Evidence map›Paper›PMID 37619985›Full record

ArticleThe clinical respiratory journal2023

Saikosaponin D attenuates inflammatory response and cell apoptosis of lipopolysaccharide-induced lung epithelial cells.

Lijie Song, Guoyu Lu, Yanyan Tao

Open access · goldAbstract read
In one paragraph

Article in The clinical respiratory journal, 2023. 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
1.6field-weighted citation impact, top 15% 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, 10 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

3 authors at 1 institution in 1 country.

Lijie SongDepartment of Emergency medical, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Guoyu LuDepartment of Emergency medical, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Yanyan TaoDepartment of Emergency medical, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China.ORCID https://orcid.org/0000-0002-2720-5298
Bengbu Medical College · CN

Funding

Natural Science Key Project of Bengbu Medical College 2021byzd157Natural Science Key Project of Bengbu Medical College BYKY2019118ZD
6 · The paper itself

Abstract

backgroundAcute lung injury (ALI) is a prevalent complication of sepsis with high mortality rate. Saikosaponin D (SSD) is a triterpenoid saponin that has been reported to alleviate sepsis-triggered renal injury in mice. Nonetheless, the therapeutic effect of SSD on sepsis-evoked ALI is unclarified.

methodsLipopolysaccharide (LPS) from Escherichia coli 055:B5 was utilized to stimulate lung epithelial cell line MLE-12. A mouse model of sepsis was established. CCK-8 assay was employed for determining cytotoxicity. ELISA was utilized for determining proinflammatory cytokine production. Flow cytometry and western blotting were implemented for evaluating cell apoptosis. Hematoxylin-eosin staining was conducted for histologic analysis of murine lung tissues.

resultsSSD alleviated LPS-triggered inflammation and cell apoptosis of MLE-12 cells. SSD treatment ameliorated the pathological damages, inflammatory response, and cell apoptosis in the lungs of septic mice.

conclusionSSD protects against sepsis-triggered ALI by inhibiting inflammation and cell apoptosis in MLE-12 cells and septic mouse mice.

Indexed as

Acute Lung InjurySaponinsSepsisAnimalsApoptosisEpithelial CellsHumansInflammationLipopolysaccharidesLungMiceOleanolic AcidLipopolysaccharidesOleanolic Acidsaikosaponin DSaponinsacute lung injuryapoptosisinflammationSaikosaponin Dsepsis

Identifiers

PMID37619985
PMCPMC10542997
OpenAlexW4386118166

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.