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Record W2475817933 · doi:10.1111/cmi.12646

GLUT1-mediated glucose uptake plays a crucial role during <i>Plasmodium</i> hepatic infection

2016· article· en· W2475817933 on OpenAlexfundno aff
Patrícia Meireles, Joana Sales-Dias, Carolina M. Andrade, João Mello-Vieira, Liliana Mâncio-Silva, J. Pedro Simas, Henry M. Staines, Miguel Prudêncio

Bibliographic record

VenueCellular Microbiology · 2016
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersInstitute of Genetics
KeywordsGLUT1BiologyGlucose transporterPlasmodium bergheiIn vivoGlucose uptakeIn vitroIntracellularTransporterCell biologyPlasmodium (life cycle)CellParasite hostingIntracellular parasiteBiochemistryMalariaImmunologyGeneEndocrinologyInsulinGenetics

Abstract

fetched live from OpenAlex

Intracellular pathogens have evolved mechanisms to ensure their survival and development inside their host cells. Here, we show that glucose is a pivotal modulator of hepatic infection by the rodent malaria parasite Plasmodium berghei and that glucose uptake via the GLUT1 transporter is specifically enhanced in P. berghei-infected cells. We further show that ATP levels of cells containing developing parasites are decreased, which is known to enhance membrane GLUT1 activity. In addition, GLUT1 molecules are translocated to the membrane of the hepatic cell, increasing glucose uptake at later stages of infection. Chemical inhibition of GLUT1 activity leads to a decrease in glucose uptake and the consequent impairment of hepatic infection, both in vitro and in vivo. Our results reveal that changes in GLUT1 conformation and cellular localization seem to be part of an adaptive host response to maintain adequate cellular nutrition and energy levels, ensuring host cell survival and supporting P. berghei hepatic development.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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

Citations71
Published2016
Admission routes1
Has abstractyes

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