This study describes for the first time the development of 3D printed microfluidic devices with integrated electrodes for label-free counting of E. coli cells incorporated inside droplets based on capacitively coupled contactless conductivity detection (CD). Microfluidic devices were fully fabricated by 3D printing in the T-junction shape containing two channels for disperse and continuous phases and two sensing electrodes for CD measurements. The disperse phase containing E. coli K12 cells and the continuous phase containing oil and 1% Span 80 were pumped through flow rates fixed at 5 and 60 μL min, respectively. The droplets with incorporated cells were monitored in the CD system applying a 500-kHz sinusoidal wave with 1 V amplitude. The generated droplets exhibited a spherical shape with average diameter of 321 ± 9 μm and presented volume of 17.3 ± 0.5 nL. The proposed approach demonstrated ability to detect E. coli cells in the concentration range between 86.5 and 8650 CFU droplet. The number of cells per droplet was quantified through the plate counting method and revealed a good agreement with the Poisson distribution. The limit of detection achieved for counting E. coli cells was 63.66 CFU droplet. The label-free counting method has offered instrumental simplicity, low cost, high sensitivity and compatibility to be integrated on single microfluidic platforms entirely fabricated by 3D printing, thus opening new possibilities of applications in microbiology.
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http://dx.doi.org/10.1016/j.aca.2019.04.045 | DOI Listing |
Biosens Bioelectron
January 2025
College of Mathematical Medicine, Zhejiang Normal University, Jinhua, China; Affiliated Dongyang Hospital of Wenzhou Medical University, Jinhua, China. Electronic address:
Sci Rep
January 2025
Fischell Department of Bioengineering, University of Maryland, College Park, USA.
The development of optical sensors for label-free quantification of cell parameters has numerous uses in the biomedical arena. However, using current optical probes requires the laborious collection of sufficiently large datasets that can be used to calibrate optical probe signals to true metabolite concentrations. Further, most practitioners find it difficult to confidently adapt black box chemometric models that are difficult to troubleshoot in high-stakes applications such as biopharmaceutical manufacturing.
View Article and Find Full Text PDFInt J Biol Sci
January 2025
Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Accurate diagnosis and assessment of breast cancer treatment responses are critical challenges in clinical practice, influencing patient treatment strategies and ultimately long-term prognosis. Currently, diagnosing breast cancer and evaluating the efficacy of neoadjuvant immunotherapy (NAIT) primarily rely on pathological identification of tumor cell morphology, count, and arrangement. However, when tumors are small, the tumors and tumor beds are difficult to detect; relying solely on tumor cell identification may lead to false negatives.
View Article and Find Full Text PDFSci Total Environ
January 2025
Laboratory of Biosensors and Bioanalysis (LABB), Department of Biological Chemistry, IQUIBICEN, University of Buenos Aires and CONICET, CABA, Argentina.
Microplastics (MPs) are in some ways the expected product of man-made plastics that are considered as a pollutant ubiquitous in the environment. This is particularly notorious in continental waters, along coastlines, and especially in the North Pacific Gyre, sometimes called the Pacific Garbage Patch. Even now, there is growing concern that MPs can harm wildlife, enter the food chain, and end up in the human body.
View Article and Find Full Text PDFMethods Appl Fluoresc
December 2024
Physics, Indian Institute of Technology Delhi, Room No.: WS-417,, Department of Physics, IIT Delhi, Hauz Khas New Delhi, Delhi, Delhi, 110016, INDIA.
The current culture-based bacterial detection technique is time-consuming and requires an extended sample preparation methodology. We propose the potential of surface-enhanced Raman spectroscopy (SERS) and surface plasmon-enhanced auto-fluorescence spectroscopy (SPEAS) for the label-free identification and quantification of bacterial pathogens at low concentrations collecting its unique auto-fluorescence and Raman signatures utilising highly anisotropic three-dimensional nanostructures of silver nano dendrites (Ag-NDs). The SERS data facilitates qualitative bacterial identification using the spectral features coming from the bacterial cell wall compound, and the SPEAS data was utilised to gain unique auto-fluorescence spectra present on the bacterial cell wall with enhanced quantification.
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