Evidence map›Paper›PMID 38886254›Full record

ArticleJournal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology2024

Novel Coumarins Derivatives for A. baumannii Lung Infection Developed by High-Throughput Screening and Reinforcement Learning.

Jing Li, Zhou Lu, Liuchang Wang, Huiqing Shi, Bixin Chu, Yingwei Qu, Zichen Ye, Di Qu

Abstract read
In one paragraph

Article in Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

Jing Li *The Key Laboratory for Surface Engineering and Remanufacturing in Shaanxi Province, Key Laboratory of Chemistry of New Material of Functional Inorganic Composites, School of Chemical Engineering, Xi'an University, Xi'an, Shanxi, China.
Zhou Lu *Department of Health Service, Medical Service Training Base, The Fourth Military Medical University, Xi'an, Shanxi, China.
Liuchang WangThe Key Laboratory for Surface Engineering and Remanufacturing in Shaanxi Province, Key Laboratory of Chemistry of New Material of Functional Inorganic Composites, School of Chemical Engineering, Xi'an University, Xi'an, Shanxi, China.
Huiqing ShiDepartment of Clinical Pharmacy, General Hospital of Western Theater Command, Chengdu, Sichuan, China.
Bixin ChuDepartment of Clinical Pharmacy, General Hospital of Western Theater Command, Chengdu, Sichuan, China.
Yingwei QuDepartment of Burn and Plastic Surgery, Zibo Prevention and Treatment Hospital for Occupation Diseases, Zibo, Shandong, China.
Zichen YeDepartment of Health Service, Medical Service Training Base, The Fourth Military Medical University, Xi'an, Shanxi, China. yzc627@163.com.
Di QuDepartment of Clinical Pharmacy, General Hospital of Western Theater Command, Chengdu, Sichuan, China. qvdi@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing resistance of Acinetobacter baumannii (A. baumannii) to antibiotics, researchers have turned their attention to the development of new antimicrobial agents. Among them, coumarin-based heterocycles have attracted much attention due to their unique biological activities, especially in the field of antibacterial infection. In this study, a series of coumarin derivatives were synthesized and screened for their bactericidal activities (Ren et al. 2018; Salehian et al. 2021). The inhibitory activities of these compounds on bacterial strains were evaluated, and the related mechanism of the new compounds was explored. Firstly, the MIC values and bacterial growth curves were measured after compound treatment to evaluate the antibacterial activity in vitro. Then, the in vivo antibacterial activities of the new compounds were assessed on A. baumannii-infected mice by determining the mice survival rates, counting bacterial CFU numbers, measuring inflammatory cytokine levels, and histopathology analysis. In addition, the ROS levels in the bacterial cells were measured with DCFH-DA detection kit. Furthermore, the potential target and detailed mechanism of the new compounds during infection disease therapy were predicted and evidenced with molecular docking. After that, ADMET characteristic prediction was completed, and novel, synthesizable, drug-effective molecules were optimized with reinforcement learning study based on the probed compound as a training template. The interaction between the selected structures and target proteins was further evidenced with molecular docking. This series of innovative studies provides important theoretical and experimental data for the development of new anti-A. baumannii infection drugs.

Indexed as

Acinetobacter baumanniiAcinetobacter InfectionsAnti-Bacterial AgentsCoumarinsHigh-Throughput Screening AssaysMicrobial Sensitivity TestsAnimalsFemaleMaleMiceMice, Inbred BALB CMolecular Docking SimulationAnti-Bacterial AgentsCoumarinsA. baumanniiCoumarinsHigh-throughput screeningLung infectionReinforcement learningStructure optimization

Identifiers

PMID38886254
PMCPMC11182843

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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.