Evidence map›Paper›PMID 29415560›Full record

ReviewExperimental biology and medicine (Maywood, N.J.)2018

Current model systems for the study of preeclampsia.

M L Martinez-Fierro, G P Hernández-Delgadillo, V Flores-Morales, E Cardenas-Vargas, M Mercado-Reyes, I P Rodriguez-Sanchez, I Delgado-Enciso, C E Galván-Tejada, J I Galván-Tejada, J M Celaya-Padilla and 1 more

Open access · greenAbstract readReview
In one paragraph

Review in Experimental biology and medicine (Maywood, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Placental Origins of Preeclampsia: Insights from Multi-Omic Studies.International journal of molecular sciences · 2024
    Review
  7. Differential Expression ofJournal of Korean medical science · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. The diagnosis values of serum STAT4 and sEng in preeclampsia.Journal of clinical laboratory analysis · 2020
    Article
  18. Article
  19. Silencing BRIT1 Facilitates the Abilities of Invasiveness and Migration in Trophoblast Cells.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Article
  20. 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

11 authors at 3 institutions in 1 country.

M L Martinez-Fierro1 Molecular Medicine Laboratory, Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, 98160 Zacatecas, México.
G P Hernández-Delgadillo3 Laboratorio de Investigación en Farmacología, 27779 Universidad Autónoma de Zacatecas , 98160 Zacatecas, México.
V Flores-Morales4 Laboratorio de Síntesis Asimétrica y Bioenergética (LSAyB), 27779 Universidad Autónoma de Zacatecas , 98160 Zacatecas, México.ORCID 0000-0003-4540-1011
E Cardenas-Vargas1 Molecular Medicine Laboratory, Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, 98160 Zacatecas, México.
M Mercado-Reyes6 Laboratorio de Biología de la Conservación, Unidad Académica de Ciencias Biológicas, 27779 Universidad Autónoma de Zacatecas , 98060 Zacatecas, México.
I P Rodriguez-Sanchez7 Departamento de Génetica, Facultad de Medicina, Universidad Autonoma de Nuevo Leon, 64460 Monterrey, México.
I Delgado-Enciso8 Faculty of Medicine, Universidad de Colima, 28040 Colima, Mexico.
C E Galván-Tejada10 Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, 98000 Zacatecas, México.
J I Galván-Tejada10 Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, 98000 Zacatecas, México.
J M Celaya-Padilla10 Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, 98000 Zacatecas, México.
I Garza-Veloz1 Molecular Medicine Laboratory, Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, 98160 Zacatecas, México.ORCID 0000-0002-6307-1696
Universidad Autónoma de Zacatecas "Francisco García Salinas" · MXUniversidad Autónoma de Nuevo León · MXUniversidad de Colima · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preeclampsia (PE) is a pregnancy complex disease, distinguished by high blood pressure and proteinuria, diagnosed after the 20th gestation week. Depending on the values of blood pressure, urine protein concentrations, symptomatology, and onset of disease there is a wide range of phenotypes, from mild forms developing predominantly at the end of pregnancy to severe forms developing in the early stage of pregnancy. In the worst cases severe forms of PE could lead to systemic endothelial dysfunction, eclampsia, and maternal and/or fetal death. Worldwide the fetal morbidity and mortality related to PE is calculated to be around 8% of the total pregnancies. PE still being an enigma regarding its etiology and pathophysiology, in general a deficient trophoblast invasion during placentation at first stage of pregnancy, in combination with maternal conditions are accepted as a cause of endothelial dysfunction, inflammatory alterations and appearance of symptoms. Depending on the PE multifactorial origin, several in vitro, in vivo, and in silico models have been used to evaluate the PE pathophysiology as well as to identify or test biomarkers predicting, diagnosing or prognosing the syndrome. This review focuses on the most common models used for the study of PE, including those related to placental development, abnormal trophoblast invasion, uteroplacental ischemia, angiogenesis, oxygen deregulation, and immune response to maternal-fetal interactions. The advances in mathematical and computational modeling of metabolic network behavior, gene prioritization, the protein-protein interaction network, the genetics of PE, and the PE prediction/classification are discussed. Finally, the potential of these models to enable understanding of PE pathogenesis and to evaluate new preventative and therapeutic approaches in the management of PE are also highlighted. Impact statement This review is important to the field of preeclampsia (PE), because it provides a description of the principal in vitro, in vivo, and in silico models developed for the study of its principal aspects, and to test emerging therapies or biomarkers predicting the syndrome before their evaluation in clinical trials. Despite the current advance, the field still lacking of new methods and original modeling approaches that leads to new knowledge about pathophysiology. The part of in silico models described in this review has not been considered in the previous reports.

Indexed as

Models, BiologicalModels, TheoreticalFemaleHumansPre-EclampsiaPregnancySystems BiologyModel systemspreeclampsiastudy

Identifiers

PMID29415560
PMCPMC5882020
OpenAlexW2790219103

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.