Evidence map›Paper›PMID 32210681›Full record

ArticleSaudi journal of biological sciences2020

Analysis of factors of pulmonary fungal infection in mice in respiratory medicine department based on logistic regression analysis model and Progranulin.

Jingya Wang, Quan Zu, Wei Wang

Open access · hybridAbstract read
In one paragraph

Article in Saudi journal of biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Observational
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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

3 authors at 2 institutions in 1 country.

Jingya WangDepartment of Respiratory Medicine, Affiliated Hospital of Jilin Medical University, Jilin City 132000, China.
Quan ZuDepartment of Cardiovascular Medicine, Jilin City People's Hospital, Jilin City 132000, China.
Wei WangDepartment of Respiratory Medicine, Affiliated Hospital of Jilin Medical University, Jilin City 132000, China.
Jilin Medical University · CNPeople 's Hospital of Jilin Province · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this research is to solve the current medical problems of a high incidence of fungal infections in the lungs, high misdiagnosis rate, and high mortality. In this study, firstly, the logistic regression model was used to conduct. Risk factors of pulmonary fungal infection in respiratory department were analyzed. Then a model of pulmonary fungal infection in mice was constructed, and the expression difference of Progranulin (PGRN) in serum was detected by enzyme-linked immuno sorbent assay (ELISA). The expression of PGRN in lung tissues of mice infected by pulmonary fungi was detected by Western bolt method and quantitative polymerase chain reaction (PCR). The PGRN protein and mRNA expression in the lung epithelial cells of mice were detected after the infection. Results logistic regression model was used to analyze the main risk factors affecting pulmonary infection in mice. The risk factors of pulmonary fungal infection were indent catheter, hypoproteinemia, long-term use of glucocorticoid and long-term use of antibiotics. The PGRN content in serum was obviously higher than that before pulmonary fungal infection (P < 0.01). The expression of PGRN mRNA and protein in lung tissue was obviously higher than that before infection (P < 0.01). The expression of PGRN mRNA and protein in lung tissues of the infected group was obviously higher than that of the non-infected group (P < 0.01). The expression of PGRN protein in the lung epithelial cells of mice was obviously higher at 24 h after infection than before infection (P < 0.01), and the expression of PGRN mRNA was obviously higher at 12 h after infection than before infection (P < 0.01), indicating that PGRN is highly expressed in fungal pulmonary infection and is involved in disease progression. Therefore, this study provides a new idea for the diagnosis and treatment of fungal pulmonary infection in the later stage and has a good guiding significance for the diagnosis and treatment of fungal pulmonary infection.

Indexed as

Fungal infectionLogistic regression analysis modelLungMicePGRN

Identifiers

PMID32210681
PMCPMC6997853
OpenAlexW2996448818

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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.