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Record W2170530800 · doi:10.1890/07-0389.1

RESPONSES OF A BACTERIAL PATHOGEN TO PHOSPHORUS LIMITATION OF ITS AQUATIC INVERTEBRATE HOST

2008· article· en· W2170530800 on OpenAlexaff
Paul C. Frost, Dieter Ebert, Val H. Smith

Bibliographic record

VenueEcology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsTrent University
Fundersnot available
KeywordsDaphniaBiologyPathogenHost (biology)Daphnia magnaInvertebrateReproductionNutrientZoologyEcologyMicrobiologyToxicityCrustaceanChemistry

Abstract

fetched live from OpenAlex

Host nutrition is thought to affect the establishment, persistence, and severity of pathogenic infections. Nutrient-deficient foods possibly benefit pathogens by constraining host immune function or benefit hosts by limiting parasite growth and reproduction. However, the effects of poor elemental food quality on a host's susceptibility to infection and disease have received little study. Here we show that the bacterial microparasite Pasteuria ramosa is affected by the elemental nutrition of its aquatic invertebrate host, Daphnia magna. We found that high food carbon:phosphorus (C:P) ratios significantly reduced infection rates of Pasteuria in Daphnia and led to lower within-host pathogen multiplication. In addition, greater virulent effects of bacterial infection on host reproduction were found in Daphnia-consuming P-deficient food. Poor Daphnia elemental nutrition thus reduced the growth and reproduction of its bacterial parasite, Pasteuria. The effects of poor host nutrition on the pathogen were further evidenced by Pasteuria's greater inhibition of reproduction in P-limited Daphnia. Our results provide strong evidence that elemental food quality can significantly influence the incidence and intensity of infectious disease in invertebrate hosts.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.315

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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 teacher head, 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

Citations115
Published2008
Admission routes1
Has abstractyes

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