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Record W7010347905

Identification of hemin- and hemoglobin-binding proteins of Actinobacillus pleuropneumoniae serotype

2003· article· en· W7010347905 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsnot available
Fundersnot available
KeywordsActinobacillus pleuropneumoniaeSerotypeStrain (injury)Bacterial outer membraneActinobacillusPasteurellaceaeSignal peptide
DOInot available

Abstract

fetched live from OpenAlex

The reference strains representing serotypes 1 to 12 of Actinobacillus pleuropneumoniae biotype 1 were examined for their ability to utilize porcine hemoglobin (Hb) or porcine hemin (Hm) as iron sources for growth. In a growth promotion assay, all of the reference strains were able to use porcine Hb, and all strains except 2 were able to use porcine Hm. Using a preliminary characterization procedure with Hm- or Hb-agarose, Hm- and Hb-binding outer membrane proteins (OMPs) of approximately 75 kDa were isolated from A. pleuropneumoniae serotype 1 strain 4074 grown under iron-restricted conditions. Matrix-assisted laser desorption ionization/time-of-flight (MALDI-TOF) analysis revealed a number of common tryptic peptides between the Hb-agarose- and Hm-agarose-purified 75 kDa OMPs, strongly suggesting that these peptides originate from the same protein. A database search of these peptide sequences revealed identities with proteins from various Gram-negative bacteria, including iron-regulated OMPs, transporter proteins, as well as TonB-dependent receptors. Taken together, our data suggest that A. pleuropneumoniae synthesizes potential Hm- and Hb-binding proteins that could be implicated in the iron uptake from porcine Hb and Hm.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.256
Teacher spread0.242 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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Same venueNPARCSame topicMicrobial infections and disease researchFrench-language works237,207