Evidence map›Paper›PMID 38523156›Full record

ArticleScientific reports2024

Using novel micropore technology combined with artificial intelligence to differentiate Staphylococcus aureus and Staphylococcus epidermidis.

Ayumi Morimura, Masateru Taniguchi, Hiroyasu Takei, Osamu Sakamoto, Norihiko Naono, Yukihiro Akeda, Daisuke Onozuka, Jumpei Yoshimura, Kazunori Tomono, Satoshi Kutsuna and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The evolving landscape ofFrontiers in immunology · 2026
    Pooled it
  2. Article
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

11 authors.

Ayumi MorimuraDepartment of Infection Control and Prevention, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Masateru TaniguchiThe Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan.
Hiroyasu TakeiAipore Inc., 26-1 Sakuraoka-cho, Shibuya-ku, Tokyo, 150-8512, Japan.
Osamu SakamotoAipore Inc., 26-1 Sakuraoka-cho, Shibuya-ku, Tokyo, 150-8512, Japan.
Norihiko NaonoAipore Inc., 26-1 Sakuraoka-cho, Shibuya-ku, Tokyo, 150-8512, Japan.
Yukihiro AkedaDepartment of Bacteriology I, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-ku, Tokyo, 162-8640, Japan.
Daisuke OnozukaDepartment of Oral Microbe Control, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Jumpei YoshimuraDepartment of Traumatology and Acute Critical Medicine, Graduate School of Medicine, Osaka University, 2-15 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Kazunori TomonoOsaka Institute of Public Health, 1-3-3 Nakamichi, Higashinari-ku, Osaka, 537-0025, Japan.
Satoshi KutsunaDepartment of Infection Control and Prevention, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Shigeto HamaguchiDivision of Infection Control and Prevention, Osaka University Hospital, 2-15 Yamadaoka, Suita, Osaka, 565-0871, Japan. hamaguchi@hp-infect.med.osaka-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methods for identifying bacterial pathogens are broadly categorised into conventional culture-based microbiology, nucleic acid-based tests, and mass spectrometry. The conventional method requires several days to isolate and identify bacteria. Nucleic acid-based tests and mass spectrometry are relatively rapid and reliable, but they require trained technicians. Moreover, mass spectrometry requires expensive equipment. The development of a novel, inexpensive, and simple technique for identifying bacterial pathogens is needed. Through combining micropore technology and assembly machine learning, we developed a novel classifier whose receiver operating characteristic (ROC) curve showed an area under the ROC curve of 0.94, which rapidly differentiated between Staphylococcus aureus and Staphylococcus epidermidis in this proof-of-concept study. Morphologically similar bacteria belonging to an identical genus can be distinguished using our method, which requires no specific training, and may facilitate the diagnosis and treatment of patients with bacterial infections in remote areas and in developing countries.

Indexed as

Nucleic AcidsStaphylococcal InfectionsArtificial IntelligenceHumansStaphylococcus aureusStaphylococcus epidermidisNucleic Acids

Identifiers

PMID38523156
PMCPMC10961322

What OpenQuestion holds

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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.