A review on 3D printing functional brain model.

Modern neuroscience increasingly relies on 3D models to study neural circuitry, nerve regeneration, and neural disease. Several different biofabrication approaches have been explored to create 3D neural tissue model structures. Among them, 3D bioprinting has shown to have great potential to emerge as a high-throughput/high precision biofabrication strategy that can address the growing need for 3D neural models. Here, we have reviewed the design principles for neural tissue engineering. The main challenge to adapt printing technologies for biofabrication of neural tissue models is the development of neural bioink, i.e., a biomaterial with printability and gelation properties and also suitable for neural tissue culture. This review shines light on a vast range of biomaterials as well as the fundamentals of 3D neural tissue printing. Also, advances in 3D bioprinting technologies are reviewed especially for bioprinted neural models. Finally, the techniques used to evaluate the fabricated 2D and 3D neural models are discussed and compared in terms of feasibility and functionality.

Selective detection of VOCs using microfluidic gas sensor with embedded cylindrical microfeatures coated with graphene oxide.

Volatile organic compounds (VOCs) are major environmental pollutants. Exposure to VOCs has been associated with adverse health outcomes. The monitoring of hazardous VOCs is a vital step towards identifying their presence and preventing the risk of acute or chronic exposure and polluting the environment. One of the challenges associated with monitoring VOCs is selectivity of the sensor. Microfluidic gas sensors offer selective and sensitive detection capabilities that have been recently applied for detection of VOCs. In this study, we achieve improved selectivity for detection of a range of VOCs by adding micro- and nanofeatures to the microchannel of microfluidic gas sensors. First, microfeatures are embedded into the microchannel and their geometries are optimized using Taguchi design of experiment method. In the next step the microfeatures embedded microchannel is coated with graphene oxide, to increase the surface to volume ratio by introducing nanofeatures to the surfaces. The nano- and microfeatures are characterized by SEM, XPS, and water contact angle measurement. Finally, the changes in the sensor response are compared to plain microfluidic gas sensor, the results show an average of 64.4% and 120.9% improvement in the selectivity of the sensor with microfeatures and both nano- and microfeatures, respectively.

A selective polypyrrole-based sub-ppm impedimetric sensor for the detection of dissolved hydrogen sulfide and ammonia in a mixture.

An impedance-transducer sensor was developed for in situ detection of hydrogen sulfide (H2S) and ammonia (NH3) in aqueous media. Using cyclic voltammetry (CV), polypyrrole (PPy) was deposited on the surface of the microfabricated interdigitated gold electrode. Due to the proton acid doping effect of H2S on PPy and ionic conduction of the film, the sensor showed a decreasing impedance response to H2S unlike other reducing chemicals, i.e., ammonia (NH3). The recorded faradaic data was then associated with an equivalent circuit and compared with that of NH3 to examine the selectivity of the sensor. An electrochemical impedance spectroscopy (EIS) analysis was applied to the mixture of H2S and NH3 prepared at different ratios for the concentrations ranging from 2 ppm to 20 ppm (below 2-ppm, no response was observed due to the formation of NH4HS, not sensible with PPy). The principal component analysis (PCA) was used to train a real-time prediction model for both classification (for the type of the analyte) and regression (the concentration of the analyte). The results showed the high performance of the sensor in determining individual analytes while the model was able to accurately predict the amount of H2S and NH3 in the mixture.

Micron-sized particle separation with standing surface acoustic wave-Experimental and numerical approaches.

Traditional cell/particle isolation methods are time-consuming and expensive and can lead to morphology disruptions due to high induced shear stress. To address these problems, novel lab-on-a-chip-based purification methods have been employed. Among various methods introduced for the separation and purification of cells and synthetics particles, acoustofluidics has been one of the most effective methods. Unlike traditional separation techniques carried out in clinical laboratories based on chemical properties, the acoustofluidic process relies on the physical properties of the sample. Using acoustofluidics, manipulating cells and particles can be achieved in a label-free, contact-free, and highly biocompatible manner. To optimize the functionality of the platform, the numerical study should be taken into account before conducting experimental tests to save time and reduce fabrication expenses. Most current numerical studies have only considered one-dimensional harmonic standing waves to simulate the acoustic pressure distribution. However, one-dimensional simulations cannot calculate the actual acoustic pressure distribution inside the microchannel due to its limitation in considering longitudinal waves. To address this limitation, a two-dimensional numerical simulation was conducted in this study. Our numerical simulation investigates the effects of the platform geometrical and operational conditions on the separation efficiency. Next, the optimal values are tested in an experimental setting to validate these optimal parameters and conditions. This work provides a guideline for future acoustofluidic chip designs with a high degree of reproducibility and efficiency.

Potentiodynamic Electrochemical Impedance Spectroscopy of Polyaniline-Modified Pencil Graphite Electrodes for Selective Detection of Biochemical Trace Elements.

In this study, we analyzed the application of potentiodynamic electrochemical impedance spectroscopy (PDEIS) for a selective in situ recognition of biological trace elements, i.e., Cr (III), Cu (II), and Fe (III). The electrochemical sensor was developed using the electropolymerization of aniline (Ani) on the surface of the homemade pencil graphite electrodes (PGE) using cyclic voltammetry (CV). The film was overoxidized to diminish the background current. A wide range of potential (V = -0.2 V to 1.0 V) was investigated to study the impedimetric and capacitive behaviour of the PAni/modified PGE. The impedance behaviors of the films were recorded at optimum potentials through electrochemical impedance spectroscopy (EIS) and scrutinized by means of an appropriate equivalent circuit at different voltages and at their corresponding oxidative potentials. The values of the equivalent circuit were used to identify features (charge transfer-resistant and double layer capacitance) that can selectivity distinguish different trace elements with the concentration of 10 µM. The PDEIS spectra represented the highest electron transfer for Cu (II) and Cr (III) in a broad potential range between +0.1 and +0.4 V while the potential V = +0.2 V showed the lowest charge transfer resistance for Fe (III). The results of this paper showed the capability of PDEIS as a complementary tool for conventional CV and EIS measurement for metallic ion sensing.

Parametric study on the geometrical parameters of a lab-on-a-chip platform with tilted planar electrodes for continuous dielectrophoretic manipulation of microparticles.

Advances in lab-on-a-chip (LOC) devices have led to significant improvements in the on-chip manipulation, separation, sorting, and isolation of particles and cells. Among various LOC-based approaches such as inertia-based methods, acoustophoresis, and magnetophoresis, the planar-slanted-electrode dielectrophoresis (DEP) method has demonstrated great potential as a label-free, cost-effective, and user-friendly approach. However, the devices built based on this method suffer from low flow throughput compared to devices functioning based on other LOC-based manipulation approaches. In order to overcome this obstacle, the geometrical parameters of these types of DEP-based devices must be studied to increase the effectiveness of DEP manipulation. With the consideration of both numerical and experimental studies, this paper studies the geometrical factors of a LOC platform consisting of tilted planar electrodes with the goal of achieving higher throughput in continuous manipulation of polystyrene particles. COMSOL Multiphysics software was used to study the effect of the electrodes geometry on the induced electric field. The simulation results show that by increasing the electrode's width and decreasing the electrode's spacing, higher DEP force is generated. Furthermore, the experimental outcomes indicated that lower channel height, higher voltage, and larger particle size resulted in the most improvement to DEP manipulation. Additionally, the experimental results demonstrated that slanted electrodes with an angle of 8° with respect to the direction of flow provide a more effective configuration.

Graphene/poly (methyl methacrylate) electrochemical impedance-transduced chemiresistor for detection of volatile organic compounds in aqueous medium.

In this paper, an impedance-transduced sensor is developed based on a nanostructured graphene (GN) and poly (methyl methacrylate) (PMMA) sensing film for the detection of individual volatile organic compounds (VOCs) in aqueous media. Benefiting from a porous and high surface area, the nanostructured nanofiber is characterized by scanning electron microscopy (SEM) and optimized by the electrochemical impedance spectroscopy (EIS) technique. The recorded EIS data indicate the selective recognition of four VOCs of interest at a constant pH while there is no redox probe. The non-faradaic responses to each analyte at different concentrations are correlated with a three-element equivalent circuit (resistances of the solution and the film, and a pseudo-capacitance). To analyze the ability of the sensing film in distinguishing between VOCs with similar average boiling points, the values of the individual equivalent circuit elements are used as features and clustered in three-dimensional (3D) plots. Among the features, the two representing the maximum differences between the VOCs are represented in a two-dimensional (2D) plot to show the selectivity of the sensor. The feature extraction analysis demonstrates that the constant phase element (CPE) of the equivalent circuit is a more accurate predictor of VOCs than the interfacial capacitance. These results show high selectivity of the sensorial platform due to the synergistic pairing of nanostructured GN and PMMA.

Topical review on monitoring tetrahydrocannabinol in breath.

Legalization of cannabis for recreational use has compelled governments to seek new tools to accurately monitor Δ9-tetrahydrocannabinol (Δ9-THC) and understand its effect on impairment. Various methods have been employed to measure Δ9-THC, and its respective metabolites, in different biological matrices. Recently, breath analysis has gained interest as a non-invasive method for the detection of chemicals that are either produced as part of biological processes or are absorbed from the environment. Existing breath analyzers function by analyzing previously collected samples or by direct real-time analysis. Portable hand-held devices are of particular interest for law enforcement and personal use. This paper reviews and compares both commercially available and prototype devices that proclaim Δ9-THC detection in exhaled breath using methods such as Field Asymmetric Ion Mobility Spectrometry, Semiconductor-Enriched Single-Walled Carbon Nanotube chemiresistors, Liquid Chromatography Tandem-mass Spectrometry, microfluidic-based artificial olfaction, and optical-based gas sensing.