Evidence map›Paper›PMID 41654958›Full record

ArticleJournal of biological engineering2026

Verification and application of an automated real-time antimicrobial susceptibility testing system: for accelerated antibiotic susceptibility testing and high-throughput screening of antibiotic synergistic effects.

Yunxiang Xiao, Xinyu Yan, Zhenzhong Liu, Jie Fu, Zhihua Wang, Dianzheng Jiang, Heran Zhu, Yue Sun, Huili Xia, Changyan Xue

Abstract read
In one paragraph

Article in Journal of biological engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Yunxiang XiaoState Key Laboratory of Marine Resources Utilization in the South China Sea, Hainan University, Haikou, 570228, China.
Xinyu YanState Key Laboratory of Marine Resources Utilization in the South China Sea, Hainan University, Haikou, 570228, China.
Zhenzhong LiuTaizhou Institute of Zhejiang University, Taizhou, 318000, China.
Jie FuHainan SMIC Technology Co., Ltd, Haikou, 570228, China.
Zhihua WangBeijing Yunwang Technology Co., Ltd, Beijing, 100010, China.
Dianzheng JiangState Key Laboratory of Marine Resources Utilization in the South China Sea, Hainan University, Haikou, 570228, China.
Heran ZhuQiongtai Normal University, Haikou, 571100, China.
Yue SunState Key Laboratory of Marine Resources Utilization in the South China Sea, Hainan University, Haikou, 570228, China. 21220856000052@hainanu.edu.cn.
Huili XiaTaizhou Institute for Food and Drug Control, Taizhou, 317700, China. 64463403@qq.com.
Changyan XueTaiZhou Vocational &Technical College, Taizhou, 317700, China. kellsey2022@tzvtc.edu.cn.

Funding

The General Scientific Research Project of Zhejiang Provincial Education Department Y202352110The Key Project of Taizhou Sci-ence and Technology Bureau 24gyz01The Taizhou Science and Technology Plan 23gyb20
6 · The paper itself

Abstract

Bacterial infections remain a serious global health threat, exacerbated by the widespread use of antibiotics leading to bacterial resistance. Faced with the continuous evolution and accelerated spread of drug-resistant bacteria, there is an urgent need to establish an efficient and automated system to accelerate bacterial resistance identification and combination therapy screening in clinical practice. Here, we present an Automated Real-time Antimicrobial Susceptibility Testing (AR-AST) system, which represents an innovation in the AST field by enabling continuous, high-resolution monitoring of microbial growth. This system demonstrated exceptional adaptability, stability, and robustness in monitoring the growth kinetics of six common pathogenic bacteria. Through the establishment of a combined interpretation system of “early bacterial growth kinetics + PPT threshold + slope verification”, it effectively reduces the risk of misclassification. This approach achieved a reduction in the time required for resistance identification of clinical Acinetobacter baumannii 186 and Escherichia coli 15,017 by approximately 75.54% (95% CI: 64.54% − 86.55%) in a hospital setting. Furthermore, when applied to screen pairwise combinations of polymyxin B, polymyxin E, and kanamycin against resistant E. coli15017, a significant synergistic effect was observed for the kanamycin and polymyxin B combination (FIC index = 0.42 < 0.5). The complete inhibition rate in the binary combination was 100% (95% CI: 47.86% − 100%), with a time saving of approximately 68.03% (95% CI: 53.20% − 82.86%). Additionally, the AR-AST System successfully facilitated the quantitative analysis of E. coli15017, exhibiting a broad detection range of six orders of magnitude (10¹ to 10⁶ CFU/mL), high accuracy (|Δ Log₁₀| < ± 0.5), and good stability (P > 0.05), thereby providing effective auxiliary validation for evaluating combination therapy efficacy.

Indexed as

Automated real-time monitoringBacterial resistance identificationCombination therapy screeningQuantitative analysisRapid analysis and identification

Identifiers

PMID41654958
PMCPMC12977749

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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.