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Record W2745136157 · doi:10.1371/journal.ppat.1006422

Infection-adapted emergency hematopoiesis promotes visceral leishmaniasis

2017· article· en· W2745136157 on OpenAlexafffund
Belma Melda Abidin, Akil Hammami, Simona Stäger, Krista M. Heinonen

Bibliographic record

VenuePLoS Pathogens · 2017
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsLeishmania donovaniHaematopoiesisImmunologyBone marrowVisceral leishmaniasisImmune systemBiologyProgenitor cellLeishmaniaLeishmaniasisMyeloidStem cellCell biologyParasite hosting

Abstract

fetched live from OpenAlex

Cells of the immune system are derived from hematopoietic stem cells (HSCs) residing in the bone marrow. HSCs become activated in response to stress, such as acute infections, which adapt the bone marrow output to the needs of the immune response. However, the impact of infection-adapted HSC activation and differentiation on the persistence of chronic infections is poorly understood. We have examined here the bone marrow outcome of chronic visceral leishmaniasis and show that the parasite Leishmania donovani induces HSC expansion and skews their differentiation towards non-classical myeloid progenitors with a regulatory phenotype. Our results further suggest that emergency hematopoiesis contributes to the pathogenesis of visceral leishmaniasis, as decreased HSC expansion results in a lower parasite burden. Conversely, monocytes derived in the presence of soluble factors from the infected bone marrow environment are more permissive to infection by Leishmania. Our results demonstrate that L. donovani is able to subvert host bone marrow emergency responses to facilitate parasite persistence, and put forward hematopoiesis as a novel therapeutic target in chronic infections.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.062
GPT teacher head0.330
Teacher spread0.268 · 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

Citations70
Published2017
Admission routes2
Has abstractyes

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