Evidence map›Paper›PMID 28544620›Full record

ReviewBirth defects research2017

Phenotyping cardiac and structural birth defects in fetal and newborn mice.

Xiaoqin Liu, Andrew J Kim, William Reynolds, Yijen Wu, Cecilia W Lo

Abstract readReview
In one paragraph

Review in Birth defects research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Fetal Mouse Heart Clearing, Imaging, and 3D Reconstruction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Data Science for Child Health.The Journal of pediatrics · 2019
    Review
  10. Proteomic-based approaches to cardiac development and disease.Current opinion in chemical biology · 2019
    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

5 authors at 1 institution in 1 country.

Xiaoqin LiuDepartment of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Andrew J KimDepartment of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
William ReynoldsDepartment of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Yijen WuDepartment of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.ORCID http://orcid.org/0000-0001-9509-5417
Cecilia W LoDepartment of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.ORCID http://orcid.org/0000-0003-4314-3434
University of Pittsburgh · US

Funding

Modeling the genetic basis for human congenital heart disease in miceU01HL098180 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LO, CECILIA W. · 2009 to 2014
$8.5M
Modeling the complex genetics of congenital heart disease in miceR01HL132024 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LO, CECILIA W. · 2016 to 2019
$3.4M
Assaying Heterotaxy Patient Genes in Cilia Motility and Left-Right PatterningR01GM104412 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHENNUBHOTLA, SRINIVAS CHAKRA, LO, CECILIA W. · 2014 to 2017
$2.4M
Confocal enhanced episcopic fluorescent image capture (EFIC)S10OD010340 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LO, CECILIA W. · 2012 to 2012
$368k
NHLBI NIH HHS R01 HL132024NHLBI NIH HHS U01 HL098180NIGMS NIH HHS R01 GM104412NIH HHS S10 OD010340
6 · The paper itself

Abstract

Mouse models are invaluable for investigating the developmental etiology and molecular pathogenesis of structural birth defects. While this has been deployed for studying a wide spectrum of birth defects, mice are particularly valuable for modeling congenital heart disease, given they have the same four-chamber cardiac anatomy as in humans. We have developed the use of noninvasive fetal ultrasound together with micro-computed tomography (micro-CT) imaging for high throughput phenotyping of mice for congenital heart defects (CHD) and other developmental anomalies. We showed the efficacy of fetal ultrasound and micro-CT imaging for diagnosis of a wide spectrum of CHD. With fetal ultrasound, longitudinal scans can be conducted to track the developmental profile of disease pathogenesis, providing both structural information with two-dimensional (2D) imaging, as well as functional data from hemodynamic assessments with color flow and spectral Doppler imaging. In contrast, with micro-CT imaging, virtual necropsies can be conducted rapidly postmortem for diagnosis of not only CHD, but also other structural birth defects. To validate the CHD diagnosis, we further showed the use of a novel histological technique with episcopic confocal microscopy to obtain rapid 3D reconstructions for accurate diagnosis of even the most complex anatomical defect. The latter histological imaging technique when combined with the use of ultrasound and micro-CT imaging provides a powerful combination of imaging modalities that will be invaluable in meeting the accelerating demands for high throughput mouse phenotyping of genetically engineered mice in the coming age of functional genomics. Birth Defects Research 109:778-790, 2017. © 2017 Wiley Periodicals, Inc.

Indexed as

AnimalsDisease Models, AnimalEchocardiography, DopplerFemaleFetal HeartHeart Defects, CongenitalHumansInfant, NewbornMicePregnancyPrenatal CareUltrasonographyUltrasonography, Prenatalcongenital heart diseasefetal ultrasound imagingforward genetic screenmicro-CTmouse modelstructural birth defects

Identifiers

PMID28544620
PMCPMC5499535
OpenAlexW2619469982

What OpenQuestion holds

Textmetadata
LicenceTDM
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.