Publications

Amyloid fibrils, which are aggregates of misfolded proteins characterized by 13-sheet-rich structures, are implicated in several neurodegenerative and systemic pathologies, including Alzheimer's and Parkinson's diseases and type II diabetes mellitus. Traditional amyloid markers, such as Congo Red and Thioflavin T, are widely used for amyloid detection but present limitations, particularly in cellular assays, due to spectral interference and aggregation inhibition. This study investigates YAT2150, a novel fluorescent dye with enhanced amyloid-binding specificity and sensitivity, as a potential alternative to conventional dyes. We evaluated YAT2150's efficacy for detecting amyloid aggregates in both in vitro and in cellula assays. First, we compared its fluorescence intensity and binding specificity to that of Thioflavin Tin amyloid fibril assays, demonstrating that YAT2150 exhibits high affinity and selectivity for amyloid structures, with minimal interference from non-aggregated proteins. Furthermore, we explored YAT2150's utility in Escherichia colt as a model system for studying protein aggregation and amyloid formation in a procaryotic cellular context. Our findings indicate that YAT2150 effectively labels amyloid-like inclusion bodies in E. colt producing a robust fluorescence signal with low background noise. These results suggest that YAT2150 is a promising new tool for amyloid research, offering greater sensitivity compared to traditional dyes, even in complex cellular environments.

JTD Keywords: Aggregation, Amyloid, Amyloid inhibitor, Bacterial inclusion-bodies, Detect, In-vitro, Inclusion bodies, Kinetics, Model, Parameters, Prion, Screening, Silico, Yat2150

The transition from insulator to electro-responsive has been successfully achieved by earlier studies for some inorganic materials by applying external stimuli that modify their 3D and/or electronic structures. In the case of insulating polymers, this transition is frequently accomplished by mixing them with other electroactive materials, even though a few physical treatments that induce suitable chemical modifications have also been reported. In this work, a smart approach based on the application of an electro-thermal reorientation process followed by a charged gas activation treatment has been developed for transforming insulating 3D printed polymers into electro-responsive materials. First, the developed procedure has been exhaustively investigated for 3D printed poly(lactic acid) (PLA) and subsequently has been extended to 3D printed polypropylene (PP) and poly(ethylene terephthalate glycol) (PETG) specimens. FTIR and Raman spectroscopies, X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, and water contact angle measurements confirmed that, while the electro-thermal reorientation mainly promotes the crystallinity of the samples, the charged gas activation oxidizes the C-O bonds at the surface and consequently modifies the surface morphology and wettability. Furthermore, cyclic voltammetry assays demonstrated that treated PLA, PP, and PETG are electro-responsive, even though the electrochemical activity was much higher for oxygen-containing polymers (PLA and PETG) than for the oxygen-free one (PP). Finally, as a proof of concept, treated 3D printed PLA specimens have been used as electrochemical sensors to detect dopamine (DA), an important neurotransmitter, in a concentration interval ranging from 50 to 1000 mu M. The peak associated with the oxidation from DA to dopaminoquinone and the linearity of the calibration plot, which was constructed using the anodic peak current, proved that treated PLA is not only electro-responsive but also able to electrocatalyze the oxidation of DA.

JTD Keywords: 3d printin, Blends, Dopamine, Electrochemical detection, Electrochemical sensors, Electroresponsive polymers, Films, Hydrogels, Pl, Plasma treatment, Release, Thermoelectric treatment, Thermoplastic polymers

There are many examples in nature in which the ability to detect is combined with decision-making, such as the basic survival instinct of plants and animals to search for food. We can technically translate this innate function via the use of robotics with integrated sensors and artificial intelligence. However, the integration of sensing capabilities into robotics has traditionally been neglected due to the significant associated technical challenges. Inspired by plant-root chemotropism, we present a miniaturized electrochemical array integrated into a robotic tip, embedding a customized micro-potentiometer. The system contains solid-state sensors fitted to the tip of the robotic root to three-dimensionally monitor potassium and pH changes in a moist, soil-like environment, providing an integrated electronic readout. The sensors measure a range of parameters compatible with realistic soil conditions. The sensors' response can trigger the movement of the robotic root with a control algorithm inspired by the behavior of the plant root that determines the optimal path toward root growth, simulating the decision-making process of a plant. This nature-inspired technology may lead, in the future, to the realization of robotic devices with the potential for monitoring and exploring the soil autonomously.

JTD Keywords: Artificial intelligenc, Biomimetic, Chemical sensor, Ion-selective electrode (ise), Nitrate, Ph, Plant roots, Potassiu, Potassium, Robotics, Soil detection, Tropism

This study investigates the potential of thermoresponsive hydrogels as innovative substrates for future in vitro diagnostic (IVD) applications using AVAC technology, developed and patented by the Mecwins biomedical company. In order to convert the hydrogel in a substrate compatible with AVAC technology, the following prerequisites were established: (1) the hydrogel layer needs to be permeable to gold nanoparticles (AuNPs), and (2) the optical properties of the hydrogel should not interfere with the detection of AuNPs with AVAC technology. These two key aspects are evaluated in this work. A silicon substrate (Sil) was coated with a layer of a thermosensitive hydrogel (TSH) based on poly(N-isopropylacrylamide-co-N,N '-methylene bis(acrylamide) (PNIPAAm-co-MBA). The TSH offers the advantage of easy modulation of its porosity through cross-linker adjustments, crucial for the plasmonic nanoparticle (NP) permeation. The platforms, denominated as (Sil)-g-(PNIPAAm-co-MBA), were fabricated by changing the cross-linker concentrations and exploring three deposition methods: drop casting (DC), spin coating (SC), and 3D printing (3D); the DC approach resulted in a very homogeneous and thin hydrogel layer, very suitable for the final application. Furthermore, after physical-chemical characterization, the TSH demonstrated its functionality in regulating nanoparticle absorption, and AVAC technology's capability to precisely identify such NPs through the hydrogel matrix was validated. The proposed hydrogel platform fulfills the initial requirements, opening the possibility for employing these hydrogels as dynamic substrates in sandwich immunoassay devices. The next step in the development of the hydrogel substrate would be its functionalization with biorecognition groups to allow for biomarker detection. By leveraging their enhanced capture efficiency and the ability to manipulate particle flow thermally, we anticipate a significant advancement in diagnostic methodologies, combining the spatial benefits of three-dimensional hydrogel structures with the precision of AVAC's digital detection.

JTD Keywords: Biomarker classification, Dark-field microscop, Gold nanoparticles, Nanoparticlepermeation, Plasmonic detection, Thermoresponsivehydrogel

The challenge of delivering therapeutics to the central nervous system due to the restrictive nature of the blood-brain barrier (BBB) is a substantial hurdle in neuropharmacology. Our research introduces a breakthrough approach using microtubule-dependent transcytosis facilitated by novel aqueous compounds. We synthesized a series of red-emitting pyran nitrile derivatives. The molecular structure of compounds, photophysical properties, and water solubility were characterized. BBB permeability of BN1 was assessed in an in vitro BBB model. The transmembrane transport mechanism was next analyzed. The derivative was injected in the wild-type mouse for evaluation of brain penetration and biodistribution in the brain. We further investigated the potential of BN1-functionalized BBB-nonpenetrated silica nanoparticles for brain targeting. This compound demonstrated an ability to form endosomes within the phospholipid layer, thus enabling efficient penetration of the BBB via microtubule-mediated transcytosis, as evidenced in vitro model. This was further confirmed by in vivo experiments that BN1 displays the excellent BBB penetration and retained in brain parenchyma. Furthermore, BBB-impermeable mesoporous silica nanoparticle codelivery system markedly enhanced the transport efficiency to the brain in vivo by BN1-functionalized. These findings indicate that our designed aqueous molecules not only are capable of traversing the BBB but also serve as a viable new strategy for central-nervous-system-targeted drug delivery.

JTD Keywords: Blood-brain-barrier, Desig, In-vivo detection, Mesoporous silica, Probes, Silica nanoparticles

The development of smart biomedical devices as efficient tools in early diagnosis and therapy monitoring has recently witnessed unprecedented growth, becoming an emerging field in biomedical engineering. Sponges for endoluminal vacuum therapy, which are intended for transmitting negative pressure as trigger for tissue regeneration and for draining infections in anastomotic leakages, are massively used implants with very complex geometry and high risk of infection. In this work, commercial polyurethane (PU) sponges have been converted into smart biomedical devices by incorporating an electrochemical sensor to monitor the growth of bacteria. Such innovative approach, which allows to track the tissue healing process avoiding further infection development, has been performed applying a three-step process: 1) activation of PU using low pressure oxygen plasma; 2) incorporation of conducting polymer (CP) nanoparticles (NPs) at the surface of the activated PU by chemical oxidative polymerization; and 3) formation of a homogeneous electroactive coating using the CP NPs obtained in 2), as growth nuclei in an electrochemical polymerization. The functionalized PU sponge is able to monitor the bacteria growth in the surrounding media by detecting the concentration of nicotinamide adenine dinucleotide (NADH) from respiration reactions in the cytosol (i.e. bacteria do not have mitochondria). Conversely, respiration in normal eukaryotic cells takes place in the mitochondria, whose double membrane is not permeable to NADH. The sensing performance of the CP-coated PU sponges (limit of detection: 0.06 mM; sensitivity: 1.21 mA/cm2) has been determined in the lab using NADH solutions, while a proof of concept have been conducted using Escherichia coli bacteria cultures.

JTD Keywords: Conducting polymer, Desig, Electrochemical coating, Esophageal cancer, Nadh, Pedot, Polyurethane functionalization, Selective detection, Sponge functionalizatio

Surgical sutures are long-established medical devices that play an important role closing and healing damaged tissues and organs postoperatively. However, current commercial sutures are not able to detect infections at the wound site, which are quite frequent after surgery. In this work, we present mechanically stable smart sutures for the real-time monitoring of bacterial growth and biofilm formation. For this purpose, a conducting polymer named poly(3,4-ethylenedioxythiophene) (PEDOT), which is able to detect bacteria metabolites, was implemented as a coating onto commercial biostable sutures. A protecting hydrogel layer with adhesive properties, which was made of polydopamine-polyacrylamide (PDA-PAM), was used to prevent the detachment of the sensing coating of PEDOT upon looping and knotting the suture. The protective hydrogel preserved not only the knot mechanical properties of the suture but also the electrochemical response of the PEDOT-coating and, therefore, its ability to detect NADH from bacteria respiration. Ex-vivo assays using sutured swine intestine samples demonstrated that the suture with the PDA-PAM hydrogel layer detects the growth of bacteria in real tissues. As a proof of concept, sutures coated with PEDOT and protected with PDA-PAM were used to inhibit the local growth of bacteria in sutured intestines by applying controlled electrostimuli. Results evidenced that smart electro-responsive sutures can be used as multi-task devices focused on fighting bacterial infections, meaning not only monitoring but also hampering bacteria growth.

JTD Keywords: 4-ethylenedioxythiophene), Bacteria growth detection, Bacteria growth inhibition, Multi-task biomedical devices, Nanoparticles, Pape, Poly(3, Polydopamine-polyacrylamide, Sensor, Smart suture

Polymeric membranes exhibit unique and modulate transport properties when they are properly functionalised, which make them ideal for ions transport, molecules separation and molecules interactions. The present work proposes the design and fabrication of nanostructured membranes, composed by biodegradable poly(lactic acid) (PLA) and poly(ethylene glycol) (PEG), incorporating a lipophilic molecule (cholesterol) covalently bonded, were especially designed to provide even more application opportunities in sensors field. Electrochemical studies, by means of electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and square wave voltammetry (SWV), revealed important differences regarding the functionalised and non-functionalised PLA systems. PEGcholesterol building block units showed a clear affinity with ascorbic acid (vitamin C) and Trolox (R) (a watersoluble analogue of vitamin E), both hydrophilic in nature, with a limit of detection capacity of 8.12 mu M for AA and 3.53 mu M for AA and Trolox, respectively, in aqueous salt solution. The bioinspired polymer may be used to incorporate antioxidant property that allow the design of anti-stress biosensors, electrodes for the detection of vitamin C or vitamin E in biomedical nutrition programs, among other applications.

JTD Keywords: Antioxidant molecules, Antioxidants, Application programs, Ascorbic acid, Biomimetics, C (programming language), Capacity, Chemical detection, Cholesterol, Cyclic voltammetry, Electrochemical detection, Electrochemical impedance spectroscopy, Functional polymers, Functionalized, Lactic acid, Molecules, Nanomembranes, Poly ethylene glycols, Poly lactic acid, Poly(ethylene glycol), Poly(ethyleneglycol), Poly(lactic acid), Polyethylene glycols, Vitamin-e

Antibodies are highly selective and sensitive, making them the gold standard for recognition affinity tools. However, their production cost is high and their downstream processing is time-consuming. Molecularly imprinted polymers (MIPs) are tailor-made by incorporating specific molecular recognition sites in their structure, thus translating into receptor-like activity mode of action. The interest in molecular imprinting technology, applied to biomacromolecules, has increased in the past decade. MIPs, produced using biomolecules as templates, commonly referred to as "plastic antibodies" or "artificial receptors", have been considered as suitable cheaper and easy to produce alternatives to antibodies. Research on MIPs, designed to recognize proteins or peptides is particularly important, with potential contributions towards biomedical applications, namely biosensors and targeted drug delivery systems. This mini review will cover recent advances on (bio)molecular imprinting technology, where proteins or peptides are targeted or mimicked for sensing and therapeutic applications. Polymerization methods are reviewed elsewhere, being out of the scope of this review. Template selection and immobilization approaches, monomers and applications will be discussed, highlighting possible drawbacks and gaps in research.Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

JTD Keywords: artificial antibodies, assay, biomimetics, biomolecules, biosensors, delivery, diagnostics, drug delivery, electrochemical detection, nanoparticles, receptors, science-and-technology, selective recognition, selective targeting, separation, templates, Artificial antibodies, Biomimetics, Biomolecules, Biosensors, Diagnostics, Drug delivery, Molecularly imprinted polymers, Nanoparticles, Selective targeting, Solid-phase synthesis

JTD Keywords: Acquisition, C-13, Detecting tumor response, Exchang, Excitation pulses, Magnetic-resonance-spectroscopy, Metabolism, Mri, Resolution, Strategies

Virtually, all implantable medical devices are susceptible to infection. As the main healthcare issue concerning implantable devices is the elevated risk of infection, different strategies based on the coating or functionalization of biomedical devices with antiseptic agents or antibiotics are proposed. In this work, an alternative approach is presented, which consists of the functionalization of implantable medical devices with sensors capable of detecting infection at very early stages through continuous monitoring of the bacteria metabolism. This approach, which is implemented in surgical sutures as a representative case of implantable devices susceptible to bacteria colonization, is expected to minimize the risk of worsening the patient's clinical condition. More specifically, non-absorbable polypropylene/polyethylene (PP/PE) surgical sutures are functionalized with conducting polymers using a combination of low-pressure oxygen plasma, chemical oxidative polymerization, and anodic polymerization, to detect metabolites coming from bacteria respiration. Functionalized suture yarns are used for real-time monitoring of bacteria growth, demonstrating the potential of this strategy to fight against infections.© 2023 Wiley-VCH GmbH.

JTD Keywords: adhesion, biofilm, conducting polymers, contamination, derivatives, detections, functionalized sutures, nadh, poly(3,4-ethylenedioxythiophene), Bacteria growth, Conducting polymers, Detections, Functionalized sutures, Monofilament, Nadh

In addition of a key catecholamine neurotransmitter, dopamine is is the metabolite predominantly produced by specific types of tumors (e.g. paragangliomas and neuroblastomas), which cannot be diagnosed using conven-tional sensitive tests. Within this context, development of flexible electrochemical sensors to monitor dopamine levels in physiological fluids for the early diagnosis and control of diseases related to abnormal levels of such compound, is necessary. In this work, a flexible self-supported membrane, which acts directly as electrode, has been developed to detect dopamine. The membrane consists of three nanoperforated polylactic acid (PLA) layers, which provide flexibility and mechanical integrity, separated by two layers of an electroactive copolymer, which are obtained by electrochemical copolymerization of 3,4-ethylenedioxythiophene and aniline. The sensitivity and detection limit provided by the electroactive copolymer, which is accessible to dopamine molecules through the nanoperforations of the PLA outer layers, is 1.846 mu A/(cm2.mu M) and 1.7 mu M, respectively, in a urea-rich environments that mimics urine. These values allow us to propose the self-standing flexible electrodes devel-oped in this study for the detection of dopamine in patients affected by paragangliomas and neuroblastomas tumors, which typically present dopamine concentrations between 2 and 7 mu M.

JTD Keywords: 4-ethylenedioxythiophene), Conducting polymer, Electrochemical sensor, Electrodes, Hydrogels, Poly(3, Polyaniline, Polylactic acid, Selective detection, Sensors, Supercapacitors

In this study, we propose a model-based tool for the detection of obstructive apnea episodes by using ECG features from a single lead channel. Several sequences of recurrent apnea were provoked in separate 15-min periods in anesthetized rats during an experimental model of obstructive sleep apnea (OSA). Morphology-based ECG markers and the beat-to-beat interval (RR) were assessed in each sequence. These markers were used to train dynamic Bayesian networks (DBN) with different orders and feature combinations to find a good tradeoff between network complexity and apnea-detection performance. By using a filtering approach, the resulting DBNs were used to infer the apnea probability signal for subsequent episodes in the same rat. These signals were then processed using by 15-s epochs to determine whether epochs were classified as apneic or nonapneic. Our results showed that fifth-order models provided suitable RMSE values, since higher order models become significantly more complex and present worse generalization. A global threshold of 0.2 gave the best overall performance for all combinations tested, with Acc = 81.3%, Se = 69.8% and Sp = 81.5%, using only two parameters including the RR and Ds (R-wave downslope) markers. We concluded that multivariate models using DBNs represent a powerful tool for detecting obstructive apnea episodes in short segments, which may also serve to estimate the number of total events in a given time period.

JTD Keywords: chronic respiratory diseases, obstructive sleep apnea, probabilistic models, Obstructive sleep apnea,probabilistic models,respiratory events,chronic respiratory disease, Respiratory events, Sleep-apnea syndrome,automated detection,oxygen-saturation,classification,recordings,signal

Microcantilever-based platforms are presented as versatile lab-on-chip devices for advanced applications spanning from material characterization and environmental monitoring to energy.

JTD Keywords: mechanical-properties, micromechanical cantilever, photothermal spectroscopy, sensitive detection, silicon cantilevers, solid-liquid interface, surface-stress, thin-films, vapor detection, Nanomechanical thermal-analysis

Isotactic polypropylene (i-PP) nonabsorbable surgical meshes are modified by incorporating a conducting polymer (CP) layer to detect the adhesion and growth of bacteria by sensing the oxidation of nicotinamide adenine dinucleotide (NADH), a metabolite produced by the respiration reactions of such microorganisms, to NAD+. A three-step process is used for such incorporation: (1) treat pristine meshes with low-pressure O2 plasma; (2) functionalize the surface with CP nanoparticles; and (3) coat with a homogeneous layer of electropolymerized CP using the nanoparticles introduced in (2) as polymerization nuclei. The modified meshes are stable and easy to handle and also show good electrochemical response. The detection by cyclic voltammetry of NADH within the interval of concentrations reported for bacterial cultures is demonstrated for the two modified meshes. Furthermore, Staphylococcus aureus and both biofilm-positive (B+) and biofilm-negative (B-) Escherichia coli cultures are used to prove real-time monitoring of NADH coming from aerobic respiration reactions. The proposed strategy, which offers a simple and innovative process for incorporating a sensor for the electrochemical detection of bacteria metabolism to currently existing surgical meshes, holds considerable promise for the future development of a new generation of smart biomedical devices to fight against post-operative bacterial infections.

JTD Keywords: adhesion, bacteria metabolism, behavior, biocompatibility, conducting polymer, electrochemical sensor, hernia repair, in-vivo, liquid, nadh detection, plasma treatment, prevention, reinforcement, sensor, smart meshes, Bacteria metabolism, Bacterial infections, Conducting polymer, Electrochemical sensor, Humans, Nad, Nadh detection, Nanoparticles, Oxidation-reduction, Plasma treatment, Polymers, Polypropylene mesh, Smart meshes, Surgical mesh

JTD Keywords: biocompatibility, blends, design, dopamine detection, electrocatalytic oxidation, electrodes, polymers, sensor, Additive manufacturing, Surface

We describe a multi-tasking flexible system that is able to release a wide spectrum antibiotic (levofloxacin, LVX) under electrostimulation and act as a pH sensor for detecting bacterial infections. Combining anodic polymer-ization with plasma polymerization processes we engineered dual pH-and electro-responsive polymeric systems. Particularly, the manufactured devices consisted on a layer of poly(hydroxymethyl-3,4-ethylenedioxythiophene) (PHEDOT) loaded with the LVX antibiotic and coated with a plasma polymer layer of poly(acrylic acid) (PAA). The PHEDOT acted as conductive and electro-responsive agent, while the PAA provided pH responsiveness, changing from a compact globular conformation in acid environments to an expanded open coil conformation in alkaline environments. The assembly between the PHEDOT layer and the PAA coating affected the electro-chemical response of the former, becoming dependent on the pH detected by the latter. The conformational change experienced by the PAA layer as a function of the pH and the redox properties of PHEDOT were leveraged for the electrochemical detection of bacteria growth and for regulating the release of the LVX antibiotic, respectively. The effectiveness of the system as a stimulus-responsive antibiotic carrier and pH sensor was also investigated on strains of Escherichia coli and Streptococcus salivarius.

JTD Keywords: Conducting polymer, Delivery, Drug delivery, Electrostimulation, Levofloxacin, Ph sensor, Plasma, Poly(acrylic acid), Selective detection

When danger is perceived, the human body responds to overcome obstacles and survive a stressful situation; however, sustained levels of stress are associated with health disorders and diminished life quality. Hence, stress biomarkers are monitored to control stress quantitatively. Herein, a porous sensor (4l-COP/p) composed of poly(3,4-ethylenedioxythiophene) (PEDOT) and poly(3,4-ethylenedioxythiophene-co-N-methylpyrrole) (COP), which is prepared in a four-layered fashion to detect dopamine (DA) and serotonin (5-HT), is presented. Specifically, the detection is conducted in phosphate-buffered saline (PBS), as well as artificial urine and sweat, by applying cyclic voltammetry. The limit of detection values obtained are as low as 5.7 x 10(-6) and 1.4 x 10(-6) m for DA and 5-HT, respectively, when assessed individually in artificial urine. When mixed in PBS, 4l-COP/p detects both biomarkers with a resolution of 0.18 V and a sensitivity of 40 and 30 mu A mm(-1) for DA and 5-HT, respectively. Additionally, by theoretical calculations, the interaction pattern that each stress biomarker establishes with the PEDOT outer layer is elucidated. Whereas DA interacts with the pi-system of PEDOT, 5-HT forms specific hydrogen bonds with the conducting polymer chains. The resolution value obtained depends upon such interactions. Overall, 4l-COP/p electrodes display potential as stress sensing devices for healthcare technologies.

JTD Keywords: Artificial body fluids, Boron-doped diamond, Cortisol, Cyclic voltammetry, Dopamine, Multilayered films, Paper, Saliva, Selective detection, Sensor, Sensors, Serotonin, Serum

Electrochemical sensors for real-time detection of several bioanalytes have been prepared by additive manufacturing, shaping non-conductive poly(lactic acid) (PLA) filaments, and applying a physical treatment to create excited species. The latter process, which consists of the application of power discharge of 100 W during 2 min in a chamber at a low pressure of O-2, converts electrochemically inert PLA into an electrochemically responsive material. The electric discharge caused the oxidation of the PLA surface as evidenced by the increment in the quantity of oxygenated species detected by FTIR spectroscopy and X-ray photoelectron spectroscopy (XPS). Indeed, changes in the surface chemical composition became more pronounced with increasing O-2 pressure. After demonstrating the performance of the chemically modified material as individual dopamine and glucose sensors, multiplexed detection has been achieved by measuring simultaneously the two voltammetric signals. This has been performed by collecting the signals in two different regions, a naked chemically modified PLA for dopamine detection and a chemically modified PLA region functionalized with Glucose Oxidase. These outcomes led to define a new paradigm for manufacturing electrodes for electrochemical sensors based on 3D printing without using conducting materials at any stage of the process.

JTD Keywords: Additive manu f a c turing, Carbon, Conductivity, Degradation, Dopamine, Dopamine detection, Glucose detection, Glucose sensors, Immobilization, Multiplexed detect i o n, Oxidase, Plasma treatment

Biosensors represent a powerful analytical tool for analyzing biomolecular interactions with the potential to achieve real-time quantitative analysis with high accuracy using low sample volumes, minimum sample pretreatment with high potential for the development of in situ and highly integrated monitoring platforms. Considering these advantages, their use in cell-culture systems has increased over the last few years. Between the different technologies for cell culture, organs-on-a-chip (OOCs) represent a novel technology that tries to mimic an organ's functionality by combining tissue engineering/organoid with microfluidics. Although there are still challenges to achieving OOC models with high organ mimicking relevance, these devices can offer effective models for drug treatment development by identifying drug targets, screening toxicity, and determining the potential effects of drugs in living beings. Consequently, in the future, we might replace animal studies by offering more ethical test models. Considering the relevance that different physiological and biochemical parameters have in the correct functionality of cells, sensing and biosensing platforms can offer an effective way for the real-time monitoring of physiological parameters and, in our opinion, more relevant, the secretion of biomarkers such as cytokines, growth factors, and others related with the influence of drugs or other types of stimulus in cell metabolism. Keeping this concept in mind, in this chapter, we focus on describing the potential use of sensors and biosensors in OOC devices to achieve fully integrated platforms that monitor physiological parameters and cell metabolism.© 2022. The Author(s), under exclusive license to Springer Nature Switzerland AG.

JTD Keywords: alignment, biosensors, cell, crystal microbalance biosensor, electrochemical biosensors, future, graphene oxide, label-free detection, organ-on-a-chip, oxygen, pre-clinical platforms, real-time analysis, screening, Biosensors, Organ-on-a-chip, Pre-clinical platforms, Screening, Sensors, Surface-plasmon resonance

The influence of the properties of different solid substrates on the tethering of two antibodies, IgG1-CR3022 and IgG1-S309, which were specifically engineered for the detection of SARS-CoV-2, has been examined at the molecular level using conventional and accelerated Molecular Dynamics (cMD and aMD, respectively). Two surfaces with very different properties and widely used in immunosensors for diagnosis, amorphous silica and the most stable facet of the face-centered cubic gold structure, have been considered. The effects of such surfaces on the structure and orientation of the immobilized antibodies have been determined by quantifying the tilt and hinge angles that describe the orientation and shape of the antibody, respectively, and the dihedrals that measure the relative position of the antibody arms with respect to the surface. Results show that the interactions with amorphous silica, which are mainly electrostatic due to the charged nature of the surface, help to preserve the orientation and structure of the antibodies, especially of the IgG1-CR3022, indicating that the primary sequence of those antibodies also plays some role. Instead, short-range van der Waals interactions with the inert gold surface cause a higher degree tilting and fraying of the antibodies with respect to amorphous silica. The interactions between the antibodies and the surface also affect the correlation among the different angles and dihedrals, which increases with their strength. Overall, results explain why amorphous silica substrates are frequently used to immobilize antibodies in immunosensors. © 2022 The Authors

JTD Keywords: amorphous silica, antibody immobilization, enzyme, gol d, gold, immobilization, immunosensor, molecu l a r dynamics, molecular dynamics, protein adsorption, sars-cov-2 immunosensor, simulations, spike protein, surface interactions, target, vaccine, Amorphous silica, Antibodies, Antibody engineering, Antibody immobilization, Antibody structure, Article, Chemical detection, Computer model, Controlled study, Dihedral angle, Gold, In-silico, Molecular dynamics, Molecular levels, Molecular-dynamics, Nonhuman, Property, Sars, Sars-cov-2 immunosensor, Severe acute respiratory syndrome coronavirus 2, Silica, Silico studies, Silicon dioxide, Solid substrates, Structure analysis, Substrate chemistry, Substrates, Van der waals forces, Virus detection

The severe neurological disorder epilepsy affects almost 1% of the world population. For patients who suffer from pharmacoresistant focal-onset epilepsy, electroencephalographic (EEG) recordings are essential for the localization of the brain area where seizures start. Apart from the visual inspection of the recordings, quantitative EEG signal analysis techniques proved to be useful for this purpose. Among other features, regularity versus irregularity and phase coherence versus phase independence allowed characterizing brain dynamics from the measured EEG signals. Can phase irregularities also characterize brain dynamics? To address this question, we use the univariate coefficient of phase velocity variation, defined as the ratio of phase velocity standard deviation and the mean phase velocity. Beyond that, as a bivariate measure we use the classical mean phase coherence to quantify the degree of phase locking. All phase-based measures are combined with surrogates to test null hypotheses about the dynamics underlying the signals. In the first part of our analysis, we use the Rössler model system to study our approach under controlled conditions. In the second part, we use the Bern-Barcelona EEG database which consists of focal and nonfocal signals extracted from seizure-free recordings. Focal signals are recorded from brain areas where the first seizure EEG signal changes can be detected, and nonfocal signals are recorded from areas that are not involved in the seizure at its onset. Our results show that focal signals have less phase variability and more phase coherence than nonfocal signals. Once combined with surrogates, the mean phase velocity proved to have the highest discriminative power between focal and nonfocal signals. In conclusion, conceptually simple and easy to compute phase-based measures can help to detect features induced by epilepsy from EEG signals. This holds not only for the classical mean phase coherence but even more so for univariate measures of phase irregularity. © 2022 American Physical Society.

JTD Keywords: brain, entropy, epileptogenic networks, functional connectivity, hilbert transform, seizure onset, surrogate data, synchronization, time-series, Biomedical signal processing, Brain areas, Brain dynamics, Dynamics, Electroencephalographic signals, Electroencephalography, Electrophysiology, Intracranial eeg signals, Localisation, Neurological disorders, Neurology, Phase based, Phase coherence, Signal detection, Simple++, Univariate, Velocity, World population

Smoldering fires are characterized by the production of early gas emissions that can include high levels of CO and Volatile Organic Compounds (VOCs) due to pyrolysis or thermal degradation. Nowadays, standalone CO sensors, smoke detectors, or a combination of these, are standard components for fire alarm systems. While gas sensor arrays together with pattern recognition techniques are a valuable alternative for early fire detection, in practice they have certain drawbacks-they can detect early gas emissions, but can show low immunity to nuisances, and sensor time drift can render calibration models obsolete. In this work, we explore the performance of a gas sensor array for detecting smoldering and plastic fires while ensuring the rejection of a set of nuisances. We conducted variety of fire and nuisance experiments in a validated standard fire room (240 m(3)). Using PLS-DA and SVM, we evaluate the performance of different multivariate calibration models for this dataset. We show that calibration models remain predictive after several months, but perfect performance is not achieved. For example, 4 months after calibration, a PLS-DA model provides 100% specificity and 85% sensitivity since the system has difficulties in detecting plastic fires, whose signatures are close to nuisance scenarios. Nevertheless, our results show that systems based on gas sensor arrays are able to provide faster fire alarm response than conventional smoke-based fire alarms. We also propose the use of small-scale fire experiments to increase the number of calibration conditions at a reduced cost. Our results show that this is an effective way to increase the performance of the model, even when evaluated on a standard fire room. Finally, the acquired datasets are made publicly available to the community (doi: 10.5281/zenodo.5643074).

JTD Keywords: Calibration, Chemical sensors, Co2, Early fire, Early fire detection, En-54, Fire alarm, Fire detection, Fire room, Fires, Gas detectors, Gas emissions, Gas sensors, Pattern recognition, Public dataset, Sensor arrays, Sensors array, Signatures, Smoke, Smoke detector, Smoke detectors, Standard fire, Standard fire room, Support vector machines, Temperature, Toxicity, Volatile organic compounds

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

The SARS-CoV-2 outbreaks highlighted the need for effective, reliable, fast, easy-to-do and cheap diagnostics procedures. We pragmatically experienced that an early positive-case detection, inevitably coupled with a mass vaccination campaign, is a milestone to control the COVID-19 pandemic. Gold nanoparticles (AuNPs) can indeed play a crucial role in this context, as their physicochemical, optics and electronics properties are being extensively used in photothermal therapy (PTT), radiation therapy (RT), drug delivery and diagnostic. AuNPs can be synthesized by several approaches to obtain different sizes and shapes that can be easily functionalized with many kinds of molecules such as antibodies, proteins, probes, and lipids. In addition, AuNPs showed high biocompatibility making them useful tool in medicine field. We thus reviewed here the most relevant evidence on AuNPs as effective way to detect the presence of SARS-CoV-2 antigens. We trust future diagnostic efforts must take this 'old-fashioned' nanotechnology tool into consideration for the development and commercialization of reliable and feasible detection kits.

JTD Keywords: Aggregation, Antibodies, Assay, Covid-19, Diagnosis, Enhanced raman-scattering, Gold nanoparticles, Immunoassay, Pandemic disease, Physicochemical properties, Rapid detection, Sars-cov-2, Sensors, Surface-plasmon resonance, Therapy

Nowadays, liquid biopsy represents one of the most promising techniques for early diagnosis, monitoring, and therapy screening of cancer. This novel methodology includes, among other techniques, the isolation, capture, and analysis of circulating tumor cells (CTCs). Nonetheless, the identification of CTC from whole blood is challenging due to their extremely low concentration (1-100 per ml of whole blood), and traditional methods result insufficient in terms of purity, recovery, throughput and/or viability of the processed sample. In this context, the development of microfluidic devices for detecting and isolating CTCs offers a wide range of new opportunities due to their excellent properties for cell manipulation and the advantages to integrate and bring different laboratory processes into the microscale improving the sensitivity, portability, reducing cost and time. This chapter explores current and recent microfluidic approaches that have been developed for the analysis and detection of CTCs, which involve cell capture methods based on affinity binding and label-free methods and detection based on electrical, chemical, and optical sensors. All the exposed technologies seek to overcome the limitations of commercial systems for the analysis and isolation of CTCs, as well as to provide extended analysis that will allow the development of novel and more efficient diagnostic tools.

JTD Keywords: Cancer detection, Cancer diagnosis, Cancer-cells, Capture, Chip, Circulating tumor cells, Enrichment, Label-free isolation, Liquid biopsy, Microchannel, Microfluidics, Separation, Ultra-fast

Under intrauterine growth restriction (IUGR), abnormal attainment of the nutrients and oxygen by the fetus restricts the normal evolution of the prenatal causing in many cases high morbidity being one of the top-ten causes of neonatal death. The current gold standards in hospitals to detect this relevant problem is the clinical observation by echography, cardiotocography and Doppler. These qualitative techniques are not conclusive and requires risky invasive fetal scalp blood testing and/or amniocentesis. We developed micro-implantable multiparametric electrochemical sensors for measuring ischemia in real time in fetal tissue and vascular. This implantable technology is designed to continuous monitoring for an early detection of ischemia to avoid potential fetal injury. Two miniaturized electrochemical sensors were developed based on oxygen and pH detection. The sensors were optimized in vitro under controlled concentration, to assess the selectivity and sensitivity required. The sensors were then validated in vivo in the ewe fetus model, by means of their insertion in the muscle leg and inside the iliac artery of the fetus. Ischemia was achieved by gradually obstructing the umbilical cord to regulate the amount of blood reaching the fetus. An important challenge in fetal monitoring is the detection of low levels of oxygen and pH changes under ischemic conditions, requiring high sensitivity sensors. Significant differences were observed in both; pH and pO(2) sensors under changes from normoxia to hypoxia states in the fetus tissue and vascular with both sensors. Herein, we demonstrate the feasibility of the developed sensors for future fetal monitoring in medical applications.

JTD Keywords: electrochemical biosensor, implantable sensor, in vivo validation, ischemia detection, tissue and vascular monitoring, Animal experiment, Animal model, Animal tissue, Article, Blood-gases, Brain, Classification, Controlled study, Diagnosis, Doppler, Early diagnosis, Electrochemical analysis, Electrochemical biosensor, Ewe, Feasibility study, Female, Fetus, Fetus disease, Fetus monitoring, Gestational age, Hypoxemia, Iliac artery, Implantable sensor, In vivo validation, Intrauterine growth restriction, Intrauterine growth retardation, Ischemia detection, Leg muscle, Management, Nonhuman, Oxygen consumption, Ph, Ph and oxygen detection, Ph measurement, Process optimization, Sheep, Tissue and vascular monitoring, Umbilical-cord occlusion

Abstract The development of nanostructured plasmonic biosensors has been widely widespread in the last years, motivated by the potential benefits they can offer in integration, miniaturization, multiplexing opportunities, and enhanced performance label-free biodetection in a wide field of applications. Between them, engineering tissues represent a novel, challenging, and prolific application field for nanostructured plasmonic biosensors considering the previously described benefits and the low levels of secreted biomarkers (?pM–nM) to detect. Here, we present an integrated plasmonic nanocrystals-based biosensor using high throughput nanostructured polycarbonate substrates. Metallic film thickness and incident angle of light for reflectance measurements were optimized to enhance the detection of antibody–antigen biorecognition events using numerical simulations. We achieved an enhancement in biodetection up to 3× as the incident angle of light decreases, which can be related to shorter evanescent decay lengths. We achieved a high reproducibility between channels with a coefficient of variation below 2% in bulk refractive index measurements, demonstrating a high potential for multiplexed sensing. Finally, biosensing potential was demonstrated by the direct and label-free detection of interleukin-6 biomarker in undiluted cell culture media supernatants from bioengineered 3D skeletal muscle tissues stimulated with different concentrations of endotoxins achieving a limit of detection (LOD) of ? 0.03 ng/mL (1.4 pM).

JTD Keywords: assay, crystals, drug, label-free biosensing, molecules, plasmonic nanostructures, sensors, skeletal muscle, tissue engineering, Biodetection, Biomarkers, Biosensors, Cell culture, Cells, Chemical detection, Histology, Interleukin-6, Interleukin6 (il6), Label free, Label-free biosensing, Muscle, Nano-structured, Nanocrystals, Plasmonic nanocrystals, Plasmonic nanostructures, Plasmonics, Polycarbonate substrates, Polycarbonates, Refractive index, Sensitivity, Skeletal muscle, Tissue engineering, Tissues engineerings

In many physiological situations, BAR proteins reshape membranes with pre-existing curvature (templates), contributing to essential cellular processes. However, the mechanism and the biological implications of this reshaping process remain unclear. Here we show, both experimentally and through modelling, that BAR proteins reshape low curvature membrane templates through a mechanochemical phase transition. This phenomenon depends on initial template shape and involves the co-existence and progressive transition between distinct local states in terms of molecular organization (protein arrangement and density) and membrane shape (template size and spherical versus cylindrical curvature). Further, we demonstrate in cells that this phenomenon enables a mechanotransduction mode, in which cellular stretch leads to the mechanical formation of membrane templates, which are then reshaped into tubules by BAR proteins. Our results demonstrate the interplay between membrane mechanics and BAR protein molecular organization, integrating curvature sensing and generation in a comprehensive framework with implications for cell mechanical responses.

JTD Keywords: aggregation, amphiphysin, domains, vesicles, Article, Cell, Cell component, Curvature, Detection method, Geomembrane, Mechanotransduction, Membrane, Molecular analysis, Phase transition, Physiology, Protein, Self organization

The human olfactory system remains one of the most challenging biological systems to replicate. Humans use it without thinking, where it can equally offer protection from harm and bring enjoyment in equal measure. It is the system’s ability to detect and analyze complex odors, without the need for specialized infra-structure, that is the envy of many scientists. The field of artificial olfaction has recruited and stimulated interdisciplinary research and commercial development for several applications that include malodor measurement, medical diagnostics, food and beverage quality, environment and security. Over the last century, innovative engineers and scientists have been focused on solving a range of problems associated with measurement and control of odor. The IEEE Sensors Journal has published Special Issues on olfaction in 2002 and 2012. Here we continue that coverage. In this article, we summarize early work in the 20th Century that served as the foundation upon which we have been building our odor-monitoring instrumental and measurement systems. We then examine the current state of the art that has been achieved over the last two decades as we have transitioned into the 21st Century. Much has been accomplished, but great progress is needed in sensor technology, system design, product manufacture and performance standards. In the final section, we predict levels of performance and ubiquitous applications that will be realized during in the mid to late 21st Century.

JTD Keywords: air-quality, breath analysis, calibration transfer, chemical sensor arrays, chemosensor arrays, drift compensation, electronic nose, gas sensors, headspace sampling, machine learning, machine olfaction, odor detection, plume structure, voc analysis, Artificial olfaction, Electrodes, Electronic nose, Electronic nose technology, Headspace sampling, Instruments, Machine learning, Machine olfaction, Monitoring, Odor detection, Olfactory, Sensor phenomena and characterization, Sensors, Temperature sensors, Voc analysis

© 2020 Wiley-VCH GmbH Conducting polymers have been increasingly used as biologically interfacing electrodes for biomedical applications due to their excellent and fast electrochemical response, reversible doping–dedoping characteristics, high stability, easy processability, and biocompatibility. These advantageous properties can be used for the rapid detection and eradication of infections associated to bacterial growth since these are a tremendous burden for individual patients as well as the global healthcare system. Herein, a smart nanotheranostic electroresponsive platform, which consists of chloramphenicol (CAM)-loaded in poly(3,4-ethylendioxythiophene) nanoparticles (PEDOT/CAM NPs) for concurrent release of the antibiotic and real-time monitoring of bacterial growth is presented. PEDOT/CAM NPs, with an antibiotic loading content of 11.9 ± 1.3% w/w, are proved to inhibit the growth of Escherichia coli and Streptococcus sanguinis due to the antibiotic release by cyclic voltammetry. Furthermore, in situ monitoring of bacterial activity is achieved through the electrochemical detection of β-nicotinamide adenine dinucleotide, a redox active specie produced by the microbial metabolism that diffuse to the extracellular medium. According to these results, the proposed nanotheranostic platform has great potential for real-time monitoring of the response of bacteria to the released antibiotic, contributing to the evolution of the personalized medicine.

JTD Keywords: bacterial detection, chloramphenicol, conducting polymers, drug, drug release, electrochemical sensors, electrochemistry, electrostimulated release, mechanism, peptide, polythiophene, sensor, sulfonate, Bacterial detection, Chloramphenicol, Conducting polymers, Controlled-release, Drug release, Electrochemical sensors, Electrostimulated release, Polythiophene

Engineered immunoglobulin-G molecules (IgGs) are of wide interest for the development of detection elements in protein-based biosensors with clinical applications. The strategy usually employed for the de novo design of such engineered IgGs consists on merging fragments of the three-dimensional structure of a native IgG, which is immobilized on the biosensor surface, and of an antibody with an exquisite target specificity and affinity. In this work conventional and accelerated classical molecular dynamics (cMD and aMD, respectively) simulations have been used to propose two IgG-like antibodies for COVID-19 detection. More specifically, the crystal structure of the IgG1 B12 antibody, which inactivates the human immunodeficiency virus-1, has been merged with the structure of the antibody CR3022 Fab tightly bounded to SARS-CoV-2 receptor-binding domain (RBD) and the structure of the 5309 antibody Fab fragment complexed with SARS-CoV-2 RBD. The two constructed antibodies, named IgG1-CR3022 and IgG1-S309, respectively, have been immobilized on a stable gold surface through a linker. Analyses of the influence of both the merging strategy and the substrate on the stability of the two constructs indicate that the IgG1-S309 antibody better preserves the neutralizing structure than the IgG1-CR3022 one. Overall, results indicate that the IgG1-S309 is appropriated for the generation of antibody based sensors for COVID-19 diagnosis. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

JTD Keywords: cr3022, igg1, molecular engineering, s309, Antibodies, Antibody engineering, Biosensors, Chemical detection, Clinical application, Cov, Cr3022, Crystal structure, Design, Diseases, Gold nanoparticles, Igg1, Igg1 antibody, Immobilization, Immunoglobulin g, Immunosensor, In-silico, Merging, Molecular dynamics, Molecular engineering, Orientation, Protein-based biosensors, Receptor-binding domains, S309, Sars, Sensor, Spike protein, Target, Vaccine, Viruses

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

Biocatalytic micro- and nanomotors have emerged as a new class of active matter self-propelled through enzymatic reactions. The incorporation of functional nanotools could enable the rational design of multifunctional micromotors for simultaneous real-time monitoring of their environment and activity. Herein, we report the combination of DNA nanotechnology and urease-powered micromotors as multifunctional tools able to swim, simultaneously sense the pH of their surrounding environment, and monitor their intrinsic activity. With this purpose, a FRET-labeled triplex DNA nanoswitch for pH sensing was immobilized onto the surface of mesoporous silica-based micromotors. During self-propulsion, urea decomposition and the subsequent release of ammonia led to a fast pH increase, which was detected by real-time monitoring of the FRET efficiency through confocal laser scanning microscopy at different time points (i.e., 30 s, 2 and 10 min). Furthermore, the analysis of speed, enzymatic activity, and propulsive force displayed a similar exponential decay, matching the trend observed for the FRET efficiency. These results illustrate the potential of using specific DNA nanoswitches not only for sensing the micromotors’ surrounding microenvironment but also as an indicator of the micromotor activity status, which may aid to the understanding of their performance in different media and in different applications.

JTD Keywords: Micromotors, DNA-nanoswitch, pH detection, Self-propulsion, Nanosensors, Nanomotors

The intermittency of the instantaneous concentration of a turbulent chemical plume is a fundamental cue for estimating the chemical source distance using chemical sensors. Such estimate is useful in applications such as environmental monitoring or localization of fugitive gas emissions by mobile robots or sensor networks. However, the inherent low-pass filtering of metal oxide (MOX) gas sensors-typically used in odor-guided robots and dense sensor networks due to their low cost, weight and size-hinders the quantification of concentration intermittency. In this paper, we design a digital differentiator to invert the low-pass dynamics of the sensor response, thus obtaining a much faster signal from which the concentration intermittency can be effectively computed. Using a fast photo-ionization detector as a reference instrument, we demonstrate that the filtered signal is a good approximation of the instantaneous concentration in a real turbulent plume. We then extract transient features from the filtered signal-the so-called “bouts”-to predict the chemical source distance, focusing on the optimization of the filter parameters and the noise threshold to make the predictions robust against changing wind conditions. This represents an advantage over previous bout-based models which require wind measurements-typically taken with expensive and bulky anemometers-to produce accurate predictions. The proposed methodology is demonstrated in a wind tunnel scenario where a MOX sensor is placed at various distances downwind of an emitting chemical source and the wind speed varies in the range 10-34 cm/s. The results demonstrate that models optimized with our methodology can provide accurate source distance predictions at different wind speeds.

JTD Keywords: Gas detectors, Chemical sensors, Signal processing, Machine learning, Time series analysis

This paper proposes the application of a low-cost gas sensor array in an assistant personal robot (APR) in order to extend the capabilities of the mobile robot as an early gas leak detector for safety purposes. The gas sensor array is composed of 16 low-cost metal-oxide (MOX) gas sensors, which are continuously in operation. The mobile robot was modified to keep the gas sensor array always switched on, even in the case of battery recharge. The gas sensor array provides 16 individual gas measurements and one output that is a cumulative summary of all measurements, used as an overall indicator of a gas concentration change. The results of preliminary experiments were used to train a partial least squares discriminant analysis (PLS-DA) classifier with air, ethanol, and acetone as output classes. Then, the mobile robot gas leak detection capabilities were experimentally evaluated in a public facility, by forcing the evaporation of (1) ethanol, (2) acetone, and (3) ethanol and acetone at different locations. The positive results obtained in different operation conditions over the course of one month confirmed the early detection capabilities of the proposed mobile system. For example, the APR was able to detect a gas leak produced inside a closed room from the external corridor due to small leakages under the door induced by the forced ventilation system of the building.

JTD Keywords: Metal-oxide semiconductor, Gas sensor, Gas leak detection, Assistant personal robot, Mobile robot

Obstructive sleep apnea (OSA) is a common disorder with a low diagnosis ratio, leaving many patients undiagnosed and untreated. In the last decades, accelerometry has been found to be a feasible solution to obtain respiratory activity and a potential tool to monitor OSA. On the other hand, many smartphone-based systems have already been developed to propose solutions for OSA monitoring and treatment. The objective of this work was to develop an automatic event detector based on smartphone accelerometry and pulse oximetry, and to assess its ability to detect thoracic movements. It was validated with a commercial OSA monitoring system at home. Results of this preliminary pilot study showed that the proposed event detector for accelerometry signals is a feasible tool to detect abnormal respiratory events, such as apneas and hypopneas, and has potential to be included in smartphone-based systems for OSA assessment.

JTD Keywords: Sleep apnea, Detectors, Pulse oximetry, Monitoring, Manuals, Band-pass filters, Pulse oximeter

Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Recently, mHealth tools are being proposed to screen OSA patients at home. In this work, we analyzed full-night audio signals recorded with a smartphone microphone. Our objective was to develop an automatic detector to identify silence events (apneas or hypopneas) and compare its performance to a commercial portable system for OSA diagnosis (ApneaLink™, ResMed). To do that, we acquired signals from three subjects with both systems simultaneously. A sleep specialist marked the events on smartphone and ApneaLink signals. The automatic detector we developed, based on the sample entropy, identified silence events similarly than manual annotation. Compared to ApneaLink, it was very sensitive to apneas (detecting 86.2%) and presented an 83.4% positive predictive value, but it missed about half the hypopnea episodes. This suggests that during some hypopneas the flow reduction is not reflected in sound. Nevertheless, our detector accurately recognizes silence events, which can provide valuable respiratory information related to the disease. These preliminary results show that mHealth devices and simple microphones are promising non-invasive tools for personalized sleep disorders management at home.

JTD Keywords: Detectors, Manuals, Sleep apnea, Microphones, Labeling, Hospitals

The limit of detection (LOD) is a key figure of merit in chemical sensing. However, the estimation of this figure of merit is hindered by the non-linear calibration curve characteristic of semiconductor gas sensor technologies such as, metal oxide (MOX), gasFETs or thermoelectric sensors. Additionally, chemical sensors suffer from cross-sensitivities and temporal stability problems. The application of the International Union of Pure and Applied Chemistry (IUPAC) recommendations for univariate LOD estimation in non-linear semiconductor gas sensors is not straightforward due to the strong statistical requirements of the IUPAC methodology (linearity, homoscedasticity, normality). Here, we propose a methodological approach to LOD estimation through linearized calibration models. As an example, the methodology is applied to the detection of low concentrations of carbon monoxide using MOX gas sensors in a scenario where the main source of error is the presence of uncontrolled levels of humidity.

JTD Keywords: Semiconductor gas sensors, Metal-oxide sensors, Limit of detection, Non-linear, Humidity interference, Temperature modulation

Metal oxide semiconductor (MOX) sensors are usually temperature-modulated and calibrated with multivariate models such as Partial Least Squares (PLS) to increase the inherent low selectivity of this technology. The multivariate sensor response patterns exhibit heteroscedastic and correlated noise, which suggests that maximum likelihood methods should outperform PLS. One contribution of this paper is the comparison between PLS and maximum likelihood principal components regression (MLPCR) in MOX sensors. PLS is often criticized by the lack of interpretability when the model complexity increases beyond the chemical rank of the problem. This happens in MOX sensors due to cross-sensitivities to interferences, such as temperature or humidity and non-linearity. Additionally, the estimation of fundamental figures of merit, such as the limit of detection (LOD), is still not standardized in multivariate models. Orthogonalization methods, such as Orthogonal Projection to Latent Structures (O-PLS), have been successfully applied in other fields to reduce the complexity of PLS models. In this work, we propose a LOD estimation method based on applying the well-accepted univariate LOD formulas to the scores of the first component of an orthogonal PLS model. The resulting LOD is compared to the multivariate LOD range derived from error-propagation. The methodology is applied to data extracted from temperature-modulated MOX sensors (FIS SB-500-12 and Figaro TGS 3870-A04), aiming at the detection of low concentrations of carbon monoxide in the presence of uncontrolled humidity (chemical noise). We found that PLS models were simpler and more accurate than MLPCR models. Average LOD values of 0.79 ppm (FIS) and 1.06 ppm (Figaro) were found using the approach described in this paper. These values were contained within the LOD ranges obtained with the error-propagation approach. The mean LOD increased to 1.13 ppm (FIS) and 1.59 ppm (Figaro) when considering validation samples collected two weeks after calibration, which represents a 43% and 46% degradation, respectively. The orthogonal score-plot was a very convenient tool to visualize MOX sensor data and to validate the LOD estimates.

JTD Keywords: Metal oxide sensors, Partial least squares, Orthogonal projection to latent structures, Maximum likelihood principal component regression, Limit of detection, Temperature modulation

Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative

JTD Keywords: Fire detection, Gas sensor, Pattern recognition, Sensor fusion, Machine learning, Toxicants, Carbon monoxide, Hydrogen cyanide, Standard test fires, Transducers, Smoke

Abstract Recent studies in neuroscience suggest that sniffing, namely sampling odors actively, plays an important role in olfactory system, especially in certain scenarios such as novel odorant detection. While the computational advantages of high frequency sampling have not been yet elucidated, here, in order to motivate further investigation in active sampling strategies, we share the data from an artificial olfactory system made of 16 MOX gas sensors under gas flow modulation. The data were acquired on a custom set up featured by an external mechanical ventilator that emulates the biological respiration cycle. 58 samples were recorded in response to a relatively broad set of 12 gas classes, defined from different binary mixtures of acetone and ethanol in air. The acquired time series show two dominant frequency bands: the low-frequency signal corresponds to a conventional response curve of a sensor in response to a gas pulse, and the high-frequency signal has a clear principal harmonic at the respiration frequency. The data are related to the study in [1], and the data analysis results reported there should be considered as a reference point.

JTD Keywords: Gas sensor array, MOX sensor, Flow modulation, Early detection, Biomimetics, Respiration, Sniffing

Abstract The design of bioinspired systems for chemical sensing is an engaging line of research in machine olfaction. Developments in this line could increase the lifetime and sensitivity of artificial chemo-sensory systems. Such approach is based on the sensory systems known in live organisms, and the resulting developed artificial systems are targeted to reproduce the biological mechanisms to some extent. Sniffing behaviour, sampling odours actively, has been studied recently in neuroscience, and it has been suggested that the respiration frequency is an important parameter of the olfactory system, since the odour perception, especially in complex scenarios such as novel odourants exploration, depends on both the stimulus identity and the sampling method. In this work we propose a chemical sensing system based on an array of 16 metal-oxide gas sensors that we combined with an external mechanical ventilator to simulate the biological respiration cycle. The tested gas classes formed a relatively broad combination of two analytes, acetone and ethanol, in binary mixtures. Two sets of low-frequency and high-frequency features were extracted from the acquired signals to show that the high-frequency features contain information related to the gas class. In addition, such information is available at early stages of the measurement, which could make the technique suitable in early detection scenarios. The full data set is made publicly available to the community.11 http://archive.ics.uci.edu/ml/datasets/Gas+sensor+array+under+flow+modulation.

JTD Keywords: Gas sensor array, MOX sensor, Flow modulation, Early detection, Biomimetics, Sniffing

Metal oxide (MOX) gas sensors arrays are a predominant technological choice to perform fundamental tasks of chemical detection. Yet, their use has been mainly limited to relatively controlled instrument configurations where the sensor array is placed within a closed measurement chamber. Usually, the experimental protocol is defined beforehand and it includes three stages: the array is first exposed to a gas reference, then to the gas sample, and finally to the reference again to recover the initial state. Such sampling procedure requires signal acquisition during the complete experimental protocol and usually delays the output prediction until the predefined measurement duration is complete. Due to the slow time response of chemical sensors, the completion of the measurement typically requires minutes. In this paper we propose the use of reservoir computing (RC) algorithms to overcome the slow temporal dynamics of chemical sensor arrays, allowing identification and quantification of chemicals of interest continuously and reducing measurement delays. We generated two datasets to test the ability of RC algorithms to provide accurate and continuous prediction to fast varying gas concentrations in real time. Both datasets - one generated with synthetic data and the other acquired from actual gas sensors - provide time series of MOX sensors exposed to binary gas mixtures where concentration levels change randomly over time. Our results show that our approach improves the time response of the sensory system and provides accurate predictions in real time, making the system specifically suitable for online monitoring applications. Finally, the collected dataset and developed code are made publicly available to the research community for further studies.

JTD Keywords: Chemical sensors, Continuous gas prediction, Electronic nose, Real-time detection, Reservoir computing

Abstract Here we describe the fabrication of a highly sensitive and label-free ITO-based impedimetric immunosensor for the detection of pathogenic bacteria Escherichia coli O157:H7. Anti-E. coli antibodies were immobilized onto ITO electrodes using a simple, robust and direct methodology. First, the covalent attachment of epoxysilane on the ITO surface was demonstrated by Atomic Force Microscopy and cyclic voltammetry. The immobilization of antibody on the epoxysilane layer was quantified by Optical Waveguide Lightmode Spectroscopy, obtaining a mass variation of 12 ng cm− 2 (0.08 pmol cm− 2). Microcontact printing and fluorescence microscopy were used to demonstrate the specific binding of E. coli O157:H7 to the antibody-patterned surface. We achieved a ratio of 1:500 Salmonella typhimurium/E. coli O157:H7, thus confirming the selectivity of the antibodies and efficiency of the functionalization procedure. Finally, the detection capacity of the ITO-based immunosensor was evaluated by Electrochemical Impedance Spectroscopy. A very low limit of detection was obtained (1 CFU mL− 1) over a large linear working range (10–106 CFU mL− 1). The specificity of the impedimetric immunosensor was also examined. Less than 20% of non-specific bacteria (S. typhimurium and E. coli K12) was observed. Our results reveal the applicability of ITO for the development of highly sensitive and selective impedimetric immunosensors.

JTD Keywords: E. coli O157:H7, Electrochemical Impedance Spectroscopy, Immunosensor, Indium tin oxide, Label-free detection

In computer-assisted beating heart surgeries, accurate tracking of the heart's motion is of huge importance and there is a continuous need to eliminate any source of error that might disturb the tracking process. One source of error is the specular reflection that appears on the glossy surface of the heart. In this paper, we propose a robust solution for the detection and removal of specular highlights. A hybrid color attributes and wavelet based edge projection approach is applied to accurately identify the affected regions. These regions are then recovered using a dynamic search-based inpainting with adaptive windowing. Experimental results demonstrate the precision and efficiency of the proposed method. Moreover, it has a real-time performance and can be generalized to various other applications.

JTD Keywords: Heart, Image color analysis, Image edge detection, Surgery, Tracking, Wavelet transforms

The use of an autonomous mobile robot to locate gas-leaks and air quality monitoring in indoor environments are promising tasks that will avoid risky human operations. However, these are challenging tasks due to the chaotic gas profile propagation originated by uncontrolled air flows. This paper proposes the localization of an acetone gas-leak in a 44 m-length indoor corridor with a mobile robot equipped with a PID sensor. This paper assesses the influence of the mobile robot velocity and the relative height of the PID sensor in the profile of the measurements. The results show weak influence of the robot velocity and strong influence of the relative height of the PID sensor. An estimate of the gas-leak location is also performed by computing the center of mass of the highest gas concentrations.

JTD Keywords: Gas source detection, LIDAR sensor, Mobile robot, PID sensor, SLAM, Acetone, Air quality, Gases, Indoor air pollution, Mobile robots, Robots, Air quality monitoring, Autonomous Mobile Robot, Gas sources, Indoor environment, Leak localization, LIDAR sensors, Profile propagation, SLAM, Ionization of gases

An array with all-solid-state, potentiometric, miniaturized sensors for pH and potassium was developed to be introduced into the stomach or other sectors of the digestive tract by means of flexible endoscopy. These sensors perform continuous and simultaneous measurement of extracellular pH and potassium. This detection seeks to sense ischemia in the gastric mucosa inside the stomach, an event indicative of local microvascular perfusion and tissue oxygenation status. Our array is proposed as a medical tool to identify the occurrence of the ischemia after gastrointestinal or gastroesophageal anastomosis. The stability and feasibility of the miniaturized working and reference electrodes integrated in the array were studied under in vitro conditions, and the behavior of the potassium and pH ion-selective membranes were optimized to work under acidic gastric conditions with high concentrations of HCl. The array was tested in vivo in pigs to measure the ischemia produced by clamping the blood flow into the stomach. Our results indicate that ischemic and reperfusion states can be sensed in vivo and that information on tissue damage can be collected by this sensor array. The device described here provides a miniaturized, inexpensive, and mass producible sensor array for detecting local ischemia caused by unfavorable anastomotic perfusion and will thus contribute to preventing anastomotic leakage and failure caused by tissue necrosis.

JTD Keywords: Endoscopy, Surgery, Tissue, Gastric anastomosis, Gastric conditions, Ion selective sensors, Ischemia, pH detection, Reference electrodes, Simultaneous measurement, Tissue oxygenation, Sensors

Abstract Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise.

JTD Keywords: Limit of detection, Information theory, Mutual information, Heteroscedasticity, False positive/negative errors, Gas discrimination and quantification

Poly(vinylchloride) (PVC) is the most common polymer matrix used in the fabrication of ion-selective electrodes (ISEs). However, the surfaces of PVC-based sensors have been reported to show membrane instability. In an attempt to overcome this limitation, here we developed two alternative methods for the preparation of highly stable and robust ion-selective sensors. These platforms are based on the selective electropolymerization of poly(3,4-ethylenedioxythiophene) (PEDOT), where the sulfur atoms contained in the polymer covalently interact with the gold electrode, also permitting controlled selective attachment on a miniaturized electrode in an array format. This platform sensor was improved with the crosslinking of the membrane compounds with poly(ethyleneglycol) diglycidyl ether (PEG), thus also increasing the biocompatibility of the sensor. The resulting ISE membranes showed faster signal stabilization of the sensor response compared with that of the PVC matrix and also better reproducibility and stability, thus making these platforms highly suitable candidates for the manufacture of robust implantable sensors.

JTD Keywords: Biomedicine, Electrochemistry, Endoscope, Implantable device, Ion-selective electrode (ISE) sensor, Ischemia, pH detection, Biocompatibility, Chemical sensors, Electrochemistry, Electrodes, Electropolymerization, Endoscopy, Functional polymers, Implants (surgical), Ion selective electrodes, Medical applications, Polyvinyl chlorides, Stabilization, Biomedical applications, Biomedicine, Implantable devices, Ion selective sensors, Ischemia, Membrane instability, pH detection, Poly(3 ,4 ethylenedioxythiophene) (PEDOT), Ion selective membranes

This paper presents an autonomous agent for gas leak source detection. The main objective of the robot is to estimate the localization of the gas leak source in an indoor environment without any human intervention. The agent implements an SLAM procedure to scan and map the indoor area. The mobile robot samples gas concentrations with a gas and a wind sensor in order to estimate the source of the gas leak. The mobile robot agent will use the information obtained from the onboard sensors in order to define an efficient scanning path. This paper describes the measurement results obtained in a long corridor with a gas leak source placed close to a wall.

JTD Keywords: Gas detection, Mobile robot agent, Laser sensor, Self-localization

The sensitivity and selectivity of metal oxide (MOX) gas sensors change significantly when the sensors operate at different temperatures. While previous investigations have presented systematic approaches to optimize the operating temperature of a single MOX sensor, in this paper we present a methodology to select the optimal operating temperature of all the MOX sensors constituent of a gas sensor array based on the multivariate response of all the sensing elements. Our approach estimates a widely used Information Theory measure, the so-called Mutual Information (MI), which quantifies the amount of information that the state of one random variable (response of the gas sensor array) can provide from the state of another random variable representing the gas quality. More specifically, our methodology builds sensor models from experimental data to solve the technical problem of populating the joint probability distribution for the MI estimation. We demonstrate the relevance of our approach by maximizing the MI and selecting the best operating temperatures of a four-sensor array sampled at 94 different temperatures to optimize the discrimination task of ethanol, acetic acid, 2-butanone, and acetone. In addition to being applicable in principle to sensor arrays of any size, our approach gives precise information on the ability of the system to discriminate odors according to the temperature of the MOX sensors, for either the optimal set of temperatures or the temperatures that may render inefficient operation of the system itself.

JTD Keywords: MOX gas sensor, Temperature optimization, Limit of detection, Mutual Information, E-nose, Sensor array, Information Theory, Chemical sensing

Rat model of Obstructive Sleep Apnea (OSA) is a realistic approach for studying physiological mechanisms involved in sleep. Rats are usually anesthetized and autonomic nervous system (ANS) could be blocked. This study aimed to assess the effect of anesthesia on ANS activity during OSA episodes. Seven male Sprague-Dawley rats were anesthetized intraperitoneally with urethane (1g/kg). The experiments were conducted applying airway obstructions, simulating 15s-apnea episodes for 15 minutes. Five signals were acquired: respiratory pressure and flow, SaO2, ECG and photoplethysmography (PPG). In total, 210 apnea episodes were studied. Normalized power spectrum of Pulse Rate Variability (PRV) was analyzed in the Low Frequency (LF) and High Frequency (HF) bands, for each episode in consecutive 15s intervals (before, during and after the apnea). All episodes showed changes in respiratory flow and SaO₂ signal. Conversely, decreases in the amplitude fluctuations of PPG (DAP) were not observed. Normalized LF presented extremely low values during breathing (median=7,67%), suggesting inhibition of sympathetic system due to anesthetic effect. Subtle increases of LF were observed during apnea. HRV and PPG analysis during apnea could be an indirect tool to assess the effect and deep of anesthesia.

JTD Keywords: electrocardiography, fluctuations, medical disorders, medical signal detection, medical signal processing, neurophysiology, photoplethysmography, pneumodynamics, sleep, ECG, SaO₂ flow, SaO₂ signal, airway obstructions, amplitude fluctuations, anesthesia effects, anesthetized nervous system, autonomic evaluation, autonomic nervous system, breathing, heart rate variability, high-frequency bands, low-frequency bands, male Sprague-Dawley rats, normalized power spectrum, obstructive sleep apnea, photoplethysmography, physiological mechanisms, pulse rate variability, rat model, respiratory flow, respiratory pressure, signal acquisition, sympathetic system inhibition, time 15 min, time 15 s, Abstracts, Atmospheric modeling, Computational modeling, Electrocardiography, Rats, Resonant frequency

Integrins are cell membrane adhesion receptors involved in morphogenesis, immunity, tissue healing, and metastasis. A central, yet unresolved question regarding the function of integrins is how these receptors regulate both their conformation and dynamic nanoscale organization on the membrane to generate adhesion-competent microclusters upon ligand binding. Here we exploit the high spatial (nanometer) accuracy and temporal resolution of single-dye tracking to dissect the relationship between conformational state, lateral mobility, and microclustering of the integrin receptor lymphocyte function-associated antigen 1 (LFA-1) expressed on immune cells. We recently showed that in quiescent monocytes, LFA-1 preorganizes in nanoclusters proximal to nanoscale raft components. We now show that these nanoclusters are primarily mobile on the cell surface with a small (ca. 5%) subset of conformational- active LFA-1 nanoclusters preanchored to the cytoskeleton. Lateral mobility resulted crucial for the formation of microclusters upon ligand binding and for stable adhesion under shear flow. Activation of high-affinity LFA-1 by extracellular Ca 2+ resulted in an eightfold increase on the percentage of immobile nanoclusters and cytoskeleton anchorage. Although having the ability to bind to their ligands, these active nanoclusters failed to support firm adhesion in static and low shear-flow conditions because mobility and clustering capacity were highly compromised. Altogether, our work demonstrates an intricate coupling between conformation and lateral diffusion of LFA-1 and further underscores the crucial role of mobility for the onset of LFA-1 mediated leukocyte adhesion.

JTD Keywords: Cumulative probability distribution, Integrin lymphocyte function-associated antigen 1, Intercellular adhesion molecule, Single molecule detection

In this work we report the fabrication and characterization of a label-free impedimetric immunosensor based on a silicon nitride (Si 3N 4) surface for the specific detection of human serum albumin (HSA) proteins. Silicon nitride provides several advantages compared with other materials commonly used, such as gold, and in particular in solid-state physics for electronic-based biosensors. However, few Si 3N 4-based biosensors have been developed; the lack of an efficient and direct protocol for the integration of biological elements with silicon-based substrates is still one of its the main drawbacks. Here, we use a direct functionalization method for the direct covalent binding of monoclonal anti-HSA antibodies on an aldehyde-functionalized Si-p/SiO 2/Si 3N 4 structure. This methodology, in contrast with most of the protocols reported in literature, requires less chemical reagents, it is less time-consuming and it does not need any chemical activation. The detection capability of the immunosensor was tested by performing non-faradaic electrochemical impedance spectroscopy (EIS) measurements for the specific detection of HSA proteins. Protein concentrations within the linear range of 10 -13-10 -7M were detected, showing a sensitivity of 0.128ΩμM -1 and a limit of detection of 10 -14M. The specificity of the sensor was also addressed by studying the interferences with a similar protein, bovine serum albumin. The results obtained show that the antibodies were efficiently immobilized and the proteins detected specifically, thus, establishing the basis and the potential applicability of the developed silicon nitride-based immunosensor for the detection of proteins in real and more complex samples.

JTD Keywords: Aldehyde, Electrochemical impedance spectroscopy, Human serum albumin, Immunosensor, Silicon nitride, Bovine serum albumins, Chemical reagents, Complex samples, Covalent binding, Detection capability, Electrochemical impedance, Electrochemical impedance spectroscopy measurements, Functionalizations, Human serum albumins, Impedimetric immunosensors, Label free, Limit of detection, Linear range, Protein concentrations, Silicon-based, Specific detection, Aldehydes

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

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

Near-field optical microscopy is a technique not limited by the laws of diffraction that enables simultaneous high-resolution fluorescence and topographic measurements at the nanometer scale. This chapter highlights the intrinsic advantages of near-field optics in the study of cellular structures. The first part of the chapter lays the foundations of the near-field concept and technical implementation of near-field scanning optical microscopy (NSOM), whereas the second part of the chapter focuses on applications of NSOM to the study of model membranes and cellular structures on the plasma membrane. The last part of the chapter discusses further directions of near-field optics, including optical antennas and fluorescence correlation spectroscopy approaches in the near-field regime.

JTD Keywords: Biological membranes, Cell membrane nanoscale compartmentalization, Cellular nanodomains, Fluorescence correlation spectroscopy in reduced volumes, Immunoreceptor imaging, Lipid rafts, Near-field scanning optical microscopy, Optical nano-antennas, Shear force imaging, Single molecule detection, Super-resolution microscopy

The valuable properties of aptamers, such as specificity, sensitivity, stability, cost-effectiveness and design flexibility, have favoured their use as biorecognition elements in biosensor development. These synthetic affinity probes can be developed for almost any target molecule, covering a wide range of applications in fields such as clinical diagnosis and therapy, environmental monitoring and food control. The combination of aptamers with high-performance electrochemical transducers, with their inherent high sensitivities, fast response times and simple equipment, has already provided several electrochemical aptamer-based sensors. Moreover, the small size and versatility of aptamers allow efficient immobilisations in high-density monolayers, an important feature towards miniaturisation and integration of compact electrochemical devices. This review describes the state-of-the-art of electrochemical aptamer-based sensors, entering into the details of the different strategies and types of electrochemical transduction and also considering their advantages when applied to the analysis of complex matrices.

JTD Keywords: Aptabeacon, Aptamer, Biosensor, Electrochemical detection, Redox label

Lateral segregation of cell membranes is accepted as a primary mechanism for cells to regulate a diversity of cellular functions. In this context, lipid rafts have been conceptualized as organizing principle of biological membranes where underlying cholesterol-mediated selective connectivity must exist even at the resting state. However, such a level of nanoscale compositional connectivity has been challenging to prove. Here we used single-molecule near-field scanning optical microscopy to visualize the nanolandscape of raft ganglioside GM1 after tightening by its ligand cholera toxin (CTxB) on intact cell membranes. We show that CTxB tightening of GM1 is sufficient to initiate a minimal raft coalescence unit, resulting in the formation of cholesterol-dependent GM1 nanodomains <120 nm in size. This particular arrangement appeared independent of cell type and GM1 expression level on the membrane. Simultaneous dual color high-resolution images revealed that GPI anchored and certain transmembrane proteins were recruited to regions proximal (<150 nm) to CTxB-GM1 nanodomains without physical intermixing. Together with in silico experiments, our high-resolution data conclusively demonstrate the existence of raft-based interconnectivity at the nanoscale. Such a linked state on resting cell membranes constitutes thus an obligatory step toward the hierarchical evolution of large-scale raft coalescence upon cell activation.

JTD Keywords: Cholera toxin, Membrane heterogeneity, Near-field scanning optical microscopy, Raft ganglioside GM1, Single-molecule detection

For many years, it was believed that the laws of diffraction set a fundamental limit to the spatial resolution of conventional light microscopy. Major developments, especially in the past few years, have demonstrated that the diffraction barrier can be overcome both in the near- and far-field regime. Together with dynamic measurements, a wealth of new information is now emerging regarding the compartmentalization of cell membranes. In this review we focus on optical methods designed to explore the nanoscale architecture of the cell membrane, with a focal point on near-field optical microscopy (NSOM) as the first developed technique to provide truly optical super-resolution beyond the diffraction limit of light. Several examples illustrate the unique capabilities offered by NSOM and highlight its usefulness on cell membrane studies, complementing the palette of biophysical techniques available nowadays.

JTD Keywords: Membrane nanodomain, Lipid raft, Single molecule detection, Near-field scanning optical microscopy, Super-resolution optical microscopy

In this work, we report the detection of proteins by means of simultaneous fluorescence and impedance measurements in a cyclo olefin polymer (COP) chip containing an ordered pillar array column, used for reversed-phase liquid chromatography, with integrated microband gold electrodes at the end of the channel.

JTD Keywords: Cyclo olefin polymer, Gold microelectrodes, Impedance, Pillar array, Protein detection

Recruitment of receptor proteins to lipid rafts has been proposed as an important mechanism to regulate their cellular function. In particular, rafts have been implicated in regulation of integrin-mediated cell adhesion, although the underlying mechanism remains elusive. We used single-molecule near-field optical microscopy (NSOM) with localization accuracy of approximately 3 nm, to capture the spatio-functional relationship between the integrin LFA-1 and raft components (GPI-APs) on immune cells. Dual color nanoscale imaging revealed the existence of a nanodomain GPI-AP subpopulation that further concentrated in regions smaller than 250 nm, suggesting a hierarchical prearrangement of GPI-APs on resting monocytes. We previously demonstrated that in quiescent monocytes, LFA-1 preorganizes in nanoclusters. We now show that integrin nanoclusters are spatially different but reside proximal to GPI-AP nanodomains, forming hotspots on the cell surface. Ligand-mediated integrin activation resulted in an interconversion from monomers to nanodomains of GPI-APs and the generation of nascent adhesion sites where integrin and GPI-APs colocalized at the nanoscale. Cholesterol depletion significantly affected the reciprocal distribution pattern of LFA-1 and GPI-APs in the resting state, and LFA-1 adhesion to its ligand. As such, our data demonstrate the existence of nanoplatforms as essential intermediates in nascent cell adhesion. Since raft association with a variety of membrane proteins other than LFA-1 has been documented, we propose that hotspots regions enriched with raft components and functional receptors may constitute a prototype of nanoscale inter-receptor assembly and correspond to a generic mechanism to offer cells with privileged areas for rapid cellular function and responses to the outside world.

JTD Keywords: Integrin LFA-1, Membrane nanocompartments, Near-field scanning optical microscopy (NSOM), Single molecule detection

Two Cys-containing analogues of the anticancer drug Kahalalide F are synthesized and conjugated to 20 and 40 nm gold nanoparticles (GNPs). The resulting complexes are characterized by different analytical techniques to confirm the attachment of peptide to the GNPs. The self-assembly capacity of a peptide dramatically influences the final ratio number of molecules per nanoparticle, saturating the nanoparticle surface and prompting multilayered capping on the surface. In such way, the nanoparticle could act as a concentrator for the delivery of drugs, thereby increasing bioactivity. The GNP sizes and the conjugation have influence on the biological activities. Kahalalide F analogues conjugated with GNPs are located subcellularly at lysosome-like bodies, which may be related to the action mechanism of Kahalalide F. The results suggest that the selective delivery and activity of Kahalalide F analogues can be improved by conjugating the peptides to GNPs.

JTD Keywords: Electrical detection, Cellular uptake, Drug-delivery, Cancer-cells, Peptide, Size, Surface, Absorption, Scattering, Therapy

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

Electrochemical impedance spectroscopy (EIS) is applied to detect pathogenic E. coli O157:H7 bacteria via a label free immunoassay-based detection method. Polyclonal anti-E.coli antibodies (PAb) are immobilized onto gold electrodes following two different strategies, via chemical bond formation between antibody amino groups and a carboxylic acid containing self-assembled molecular monolayer (SAM) and alternatively by linking a biotinylated anti-E. coli to Neutravidin on a mixed-SAM. Impedance spectra for sensors of both designs for increasing concentrations of E. coli are recorded in phosphate buffered saline (PBS). The Nyquist plots can be modeled with a Randle equivalent circuit, identifying the charge transfer resistance RCT as the relevant concentration dependent parameter. Sensors fabricated from both designs are able to detect very low concentration of E. coli with limits of detection as low as 10-100 cfu/ml. The influence of the different immobilization protocols on the sensor performance is evaluated in terms of sensitivity, dynamic range and resistance against nonspecific absorption.

JTD Keywords: Bacteria detection, Biosensors, E-coli, Impedance spectroscopy

A first step towards the multidetection of anabolic androgenic steroids by Enzyme-linked immunosorbent assays (ELISA) has been performed in this study. This proposal combines an array of classical ELISA assays with different selectivities and multivariate data analysis techniques. Data has been analyzed by principal component analysis in conjunction with a k-nearest line classifier has been used. This proposal allows to detect simultaneously four different compounds in the range of concentration from 10(-1.5) to 10(3) mM with a total rate of 90.6% of correct detection.

JTD Keywords: Immunoarray, Anabolic androgenic steroid, Multidetection, Pattern recognition, K-nearlest line

Interleukin 2 and interleukin 15 (IL2 and IL15, respectively) provide quite distinct contributions to T-cell-mediated immunity, despite having similar receptor composition and signaling machinery. As most of the proposed mechanisms underlying this apparent paradox attribute key significance to the individual {alpha}-chains of IL2 and IL15 receptors, we investigated the spatial organization of the receptors IL2R{alpha} and IL15R{alpha} at the nanometer scale expressed on a human CD4+ leukemia T cell line using single-molecule-sensitive near-field scanning optical microscopy (NSOM). In agreement with previous findings, we here confirm clustering of IL2R{alpha} and IL15R{alpha} at the submicron scale. In addition to clustering, our single-molecule data reveal that a non-negligible percentage of the receptors are organized as monomers. Only a minor fraction of IL2R{alpha} molecules reside outside the clustered domains, whereas [~]30% of IL15R{alpha} molecules organize as monomers or small clusters, excluded from the main domain regions. Interestingly, we also found that the packing densities per unit area of both IL2R{alpha} and IL15R{alpha} domains remained constant, suggesting a `building block' type of assembly involving repeated structures and composition. Finally, dual-color NSOM demonstrated co-clustering of the two {alpha}-chains. Our results should aid understanding the action of the IL2R-IL15R system in T cell function and also might contribute to the more rationale design of IL2R- or IL15R-targeted immunotherapy agents for treating human leukemia.

JTD Keywords: Near-field scanning optical microscopy (NSOM), Interleukin receptors IL2R, IL15R, Single-molecule detection, Nanometer-scale membrane organization

We present a single-molecule study on femtosecond dynamics in multichromophoric systems, combining fs pump-probe, emission-spectra and fluorescence-lifetime analysis. The ultrafast fs approach gives direct information on the initial exciton dynamics after excitation. The lifetime data show superradiance, a direct measure for the extent of the coherent coupling and static disorder. The spectra finally reveal the role of exciton-phonon coupling. At the single-molecule level a wide range of exciton delocalization lengths and energy redistribution times is revealed.

JTD Keywords: Single-molecule detection, Pump-probe, Exciton delocalization, Superradiance, Exciton-phonon coupling