38
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      A survey on parameter identification, state estimation and data analytics for lateral flow immunoassay: from systems science perspective

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references106

          • Record: found
          • Abstract: found
          • Article: not found

          SHERLOCK: nucleic acid detection with CRISPR nucleases

          Rapid detection of nucleic acids is integral to applications in clinical diagnostics and biotechnology. We have recently established a CRISPR-based diagnostic platform that combines nucleic acid pre-amplification with CRISPR-Cas enzymology for specific recognition of desired DNA or RNA sequences. This platform, termed specific high-sensitivity enzymatic reporter unlocking (SHERLOCK), allows multiplexed, portable, and ultra-sensitive detection of RNA or DNA from clinically relevant samples. Here, we provide step-by-step instructions for setting up SHERLOCK assays with recombinase-mediated polymerase pre-amplification of DNA or RNA and subsequent Cas13- or Cas12-mediated detection via fluorescence and colorimetric readouts that provide results in <1 h with a setup time of less than 15 min. We also include guidelines for designing efficient CRISPR RNA (crRNA) and isothermal amplification primers, as well as discuss important considerations for multiplex and quantitative SHERLOCK detection assays.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Internet of medical things (IoMT)-integrated biosensors for point-of-care testing of infectious diseases

              On global scale, the current situation of pandemic is symptomatic of increased incidences of contagious diseases caused by pathogens. The faster spread of these diseases, in a moderately short timeframe, is threatening the overall population wellbeing and conceivably the economy. The inadequacy of conventional diagnostic tools in terms of time consuming and complex laboratory-based diagnosis process is a major challenge to medical care. In present era, the development of point-of-care testing (POCT) is in demand for fast detection of infectious diseases along with “on-site” results that are helpful in timely and early action for better treatment. In addition, POCT devices also play a crucial role in preventing the transmission of infectious diseases by offering real-time testing and lab quality microbial diagnosis within minutes. Timely diagnosis and further treatment optimization facilitate the containment of outbreaks of infectious diseases. Presently, efforts are being made to support such POCT by the technological development in the field of internet of medical things (IoMT). The IoMT offers wireless-based operation and connectivity of POCT devices with health expert and medical centre. In this review, the recently developed POC diagnostics integrated or future possibilities of integration with IoMT are discussed with focus on emerging and re-emerging infectious diseases like malaria, dengue fever, influenza A (H1N1), human papilloma virus (HPV), Ebola virus disease (EVD), Zika virus (ZIKV), and coronavirus (COVID-19). The IoMT-assisted POCT systems are capable enough to fill the gap between bioinformatics generation, big rapid analytics, and clinical validation. An optimized IoMT-assisted POCT will be useful in understanding the diseases progression, treatment decision, and evaluation of efficacy of prescribed therapy.
                Bookmark

                Author and article information

                Contributors
                Journal
                International Journal of Systems Science
                International Journal of Systems Science
                Informa UK Limited
                0020-7721
                1464-5319
                June 11 2022
                : 1-21
                Affiliations
                [1 ]Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, People's Republic of China
                [2 ]Department of Mathematics, Yangzhou University, Yangzhou, People's Republic of China
                [3 ]Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
                Article
                10.1080/00207721.2022.2083262
                b789a266-afe8-451a-91e4-6d5441565800
                © 2022
                History

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content811

                Cited by19

                Most referenced authors1,293