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Record W2900063234 · doi:10.1186/s13223-018-0305-2

Unraveling the enigma: elucidating the relationship between the physicochemical properties of aluminium-based adjuvants and their immunological mechanisms of action

2018· review· en· W2900063234 on OpenAlexvenueno aff
Emma Shardlow, Matthew Mold, Christopher Exley

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsnot available
Fundersnot available
KeywordsAdjuvantAluminiumVaccine adjuvantCytotoxicityChemistryImmunologyBiologyBiochemistryIn vitroOrganic chemistry

Abstract

fetched live from OpenAlex

Aluminium salts are by far the most commonly used adjuvants in vaccines. There are only two aluminium salts which are used in clinically-approved vaccines, Alhydrogel® and AdjuPhos®, while the novel aluminium adjuvant used in Gardasil® is a sulphated version of the latter. We have investigated the physicochemical properties of these two aluminium adjuvants and specifically in milieus approximating to both vaccine vehicles and the composition of injection sites. Additionally we have used a monocytic cell line to establish the relationship between their physicochemical properties and their internalisation and cytotoxicity. We emphasise that aluminium adjuvants used in clinically approved vaccines are chemically and biologically dissimilar with concomitantly potentially distinct roles in vaccine-related adverse events.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.121
GPT teacher head0.344
Teacher spread0.223 · 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 designOther design
Domainnot available
GenreReview

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

Citations78
Published2018
Admission routes1
Has abstractyes

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