Evidence map›Paper›PMID 41179629›Full record

ReviewArchives of Razi Institute2025

Nanonbiosensors; Rapid Detection of

Chaleshgari Soheila, Mostofi Fakhrani Zahra, Salimpour Kavasebi Shahla, Komeili Nima

Abstract readReview
In one paragraph

Review in Archives of Razi Institute, 2025. 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
–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

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

4 authors.

Chaleshgari SoheilaAvian disease health, Shahid Chamran University, Ahvaz, Iran.
Mostofi Fakhrani ZahraIslamic Azad University of Shoushtar, Khuzestan, Iran.
Salimpour Kavasebi ShahlaDepartment of Science, Urmia University, Urmia, Iran.
Komeili NimaFaculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Zoonotic diseases, defined as those that are infectious and transmitted from animals to humans, constitute a substantial global health concern. Despite concerted efforts to eradicate or control these diseases, healthcare systems continue to face a substantial burden due to their re-emergence. The early and accurate detection of bacterial pathogens is of crucial importance in order to prevent the potential health consequences associated with zoonotic infections. However, conventional diagnostic methods such as Polymerase Chain Reaction (PCR), culture-based techniques, and immunological assays have limitations, including costliness, labour-intensiveness, and lengthy turnaround times for results. There is an increasing interest in the development of faster, more accurate, and cost-effective diagnostic methods to address these challenges. The utilization of nanobiosensors has emerged as a promising tool for the rapid detection of infectious disease agents. The utilization of biological recognition elements by these devices enables the detection of specific pathogens, with the potential to effect a paradigm shift in diagnostic practices. Furthermore, the incorporation of nanotechnology, particularly nanomaterials, has been demonstrated to enhance the performance of biosensors by improving their specificity and sensitivity. This review explores the application of biosensors and nanobiosensors to rapidly detect Salmonella, Clostridium, Escherichia, and Brucella spp. infections. These innovative technologies offer several advantages over traditional diagnostic methods, including reduced cost, simplified workflows, and faster results. The capacity of nanobiosensors to discern the presence of bacterial pathogens in a variety of sample types, encompassing environmental samples, animal specimens and clinical samples, renders them a versatile instrument for the implementation of disease surveillance and control measures. Furthermore, nanobiosensors have demonstrated considerable potential in enhancing the sensitivity and specificity of detection assays, thereby facilitating the early identification of Salmonella, Clostridium, Escherichia, and Brucella spp., even at low concentrations. By leveraging advancements in nanotechnology, researchers can further improve the performance and reliability of biosensors for zoonotic disease diagnosis. The integration of biosensors and nanotechnology has been demonstrated to hold significant potential for enhancing the detection and characterisation of Salmonella, Clostridium, Escherichia, and Brucella spp. The implementation of these innovative diagnostic tools has the potential to transform disease surveillance efforts, mitigate the spread of zoonotic diseases, and ultimately improve public health outcomes on a global scale.

Indexed as

Biosensing TechniquesBrucellosisNanotechnologyZoonosesAnimalsBrucellaClostridiumHumansSalmonellaClostridiumRapid DetectionNanobiosensorsNanomaterialsSalmonella

Identifiers

PMID41179629
PMCPMC12572706

What OpenQuestion holds

Textmetadata
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.