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Record W7111777961

A study to investigate the mechanisms underlying circadian rhythm in asthma

2017· article· en· W7111777961 on OpenAlexaff

Bibliographic record

VenueResearch Explorer (The University of Manchester) · 2017
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsLMC Diabetes & Endocrinology (Canada)Institute of Infection and Immunity
Fundersnot available
KeywordsCircadian rhythmAsthmaSputumBiomarkerMorningPathogenesisAsthma exacerbations
DOInot available

Abstract

fetched live from OpenAlex

Background: Time of day is critical in the pathogenesis of asthma, and has been realised for centuries. Symptoms of asthma are worse around 4am, when airway restriction is at its highest. Many asthma treatments are taken in the morning or evening, however there is increasing data that steroids are more efficacious if taken mid-afternoon. Investigating the biological timing of asthma is crucial to better understand the pathogenesis of asthma, this may lead to the discovery of new drug targets, and the identification of dynamic biomarkers that change by time of day and would be useful in a future chronotherapeutics study. Aims: • Define new biochemical pathways involved in the circadian variation in asthma • Determine a circadian biomarker in asthma Method: We recruited 10 atopic, moderately severe asthmatics and 10 healthy volunteers to complete 4 study visits, including an overnight stay. Blood, induced sputum and breath were sampled at intervals throughout the day and night, and physiological measurements made. PBMCs were harvested from peripheral blood at 4am and 4pm and plated in 6 groups, control, + LPS/anti-CD3/anti CD28, +P38i, +LPS/anti-CD3/anti CD28+ P381, + Dexamethasone, +LPS/anti-CD3/anti CD28+ dexamethasone for 2 hours. Conditioned medium was collected and frozen at -80, cell lysates were prepared for RNA extraction, and protein purification. REC reference: 14/NW/1352. Results: There is a high amplitude circadian change in FEV1 in asthmatics compared to healthy controls. The nadir is at 4am (figure 1). There was also an increase in sputum and serum eosinophils (a key effector cell in asthma) at 4am compared to 4pm in asthmatics (Figure1). On-going workflow includes: • Transcript measurement from PBMCs using a combination of RNA-Sequencing and nanostring technology (for clock genes; inflammatory mediators; Signalling regulators; MAP kinase family members) • Bioplex screen for expression and activation of additional MAPkinase components, and IkBa, from protein extracts and conditioned media • Lipidomic analyses of serial, matched serum samples will allow analysis of the ceramide/sphingolipid pathway • Breathomics analysis for volatile organic compounds in serial, matched breath samples. Discussion: We have demonstrated a significant diurnal effect on asthma lung physiology and eosinophil profiles. Further downstream analysis of serum, breath and sputum is underway.

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)0.002
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.242
GPT teacher head0.355
Teacher spread0.113 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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