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Polysaccharide Vaccines: A Perspective on Non-Typhoidal Salmonella

2021· article· en· W3199391642 on OpenAlexafffund
Sumudu R Perera, Akosiererem S. Sokaribo, Aaron P. White

Bibliographic record

VenuePolysaccharides · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsMcMaster UniversityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaSaskatchewan Health Research Foundation
KeywordsSalmonellaImmunogenicitySerotypeAntigenMicrobiologyImmune systemBiologyBacteriaImmunologyGenetics

Abstract

fetched live from OpenAlex

Polysaccharides are often the most abundant antigens found on the extracellular surfaces of bacterial cells. These polysaccharides play key roles in interactions with the outside world, and for many bacterial pathogens, they represent what is presented to the human immune system. As a result, many vaccines have been or currently are being developed against carbohydrate antigens. In this review, we explore the diversity of capsular polysaccharides (CPS) in Salmonella and other selected bacterial species and explain the classification and function of CPS as vaccine antigens. Despite many vaccines being developed using carbohydrate antigens, the low immunogenicity and the diversity of infecting strains and serovars present an antigen formulation challenge to manufacturers. Vaccines tend to focus on common serovars or have changing formulations over time, reflecting the trends in human infection, which can be costly and time-consuming. We summarize the approaches to generate carbohydrate-based vaccines for Salmonella, describe vaccines that are in development and emphasize the need for an effective vaccine against non-typhoidal Salmonella strains.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.256
Teacher spread0.238 · 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.

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

Citations28
Published2021
Admission routes2
Has abstractyes

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