MétaCan
Menu
Back to cohort
Record W3110487414 · doi:10.1080/10428194.2020.1850718

Investigating the gut microbial community and genes in children with differing levels of change in serum asparaginase activity during pegaspargase treatment for acute lymphoblastic leukemia

2020· article· en· W3110487414 on OpenAlexafffund
Katherine A. Dunn, Jessica Connors, Joseph P. Bielawski, Jacob T. Nearing, Morgan G. I. Langille, Johan Van Limbergen, Conrad V. Fernandez, Tamara MacDonald, Ketan Kulkarni

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
FundersIWK Health CentreNova Scotia Health Research FoundationCrohn's and Colitis Foundation
KeywordsAsparaginaseLymphoblastic LeukemiaMedicineMicrobiomeMetagenomicsGeneEscherichia coliBacteroidesMicrobial population biologyMicrobiologyImmunologyBiologyLeukemiaBacteriaBioinformaticsBiochemistryGenetics

Abstract

fetched live from OpenAlex

Asparaginase (ASNase) is an effective treatment of pediatric acute lymphoblastic leukemia (ALL). Changes in ASNase activity may lead to suboptimal treatment and poorer outcomes. The gut microbiome produces metabolites that could impact ASNase therapy, however, remains uninvestigated. We examined gut-microbial community and microbial-ASNase and asparagine synthetase (ASNS) genes using 16SrRNA and metagenomic sequence data from stool samples of pediatric ALL patients. Comparing ASNase activity between consecutive ASNase-doses, we found microbial communities differed between decreased- and increased-activity samples. Escherichia predominated in the decreased-activity community while Bacteroides and Streptococcus predominated in the increased-activity community. In addition microbial ASNS was significantly (p=.004) negatively correlated with change in serum ASNase activity. These preliminary findings suggest microbial communities prior to treatment could affect serum ASNase levels, although the mechanism is unknown. Replication in an independent cohort is needed, and future research on manipulation of these communities and genes could prove useful in optimizing ASNase therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.044
GPT teacher head0.287
Teacher spread0.243 · 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 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

Citations11
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueLeukemia & lymphoma/Leukemia and lymphomaSame topicAcute Lymphoblastic Leukemia researchFrench-language works237,207