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The rate of environmental change drives adaptation to an antibiotic sink

2008· article· en· W1995677704 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Evolutionary Biology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsMcGill University
FundersClarendon FundNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsRoyal SocietyLeverhulme Trust
KeywordsBiologyAdaptation (eye)Experimental evolutionImmigrationPopulationAntibioticsEnvironmental changePseudomonas aeruginosaResistance (ecology)BacteriaMicrobiologyEcologyClimate changeGeneticsDemographyGene

Abstract

fetched live from OpenAlex

Recent accelerated trends of human-induced global changes are providing many examples of adaptation to novel environments. Although the rate of environmental change can vary dramatically, its effect on evolving populations is unknown. A crucial feature explaining the adaptation to harsh environments is the supply of beneficial mutations via immigration from a 'source' population. In this study, we tested the effect of immigration on adaptation to increasing concentrations of antibiotics. Using experimental population of Pseudomonas aeruginosa, a pathogenic bacterium, we show that higher immigration rates and a slow increase in antibiotic concentration result in a more rapid evolution of resistance; however, a high immigration rate combined with rapid increases in concentration resulted in higher maximal levels of resistance. These findings, which support recent theoretical work, have important implications for the control of antibiotic resistance because they show that rapid rates of change can produce variants with the ability to resist future treatments.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.018
GPT teacher head0.251
Teacher spread0.233 · 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