Evidence mapPaperPMID 36291007Full record

ReviewBiosensors2022

Recent Progress in Spectroscopic Methods for the Detection of Foodborne Pathogenic Bacteria.

Mubashir Hussain, Jun Zou, He Zhang, Ru Zhang, Zhu Chen, Yongjun Tang

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Impact of Farm Management Practices onFoods (Basel, Switzerland) · 2026
    Review
  6. Review
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. 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

6 authors at 3 institutions in 1 country.

Mubashir HussainSchool of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China.ORCID 0000-0002-1673-7109
Jun ZouSchool of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China.
He ZhangSchool of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China.
Ru ZhangSchool of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan 411104, China.
Zhu ChenHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
Yongjun TangPostdoctoral Innovation Practice, Shenzhen Polytechnic, Liuxian Avenue, Nanshan District, Shenzhen 518055, China.
Hunan Institute of Engineering · CNShenzhen Polytechnic University · CNHunan University of Technology · CN

Funding

National Natural Science Foundation of China 81874332Natural Science Foundation of Hunan Province 2020JJ2012Natural Science Youth Foundation of China 61801307Scientific Research Fund of the Shenzhen International cooperation Projects GJHZ20190819151403615
6 · The paper itself

Abstract

Detection of foodborne pathogens at an early stage is very important to control food quality and improve medical response. Rapid detection of foodborne pathogens with high sensitivity and specificity is becoming an urgent requirement in health safety, medical diagnostics, environmental safety, and controlling food quality. Despite the existing bacterial detection methods being reliable and widely used, these methods are time-consuming, expensive, and cumbersome. Therefore, researchers are trying to find new methods by integrating spectroscopy techniques with artificial intelligence and advanced materials. Within this progress report, advances in the detection of foodborne pathogens using spectroscopy techniques are discussed. This paper presents an overview of the progress and application of spectroscopy techniques for the detection of foodborne pathogens, particularly new trends in the past few years, including surface-enhanced Raman spectroscopy, surface plasmon resonance, fluorescence spectroscopy, multiangle laser light scattering, and imaging analysis. In addition, the applications of artificial intelligence, microfluidics, smartphone-based techniques, and advanced materials related to spectroscopy for the detection of bacterial pathogens are discussed. Finally, we conclude and discuss possible research prospects in aspects of spectroscopy techniques for the identification and classification of pathogens.

Indexed as

Biosensing TechniquesFood MicrobiologyArtificial IntelligenceBacteriaSpectrum Analysisbiomedical devicesbiosensorspathogen detectionspectroscopy

Identifiers

PMID36291007
PMCPMC9599795
OpenAlexW4306149854

What Socratic 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 Socratic graph.