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Record W4410981393 · doi:10.1139/gen-2024-0177

Diversity and T-cell antigenic potentials of <i>Mycoplasma mycoides</i> subsp. <i>mycoides</i> vaccine candidates

2025· article· en· W4410981393 on OpenAlexvenueno aff
Emily L. Wynn, Rohana P. Dassanayake, Daniel W. Nielsen, Eduardo Casas, Michael L. Clawson

Bibliographic record

VenueGenome · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsnot available
FundersOak Ridge Institute for Science and Education
KeywordsMycoplasma mycoidesBiologyVirologyAntigenMicrobiologyMycoplasmaGenetics

Abstract

fetched live from OpenAlex

Mycoplasma mycoides subsp. mycoides ( Mmm) is the causative agent of contagious bovine pleuropneumonia (CBPP), a severe respiratory disease affecting cattle mostly in sub-Saharan African countries. CBPP can cause significant economic losses, and there is a need for efficacious vaccines to help bring the disease under control. To that end, all publicly available non-redundant whole genome sequences of Mmm strains isolated from cattle ( n = 15) were used to identify a 93% core genome of 806 genes, which included 86 of 208 genes encoding outer membrane and extracellular proteins identified from the literature. Many of them and their encoded protein products were found to be highly conserved at the sequence level, including at the sites of predicted epitope binding with bovine major histocompatibility complex (MHC) Class I and II molecules. Despite the high sequence conservation, multiple proteins had large differences in the numbers of MHC Class I and II epitopes and their predicted binding strengths. These results highlight several promising targets supporting the development of new recombinant protein vaccines for CBPP.

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 score0.003

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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
Published2025
Admission routes1
Has abstractyes

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