Evidence map›Paper›PMID 27249674›Full record

ReviewThe Journal of clinical investigation2016

Current therapies and future possibilities for drug development against liver-stage malaria.

Rene Raphemot, Dora Posfai, Emily R Derbyshire

Open access · bronzeAbstract readReview
In one paragraph

Review in The Journal of clinical investigation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.1field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. RTS,S: the first malaria vaccine.The Journal of clinical investigation · 2022
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Repurposing Drugs to Fight Hepatic Malaria Parasites.Molecules (Basel, Switzerland) · 2020
    Review
  13. Article
  14. Article
  15. Article
  16. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Rene Raphemot
Dora Posfai
Emily R Derbyshire
Duke University · US

Funding

Discovering new compounds to treat global infectious diseaseR00GM099796 · NIGMS · DUKE UNIVERSITY · PI DERBYSHIRE, EMILY R · 2014 to 2016
$747k
Discovering new compounds to treat global infectious diseaseK99GM099796 · NIGMS · HARVARD MEDICAL SCHOOL · PI DERBYSHIRE, EMILY R · 2013 to 2014
$120k
Discovery of novel liver host targets for malaria treatmentF32AI118294 · NIAID · DUKE UNIVERSITY · PI RAPHEMOT, RENE · 2016 to 2017
$75k
NIAID NIH HHS F32 AI118294NIGMS NIH HHS K99 GM099796NIGMS NIH HHS R00 GM099796
6 · The paper itself

Abstract

Malaria remains a global public health threat, with half of the world's population at risk. Despite numerous efforts in the past decade to develop new antimalarial drugs to surmount increasing resistance to common therapies, challenges remain in the expansion of the current antimalarial arsenal for the elimination of this disease. The requirement of prophylactic and radical cure activities for the next generation of antimalarial drugs demands that new research models be developed to support the investigation of the elusive liver stage of the malaria parasite. In this Review, we revisit current antimalarial therapies and discuss recent advances for in vitro and in vivo malaria research models of the liver stage and their importance in probing parasite biology and the discovery of novel drug candidates.

Indexed as

AnimalsAntimalarialsDrug DesignDrug DiscoveryDrug ResistanceHumansLiverMalariaModels, BiologicalPlasmodiumAntimalarials

Identifiers

PMID27249674
PMCPMC4887158
OpenAlexW2418216524

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.