Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual's diagnosis and/or help clarify risk in healthy populations.

In this paper, we demonstrate an organic electrochemical transistor (OECT) based on the conductive polymer PEDOT:PSS for the analysis of the cell culture medium upon interaction with circulating cells isolated form peripheral blood sampling of health, sub-clinical and cancer patients. The device comprises arrays of super-hydrophobic micro-pillars in which a finite number of pillars incorporates nano-electrodes for site specific measurements of a solution. Due to its nano-scale architecture, the device realizes time and space resolved measurement of biological solution. Tumor metabolism could produce reactive species able to determine a different electronic behavior of correspondent microenviroment. On this basis, the device here presented the changes in the ESR signals was used to identify electronic changes occurring in the analysis of different type of microenvironment. Our results demonstrate that the device is able to register significative difference to differentiate healthy individuals form cancer patients, through an easy blood sampling. In conclusion, these preliminary data are suggestive of a novel test potentially useful to early identification of subjects at risk to development cancer disease.

Understanding how simple biological entities perform complex tasks (such as moving away from predators, reproduction and seeking for food) is one of the main goals of researchers across the world. The C. elegans nematode is one of the simplest and well characterised biological nervous systems (BNS) and the Si elegans EU FP7 project aims to develop a framework to mimic its functionality and better understand basic functions. This paper presents a small scale emulation environment composed of 8 neurons running on field programmable gate arrays (FPGAs), where each neuron FPGA is interconnected to all of the other neuron FPGAs via an innovative optical synaptic connectivity strategy. This paper evaluates the fidelity of synaptic communication for transmission of spikes using both wired and optical methods.

Using C. elegans as a model organism, we present on an optimization strategy for reducing the spatial needs and power consumption in an optical connectome implementation. By means of a cluster analysis algorithm1, the interconnectivity of 279 neurons can be subdivided into 3 groups. This clustering reveals 2 independent neural populations, whose members interconnect only within their cluster-community and through a relay group of inter-cluster connections. Using this strategy, the expected spatial needs could be cut down by one fourth, thereby reducing the required light intensities by the same amount. A follow-up sub-partitioning of the individual clusters led to an additional power saving of up to 7%.

Objective. In light of recent progress in mapping neural function to behavior, we briefly and selectively review past and present endeavors to reveal and reconstruct nervous system function in Caenorhabditis elegans through simulation. Approach. Rather than presenting an all-encompassing review on the mathematical modeling of C. elegans, this contribution collects snapshots of pathfinding key works and emerging technologies that recent single- and multi-center simulation initiatives are building on. We thereby point out a few general limitations and problems that these undertakings are faced with and discuss how these may be addressed and overcome. Main results. Lessons learned from past and current computational approaches to deciphering and reconstructing information flow in the C. elegans nervous system corroborate the need of refining neural response models and linking them to intra- and extra-environmental interactions to better reflect and understand the actual biological, biochemical and biophysical events that lead to behavior. Together with single-center research efforts, the Si elegans and OpenWorm projects aim at providing the required, in some cases complementary tools for different hardware architectures to support advancement into this direction. Significance. Despite its seeming simplicity, the nervous system of the hermaphroditic nematode C. elegans with just 302 neurons gives rise to a rich behavioral repertoire. Besides controlling vital functions (feeding, defecation, reproduction), it encodes different stimuli-induced as well as autonomous locomotion modalities (crawling, swimming and jumping). For this dichotomy between system simplicity and behavioral complexity, C. elegans has challenged neurobiologists and computational scientists alike. Understanding the underlying mechanisms that lead to a context-modulated functionality of individual neurons would not only advance our knowledge on nervous system function and its failure in pathological states, but have directly exploitable benefits for robotics and the engineering of brain-mimetic computational architectures that are orthogonal to current von-Neumann-type machines.

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PEDOT:PSS is a conductive polymer that can be integrated into last generation Organic Electrochemical Transistor (OECT) devices for biological inspection, identification and analysis. While a variety of reports in literature demonstrated the chemical and biological sensitivity of these devices, still their ability in resolving complex mixtures remains controversial. Similar OECT devices display good time dynamics behavior but lack spatial resolution. In this work, we integrated PEDOT:PSS with patterns of super-hydrophobic pillars in which a finite number of those pillars is independently controlled for site-selective measurement of a solution. We obtained a multifunctional, hierarchical OECT device that bridges the micro- to the nano-scales for specific, combined time and space resolved analysis of the sample. Due to super-hydrophobic surface properties, the biological species in the drop are driven by convection, diffusion and the externally applied electric field: the balance/unbalance between these forces will cause the molecules to be transported differently within its volume depending on particle size thus realizing a size-selective separation. Within this framework, the separation and identification of two different molecules, namely Cetyl Trimethyl Ammonium Bromid (CTAB) and adrenaline, in a biological mixture have been demonstrated, showing that geometrical control at the micro-nano scale impart unprecedented selectivity to the devices.

With exactly 302 neurons and about 8000 connections, the hermaphrodite of the soil-dwelling ringworm Caenorhabditis elegans features one of the simplest nervous systems in nature. The Si elegans project will provide a reverse-engineerable model of this nematode by emulating its nervous system and embodying it in a virtual world. The hardware will consist of 302 individual FPGAs, each carrying a neuron-specific neural response model. The FPGA neurons will be interconnected by an electro-optical connectome to distribute the signal at the axonal output or gap-junction pin of an FPGA neuron onto the respective synaptic input or gap-junction pins of postsynaptic FPGA neurons. This technology will replicate the known connectome of the nematode to allow for a biomimetic parallel information flow between neurons. This chapter focuses on the comparison of different electro-optical connectome concepts and on the required implementation steps with their advantages and disadvantages being explained.

Conducting polymers are materials displaying high electrical conductivity, easy of fabrication, flexibility and biocompatibility, for this, they are routinely employed in organic electronics, printed electronics, and bioelectronics. Organic electrochemical transistors (OECTs) are a second generation of organic thin transistors, in which the insulator layer is an electrolyte medium and the conductive polymer is electrochemically active. OECT devices have been demonstrated in chemical and biological sensing: while accurate in determining the size of individual ions in solution, similar devices break down if challenged with complex mixtures. Here, we combine a conductive PEODOT:PSS polymer with a super-hydrophobic scheme to obtain a family of advanced devices, in which the ability to manipulate a biological solution couples to a precise texture of the substrate (which incorporates five micro-electrodes in a line, and each is a site specific measurement point), and this permits to realize time and space resolved analysis of a solution. While the competition between convection and diffusion in a super-hydrophobic drop operates the separation of different species based on their size and charge, the described device delivers the ability to register a similar difference. In the following, we demonstrate the device in the sensing of a solution in which CTAB and adrenaline are separated with good sensitivity, selectivity and reliability.

The chemical environment of cells is an extremely complex and multifaceted system that includes many types of proteins, lipids, nucleic acids and various other components. With the final aim of studying these components in detail, we have developed multiband plasmonic antennas, which are suitable for highly sensitive surface enhanced Raman spectroscopy (SERS) and are activated by a wide range of excitation wavelengths. The three-dimensional hollow nanoantennas were produced on an optical resist by a secondary electron lithography approach, generated by fast ion-beam milling on the polymer and then covered with silver in order to obtain plasmonic functionalities. The optical properties of these structures have been studied through finite element analysis simulations that demonstrated the presence of broadband absorption and multiband enhancement due to the unusual geometry of the antennas. The enhancement was confirmed by SERS measurements, which showed a large enhancement of the vibrational features both in the case of resonant excitation and out-of-resonance excitation. Such characteristics indicate that these structures are potential candidates for plasmonic enhancers in multifunctional opto-electronic biosensors.

Biological nervous systems are robust and highly adaptive information processing entities that excel current computer architectures in almost all aspects of sensory-motor integration. While they are slow and inefficient in the serial processing of stimuli or data chains, they outperform artificial computational systems in seemingly ordinary pattern recognition, orientation or navigation tasks. Even one of the simplest nervous systems in nature, that of the hermaphroditic nematode Caenorhabditis elegans with just 302 neurons and less than 8,000 synaptic connections, gives rise to a rich behavioural repertoire that – among controlling vital functions encodes different locomotion modalities (crawling, swimming and jumping). It becomes evident that both robotics and information and computation technology (ICT) would strongly benefit if the working principles of nervous systems could be extracted and applied to the engineering of brain-mimetic computational architectures. C. elegans, being one of the five best-characterized animal model systems, promises to serve as the most manageable organism to elucidate the information coding and control mechanisms that give rise to complex behaviour. This short paper reviews past and present endeavours to reveal and harvest the potential of nervous system function in C. elegans.

In nature, interneural signaling is highly parallel and temporally precisely structured. It would require equal parallelism and temporal accuracy to faithfully mimic neural communication in hardware representations. Light-based communication schemes fulfil this prerequisite. We report on a prototype of an optical connectome implementation for a neuromorphic system eventually consisting of eight neurons. The platform is based on field-programmable gate arrays (FPGAs) that run neuron-specific response models. Their axons are represented by light-emitting diodes (LEDs) with axonal arbors in the form of micropatterned transparencies. They distribute membrane voltage threshold crossings, which are represented by light pulses, onto synapse-specific photodiodes of postsynaptic neurons. This contribution sketches out the overall system design and discusses its prospective application in replicating the connectome of the nematode C. elegans in the framework of the Si elegans project.

Our current understanding of brain function is still too limited to take advantage of the computational power of even the simplest biological nervous systems. To fill this gap, the Si elegans project (www.si-elegans.eu) aims at developing a computational framework that will replicate the nervous system and rich behavior of the nematode Caenorhabditis elegans, a tiny worm with just 302 neurons. One key element of this emulation testbed is an electro-optical, micromirrorbased connectome. Unlike any other current ICT communication protocol, we expect it to accurately mimic the parallel information transfer between neurons. This strategy promises to give new insights into the nature of two hypothesized key mechanisms - the parallel and precisely timed information flow - that make brains excel von-Neumann-type machines. In this contribution, we briefly introduce the overall Si elegans concept to then describe the requirements for designing a light-based connectome within the given boundary conditions imposed by the hardware infrastructure it will be integrated into.

Recent progresses in nanotechnology fabrication gives the opportunity to build highly functional nano-devices. 3D structures based on noble metals or covered by them can be realized down to the nano-scales, obtaining different devices with the functionalities of plasmonic nano-lenses or nano-probes. Here, nano-cones decorated with silver nano-grains were fabricated using advanced nano-fabrication techniques. In fabricating the cones, the angle of the apex was varied over a significant range and, in doing so, different geometries were realized. In depositing the silver nano-particles, the concentration of solution was varied, whereby different growth conditions were realized. The combined effect of tip geometry and growth conditions influences the size and distribution of the silver nano grains. The tips have the ability to guide or control the growth of the grains, in the sense that the nano-particles would preferentially distribute along the cone, and especially at the apex of the cone, with no o minor concentration effects on the substrate. The arrangement of metallic nano-particles into three-dimensional (3D) structures results in a Surface Enhanced Raman Spectroscopy (SERS) device with improved interface with analytes compared to bi-dimensional arrays of metallic nanoparticles. In the future, similar devices may find application in microfluidic devices, and in general in flow chambers, where the system can be inserted as to mimic a a nano-bait, for the recognition of specific biomarkers, or the manipulation and chemical investigation of single cells directly in native environments with good sensitivity, repeatability and selectivity.

The tiny worm Caenorhabditis elegans features one of the simplest nervous systems in nature. The hermaphrodite contains exactly 302 neurons and about 8000 connections. The Si elegans project aims at providing a reverse-engineerable model of this nematode by emulating its nervous system in hardware and embodying it in a virtual world. The hardware will consist of 302 individual FPGAs, each carrying a neuron-specific neural response model. The FPGA neurons will be interconnected by an electro-optical connectome to distribute the signal at the axonal output or gap-junction pin of an FPGA neuron onto the respective synaptic input or gap-junction pins of those target FPGA neurons that a neuron interconnects with. This technology will replicate the known connectome of the nematode to allow for an as biologically meaningful as possible and truly parallel information flow between neurons. This article focuses on the concepts and first implementation steps of such optical connectome.

Biological neural systems are powerful, robust and highly adaptive computational entities that outperformconventional computers in almost all aspects of sensory-motor integration. Despite dramatic progress ininformation technology, there is a big performance discrepancy between artificial computational systemsand brains in seemingly simple orientation and navigation tasks. In fact, no system exists that can faithfullyreproduce the rich behavioural repertoire of the tiny worm Caenorhabditis elegans which features one of thesimplest nervous systems in nature made of 302 neurons and about 8000 connections. The Si elegans projectaims at providing this missing link. This article is sketching out the main platform components.

Controlling light propagation into multimode optical fibers through spatial light modulators provides highly miniaturized endoscopes and optical micromanipulation probes. We increase the numerical aperture up to nearly 1 by micro-optics fabricated on the fiber-end.

Caenorhabditis elegans features one of the simplest nervous systems in nature, yet its biological information processing still evades our complete understanding. The position of its 302 neurons and almost its entire connectome has been mapped. However, there is only sparse knowledge on how its nervous system codes for its rich behavioral repertoire. The EU-funded Si elegans project aims at reverse-engineering C. elegans‘ nervous system function by its emulation. 302 in parallel interconnected field-programmable gate array (FPGA) neurons will interact through their sensory and motor neurons with a biophysically accurate soft-body representation of the nematode in a virtual behavioral arena. Each FPGA will feature its own reprogrammable neural response model that researchers world-wide will be able to modify to test their neuroscientific hypotheses. In a closed-feedback loop, any sensory experience of the virtual nematode in its virtual environment will be processed by sensory and subsequently interconnected neurons to result in motor commands at neuromuscular junctions at the hardware-software interface to actuate virtual muscles of the virtual nematode. Postural changes in the virtual world will lead to a new sensory experience and thus close the loop. In this contribution we present the overall concepts with special focus on the virtual embodiment of the nematode. For further information and recent news please visit http://www.si-elegans.eu.

We present suitable materials with good optical and mechanical properties, simple processing, efficient and optimized for two-photon polymerization (TPP) with femtosecond fiber lasers. We selected readily available acrylic monomer Bisphenol A ethoxylate diacrylate (BPA-EDA) with three different photoinitiators (PIs), isopropyl thioxanthone (ITX), 7-diethylamino-3-thenoylcoumarin (DETC), and 4,4' bis(diethylamino) benzophenone (BDEB), since their absorption spectra match well with the laser wavelength at 780 nm. These PIs grant efficient radical generation, reactivity and high solubility in acrylic monomers. Finally, good optical and mechanical properties are demonstrated by the fabrication of different micro-structures. (C) 2014 Elsevier B.V. All rights reserved.