Evidence map›Paper›PMID 39798076›Full record

ReviewTissue barriers2025

Cell-cell crosstalk in the pathogenesis of acute lung injury and acute respiratory distress syndrome.

Zhenzhen Zhu, Ying Zhang, Huan Chen, Huali Zhang

Abstract readReview
In one paragraph

Review in Tissue barriers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Journal of inflammation research · 2026
    Article
  4. Review
  5. Review
  6. Research Progress on the Mechanisms of High Mucus Secretion in the Airway: A Scoping Review.International journal of chronic obstructive pulmonary disease · 2026
    Article
  7. 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.

Zhenzhen ZhuSepsis Translational Medicine Key Laboratory of Hunan Province, Department of Pathophysiology, School of Basic Medicine Science, Central South University, Changsha, Hunan, PR China.
Ying ZhangSepsis Translational Medicine Key Laboratory of Hunan Province, Department of Pathophysiology, School of Basic Medicine Science, Central South University, Changsha, Hunan, PR China.
Huan ChenSepsis Translational Medicine Key Laboratory of Hunan Province, Department of Pathophysiology, School of Basic Medicine Science, Central South University, Changsha, Hunan, PR China.
Huali ZhangSepsis Translational Medicine Key Laboratory of Hunan Province, Department of Pathophysiology, School of Basic Medicine Science, Central South University, Changsha, Hunan, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are the result of an exaggerated inflammatory response triggered by a variety of pulmonary and systemic insults. The lung tissues are comprised of a variety of cell types, including alveolar epithelial cells, pulmonary vascular endothelial cells, macrophages, neutrophils, and others. There is mounting evidence that these diverse cell populations within the lung interact to regulate lung inflammation in response to both direct and indirect stimuli. The aim of this review is to provide a summary and discussion of recent advances in the understanding of the importance of cell-cell crosstalk in the pathogenesis of ALI/ARDS, with a specific focus on the cell-cell interactions that may offer prospective therapeutic avenues for ALI/ARDS.

Indexed as

Acute Lung InjuryCell CommunicationRespiratory Distress SyndromeAnimalsHumansAcute lung injury (ALI)acute respiratory distress syndrome (ARDS)cell-cell interactionsimmune responses

Identifiers

PMID39798076
PMCPMC12506906

What Socratic 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 Socratic graph.