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Record W2734515876 · doi:10.1038/s41598-017-05609-1

Protein Tyrosine Phosphatase Inhibition Prevents Experimental Cerebral Malaria by Precluding CXCR3 Expression on T Cells

2017· article· en· W2734515876 on OpenAlexafffund
Kristin M. Van Den Ham, Logan K. Smith, Martin J. Richer, Martin Olivier

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsOccupational Cancer Research CentreMcGill UniversityMcGill University Health Centre
FundersMcGill University Health CentreMcGill University
KeywordsPlasmodium bergheiCerebral MalariaProtein tyrosine phosphataseCXCR3Cytotoxic T cellDownregulation and upregulationT cellBiologyCell biologyChemistryImmunologyImmune systemMalariaPhosphorylationBiochemistryChemokine receptorPlasmodium falciparumChemokine

Abstract

fetched live from OpenAlex

Abstract Cerebral malaria induced by Plasmodium berghei ANKA infection is dependent on the sequestration of cytotoxic T cells within the brain and augmentation of the inflammatory response. Herein, we demonstrate that inhibition of protein tyrosine phosphatase (PTP) activity significantly attenuates T cell sequestration within the brain and prevents the development of neuropathology. Mechanistically, the initial upregulation of CXCR3 on splenic T cells upon T cell receptor stimulation was critically decreased through the reduction of T cell-intrinsic PTP activity. Furthermore, PTP inhibition markedly increased IL-10 production by splenic CD4+ T cells by enhancing the frequency of LAG3+CD49b+ type 1 regulatory cells. Overall, these findings demonstrate that modulation of PTP activity could possibly be utilized in the treatment of cerebral malaria and other CXCR3-mediated diseases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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 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

Citations5
Published2017
Admission routes2
Has abstractyes

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