Publications

Supramolecular systems chemistry has been an area of active research to develop nanomaterials with life-like functions. Progress in systems chemistry relies on our ability to probe the nanostructure formation in solution. Often visualizing the dynamics of nanostructures which transform over time is a formidable challenge. This necessitates a paradigm shift from dry sample imaging towards solution-based techniques. We review the application of state-of-the-art techniques for real-time, in situ visualization of dynamic self-assembly processes. We present how solution-based techniques namely optical super-resolution microscopy, solution-state atomic force microscopy, liquid-phase transmission electron microscopy, molecular dynamics simulations and other emerging techniques are revolutionizing our understanding of active and adaptive nanomaterials with life-like functions. This Review provides the visualization toolbox and futuristic vision to tap the potential of dynamic nanomaterials.© 2022 Wiley-VCH GmbH.

JTD Keywords: electron-microscopy, fluorescence microscopy, in-situ, mechanical-properties, molecular simulations, nanostructures, polymerization, polymers, stimulated-emission, super-resolution microscopy, supramolecular chemistry, systems chemistry, water, Atomic-force microscopy, Liquid tem, Nanostructures, Super-resolution microscopy, Supramolecular chemistry, Systems chemistry

Local cancer treatment by in situ injections of thermo-responsive hydrogels (HG) offers several advantages over conventional systemic anti-cancer treatments. In this work, a biodegradable and multicompartmental HG composed of N-isopropylacrylamide, cellulose, citric acid, and ceric ammonium nitrate was developed for the controlled release of hydrophilic (doxorubicin) and hydrophobic (niclosamide) drugs. The formulation presented ideal properties regarding thermo-responsiveness, rheological behavior, drug release profile, biocompatibility, and biological activity in colon and ovarian cancer cells. Cellulose was found to retard drugs release rate, being only 4 % of doxorubicin and 30 % of niclosamide released after 1 week. This low release was sufficient to cause cell death in both cell lines. Moreover, HG demonstrated a proper injectability, in situ prevalence, and safety profile in vivo. Overall, the HG properties, together with its natural and eco-friendly composition, create a safe and efficient platform for the local treatment of non-resectable tumors or tumors requiring pre-surgical adjuvant therapy.

JTD Keywords: Ammonium-nitrate, Biodegradable, Cancer treatment, Cellulose, Controlled-release formulation, Delivery, Drug delivery systems, Hydrogel, Reduce, Thermo-responsiveness

Galleria mellonella is an alternative animal model of infection. The use of this species presents a wide range of advantages, as its maintenance and rearing are both easy and inexpensive. Moreover, its use is considered to be more ethically acceptable than other models, it is conveniently sized for manipulation, and its immune system has multiple similarities with mammalian immune systems. Hemocytes are immune cells that help encapsulate and eliminate pathogens and foreign particles. All of these reasons make this insect a promising animal model. However, cultivating G. mellonella hemocytes in vitro is not straightforward and it has many difficult challenges. Here, we present a methodologically optimized protocol to establish and maintain a G. mellonella hemocyte primary culture. These improvements open the door to easily and quickly study the toxicity of nanoparticles and the interactions of particles and materials in an in vitro environment.

JTD Keywords: Bacteria, Cell culture, Galleria mellonella, Hemolin, Infection, Insect hemocytes, Larvae, Lepidoptera, Nanoparticle, Phagocytosis, Prophenoloxidase, Suspension, Systems

Organ-on-chip platforms combined with high-throughput sensing technology allow bridging gaps in information presented by 2D cultures modeled on static microphysiological systems. While these platforms do not aim to replicate whole organ systems with all physiological nuances, they try to mimic relevant structural, physiological, and functional features of organoids and tissues to best model disease and/or healthy states. The advent of this platform has not only challenged animal testing but has also presented the opportunity to acquire real-time, high-throughput data about the pathophysiology of disease progression by employing biosensors. Biosensors allow monitoring of the release of relevant biomarkers and metabolites as a result of physicochemical stress. It, therefore, helps conduct quick lead validation to achieve personalized medicine objectives. The organ-on-chip industry is currently embarking on an exponential growth trajectory. Multiple pharmaceutical and biotechnology companies are adopting this technology to enable quick patient-specific data acquisition at substantially low costs.

JTD Keywords: A-chip, Biosensor, Biosensors, Cancer, Cells, Culture, Disease models, Epithelial electrical-resistance, Hydrogel, Microfabrication, Microphysiological systems, Models, Niches, Organ-on-a-chips, Platform

The ability to engineer complex multicellular systems has enormous potential to inform our understanding of biological processes and disease and alter the drug development process. Engineering living systems to emulate natural processes or to incorporate new functions relies on a detailed understanding of the biochemical, mechanical, and other cues between cells and between cells and their environment that result in the coordinated action of multicellular systems. On April 3-6, 2022, experts in the field met at the Keystone symposium "Engineering Multicellular Living Systems" to discuss recent advances in understanding how cells cooperate within a multicellular system, as well as recent efforts to engineer systems like organ-on-a-chip models, biological robots, and organoids. Given the similarities and common themes, this meeting was held in conjunction with the symposium "Organoids as Tools for Fundamental Discovery and Translation".

JTD Keywords: Brain organoids, Cell diversity, Computational, Dynamics, Engineered living, Engineered organs, Heart, Maturation, Model, Multicellular, Mycobacterium-tuberculosis, Quantitative-analysis, Systems, Tissue deformation

Over the last decades, photopharmacology has gone far beyond its proof-of-concept stage to become a bona fide approach to study neural systems in vivo. Indeed, photopharmacological control has expanded over a wide range of endogenous targets, such as receptors, ion channels, transporters, kinases, lipids, and DNA transcription processes. In this review, we provide an overview of the recent progresses in the in vivo photopharmacological control of neuronal circuits and behavior. In particular, the use of small aquatic animals for the in vivo screening of photopharmacological compounds, the recent advances in optical modulation of complex behaviors in mice, and the development of adjacent techniques for light and drug delivery in vivo are described.

JTD Keywords: Architecture, Azobenzene photoswitches, Brain circuits, Channels, Circadian rhythm, In vivo photomodulation, In vivo technology, Light, Modulator, Neuronal receptors, Optical control, Optogenetics, Pharmacology, Photopharmacology, Receptors, Systems

Antibody-functionalized nanoparticles (NPs) are commonly used to increase the targeting selectivity toward cells of interest. At a molecular level, the number of functional antibodies on the NP surface and the density of receptors on the target cell determine the targeting interaction. To rationally develop selective NPs, the single-molecule quantitation of both parameters is highly desirable. However, techniques able to count molecules with a nanometric resolution are scarce. Here, we developed a labeling approach to quantify the number of functional cetuximabs conjugated to NPs and the expression of epidermal growth factor receptors (EGFRs) in breast cancer cells using direct stochastic optical reconstruction microscopy (dSTORM). The single-molecule resolution of dSTORM allows quantifying molecules at the nanoscale, giving a detailed insight into the distributions of individual NP ligands and cell receptors. Additionally, we predicted the fraction of accessible antibody-conjugated NPs using a geometrical model, showing that the total number exceeds the accessible number of antibodies. Finally, we correlated the NP functionality, cell receptor density, and NP uptake to identify the highest cell uptake selectivity regimes. We conclude that single-molecule functionality mapping using dSTORM provides a molecular understanding of NP targeting, aiding the rational design of selective nanomedicines.

JTD Keywords: active targeting, active targeting dstorm, antibodies, dstorm, heterogeneity, multivalency, nanomedicine, nanoparticle functionality, size, super-resolution microscopy, surface, Active targeting, Antibodies, Cell membranes, Cell receptors, Cytology, Direct stochastic optical reconstruction microscopy, Dstorm, Heterogeneity, Ligands, Medical nanotechnology, Molecules, Nanomedicine, Nanoparticle functionality, Nanoparticle targeting, Nanoparticles, Optical reconstruction, Single molecule, Stochastic systems, Stochastics, Super-resolution microscopy, Superresolution microscopy

Remarkable progress in bioengineering over the past two decades has enabled the formulation of fundamental design principles for a variety of medical and non-medical applications. These advancements have laid the foundation for building multicellular engineered living systems (M-CELS) from biological parts, forming functional modules integrated into living machines. These cognizant design principles for living systems encompass novel genetic circuit manipulation, self-assembly, cell–cell/matrix communication, and artificial tissues/organs enabled through systems biology, bioinformatics, computational biology, genetic engineering, and microfluidics. Here, we introduce design principles and a blueprint for forward production of robust and standardized M-CELS, which may undergo variable reiterations through the classic design-build-test-debug cycle. This Review provides practical and theoretical frameworks to forward-design, control, and optimize novel M-CELS. Potential applications include biopharmaceuticals, bioreactor factories, biofuels, environmental bioremediation, cellular computing, biohybrid digital technology, and experimental investigations into mechanisms of multicellular organisms normally hidden inside the “black box” of living cells.

JTD Keywords: cell-fate specification, endothelial-cells, escherichia-coli, extracellular-matrix, gene-expression noise, nuclear hormone-receptors, pluripotent stem-cells, primitive endoderm, transcription factors, Artificial tissues, Assembly cells, Biological parts, Biological systems, Bioremediation, Blood-brain-barrier, Cell engineering, Cell/matrix communication, Design principles, Environmental technology, Functional modules, Fundamental design, Genetic circuits, Genetic engineering, Living machines, Living systems, Medical applications, Molecular biology, Synthetic biology

The characterization of newly synthesized materials is a cornerstone of all chemistry and nanotechnology laboratories. For this purpose, a wide array of analytical techniques have been standardized and are used routinely by laboratories across the globe. With these methods we can understand the structure, dynamics and function of novel molecular architectures and their relations with the desired performance, guiding the development of the next generation of materials. Moreover, one of the challenges in materials chemistry is the lack of reproducibility due to improper publishing of the sample preparation protocol. In this context, the recent adoption of the reporting standard MIRIBEL (Minimum Information Reporting in Bio–Nano Experimental Literature) for material characterization and details of experimental protocols aims to provide complete, reproducible and reliable sample preparation for the scientific community. Thus, MIRIBEL should be immediately adopted in publications by scientific journals to overcome this challenge. Besides current standard spectroscopy and microscopy techniques, there is a constant development of novel technologies that aim to help chemists unveil the structure of complex materials. Among them super-resolution microscopy (SRM), an optical technique that bypasses the diffraction limit of light, has facilitated the study of synthetic materials with multicolor ability and minimal invasiveness at nanometric resolution. Although still in its infancy, the potential of SRM to unveil the structure, dynamics and function of complex synthetic architectures has been highlighted in pioneering reports during the last few years. Currently, SRM is a sophisticated technique with many challenges in sample preparation, data analysis, environmental control and automation, and moreover the instrumentation is still expensive. Therefore, SRM is currently limited to expert users and is not implemented in characterization routines. This perspective discusses the potential of SRM to transition from a niche technique to a standard routine method for material characterization. We propose a roadmap for the necessary developments required for this purpose based on a collaborative effort from scientists and engineers across disciplines.

JTD Keywords: blinking, fluorophore, intramolecular spirocyclization, localization, nanoparticles, resolution limit, reveals, single-molecule fluorescence, stimulated-emission, Characterization techniques, Diffraction, Distributed computer systems, Environmental management, Information reporting, Material chemistry, Materials characterization, Minimum information, Optical reconstruction microscopy, Optical resolving power, Sample preparation, Structure dynamics, Structure functions, Super-resolution microscopy, Synthesized materials

Charge separation and transport through the reaction center of photosystem I (PSI) is an essential part of the photosynthetic electron transport chain. A strategy is developed to immobilize and orient PSI complexes on gold electrodes allowing to probe the complex's electron acceptor side, the chlorophyll special pair P700. Electrochemical scanning tunneling microscopy (ECSTM) imaging and current-distance spectroscopy of single protein complex shows lateral size in agreement with its known dimensions, and a PSI apparent height that depends on the probe potential revealing a gating effect in protein conductance. In current-distance spectroscopy, it is observed that the distance-decay constant of the current between PSI and the ECSTM probe depends on the sample and probe electrode potentials. The longest charge exchange distance (lowest distance-decay constant ?) is observed at sample potential 0 mV/SSC (SSC: reference electrode silver/silver chloride) and probe potential 400 mV/SSC. These potentials correspond to hole injection into an electronic state that is available in the absence of illumination. It is proposed that a pair of tryptophan residues located at the interface between P700 and the solution and known to support the hydrophobic recognition of the PSI redox partner plastocyanin, may have an additional role as hole exchange mediator in charge transport through PSI.© 2021 Wiley-VCH GmbH.

JTD Keywords: azurin, current distance decay spectroscopy, cytochrome c(6), electrochemical scanning tunneling microscopy (ecstm), electrochemistry, photosystem i, photosystem-i, plastocyanin, protein electron transfer, recognition, single metalloprotein, single molecules, structural basis, tunneling spectroscopy, 'current, Amino acids, Charge transfer, Chlorine compounds, Current distance decay spectroscopy, Decay spectroscopies, Distance decay, Electrochemical scanning tunneling microscopy, Electrochemical scanning tunneling microscopy (ecstm), Electrodes, Electron transfer, Electron transport properties, Gold compounds, Photosystem i, Photosystems, Protein electron transfer, Protein electron-transfer, Proteins, Scanning tunneling microscopy, Silver halides, Single molecule, Single molecules

The impact of diet and digestive disorders in flatus composition remains largely unexplored. This is partially due to the lack of standardized sampling collection methods, and the easy atmospheric contamination. This paper describes a method to quantitatively determine the major gases in flatus and their application in a nutritional intervention. We describe how to direct sample flatus into Tedlar bags, and simultaneous analysis by gas chromatography–thermal conductivity detection (GC–TCD). Results are analyzed by univariate hypothesis testing and by multilevel principal component analysis. The reported methodology allows simultaneous determination of the five major gases with root mean measurement errors of 0.8% for oxygen (O2), 0.9% for nitrogen (N2), 0.14% for carbon dioxide (CO2), 0.11% for methane (CH4), and 0.26% for hydrogen (H2). The atmospheric contamination was limited to 0.86 (95% CI: [0.7–1.0])% for oxygen and 3.4 (95% CI: [1.4–5.3])% for nitrogen. As an illustration, the method has been successfully applied to measure the response to a nutritional intervention in a reduced crossover study in healthy subjects. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: breath, colonic microbiota, diet effect on flatus, disorders, evacuation, excretion, flatulence, hydrogen gas, major flatus gas components, multilevel principal component analysis, rectal gas collection, systems, volume, Atmospheric contamination, Carbon dioxide, Conductivity detection, Diet effect on flatus, Gas chromatography, Gas collections, Gas component, Gases, Major flatus gas component, Major flatus gas components, Multilevel principal component analyse, Multilevel principal component analysis, Multilevels, Nitrogen, Nutrition, Oxygen, Principal component analysis, Principal-component analysis, Rectal gas collection, Volatile organic-compounds

Supramolecular chemistry is the quintessential backbone of all biological processes. It encompasses a wide range from the metabolic network to the self-assembled cytoskeletal network. Combining the chemical diversity with the plethora of functional depth that biological systems possess is a daunting task for synthetic chemists to emulate. The only route for approaching such a challenge lies in understanding the complex and dynamic systems through advanced analytical techniques. The supramolecular complexity that can be successfully generated and analyzed is directly dependent on the analytical treatment of the system parameters. In this review, we illustrate advanced analytical techniques that have been used to investigate various supramolecular systems including complex mixtures, dynamic self-assembly, and functional nanomaterials. The underlying theme of such an overview is not only the exceeding detail with which traditional experiments can be probed but also the fact that complex experiments can now be attempted owing to the analytical techniques that can resolve an ensemble in astounding detail. Furthermore, the review critically analyzes the current state of the art analytical techniques and suggests the direction of future development. Finally, we envision that integrating multiple analytical methods into a common platform will open completely new possibilities for developing functional chemical systems.

JTD Keywords: analytical techniques, dynamic self-assembly, high-speed afm, liquid cell tem, Analytical technique, Analytical techniques, Biological process, Chemical analysis, Chemical diversity, Complex networks, Cytoskeletal network, Dynamic self-assembly, High-speed afm, Hydrogels, In-situ, Liquid cell tem, Metabolic network, Microscopy, Nanoscale, Proteins, Self assembly, Supramolecular chemistry, Supramolecular systems, System chemistry, Systems chemistry

The importance of PEG architecture on nanoparticle (NP) functionality is known but still difficult to investigate, especially at a single particle level. Here, we apply DNA Point Accumulation for Imaging in Nanoscale Topography (DNA-PAINT), a super-resolution microscopy (SRM) technique, to study the surface functionality in poly(lactide-co-glycolide)-poly(ethylene glycol) (PLGA-PEG) NPs with different PEG structures. We demonstrated how the length of the PEG spacer can influence the accessibility of surface chemical functionality, highlighting the importance of SRM techniques to support the rational design of functionalized NPs.

JTD Keywords: chain-length, density, plga, surface, systems, Chain-length, Density, Dna, Microscopy technique, Nanoparticles, Nanoscale topography, Paint, Peg spacers, Plga, Poly lactide-co-glycolide, Poly-lactide-co-glycolide, Polyethylene glycols, Polylactide-co-glycolide, Single-particle, Super-resolution microscopy, Superresolution microscopy, Surface, Surface chemicals, Surface functionalities, Systems

Microphysiological systems (MPS) or organs-on-chips (OoC) can emulate the physiological functions of organs in vitro and are effective tools for determining human drug responses in preclinical studies. However, the analysis of MPS has relied heavily on optical tools, resulting in difficulties in real-time and high spatial resolution imaging of the target cell functions. In this study, the role of scanning probe microscopy (SPM) as an analytical tool for MPS is evaluated. An access hole is made in a typical MPS system with stacked microchannels to insert SPM probes into the system. For the first study, a simple vascular model composed of only endothelial cells is prepared for SPM analysis. Changes in permeability and local chemical flux are quantitatively evaluated during the construction of the vascular system. The morphological changes in the endothelial cells after flow stimulation are imaged at the single-cell level for topographical analysis. Finally, the possibility of adapting the permeability and topographical analysis using SPM for the intestinal vascular system is further evaluated. It is believed that this study will pave the way for an in situ permeability assay and structural analysis of MPS using SPM.

JTD Keywords: cell, electrochemical microscopy, membrane-permeability, microphysiological systems, organs-chips, platform, scanning electrochemical microscopy, scanning ion conductance microscopy, scanning probe microscopy, shear-stress, surface-topography, Ion conductance microscopy, Microphysiological systems, Organs-chips, Scanning electrochemical microscopy, Scanning ion conductance microscopy, Scanning probe microscopy

Chronic wounds represent a major health burden and drain on medical system. Efficient wound repair is only possible if the dressing materials target simultaneously multiple factors involved in wound chronicity, such as deleterious proteolytic and oxidative enzymes and high bacterial load. Here we develop multifunctional hydrogels for chronic wound management through self-assembling of thiolated hyaluronic acid (HA-SH) and bioactive silver-lignin nanoparticles (Ag@Lig NPs). Dynamic and reversible interactions between the polymer and Ag@Lig NPs yield hybrid nanocomposite hydrogels with shear-thinning and self-healing properties, coupled to zero-order kinetics release of antimicrobial silver in response to infection-related hyalurodinase. The hydrogels inhibit the major enzymes myeloperoxidase and matrix metalloproteinases responsible for wound chronicity in a patient's wound exudate. Furthermore, the lignin-capped AgNPs provide the hydrogel with antioxidant properties and strong antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa. The nanocomposite hydrogels are not toxic to human keratinocytes after 7 days of direct contact. Complete tissue remodeling and restoration of skin integrity is demonstrated in vivo in a diabetic mouse model. Hematological analysis reveals lack of wound inflammation due to bacterial infection or toxicity, confirming the potential of HA-SH/Ag@Lig NPs hydrogels for chronic wound management. Statement of significance: Multifunctional hydrogels are promising materials to promote healing of complex wounds. Herein, we report simple and versatile route to prepare biocompatible and multifunctional self-assembled hydrogels for efficient chronic wound treatment utilizing polymer-nanoparticle interactions. Hybrid silver-lignin nanoparticles (Ag@Lig NPs) played both: i) structural role, acting as crosslinking nodes in the hydrogel and endowing it with shear-thinning (ability to flow under applied shear stress) and self-healing properties, and ii) functional role, imparting strong antibacterial and antioxidant activity. Remarkably, the in situ self-assembling of thiolated hyaluronic acid and Ag@Lig NPs yields nanocomposite hydrogels able to simultaneously inhibits the major factors involved in wound chronicity, namely the overexpressed deleterious proteolytic and oxidative enzymes, and high bacterial load.

JTD Keywords: catechol, chronic wounds, dressing materials, inhibition, mechanism, nano-enabled hydrogels, polyphenols, promogran, self-assembling, silver-lignin nanoparticles, systems, tannins, Chronic wounds, Degradation, Dressing materials, Nano-enabled hydrogels, Self-assembling, Silver-lignin nanoparticles, Thiolated hyaluronic acid

A plethora of applications using polysaccharides have been developed in recent years due to their availability as well as their frequent nontoxicity and biodegradability. These polymers are usually obtained from renewable sources or are byproducts of industrial processes, thus, their use is collaborative in waste management and shows promise for an enhanced sustainable circular economy. Regarding the development of novel delivery systems for biotherapeutics, the potential of polysaccharides is attractive for the previously mentioned properties and also for the possibility of chemical modification of their structures, their ability to form matrixes of diverse architectures and mechanical properties, as well as for their ability to maintain bioactivity following incorporation of the biomolecules into the matrix. Biotherapeutics, such as proteins, growth factors, gene vectors, enzymes, hormones, DNA/RNA, and antibodies are currently in use as major therapeutics in a wide range of pathologies. In the present review, we summarize recent progress in the development of polysaccharide-based hydrogels of diverse nature, alone or in combination with other polymers or drug delivery systems, which have been implemented in the delivery of biotherapeutics in the pharmaceutical and biomedical fields. © 2021 American Chemical Society.

JTD Keywords: biodegradable dextran hydrogels, biotherapeutics, bone morphogenetic protein-2, carrageenan-based hydrogels, chitosan-based hydrogels, controlled delivery, controlled-release, cross-linked hydrogels, growth-factor delivery, hydrogels, in-vitro characterization, polysaccharides, self-healing hydrogel, stimuli-responsiveness, tissue engineering, Antibodies, Bioactivity, Biodegradability, Biomedical fields, Biomolecules, Biotherapeutics, Chemical modification, Circular economy, Controlled delivery, Controlled drug delivery, Delivery systems, Drug delivery system, Functional polymers, Hyaluronic-acid hydrogels, Hydrogels, Industrial processs, Polysaccharides, Recent progress, Renewable sources, Stimuli-responsiveness, Targeted drug delivery, Tissue engineering, Waste management

Biomimetic calcium-deficient hydroxyapatite (CDHA) as a bioactive material exhibits exceptional intrinsic osteoinductive and osteogenic properties because of its nanostructure and composition, which promote a favorable microenvironment. Its high reactivity has been hypothesized to play a relevant role in the in vivo performance, mediated by the interaction with the biological fluids, which is amplified by its high specific surface area. Paradoxically, this high reactivity is also behind the in vitro cytotoxicity of this material, especially pro-nounced in static conditions. The present work explores the structural and physicochemical changes that CDHA undergoes in contact with physiological fluids and to investigate its interaction with proteins. Calcium-deficient hydroxyapatite discs with different micro/nanostructures, coarse (C) and fine (F), were exposed to cell-free complete culture medium over extended periods of time: 1, 7, 14, 21, 28, and 50 days. Precipitate formation was not observed in any of the materials in contact with the physiological fluid, which would indicate that the ionic exchanges were linked to incorporation into the crystal structure of CDHA or in the hydrated layer. In fact, CDHA experienced a maturation process, with a progressive increase in crystallinity and the Ca/P ratio, accompanied by an uptake of Mg and a B-type carbonation process, with a gradual propagation into the core of the samples. However, the reactivity of biomimetic hydroxyapatite was highly dependent on the specific surface area and was amplified in nanosized needle-like crystal structures (F), whereas in coarse specimens the ionic exchanges were restricted to the surface, with low penetration in the material bulk. In addition to showing a higher protein adsorption on F substrates, the proteomics study revealed the existence of protein selectivity to-ward F or C microstructures, as well as the capability of CDHA, and more remarkably of F-CDHA, to concentrate specific proteins from the culture medium. Finally, a substantial improvement in the material's ability to support cell proliferation was observed after the CDHA maturation process.

JTD Keywords: calcium phosphates, ion exchange, nanostructure, protein adsorption, Biological-systems, Biomaterials, Biomimetic hydroxyapatites, Biomimetics, Bone-formation, Calcium deficient hydroxyapatite, Calcium phosphate, Calcium phosphates, Cell proliferation, Crystal structure, Crystallinity, Crystals structures, Culture medium, Growth, High reactivity, Hydroxyapatite, In-vitro, Ion exchange, Ionic exchange, Molecular biology, Nanocrystalline apatites, Nanostructure, Nanostructures, Octacalcium phosphate, Physicochemical studies, Physiological fluids, Physiology, Protein adsorption, Proteins, Proteomic studies, Raman spectroscopy, Serum-albumin, Specific surface area

Biological cognition is based on the ability to autonomously acquire knowledge, or epistemic autonomy. Such self-supervision is largely absent in artificial neural networks (ANN) because they depend on externally set learning criteria. Yet training ANN using error backpropagation has created the current revolution in artificial intelligence, raising the question of whether the epistemic autonomy displayed in biological cognition can be achieved with error backpropagation-based learning. We present evidence suggesting that the entorhinal–hippocampal complex combines epistemic autonomy with error backpropagation. Specifically, we propose that the hippocampus minimizes the error between its input and output signals through a modulatory counter-current inhibitory network. We further discuss the computational emulation of this principle and analyze it in the context of autonomous cognitive systems. © 2021 Elsevier Ltd

JTD Keywords: computational model, dentate gyrus, error backpropagation, granule cells, grid cells, hippocampus, inhibition, input, neural-networks, neurons, transformation, Artificial intelligence, Artificial neural network, Back propagation, Backpropagation, Brain, Cognitive systems, Counter current, Error back-propagation, Error backpropagation, Errors, Expressing interneurons, Hippocampal complex, Hippocampus, Human experiment, Input and outputs, Learning, Mammal, Mammalian hippocampus, Mammals, Neural networks, Nonhuman, Review, Self-supervised learning

Purpose: This paper aims to explore how the cross-fertilization of knowledge and technologies in EU-funded research projects, including serious games and gamification, is influenced by the following variables: multidisciplinarity, knowledge base and organizations (number and diversity). The interrelation of actors and projects form a network of innovation. The largest contribution to cross-fertilization comes from the multidisciplinary nature of projects and the previous knowledge and technology of actors. The analysis draws on the understanding of how consortia perform as an innovation network, what their outcomes are and what capabilities are needed to reap value. Design/methodology/approach: All the research projects including serious games and/or gamification, funded by the EU-Horizon 2020 work programme, have been analyzed to test the hypotheses in this paper. The study sample covers the period between 2014 and 2016 (June), selecting the 87 research projects that comprised 519 organizations as coordinators and participants, and 597 observations – because more organizations participate in more than one project. The data were complemented by documentary and external database analysis. Findings: To create cross-fertilization of knowledge and technologies, the following emphasis should be placed on projects: partners concern various disciplines; partners have an extensive knowledge base for generating novel combinations and added-value technologies; there is a diverse typology of partners with unique knowledge and skills; and there is a limited number of organizations not too closely connected to provide cross-fertilization. Research limitations/implications: First, the database sample covers a period of 30 months. The authors’ attention was focused on this period because H2020 prioritized for the first time the serious games and gamification with two specific calls (ICT-21–14 and ICT-24–16) and, second, for the explosion of projects including these technologies in the past years (Adkins, 2017). These facts can be understood as a way to push the research to higher technology readiness levels (TRLs) and introducing the end-user in the co-creation and co-development along the value chain. Second, an additional limitation makes reference to the European focus of the projects, missing strong regional initiatives not identified and studied. Originality/value: This paper has attempted to explore and define theoretically and empirically the characteristics found in the cross-fertilization of collaborative research projects, emphasizing which variables, and how, need to be stimulated to benefit more multidisciplinary consortia and accelerate the process of innovation. © 2021, Manel González-Piñero, Cristina Páez-Avilés, Esteve Juanola-Feliu and Josep Samitier.

JTD Keywords: absorptive-capacity, business model, cross-fertilization of knowledge, diversity, front-end, impact, innovation systems, knowledge management, management research, science, social networks, team, technology, Cross-fertilization of knowledge, Innovation, Knowledge management, Management research, Research-and-development, Technology

The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observation that the entorhinal-hippocampal complex (EHC) forms a closed loop and projects inhibitory signals “countercurrent” to the trisynaptic pathway to build a self-supervised model that learns to reconstruct its own inputs by error backpropagation. The EHC is then abstracted as an autoencoder, with the hidden layers acting as an information bottleneck. With the inputs mimicking the firing activity of lateral and medial entorhinal cells, our model is shown to generate place cells and to respond to environmental manipulations as observed in rodent experiments. Altogether, we propose that the hippocampus builds conjunctive compressed representations of the environment by learning to reconstruct its own entorhinal inputs via gradient descent.

JTD Keywords: cognitive neuroscience, grid cells, long-term, networks, neural networks, novelty, oscillations, pattern separation, region, representation, working-memory, Cognitive neuroscience, Neural networks, Rat dentate gyrus, Systems neuroscience

Plaques of the amyloid beta (A beta) peptide are a pathological hallmark of Alzheimer's disease (AD), the most common form of dementia. Mutations in A beta also cause familial forms of AD (fAD). Here, we use deep mutational scanning to quantify the effects of >14,000 mutations on the aggregation of A beta. The resulting genetic landscape reveals mechanistic insights into fibril nucleation, including the importance of charge and gatekeeper residues in the disordered region outside of the amyloid core in preventing nucleation. Strikingly, unlike computational predictors and previous measurements, the empirical nucleation scores accurately identify all known dominant fAD mutations in A beta, genetically validating that the mechanism of nucleation in a cell-based assay is likely to be very similar to the mechanism that causes the human disease. These results provide the first comprehensive atlas of how mutations alter the formation of any amyloid fibril and a resource for the interpretation of genetic variation in A beta.

JTD Keywords: aggregation, kinetics, oligomers, onset, rates, state, Aggregation, Alzheimer's, Amyloid, Computational biology, Deep mutagenesis, Genetics, Genomics, Kinetics, Nucleation, Oligomers, Onset, Precursor protein, Rates, S. cerevisiae, State, Systems biology

© 2020 The Author(s) The dominant biomedical perspective on addictions has been that they are chronic brain diseases. While we acknowledge that the brains of people with addictions differ from those without, we argue that the “broken brain” model of addiction has important limitations. We propose that a systems-level perspective more effectively captures the integrated architecture of the embodied and situated human mind and brain in relation to the development of addictions. This more dynamic conceptualization places addiction in the broader context of the addicted brain that drives behavior, where the addicted brain is the substrate of the addicted mind, that in turn is situated in a physical and socio-cultural environment. From this perspective, neurorehabilitation should shift from a “broken-brain” to a systems theoretical framework, which includes high-level concepts related to the physical and social environment, motivation, self-image, and the meaning of alternative activities, which in turn will dynamically influence subsequent brain adaptations. We call this integrated approach system-oriented neurorehabilitation. We illustrate our proposal by showing the link between addiction and the architecture of the embodied brain, including a systems-level perspective on classical conditioning, which has been successfully translated into neurorehabilitation. Central to this example is the notion that the human brain makes predictions on future states as well as expected (or counterfactual) errors, in the context of its goals. We advocate system-oriented neurorehabilitation of addiction where the patients' goals are central in targeted, personalized assessment and intervention.

JTD Keywords: addiction, brain disease model, neurorehabilitation, Addiction, Brain disease model, Neurorehabilitation, Systems approach

© 2020 Elsevier Inc. Severe asthma is associated with an increased airway smooth muscle (ASM) mass and altered composition of the extracellular matrix (ECM). Studies have indicated that ECM-ASM cell interactions contribute to this remodeling and its limited reversibility with current therapy. Three-dimensional matrices allow the study of complex cellular responses to different stimuli in an almost natural environment. Our goal was to obtain acellular bronchial matrices and then develop a recellularization protocol with ASM cells. We studied equine bronchi as horses spontaneously develop a human asthma-like disease. The bronchi were decellularized using Triton/Sodium Deoxycholate. The obtained scaffolds retained their anatomical and histological properties. Using immunohistochemistry and a semi-quantitative score to compare native bronchi to scaffolds revealed no significant variation for matrixial proteins. DNA quantification and electrophoresis revealed that most DNA was 29.6 ng/mg of tissue ± 5.6, with remaining fragments of less than 100 bp. Primary ASM cells were seeded on the scaffolds. Histological analysis of the recellularizations showed that ASM cells migrated and proliferated primarily in the decellularized smooth muscle matrix, suggesting a chemotactic effect of the scaffolds. This is the first report of primary ASM cells preferentially repopulating the smooth muscle matrix layer in bronchial matrices. This protocol is now being used to study the molecular interactions occurring between the asthmatic ECMs and ASM to identify effectors of asthmatic bronchial remodeling.

JTD Keywords: 2d, airway smooth muscle cells, asthma, decellularization, disease, elastin, extracellular matrix, lung scaffolds, migration, peptide, recellularization, tissues, Airway smooth muscle cells, Asthma, Culture-systems, Decellularization, Extracellular matrix, Recellularization

Recent advances in miniaturization of chemical instrumentation and in low-cost small drones are catalyzing exponential growth in the use of such platforms for environmental chemical sensing applications. The versatility of chemically sensitive drones is reflected by their rapid adoption in scientific, industrial, and regulatory domains, such as in atmospheric research studies, industrial emission monitoring, and in enforcement of environmental regulations. As a result of this interdisciplinarity, progress to date has been reported across a broad spread of scientific and non-scientific databases, including scientific journals, press releases, company websites, and field reports. The aim of this paper is to assemble all of these pieces of information into a comprehensive, structured and updated review of the field of chemical sensing using small drones. We exhaustively review current and emerging applications of this technology, as well as sensing platforms and algorithms developed by research groups and companies for tasks such as gas concentration mapping, source localization, and flux estimation. We conclude with a discussion of the most pressing technological and regulatory limitations in current practice, and how these could be addressed by future research.

JTD Keywords: Unmanned aircraft systems, Remotely piloted aircraft systems, Chemical sensors, Gas sensors, Environmental monitoring, Industrial emission monitoring

Metal Oxide (MOX) gas sensors rely on chemical reactions that occur efficiently at high temperatures, resulting in too-demanding power requirements for certain applications. Operating the sensor under a Pulsed-Temperature Operation (PTO), by which the sensor heater is switched ON and OFF periodically, is a common practice to reduce the power consumption. However, the sensor performance is degraded as the OFF periods become larger. Other research works studied, generally, PTO schemes applying waveforms to the heater with time periods of seconds and duty cycles above 20%. Here, instead, we explore the behaviour of PTO sensors working under aggressive schemes, reaching power savings of 99% and beyond with respect to continuous heater stimulation. Using sensor sensitivity and the limit of detection, we evaluated four Ultra Low Power (ULP) sensors under different PTO schemes exposed to ammonia, ethylene, and acetaldehyde. Results show that it is possible to operate the sensors with total power consumption in the range of microwatts. Despite the aggressive power reduction, sensor sensitivity suffers only a moderate decline and the limit of detection may degrade up to a factor five. This is, however, gas-dependent and should be explored on a case-by-case basis since, for example, the same degradation has not been observed for ammonia. Finally, the run-in time, i.e., the time required to get a stable response immediately after switching on the sensor, increases when reducing the power consumption, from 10 minutes to values in the range of 10–20 hours for power consumptions smaller than 200 microwatts.

JTD Keywords: Robot sensing systems, Temperature sensors, Heating systems, Gas detectors, Power demand, Sensitivity, Electronic nose, gas sensors, low-power operation, machine olfaction, pulsed-temperature operation, temperature modulation

Low-cost gas sensors allow for large-scale spatial monitoring of air quality in the environment. However they require calibration before deployment. Methods such as multivariate regression techniques have been applied towards sensor calibration. In this work, we propose instead, the use of deep learning methods, particularly, recurrent neural networks for predicting the gas concentrations based on the outputs of these sensors. This paper presents a first study of using Gated Recurrent Unit (GRU) neural network models for gas concentration prediction. The GRU networks achieve on average, a 44.69% and a 25.17% RMSE improvement in concentration prediction on a gas dataset when compared with Support Vector Regression (SVR) and Multilayer Perceptron (MLP) models respectively. With the current advances in deep network hardware accelerators, these networks can be combined with the sensors for a compact embedded system suitable for edge applications.

JTD Keywords: Robot sensing systems, Predictive models, Logic gates, Gas detectors, Training, Temperature measurement, Support vector machines

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Soft robotics, Biomimetics, Insect navigation, Synthetic nervous system, Computer vision, Bio-inspired materials, Visual homing, Locomotion+, Image processing, Intelligent robots, Human-robot interaction, Machine learning, Snake robot, Mobile robots, Robotic systems, Drosophila, Robots, Sensors, Signal processing

Insoluble protein aggregates are the hallmarks of many neurodegenerative diseases. For example, aggregates of TDP-43 occur in nearly all cases of amyotrophic lateral sclerosis (ALS). However, whether aggregates cause cellular toxicity is still not clear, even in simpler cellular systems. We reasoned that deep mutagenesis might be a powerful approach to disentangle the relationship between aggregation and toxicity. We generated >50,000 mutations in the prion-like domain (PRD) of TDP-43 and quantified their toxicity in yeast cells. Surprisingly, mutations that increase hydrophobicity and aggregation strongly decrease toxicity. In contrast, toxic variants promote the formation of dynamic liquid-like condensates. Mutations have their strongest effects in a hotspot that genetic interactions reveal to be structured in vivo, illustrating how mutagenesis can probe the in vivo structures of unstructured proteins. Our results show that aggregation of TDP-43 is not harmful but protects cells, most likely by titrating the protein away from a toxic liquid-like phase.

JTD Keywords: Computational biology and bioinformatics, Genomics, Mechanisms of disease, Neurodegeneration, Systems biology

Understanding how polyprotic compounds distribute within liposome (LP) suspensions is of major importance to design effective drug delivery strategies. Advances in this research field led to the definition of LP-based active drug encapsulation methods driven by transmembrane pH gradients with evidenced efficacy in the management of cancer and infectious diseases. An accurate modeling of membrane-solution drug partitioning is also fundamental when designing drug delivery systems for poorly endocytic cells, such as red blood cells (RBCs), in which the delivered payloads rely mostly on the passive diffusion of drug molecules across the cell membrane. Several experimental models have been proposed so far to predict the partitioning of polyprotic basic/acid drugs in artificial membranes. Nevertheless, the definition of a model in which the membrane-solution partitioning of each individual drug microspecies is studied relative to each other is still a topic of ongoing research. We present here a novel experimental approach based on mathematical modeling of drug encapsulation efficiency (EE) data in liposomal systems by which microspecies-specific partition coefficients are reported as a function of pH and phospholipid compositions replicating the RBC membrane in a simple and highly translatable manner. This approach has been applied to the study of several diprotic basic antimalarials of major clinical importance (quinine, primaquine, tafenoquine, quinacrine, and chloroquine) describing their respective microspecies distribution in phosphatidylcholine-LP suspensions. Estimated EE data according to the model described here closely fitted experimental values with no significant differences obtained in 75% of all pH/lipid composition-dependent conditions assayed. Additional applications studied include modeling drug EE in LPs in response to transmembrane pH gradients and lipid bilayer asymmetric charge, conditions of potential interest reflected in our previously reported RBC-targeted antimalarial nanotherapeutics.

JTD Keywords: Distribution coefficient, Liposomal systems, Malaria therapy, Nanomedicine, Partition coefficient, PH-controlled drug encapsulation, Polyprotic drug, Targeted drug delivery

Can machines be endowed with morality? We argue that morality in the descriptive or epistemic sense can be extended to artificial systems. Following arguments from evolutionary game-theory, we identify two main ingredients required to operationalize this notion of morality in machines. The first, being a group theory of mind, and the second, being an assignment of valence. We make the case for the plausibility of these operations in machines without reference to any form of intentionality or consciousness. The only systems requirements needed to support the above two operations are autonomous goal-directed action and the ability to interact and learn from the environment. Following this we have outlined a theoretical framework based on conceptual spaces and valence assignments to gauge latent morality in autonomous machines and algorithms.

JTD Keywords: Autonomous systems, Ethics of algorithms, Goal-directed action, Philosophy of morality, Qualia, Theory of mind

Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO2) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO2, desaturation duration dtSaO2 and desaturation area dSaO2A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO2 parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO2 suggests an almost subject-independent proportion increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO2 reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO2A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO2 parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.

JTD Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization

Emerging nanobiotechnologies can offer solutions to the current and future challenges in medicine. By covering topics from regenerative medicine, tissue engineering, drug delivery, bionanofabrication, and molecular biorecognition, this Special Issue aims to provide an update on the trends in nanomedicine and drug delivery using biomimetic approaches, and the development of novel biologically inspired devices for the safe and effective diagnosis, prevention, and treatment of disease.

JTD Keywords: Bioinspired nanotechnologies, Bionanofabrication, Bio-nano measurement and microscopy, Nanomaterials for biological and medical applications, Nanoassemblies, Nanostructured surfaces, Drug delivery, Nanobioelectronics, Integrated systems/nanobiosensors, Nanotoxicology, Graphene-based applications

Endocytosis and vesicular trafficking are cellular processes that regulate numerous functions required to sustain life. From a translational perspective, they offer avenues to improve the access of therapeutic drugs across cellular barriers that separate body compartments and into diseased cells. However, the fact that many factors have the potential to alter these routes, impacting our ability to effectively exploit them, is often overlooked. Altered vesicular transport may arise from the molecular defects underlying the pathological syndrome which we aim to treat, the activity of the drugs being used, or side effects derived from the drug carriers employed. In addition, most cellular models currently available do not properly reflect key physiological parameters of the biological environment in the body, hindering translational progress. This article offers a critical overview of these topics, discussing current achievements, limitations and future perspectives on the use of vesicular transport for drug delivery applications.

JTD Keywords: Cellular vesicles, Vesicle fusion, Fission and intracellular trafficking, Drug delivery systems and nanomedicines, Transcytosis and endocytosis of drugs carriers, Disease effects on vesicular trafficking, Drug effects on vesicular trafficking, Role of the biological environment

Movement of skeletal-muscle fibers is generated by the coordinated action of several cells taking part within the locomotion circuit (motoneurons, sensory-neurons, Schwann cells, astrocytes, microglia, and muscle-cells). Failures in any part of this circuit could impede or hinder coordinated muscle movement and cause a neuromuscular disease (NMD) or determine its severity. Studying fragments of the circuit cannot provide a comprehensive and complete view of the pathological process. We trace the historic developments of studies focused on in-vitro modeling of the spinal-locomotion circuit and how bioengineered innovative technologies show advantages for an accurate mimicking of physiological conditions of spinal-locomotion circuit. New developments on compartmentalized microfluidic culture systems (cμFCS), the use of human induced pluripotent stem cells (hiPSCs) and 3D cell-cultures are analyzed. We finally address limitations of current study models and three main challenges on neuromuscular studies: (i) mimic the whole spinal-locomotion circuit including all cell-types involved and the evaluation of independent and interdependent roles of each one; (ii) mimic the neurodegenerative response of mature neurons in-vitro as it occurs in-vivo; and (iii) develop, tune, implement, and combine cμFCS, hiPSC, and 3D-culture technologies to ultimately create patient-specific complete, translational, and reliable NMD in-vitro model. Overcoming these challenges would significantly facilitate understanding the events taking place in NMDs and accelerate the process of finding new therapies.

JTD Keywords: 3D-culture, Compartmentalized microfluidic culture systems (cμFCS), HiPSC, In-vitro models, Neuromuscular circuit

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

JTD Keywords: Autobiographical Memory., Biology, Cognition, Cognitive Robotics, Computer architecture, Distributed Adaptive Control, Grounding, Human-Robot Interaction, Humanoid robots, Robot sensing systems, Symbol Grounding

Kidney morphogenesis and patterning have been extensively studied in animal models such as the mouse and zebrafish. These seminal studies have been key to define the molecular mechanisms underlying this complex multistep process. Based on this knowledge, the last 3 years have witnessed the development of a cohort of protocols allowing efficient differentiation of human pluripotent stem cells (hPSCs) towards defined kidney progenitor populations using two-dimensional (2D) culture systems or through generating organoids. Kidney organoids are three-dimensional (3D) kidney-like tissues, which are able to partially recapitulate kidney structure and function in vitro. The current possibility to combine state-of-the art tissue engineering with clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated systems 9 (Cas9)-mediated genome engineering provides an unprecedented opportunity for studying kidney disease with hPSCs. Recently, hPSCs with genetic mutations introduced through CRISPR/Cas9-mediated genome engineering have shown to produce kidney organoids able to recapitulate phenotypes of polycystic kidney disease and glomerulopathies. This mini review provides an overview of the most recent advances in differentiation of hPSCs into kidney lineages, and the latest implementation of the CRISPR/Cas9 technology in the organoid setting, as promising platforms to study human kidney development and disease.

JTD Keywords: Clustered regularly interspaced short palindromic repeats/CRISPR-associated systems 9, Disease modeling, Gene editing, Human pluripotent stem cells, Kidney genetics, Tissue engineering

This book constitutes the proceedings of the 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, held in Paris, France, in July 2018. The 40 full and 18 short papers presented in this volume were carefully reviewed and selected from 60 submissions. The theme of the conference targeted at the intersection of research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial neural network, Bio-actuators, Bio-robotics, Biohybrid systems, Biomimetics, Bipedal robots, Earthoworm-like robots, Robotics, Decision-making, Tactile sensing, Soft robots, Locomotion, Insects, Sensors, Actuators, Robots, Artificial intelligence, Neural networks, Motion planning, Learning algorithms

Biomimetics is the development of novel technologies through the distillation of ideas from the study of biological systems. Biohybrids are formed through the combination of at least one biological component—an existing living system—and at least one artificial, newly engineered component. These two fields are united under the theme of Living Machines—the idea that we can construct artifacts that not only mimic life but also build on the same fundamental principles. The research described in this volume seeks to understand and emulate life’s ability to self-organize, metabolize, grow, and reproduce; to match the functions of living tissues and organs such as muscles, skin, eyes, ears, and neural circuits; to replicate cognitive and physical capacities such as perception, attention, locomotion, grasp, emotion, and consciousness; and to assemble all of these elements into integrated systems that can hold a technological mirror to life or that have the capacity to merge with it. We conclude with contributions from philosophers, ethicists, and futurists on the potential impacts of this remarkable research on society and on how we see ourselves.

JTD Keywords: Novel technologies, Biomimetics, Biohybrids, Living systems, Living machines, Biological principles, Technology ethics, Societal impacts

Conventional fire alarms are based on smoke detection. Nevertheless, in some fire scenarios volatiles are released before smoke. Fire detectors based only on chemical sensors have already been proposed as they may provide faster response, but they are still prone to false alarms in the presence of nuisances. These systems rely heavily on pattern recognition techniques to discriminate fires from nuisances. In this context, it is important to test the systems according to international standards for fires and testing the system against a diversity of nuisances. In this work, we investigate the behavior of a gas sensor array coupled to sensor fusion algorithms for fire detection when exposed to standardized fires and several nuisances. Results confirmed the ability to detect fires (97% Sensitivity), although the system still produces a significant rate of false alarms (35%) for nuisances not presented in the training set.

JTD Keywords: Fire alarm, Gas sensor array, Machine Olfaction, Multisensor system, Sensor fusion

In this work, the cardiorespiratory pattern of patients undergoing extubation process is studied. First, the respiratory and cardiac signals were resampled, next the Symbolic Dynamics (SD) technique was implemented, followed of a dimensionality reduction applying Forward Selection (FS) and Moving Window with Variance Analysis (MWVA) methods. Finally, the Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM) classifiers were used. The study analyzed 153 patients undergoing weaning process, classified into 3 groups: Successful Group (SG: 94 patients), Failed Group (FG: 39 patients), and patients who had been successful during the extubation and had to be reintubated before 48 hours, Reintubated Group (RG: 21 patients). According to the results, the best classification present an accuracy higher than 88.98 ± 0.013% in all proposed combinations.

JTD Keywords: Support vector machines, Standards, Time series analysis, Resonant frequency, Nonlinear dynamical systems, Ventilation

The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.

JTD Keywords: Computer architecture, Estimation, Force, Microprocessors, Robot sensing systems, Surgery

In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.

JTD Keywords: Histograms, Joints, Robot sensing systems, Thumb, Tracking, Human activity recognition, Disable and elderly assistance

This paper addresses the issue of lack of force feedback in robotic-assisted minimally invasive surgeries. Force is an important measure for surgeons in order to prevent intra-operative complications and tissue damage. Thus, an innovative neuro-vision based force estimation approach is proposed. Tissue surface displacement is first measured via minimization of an energy functional. A neuro approach is then used to establish a geometric-visual relation and estimate the applied force. The proposed approach eliminates the need of add-on sensors, carrying out biocompatibility studies and is applicable to tissues of any shape. Moreover, we provided an improvement from 15.14% to 56.16% over other approaches which demonstrate the potential of our proposal.

JTD Keywords: Estimation, Force, Minimally invasive surgery, Robot sensing systems, Three-dimensional displays

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources.

JTD Keywords: Environmental monitoring, Gas discrimination, Gas distribution mapping, Service robots, Open sampling systems, PID, Metal oxide sensors

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

JTD Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems

Some of the most common clinical problems in elderly patients are related to diseases of the cardiac and respiratory systems. Elderly patients often have altered breathing patterns, such as periodic breathing (PB) and Cheyne-Stokes respiration (CSR), which may coincide with chronic heart failure. In this study, we used the envelope of the respiratory flow signal to characterize respiratory patterns in elderly patients. To study different breathing patterns in the same patient, the signals were segmented into windows of 5 min. In oscillatory breathing patterns, frequency and time-frequency parameters that characterize the discriminant band were evaluated to identify periodic and non-periodic breathing (PB and nPB). In order to evaluate the accuracy of this characterization, we used a feature selection process, followed by linear discriminant analysis. 22 elderly patients (7 patients with PB and 15 with nPB pattern) were studied. The following classification problems were analyzed: patients with either PB (with and without apnea) or nPB patterns, and patients with CSR versus PB, CSR versus nPB and PB versus nPB patterns. The results showed 81.8% accuracy in the comparisons of nPB and PB patients, using the power of the modulation peak. For the segmented signal, the power of the modulation peak, the frequency variability and the interquartile ranges provided the best results with 84.8% accuracy, for classifying nPB and PB patients.

JTD Keywords: cardiovascular system, diseases, feature extraction, geriatrics, medical signal processing, oscillations, pneumodynamics, signal classification, time-frequency analysis, Cheyne-Stokes respiration, apnea, cardiac systems, chronic heart failure, classification problems, discriminant band, diseases, elderly patients, feature selection process, frequency variability, interquartile ranges, linear discriminant analysis, nonperiodic breathing, oscillatory breathing pattern, periodic breathing, respiratory How signal, respiratory systems, signal segmentation, time 5 min, time-frequency parameters, Accuracy, Aging, Frequency modulation, Heart, Senior citizens, Time-frequency analysis

Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor. This sensor provides integral concentration measurements over the path of the laser beam. Existing gas distribution mapping algorithms can only handle local measurements obtained from traditional in-situ chemical sensors. In this paper we also describe an algorithm to generate 3D methane concentration maps from integral concentration and depth measurements. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.

JTD Keywords: Laser beams, Measurement by laser beam, Mobile robots, Robot kinematics, Robot sensing systems

Background: Sepsis is one of the main causes of death in adult intensive care units. The major drawbacks of the different methods used for its diagnosis and monitoring are their inability to provide fast responses and unsuitability for bedside use. In this study, performed using a rat sepsis model, we evaluate breath analysis with Ion Mobility Spectrometry (IMS) as a fast, portable and non-invasive strategy. Methods: This study was carried out on 20 Sprague-Dawley rats. Ten rats were injected with lipopolysaccharide from Escherichia coli and ten rats were IP injected with regular saline. After a 24-h period, the rats were anaesthetized and their exhaled breaths were collected and measured with IMS and SPME-gas chromatography/mass spectrometry (SPME-GC/MS) and the data were analyzed with multivariate data processing techniques. Results: The SPME-GC/MS dataset processing showed 92% accuracy in the discrimination between the two groups, with a confidence interval of between 90.9% and 92.9%. Percentages for sensitivity and specificity were 98% (97.5–98.5%) and 85% (84.6–87.6%), respectively. The IMS database processing generated an accuracy of 99.8% (99.7–99.9%), a specificity of 99.6% (99.5–99.7%) and a sensitivity of 99.9% (99.8–100%). Conclusions: IMS involving fast analysis times, minimum sample handling and portable instrumentation can be an alternative for continuous bedside monitoring. IMS spectra require data processing with proper statistical models for the technique to be used as an alternative to other methods. These animal model results suggest that exhaled breath can be used as a point-of-care tool for the diagnosis and monitoring of sepsis.

JTD Keywords: Sepsis, Volatile organic compounds, Ion mobility spectrometer, Rat model, Bedside patient systems, Non-invasive detection

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.

JTD Keywords: Chemical sensors, Electronic nose, Intelligent sensors, Measurement techniques, Sensor arrays, Sensor systems

In this paper, we present a new Multi-Agent System for reduction of the bullwhip effect in fuzzy supply chains. First, we show that a supply chain that uses an optimal ordering policy without data sharing among echelons still suffers from the bullwhip effect. Then, we propose the multi-agent solution to manage and reduce the bullwhip effect. The proposed multi-agent system includes four different types of agents in which each agent has its own list of actions. The proposed Multi-agent System applies a new Tabu Search algorithm for fuzzy rule generation, and a new data filtering algorithm for extraction of the bullwhip-free data from supply chain data warehouse. We validate the multi-agent system under different conditions and discuss how the system responds to different factors. The results show that the proposed multi-agent system reduces the bullwhip effect significantly in a rational time.

JTD Keywords: Bullwhip effect, Bullwhip-free data, Decentralized decision making, Fuzzy rule base, Fuzzy supply chain, Fuzzy time series, Multi-agent system, Supply chain management

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

JTD Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

The design of mechanical joints that kinematically behave as their biological counterparts is a challenge that if not addressed properly can cause inadequate forces transmission between robot and patient. This paper studies the interaction forces in rehabilitation therapies of the elbow joint. To measure the effect of orthosis-patient misalignments, a force sensor with a novel distributed architecture has been designed and used for this study. A test-bed based on an industrial robot acting as a virtual exoskeleton that emulates the action of a therapist has been developed and the interaction forces analyzed.

JTD Keywords: Force, Force measurement, Force sensors, Joints, Medical treatment, Robot sensing systems, Force sensors, Medical robotics, Patient rehabilitation, Biological counterparts, Distributed architecture, Elbow joint, Force sensor, Inadequate forces transmission, Industrial robot, Mechanical joints design, Orthosis-patient misalignments, Patient-orthosis interaction forces, Rehabilitation therapies, Robot, Test-bed, Virtual exoskeleton

Electrokinetic techniques are contact-free methods currently used in many applications, where precise handling of biological entities, such as cells, bacteria or nucleic acids, is needed. These techniques are based on the effect of electric fields on molecules suspended in a fluid, and the corresponding induced motion, which can be tuned according to some known physical laws and observed behaviours. Increasing interest on the application of such strategies in order to improve the detection of DNA strands has appeared during the recent decades. Classical electrode-based DNA electrochemical biosensors with combined electrokinetic techniques present the advantage of being able to improve the working electrode's bioactive part during their fabrication and also the hybridization yield during the sensor detection phase. This can be achieved by selectively manipulating, driving and directing the molecules towards the electrodes increasing the speed and yield of the floating DNA strands attached to them. On the other hand, this technique can be also used in order to make biosensors reusable, or reconfigurable, by simply inverting its working principle and pulling DNA strands away from the electrodes. Finally, the combination of these techniques with nanostructures, such as nanopores or nanochannels, has recently boosted the appearance of new types of electrochemical sensors that exploit the time-varying position of DNA strands in order to continuously scan these molecules and to detect their properties. This review gives an insight into the main forces involved in DNA electrokinetics and discusses the state of the art and uses of these techniques in recent years.

JTD Keywords: Electrochemical DNA biosensors, Lab-on-a-chip (LOC), Micro-total analysis systems (mu TAS), Nanopore

Sleep science and respiratory engineering as medical subspecialties and research areas grew up side-by-side with biomedical engineering. The formation of EMBS in the 1950's and the discovery of REM sleep in the 1950's led to parallel development and interaction of sleep and biomedical engineering in diagnostics and therapeutics.

JTD Keywords: Practical/ biomedical equipment, Biomedical measurement, Patient diagnosis, Patient monitoring, Patient treatment, Pneumodynamics, Sleep/ sleep engineering, Respiratory engineering, Automatic sleep analysis, Automatic sleep interpretation systems, Breathing, Biomedical, Engineering, Diagnostics, Therapeutics, REM sleep, Portable, Measurement, Ambulatory measurement, Monitoring

The design of orthotic devices that tries to fit to the anthropomorphic structure of human limbs faces the problem of achieving the highest approximation to the anatomical kinematics. This paper studies the main characteristics and performances of orthotic devices, mainly focusing on the upper limbs, and proposes a solution to the problem of the superposition of rotation and displacement of some joints, as the shoulder, elbow or knee. A 3 DoF virtual joint is proposed to emulate a human joint, solving the isocentricity and size adaptation of most current orthosis.

JTD Keywords: Prosthetics and other practical applications, Prosthetics and orthotics, Prosthetic and orthotic control systems, Robotics, Biomechanics (mechanical engineering), Robot and manipulator mechanics

We present the experimental demonstration of low-frequency dielectric constant imaging of single-layer supported biomembranes at the nanoscale. The dielectric constant image has been quantitatively reconstructed by combining the thickness and local capacitance obtained using a scanning force microscope equipped with a sub-attofarad low-frequency capacitance detector. This work opens new possibilities for studying bioelectric phenomena and the dielectric properties of biological membranes at the nanoscale.

JTD Keywords: Atomic-force microscopy, Nnear-field microscopy, Purple membrane, Scanning capacitance, Biological-systems, Fluid, Spectroscopy, Resolution, Proteins, Dynamics

Analytical devices able to perform accurate and fast automatic DNA detection or sequencing procedures have many potential benefits in the biomedical and environmental fields. The conversion of biological or biochemical responses into quantifiable optical, mechanical or electronic signals is achieved by means of biosensors. Most of these transducing elements can be miniaturized and incorporated into lab-on-a-chip devices, also known as Micro Total Analysis Systems. The use of multiple DNA biosensors integrated in these miniaturized laboratories, which perform several analytical operations at the microscale, has many cost and efficiency advantages. Tiny amounts of reagents and samples are needed and highly sensitive, fast and parallel assays can be done at low cost. A particular type of DNA biosensors are the ones used based on electrochemical principles. These sensors offer several advantages over the popular fluorescence-based detection schemes. The resulting signal is electrical and can be processed by conventional electronics in a very cheap and fast manner. Furthermore, the integration and miniaturization of electrochemical transducers in a microsystem makes easier its fabrication in front of the most common currently used detection method. In this review, different electrochemical DNA biosensors integrated in analytical microfluidic devices are discussed and some early stage commercial products based on this strategy are presented.

JTD Keywords: DNA, Electrochemical DNA biosensors, Electrochemistry, Lab-on-a-chip, Micro Total Analysis systems, Field-effect transistors, Sequence-specific detection, Chemical-analysis systems, Solid-state nanopores, Carbon nanotubes, Microfluidic device, Electrical detection, Hybridization, Molecules, Sensor

Continuous advances on diagnostic techniques based on medical images, as well as the incorporation of new techniques in surgical instruments are progressively changing the new surgical procedures. Also, new minimally invasive techniques, which are currently highly consolidated, have produced significant advances, both from the technological and from the surgical treatment perspectives. The limitations that the manual realization of surgical interventions implies, in what refers to precision and accessibility, can be tackled with the help of robotics. In the same way, sensor based robot control techniques are opening new possibilities for the introduction of more improvements in these procedures, either relying on teleoperation, in which the surgeon and the robot establish their best synergy to get the optimal results, or by means of the automation of some specific actions or tasks. In this article the effect of robotics in the evolution of surgical techniques is described. Starting with a review of the robotics application fields, the article continues analyzing the methods and technologies involved in the process of robotizing surgical procedures, as well as the surgeon-robot interaction systems.

JTD Keywords: Robotics, Medical Applications, Teleoperation, Biomedical Systems, Computer Aided Surgery, Human-Machine Interaction

This paper presents a strategy for a cooperative multirobot system, constituting a virtual robot. The virtual robot is composed of a set of robotic arms acting as only one, transferring the execution of a teleoperated task from one to another when necessary. To decide which of the robots is the most suitable to execute the task at every instant, a multiparametric decision function has been defined. This function is based on a set of intrinsic and extrinsic evaluation indexes of the robot. Since the internal operation of the virtual robot must be transparent to the user, a control architecture has been developed.

JTD Keywords: Control engineering computing, Manipulators, Multi-robot systems, Optimsation, Telerobotics, Virtual reality

Novel medical and biological applications are driving increased interest in the fabrication of micropipette or micro-dispensers. Reduced volume samples and drug dosages are prime motivators in this effort. We have combined microfabrication technology with ion beam milling techniques to successfully produce cantilever-type polysilicon micro-dispensers with 3D enclosed microchannels. The microfabrication technology described here allows for the designing of nozzles with multiple shapes. The contribution of ion beam milling has had a large impact on the fabrication process and on further customizing shapes of nozzles and inlet ports. Functionalization tests were conducted to prove the viability of ion beam-fabricated micro-dispensers. Self-assembled monolayers were successfully formed when a gold surface was patterned with a thiol solution dispensed by the fabricated micro-dispensers.

JTD Keywords: Dip-pen nanolithography, Silicon, Deposition, Microneedles, Delivery, Arrays, Polysilicon, Capillary, Systems, Gene