Evidence map›Paper›PMID 33235610›Full record

ArticleExperimental and therapeutic medicine2021

PM2.5 induces autophagy-mediated cell apoptosis via PI3K/AKT/mTOR signaling pathway in mice bronchial epithelium cells.

Xuemei Han, Yan Zhuang

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

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  12. Apoptotic volume decrease (AVD) in AFrontiers in physiology · 2023
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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 at 1 institution in 1 country.

Xuemei HanRespiratory Department, The Second Hospital of Tianjin Medical University, Tianjin 300211, P.R. China.
Yan ZhuangRespiratory Department, The Second Hospital of Tianjin Medical University, Tianjin 300211, P.R. China.
Tianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution can highly impact the respiratory system in healthy individuals. Studies have indicated that particles with an aerodynamic diameter of ≤2.5 µm (PM2.5) can be considered to be harmful for lung alveoli and bronchial epithelium cells. PM2.5 can be directly inhaled and can deeply penetrate into the lung alveoli, causing lung dysfunction. However, the toxicological mechanism mediated by PM2.5 for respiratory disease has still not been clearly determined. The purpose of the current study was to investigate the effects of PM2.5 on mouse bronchial epithelium cells (MBECs) and explored the possible mechanism mediated by PM2.5 in MBECs. The results of the current study indicated that PM2.5 markedly decreased lung function, including total lung capacity, residual volume, vital capacity and airway resistance in experimental mice. The results demonstrated that PM2.5 markedly induced inflammatory responses, oxidative injury and MBEC apoptosis. PM2.5 increased interleukin (IL)-1β and IL-6 expression, and reactive oxygen species production in MBECs. Furthermore, PM2.5 specifically induced PI3K, AKT and mTOR expression in MBECs. Disruption of PI3K/AKT/mTOR signaling was also indicated to effectively inhibit apoptosis of MBECs. In conclusion, the results of the current study systematically demonstrated the role of apoptosis-mediated MBEC apoptosis in PM2.5-treated mice, and provides a potential strategy for preclinical intervention in patients with PM2.5-induced lung diseases.

Indexed as

AKTapoptosisautophagybronchial epithelium cellsmTORPI3KPM2.5

Identifiers

PMID33235610
PMCPMC7678636
OpenAlexW3096592448

What OpenQuestion holds

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Registered trials

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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.