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Record W2528725597 · doi:10.1038/srep34479

Hierarchical phosphorylation of apical membrane antigen 1 is required for efficient red blood cell invasion by malaria parasites

2016· article· en· W2528725597 on OpenAlexaff
Boris Prinz, Katherine Harvey, Louisa Wilcke, Ulrike Ruch, Klemens Engelberg, Laura Biller, Isabelle S. Lucet, Steffen Erkelenz, Dorothee Heincke, Tobias Spielmann, Christian Doerig, Conrad Kunick, Brendan S. Crabb, Paul R. Gilson, Tim‐Wolf Gilberger

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsMcMaster University
FundersUniversität HamburgUniversity of MelbourneDeutsche ForschungsgemeinschaftBurnet Institute
KeywordsPlasmodium falciparumPhosphorylationBiologyCell biologySerineThreonineKinaseAntigenPhosphorylation cascadeApical membraneProtein kinase AParasite hostingProtein phosphorylationBiochemistryMalariaImmunologyMembrane

Abstract

fetched live from OpenAlex

Abstract Central to the pathogenesis of malaria is the proliferation of Plasmodium falciparum parasites within human erythrocytes. Parasites invade erythrocytes via a coordinated sequence of receptor-ligand interactions between the parasite and host cell. One key ligand, Apical Membrane Antigen 1 (AMA1), is a leading blood-stage vaccine and previous work indicates that phosphorylation of its cytoplasmic domain (CPD) is important to its function during invasion. Here we investigate the significance of each of the six available phospho-sites in the CPD. We confirm that the cyclic AMP/protein kinase A (PKA) signalling pathway elicits a phospho-priming step upon serine 610 (S 610 ), which enables subsequent phosphorylation in vitro of a conserved, downstream threonine residue (T 613 ) by glycogen synthase kinase 3 (GSK3). Both phosphorylation steps are required for AMA1 to function efficiently during invasion. This provides the first evidence that the functions of key invasion ligands of the malaria parasite are regulated by sequential phosphorylation steps.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.016
GPT teacher head0.266
Teacher spread0.251 · 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 designBench or experimental
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

Citations33
Published2016
Admission routes1
Has abstractyes

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