Evidence map›Paper›PMID 36620533›Full record

ArticleBio-protocol2022

Vandana Kumari, Anasuya C Pal, Pallavi Singh, Choukri Ben Mamoun

Open access · greenAbstract read
In one paragraph

Article in Bio-protocol, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Evaluating acridones as novel therapeutics for human babesiosis.Antimicrobial agents and chemotherapy · 2026
    Article
  2. Article
  3. Pathogens (Basel, Switzerland) · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Transfection ofBio-protocol · 2024
    Article
  8. Article
  9. Article
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

4 authors at 1 institution in 1 country.

Vandana KumariSection of Infectious Disease, Department of Medicine and Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, USA.
Anasuya C PalSection of Infectious Disease, Department of Medicine and Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, USA.
Pallavi SinghSection of Infectious Disease, Department of Medicine and Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, USA.
Choukri Ben MamounSection of Infectious Disease, Department of Medicine and Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, USA.
Yale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Fosinopril analogs for the treatment of human babesiosisR01AI153100 · NIAID · YALE UNIVERSITY · PI BEN MAMOUN, CHOUKRI · 2021 to 2025
$3.6M
Hit-to-Lead Development of the Kalihinol Scaffold for Malaria TreatmentR01AI138139 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI BEN MAMOUN, CHOUKRI, LE ROCH, KARINE GAELLE · 2018 to 2022
$3.6M
Development of endochin-like quinolones for babesiosis therapyR01AI123321 · NIAID · YALE UNIVERSITY · PI BEN MAMOUN, CHOUKRI · 2017 to 2020
$2.7M
Antigen Discovery and Vaccine Development for Human Babesia ParasitesR01AI152220 · NIAID · YALE UNIVERSITY · PI BEN MAMOUN, CHOUKRI · 2020 to 2024
$2.1M
An antigen-detection assay to diagnose Babesia microti infectionR44AI136118 · NIAID · L2 DIAGNOSTICS, LLC · PI LEDIZET, MICHEL · 2020 to 2022
$2.1M
An antigen-detection assay to diagnose Babesia microti infectionR43AI136118 · NIAID · L2 DIAGNOSTICS, LLC · PI LEDIZET, MICHEL · 2018 to 2018
$300k
NCATS NIH HHS UL1 TR001863NIAID NIH HHS R01 AI123321NIAID NIH HHS R01 AI138139NIAID NIH HHS R01 AI152220NIAID NIH HHS R01 AI153100NIAID NIH HHS R43 AI136118NIAID NIH HHS R44 AI136118
6 · The paper itself

Abstract

Babesiosis is a tick-borne disease caused by pathogens belonging to the genus Babesia. In humans, the disease presents as a malaria-like illness and can be fatal in immunocompromised and elderly people. In the past few years, human babesiosis has been a rising concern worldwide. The disease is transmitted through tick bite, blood transfusion, and transplacentally in rare cases, with several species of Babesia causing human infection. Babesia microti, Babesia duncani, and Babesia divergens are of particular interest because of their important health impact and amenability to research inquiries. B. microti, the most commonly reported Babesia pathogen infecting humans, can be propagated in immunocompetent and immunocompromised mice but so far has not been successfully continuously propagated in vitro in human red blood cells (hRBCs). Conversely, B. divergens can be propagated in vitro in human red blood cells but lacks a mouse model to study its virulence. Recent studies have highlighted the uniqueness of B. duncani as an ideal model organism to study intraerythrocytic parasitism in vitro and in vivo. An optimized B. duncani in culture and in mouse (ICIM) model has recently been described, combining long-term continuous in vitro culture of the parasite in hRBCs with an animal model of parasitemia (P) and lethal infection in C3H/HeJ mice. Here, we provide a detailed protocol for the use of the B. duncani ICIM model in research. This model provides a unique and sound foundation to gain further insights into the biology, pathogenesis, and virulence of Babesia and other intraerythrocytic parasites, and has been validated as an efficient system to evaluate novel strategies for the treatment of human babesiosis and possibly other parasitic diseases.

Indexed as

Babesia duncaniErythrocyteHuman babesiosisInfectionMiceParasiteSmearVirulence

Identifiers

PMID36620533
PMCPMC9795036
OpenAlexW4313121850

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.