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Record W2899245999 · doi:10.1186/s12865-018-0270-z

Altered endotoxin responsiveness in healthy children with Down syndrome

2018· article· en· W2899245999 on OpenAlexaff
Dean Huggard, Fiona McGrane, Niamh Lagan, Edna Roche, Joanne Balfe, Timothy Ronan Leahy, Orla Franklin, Ana Carolina Ramos Moreno, Ashanty M. Melo, Derek G. Doherty, Eleanor J. Molloy

Bibliographic record

VenueBMC Immunology · 2018
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsTrinity College
FundersNational Children's Research Centre
KeywordsMedicineImmunologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Down syndrome (DS) is the most common syndromic immunodeficiency with an increased risk of infection, mortality from sepsis, and autoinflammation. Innate immune function is altered in DS and therefore we examined responses in CD11b and Toll like receptor 4 (TLR-4), which are important immune cell surface markers upregulated in response to Lipopolysaccharide (LPS) endotoxin, and the immunomodulator melatonin. Neutrophil and monocyte responses to LPS and melatonin in children with Down syndrome (DS) who were clinically stable were compared to age-matched controls. Whole blood was incubated with LPS and melatonin and the relative expression of CD11b and TLR-4 evaluated by flow cytometry. RESULTS: Children with DS had an increased response to LPS in neutrophils and intermediate monocytes, while also having elevated TLR-4 expression on non-classical monocytes compared to controls at baseline. Melatonin reduced CD11b expression on neutrophils, total monocytes, both classical and intermediate sub-types, in children with DS and controls. CONCLUSION: Melatonin could represent a useful clinical adjunct in the treatment of sepsis as an immunomodulator. Children with DS had increased LPS responses which may contribute to the more adverse outcomes seen in sepsis.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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)0.0020.000

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 head0.037
GPT teacher head0.328
Teacher spread0.291 · 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 designObservational
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

Citations33
Published2018
Admission routes1
Has abstractyes

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