ReviewArchives of microbiology2024
Recent advances in the biosensors application for reviving infectious disease management in silkworm model: a new way to combat microbial pathogens.
Review in Archives of microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Silkworms are an essential economic insect but are susceptible to diseases during rearing, leading to yearly losses in cocoon production. While chemical control is currently the primary method to reduce disease incidences, its frequent use can result in loss of susceptibility to pathogens and, ultimately, antibiotic resistance. To effectively prevent or control disease, growers must accurately, sensitively, and quickly detect causal pathogens to determine the best management strategies. Accurate recognition of diseased silkworms can prevent pathogen transmission and reduce cocoon loss. Different pathogen detection methods have been developed to achieve this objective, but they need more precision, specificity, consistency, and promptness and are generally unsuitable for in-situ analysis. Therefore, detecting silkworm diseases under rearing conditions is still an unsolved problem. As a consequence of this, there is an enormous interest in the development of biosensing systems for the early and precise identification of pathogens. There is also significant room for improvement in translating novel biosensor techniques to identify silkworm pathogens. This study explores the types of silkworm diseases, their symptoms, and their causal microorganisms. Moreover, we compare the traditional approaches used in silkworm disease diagnostics along with the latest sensing technologies, with a precise emphasis on lateral flow assay-based biosensors that can detect and manage silkworm pathogens.
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Registered trials
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.