatory networks in bacteria, it responds to fluctuations in the numbers of bacteria and regulates the expression of a number of genes, thus affecting cell behavior. We summarize here the known relationships between the LuxS/AI-2 system and drug resistance, discuss the inhibition of LuxS/AI-2 system as an approach to prevent bacterial resistance, and present new strategies for the treatment of drug-resistant pathogens.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.281
Teacher spread0.264 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations184
Published2019
Admission routes1
Has abstractyes

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