Urs Frey


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Frey

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Urs

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Publications 1 - 10 of 33
  • Ronchi, Silvia; Fiscella, Michele; Marchetti, C.; et al. (2018)
    Neuroscience 2018 Abstracts
  • Seichepine, Florent; Rothe, Jörg; Dudina, Alexandra; et al. (2014)
    18th International Conference on Miniaturized Systems for Chemistry and Life Sciences (MicroTAS 2014)
    We report on the integration of single and small bundles of carbon nanotube (CNT) biosensors on a CMOS-integrated array featuring 1024 devices. The system has been designed to allow for direct and versatile readout of each nanosensor. A parallel integration of the CNT nanosensors has been achieved by using semi-sacrificial electrodes and dielectrophoresis (DEP). The developed sensing platform will be used for high-resolution chemical monitoring of complex biological systems. Here, we present the onchip CNT integration process and statistical analysis of the fabricated devices.
  • Huber, Stefan; Bullmann, Torsten; Deligkaris, Kosmas; et al. (2016)
    Frontiers in Neuroscience ~ Conference Abstract: MEA Meeting 2016 | 10th International Meeting on Substrate-Integrated Electrode Arrays
  • Ronchi, Silvia; Fiscella, Michele; Marchetti, Camilla; et al. (2019)
    Frontiers in Neuroscience
    Non-invasive electrical stimulation can be used to study and control neural activity in the brain or to alleviate somatosensory dysfunctions. One intriguing prospect is to precisely stimulate individual targeted neurons. Here, we investigated single-neuron current and voltage stimulation in vitro using high-density microelectrode arrays featuring 26,400 bidirectional electrodes at a pitch of 17.5 μm and an electrode area of 5 × 9 μm2. We determined optimal waveforms, amplitudes and durations for both stimulation modes. Owing to the high spatial resolution of our arrays and the close proximity of the electrodes to the respective neurons, we were able to stimulate the axon initial segments (AIS) with charges of less than 2 pC. This resulted in minimal artifact production and reliable readout of stimulation efficiency directly at the soma of the stimulated cell. Stimulation signals as low as 70 mV or 100 nA, with pulse durations as short as 18 μs, yielded measurable action potential initiation and propagation. We found that the required stimulation signal amplitudes decreased with cell growth and development and that stimulation efficiency did not improve at higher electric fields generated by simultaneous multi-electrode stimulation.
  • Frey, Urs; Heer, Flavio; Pedron, Rene; et al. (2007)
    2007 IEEE 20th International Conference on Micro Electro Mechanical Systems (MEMS)
  • Sessi, Violetta; Ibarlucea, Bergoi; Seichepine, Florent; et al. (2022)
    Frontiers in Neuroscience
    Many biomarkers including neurotransmitters are found in external body fluids, such as sweat or saliva, but at lower titration levels than they are present in blood. Efficient detection of such biomarkers thus requires, on the one hand, to use techniques offering high sensitivity, and, on the other hand, to use a miniaturized format to carry out diagnostics in a minimally invasive way. Here, we present the hybrid integration of bottom-up silicon-nanowire Schottky-junction FETs (SiNW SJ-FETs) with complementary-metal-oxide-semiconductor (CMOS) readout and amplification electronics to establish a robust biosensing platform with 32 x 32 aptasensor measurement sites at a 100 mu m pitch. The applied hetero-junctions yield a selective biomolecular detection down to femtomolar concentrations. Selective and multi-site detection of dopamine is demonstrated at an outstanding sensitivity of similar to 1 V/fM. The integrated platform offers great potential for detecting biomarkers at high dilution levels and could be applied, for example, to diagnosing neurodegenerative diseases or monitoring therapy progress based on patient samples, such as tear liquid, saliva, or eccrine sweat.
  • Weber, Wilfried; Luzi, Stefan; Karlsson, Maria; et al. (2009)
    Nucleic Acids Research
  • Mika, Moana; Mack, Ines; Korten, Insa; et al. (2015)
    Journal of Allergy and Clinical Immunology
    Background Understanding the composition and dynamics of the upper respiratory tract microbiota in healthy infants is a prerequisite to investigate the role of the microbiota in patients with respiratory diseases. This is especially true in early life, when the immune system is in development. Objective We sought to describe the dynamics of the upper respiratory tract microbiota in healthy infants within the first year of life. Methods After exclusion of low-quality samples, microbiota characterization was performed by using 16S rDNA pyrosequencing of 872 nasal swabs collected biweekly from 47 unselected infants. Results Bacterial density increased and diversity decreased within the first year of life (R2 = 0.95 and 0.73, respectively). A distinct profile for the first 3 months of life was found with increased relative abundances of Staphlyococcaceae and Corynebacteriaceae (exponential decay: R2 = 0.94 and 0.96, respectively). In addition, relative bacterial abundance and composition differed significantly from summer to winter months. The individual composition of the microbiota changed with increasing time intervals between samples and was best modeled by an exponential function (R2 = 0.97). Within-subject dissimilarity in a 2-week time interval was consistently lower than that between subjects, indicating a personalized microbiota. Conclusion This study reveals age and seasonality as major factors driving the composition of the nasal microbiota within the first year of life. A subject's microbiota is personalized but dynamic throughout the first year. These data are indispensable to interpretation of cross-sectional studies and investigation of the role of the microbiota in both healthy subjects and patients with respiratory diseases. They might also serve as a baseline for future intervention studies.
  • Yuan, Xinyue; Schröter, Manuel; Obien, Marie Engelene J.; et al. (2020)
    Nature Communications
    Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.
  • Yuan, Xinyue; Emmenegger, Vishalini; Obien, Marie E.; et al. (2018)
    2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)
    In recent electrophysiological studies, CMOS-based high-density microelectrode arrays (HD-MEA) have been widely used for studies of both in-vitro and in-vivo neuronal signals and network behavior. Yet, an open issue in MEA design concerns the tradeoff between signal-to-noise ratio (SNR) and number of readout channels. Here we present a new HD-MEA design in 0.18 μm CMOS technology, consisting of 19,584 electrodes at a pitch of 18.0 μm. By combing two readout structures, namely active-pixel-sensor (APS) and switch-matrix (SM) on a single chip, the dual-mode HD-MEA is capable of recording simultaneously from the entire array and achieving high signal-to-noise-ratio recordings on a subset of electrodes. The APS readout circuits feature a noise level of 10.9 μV rms for the action potential band (300 Hz - 5 kHz), while the noise level for the switch-matrix readout is 3.1 μV rms .
Publications 1 - 10 of 33