Microtrap electrode devices for single cell trapping and impedance measurement

Real-time capture of single particles in controlled flow by a rapidly generated foci array with adjustable intensity and pattern

We propose a new, to the best of our knowledge, technique to capture single particles in real-time in a microfluidic system with controlled flow using micro-pillar traps fabricated by one-step. The micro pillars are fabricated in parallel by femtosecond multi-foci laser beams, which are generated by multiplexing gratings. As the generation process does not need integration loops, the pattern and the intensity distribution of the foci array can be controlled in real-time by changing the parameters of gratings. The real-time control of the foci array enables rapidly fabricating microtraps in the microchannel with adjustment of the pillar spaces and patterns according to the sizes and shapes of target particles. This technology provides an important step towards using platforms based on single-particle analysis, and it paves the way for the development of innovative microfluidic devices for single-cell analysis.

Label-Free Biomolecule Detection in Physiological Solutions With Enhanced Sensitivity Using Graphene Nanogrids FET Biosensor

Recently, graphene nanogrid sensor has been reported to be capable of sub-femtomolar sensing of Hepatitis B (Hep-B) surface antigen in buffer. However, for such low concentration of Hep-B in serum, it has been observed during real-time operation that there is an overlap of around 50% in the drain-source current sensitivity values between different concentrations of the target biomolecule, in the range from 0.1 to 100 fM. This has been attributed to the fact that the concentration of non-specific antigen in serum being significantly higher than that of the target antigen, there is a considerable deviation in the number of captured target antigen for the same concentration. Further, this degree of overlap varies from one set to another set of sensor, depending on the statistical variations in the sensor fabrication process. This phenomenon challenges the quantification of target antigen for ultralow limit in physiological analyte. In this paper, we introduce probabilistic neural network (PNN) for quantification of Hep-B down to 0.1 fM in serum using graphene nanogrids field-effect transistor biosensor. The sensor has been operated in heterodyne mode in the frequency range of 100 kHz to 1 MHz applied between drain and source to overcome the problem of Debye screening effect. The application of PNN limits the quantification error within 10% in the range of 0.1 to 100 fM in contrast to 77% and 66% using polynomial fit and static neural network models, respectively. Further, the proposed methodology lowers the detection limit of Hep-B in serum by more than three orders of magnitude compared with the state-of-the-art, real-time, label-free sensors.

Quantitative differentiation of multiple virus in blood using nanoporous silicon oxide immunosensor and artificial neural network

In spite of the rapid developments in various nanosensor technologies, it still remains challenging to realize a reliable ultrasensitive electrical biosensing platform which will be able to detect multiple viruses in blood simultaneously with a fairly high reproducibility without using secondary labels. In this paper, we have reported quantitative differentiation of Hep-B and Hep-C viruses in blood using nanoporous silicon oxide immunosensor array and artificial neural network (ANN). The peak frequency output (f_p) from the steady state sensitivity characteristics and the first cut off frequency (f_c) from the transient characteristics have been considered as inputs to the multilayer ANN. Implementation of several classifier blocks in the ANN architecture and coupling them with both the sensor chips, functionalized with Hep-B and Hep-C antibodies have enabled the quantification of the viruses with an accuracy of around 95% in the range of 0.04fM-1pM and with an accuracy of around 90% beyond 1pM and within 25nM in blood serum. This is the most sensitive report on multiple virus quantification using label free method.

Single Cell Electrical Characterization Techniques

Electrical properties of living cells have been proven to play significant roles in understanding of various biological activities including disease progression both at the cellular and molecular levels. Since two decades ago, many researchers have developed tools to analyze the cell’s electrical states especially in single cell analysis (SCA). In depth analysis and more fully described activities of cell differentiation and cancer can only be accomplished with single cell analysis. This growing interest was supported by the emergence of various microfluidic techniques to fulfill high precisions screening, reduced equipment cost and low analysis time for characterization of the single cell’s electrical properties, as compared to classical bulky technique. This paper presents a historical review of single cell electrical properties analysis development from classical techniques to recent advances in microfluidic techniques. Technical details of the different microfluidic techniques are highlighted, and the advantages and limitations of various microfluidic devices are discussed.

Making a big thing of a small cell--recent advances in single cell analysis

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.

Microfluidic single sperm entrapment and analysis

Selection of healthy spermatozoa is of crucial importance for the success rates of assisted reproduction technologies (ART) such as in vitro fertilization and intra-cytoplasmic sperm injection. Although sperm selection for ART procedures is predominantly based on sperm motility, successful fertilization is not predicted by good motility alone. For example, sperm characteristics such as the acrosome state and DNA integrity have shown significant impact on ART outcome. Although fertilization can be achieved with a single spermatozoon of high quality, current quality assessments are population-based and do not allow investigation of multiple sperm characteristics on a single spermatozoon simultaneously. In order to study sperm cells on the single cell level, we designed and characterized a PDMS microfluidic platform that allows single sperm entrapment. After spatially confining individual sperm cells within microfluidic cell traps, the cell viability, chromosomal content and acrosome state were studied. This platform is suitable for the analysis of individual sperm cells, which could be exploited for (non-invasive) sperm analysis and selection by impedance or Raman spectroscopy.