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Antibiotic production in relation to bacterial growth and nematode development in<i>PhotorhabdusâHeterorhabditis</i>infected<i>Galleria mellonella</i>larvae

2000· article· en· W2047462163 on OpenAlexafffund
Kaiji Hu, John Webster

Bibliographic record

VenueFEMS Microbiology Letters · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaDirectorate for Biological Sciences
KeywordsGalleria mellonellaPhotorhabdus luminescensBiologyPhotorhabdusHeterorhabditisMicrobiologyHeterorhabditis bacteriophoraNematodeEntomopathogenic nematodeXenorhabdusLarvaPopulationAntibioticsBiological pest controlEcologyVirulence

Abstract

fetched live from OpenAlex

The population of Photorhabdus luminescens C9, bacterial symbiont of the entomopathogenic nematode, Heterorhabditis megidis 90, increased rapidly to 1.2-2.6x10(9) cells g(-1) wet Galleria mellonella larvae within 24 h of nematode infection of the larvae, and maintained a relatively constant level (1.2-2.0x10(10) cells g(-1)) through the entire 14-day period of nematode development. The antibiotic, 3, 5-dihydroxy-4-isopropylstilbene, was produced by P. luminescens C9 after 24 h of nematode infection, increased rapidly at 2-5 days postinfection and remained at a level of 3000-3600 microg g(-1) wet larvae until about 21 days, decreasing gradually thereafter. The early production and continued presence of a relatively large amount of 3,5-dihydroxy-4-isopropylstilbene in the infected insect supports the hypothesis that the antibiotics produced by the bacterial symbiont help minimize competition from other microorganisms and prevents the putrefaction of the nematode-infected insect cadaver.

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 integrity0.0000.000
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 head0.006
GPT teacher head0.177
Teacher spread0.171 · 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

Citations89
Published2000
Admission routes2
Has abstractyes

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Same venueFEMS Microbiology LettersSame topicEntomopathogenic Microorganisms in Pest ControlFrench-language works237,207