Food security is a global issue, since it is closely related to human health. Antibiotics play a significant role in animal husbandry owing to their desirable broad-spectrum antibacterial activity. However, irrational use of antibiotics has caused serious environmental pollution and food safety problems; thus, the on-site detection of antibiotics is in high demand in environmental analysis and food safety assessment. Aptamer-based sensors are simple to use, accurate, inexpensive, selective, and are suitable for detecting antibiotics for environmental and food safety analysis. This review summarizes the recent advances in aptamer-based electrochemical, fluorescent, and colorimetric sensors for antibiotics detection. The review focuses on the detection principles of different aptamer sensors and recent achievements in developing electrochemical, fluorescent, and colorimetric aptamer sensors. The advantages and disadvantages of different sensors, current challenges, and future trends of aptamer-based sensors are also discussed.
Background: Highly pathogenic strains of avian influenza A virus H5N1 have caused the deaths of more than 262 people since 2003, corresponding to a death rate of about 60% for known infections (information from WHO website). If these viruses acquire the ability for efficient transmission between humans, the next pandemic will come. Therefore, it is important to study the factors that limit the transmission of avian viruses within humans. Methods: The non-structure protein NS1 of H5N1 influenza virus contributes to virulence during virus infection by allowing the virus to disarm the IFN-based defence system of the host cell. To identify new potential antiviral genes regulated by NS1, we measured the expression pattern of cellular gene using DNA microarray technology. The down-regulation of several NF-κB-mediated downstream genes, IL-6, IL-8, COX-2, CCL-20, etc, was observed in the presence of NS1. Real-time PCR and ELISA were used to further confirm the microarray results. Luciferase activity assay indicated that the NF-κB binding sites were essential for the regulation of IL-6 and IL-8 by NS1 protein. Further studies demonstrated that NS1 protein can suppress NF-κB activity in a dose-dependent manner. Western blot assay suggested that NS1 did not alter the expression level of NF-κB, but prevented the translocation of NF-κB from cytosol to nucleus. This inhibitory property of the NS1 protein was dependent on its ability to bind IKKα and IKKβ, which confirmed by the GST pull down, co-immunoprecipitation and confocal assay. Results: We for the first time demonstrated that NS1 can prevent activation of NF-κB through binding to IKK& and IKK$. Conclusion: NF-κB, an important transcription factor, plays an essential role in the regulation of immune and inflammatory responses. Therefore, NS1-mediated inhibition of the NF-κB pathway may thus play a key role in regulating the host innate and adaptive immune responses during virus infection. Abstracts for SupplementInternational Journal of Infectious DiseasesVol. 14Preview Full-Text PDF Open Archive
Cells act as physical computational programs that utilize input signals to orchestrate molecule-level protein-protein interactions (PPIs), generating and responding to forces, ultimately shaping all of the physiological and pathophysiological behaviors. Genome editing and molecule drugs targeting PPIs hold great promise for the treatments of diseases. Linking genes and molecular drugs with protein-performed cellular behaviors is a key yet challenging issue due to the wide range of spatial and temporal scales involved. Building predictive spatiotemporal modeling systems that can describe the dynamic behaviors of cells intervened by genome editing and molecular drugs at the intersection of biology, chemistry, physics, and computer science will greatly accelerate pharmaceutical advances. Here, we review the mechanical roles of cytoskeletal proteins in orchestrating cellular behaviors alongside significant advancements in biophysical modeling while also addressing the limitations in these models. Then, by integrating generative artificial intelligence (AI) with spatiotemporal multiscale biophysical modeling, we propose a computational pipeline for developing virtual cells, which can simulate and evaluate the therapeutic effects of drugs and genome editing technologies on various cell dynamic behaviors and could have broad biomedical applications. Such virtual cell modeling systems might revolutionize modern biomedical engineering by moving most of the painstaking wet-laboratory effort to computer simulations, substantially saving time and alleviating the financial burden for pharmaceutical industries.
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