Evidence map›Paper›PMID 35003414›Full record

ArticleWorld journal of emergency medicine2022

Effects of Maxingloushi decoction on immune inflammation and programmed death markers in mice with chronic obstructive pulmonary disease.

Li Li, Jun Yan, Lin-Qin Ma, Wei Bi, Cai-Jun Wu

Open access · bronzeAbstract read
In one paragraph

Article in World journal of emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Li LiEmergency Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.
Jun YanEmergency Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.
Lin-Qin MaEmergency Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.
Wei BiEmergency Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.
Cai-Jun WuEmergency Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.
Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine · CNBeijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo investigate effects of Maxingloushi decoction on lung inflammation and programmed death markers (programmed death-1 [PD-1], programmed death-ligand 1 [PD-L1]) in the lung tissue, peripheral blood, and bronchoalveolar lavage fluid (BLF) in a mouse model of chronic obstructive pulmonary disease (COPD).

methodsThirty-six mature male BALB/C mice were randomly divided into normal group (group A,

resultsIn plasma and BLF, the expression of PD-1 in the group B was higher than that in the group A, and the expression of PD-L1 was lower than that in the group A. The expression of PD-1 and PD-L1 in the lung tissue was normalized in the group C in comparison with the group B (

conclusionsThese findings reveal that COPD causes an immune imbalance in the peripheral blood and lung tissue, and that both Maxingloushi decoction and PD-1 inhibitor treatment can mitigate lung inflammation in COPD by reducing PD-1 expression and increasing PD-L1 expression. The treatment effect of Maxingloushi decoction may be superior to that of PD-1 inhibitor.

Indexed as

Chronic obstructive pulmonary diseaseImmuneMaxingloushi decoctionMiceProgrammed death-1Programmed death-ligand 1

Identifiers

PMID35003414
PMCPMC8677923
OpenAlexW4200394229

What OpenQuestion holds

Textmetadata
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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.