MétaCan
Menu
Back to cohort
Record W3013534036 · doi:10.1016/j.celrep.2020.02.098

The Absence of HIF-1α Increases Susceptibility to Leishmania donovani Infection via Activation of BNIP3/mTOR/SREBP-1c Axis

2020· article· en· W3013534036 on OpenAlexafffund
Inês Mesquita, Carolina Ferreira, Diana Moreira, George Eduardo Gabriel Kluck, Ana Margarida Barbosa, Egídio Torrado, Ricardo Jorge Dinis‐Oliveira, Luís G. Gonçalves, Charles-Joly Beauparlant, Arnaud Droit, Luciana Berod, Tim Sparwasser, Neelam Bodhale, Bhaskar Saha, Fernando Rodrigues, Cristina Cunha, Agostinho Carvalho, António G. Castro, Jérôme Estaquier, Ricardo Silvestre

Bibliographic record

VenueCell Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsUniversité Laval
FundersNational Institute of Allergy and Infectious DiseasesEuropean Regional Development FundCanada Research ChairsAgence Nationale de la RechercheFundação para a Ciência e a TecnologiaSeventh Framework ProgrammeDepartment of Biotechnology, Ministry of Science and Technology, IndiaNational Institutes of HealthCase Western Reserve UniversityInstituto de Tecnologia Química e Biológica, Universidade Nova de LisboaFoundation for the National Institutes of Health
KeywordsLeishmania donovaniBiologyLipogenesisLipid metabolismCell biologyInnate immune systemMyeloidSterol regulatory element-binding proteinPI3K/AKT/mTOR pathwaymTORC2Immune systemCancer researchImmunologyTranscription factormTORC1Signal transductionBiochemistryGeneLeishmaniasisVisceral leishmaniasis

Abstract

fetched live from OpenAlex

macrophages. L. donovani-infected HIF-1α-deficient mice develop hypertriglyceridemia and lipid accumulation in splenic and hepatic myeloid cells. Most importantly, our data demonstrate that manipulating FASN or SREBP-1c using pharmacological inhibitors significantly reduced parasite burden. As such, genetic deficiency of HIF-1α is associated with increased lipid accumulation, which results in impaired host-protective anti-leishmanial functions of myeloid cells.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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.

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

Citations48
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCell ReportsSame topicResearch on Leishmaniasis StudiesFrench-language works237,207