Evidence map›Paper›PMID 38849894›Full record

ReviewRespiratory research2024

Novel insights into the potential applications of stem cells in pulmonary hypertension therapy.

Sijia Guo, Dachun Wang

Abstract readReview
In one paragraph

Review in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

2 authors.

Sijia GuoStem Cell Laboratory, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China. guosijia@fjmu.edu.cn.
Dachun WangStem Cell Laboratory, Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.

Funding

Fujian Provincial Health Commission 2020QNB029Science and Technology Bureau of Quanzhou 2020N033s
6 · The paper itself

Abstract

Pulmonary hypertension (PH) refers to a group of deadly lung diseases characterized by vascular lesions in the microvasculature and a progressive increase in pulmonary vascular resistance. The prevalence of PH has increased over time. Currently, the treatment options available for PH patients have limited efficacy, and none of them can fundamentally reverse pulmonary vascular remodeling. Stem cells represent an ideal seed with proven efficacy in clinical studies focusing on liver, cardiovascular, and nerve diseases. Since the potential therapeutic effect of mesenchymal stem cells (MSCs) on PH was first reported in 2006, many studies have demonstrated the efficacy of stem cells in PH animal models and suggested that stem cells can help slow the deterioration of lung tissue. Existing PH treatment studies basically focus on the paracrine action of stem cells, including protein regulation, exosome pathway, and cell signaling; however, the specific mechanisms have not yet been clarified. Apoptotic and afunctional pulmonary microvascular endothelial cells (PMVECs) and alveolar epithelial cells (AECs) are two fundamental promoters of PH although they have not been extensively studied by researchers. This review mainly focuses on the supportive communication and interaction between PMVECs and AECs as well as the potential restorative effect of stem cells on their injury. In the future, more studies are needed to prove these effects and explore more radical cures for PH.

Indexed as

Hypertension, PulmonaryAnimalsHumansMesenchymal Stem Cell TransplantationStem Cell TransplantationAlveolar epithelial cellsEndothelial cellsPotential therapeuticPulmonary hypertensionPulmonary microvascularStem cells

Identifiers

PMID38849894
PMCPMC11162078

What OpenQuestion holds

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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.