Dopamine is a key molecule in neurotransmission and has been known to be responsible for several neurological diseases. Hence, its sensitive and selective detection is important for the early diagnosis of diseases related to abnormal levels of dopamine. In this study, we reported a new cylindrical gold nanoelectrode (CAuNE) platform fabricated via sequential laser interference lithography and electrochemical deposition. Among the fabricated electrodes, CAuNEs with a diameter of 700 nm, 150 s deposited, was found to be the best for electrochemical dopamine detection. According to cyclic voltammetry results, the linear range of the CAuNE-700 nm was 1–100 µM of dopamine with a limit of detection (LOD) of 5.83 µM. Moreover, owing to the homogeneous periodic features of CAuNEs, human neural cells were successfully cultured and maintained for more than 5 daysin vitrowithout the use of any extracellular matrix proteins and dopamine was detectable in the presence of these cells on the electrode. Therefore, we concluded that the developed dopamine sensing platform CAuNE can be used for many applications including early diagnosis of neurological diseases; function tests of dopaminergic neurons derived from various stem cell sources; and toxicity assessments of drugs, chemicals, and nanomaterials on human neuronal cells.

Drug candidates often cause an unwanted blockage of the potassium ion channel of the human ether-a-go-go-related gene (hERG). The blockage leads to long QT syndrome (LQTS), which is a severe life-threatening cardiac side effect. Therefore, a virtual screening method to predict drug-induced hERG-related cardiotoxicity could facilitate drug discovery by filtering out toxic drug candidates. In this study, we generated a reliable hERG-related cardiotoxicity dataset composed of 2130 compounds, which were carried out under constant conditions. Based on our dataset, we developed a computational hERG-related cardiotoxicity prediction model. The neural network model achieved an area under the receiver operating characteristic curve (AUC) of 0.764, with an accuracy of 90.1%, a Matthews correlation coefficient (MCC) of 0.368, a sensitivity of 0.321, and a specificity of 0.967, when ten-fold cross-validation was performed. The model was further evaluated using ten drug compounds tested on guinea pigs and showed an accuracy of 80.0%, an MCC of 0.655, a sensitivity of 0.600, and a specificity of 1.000, which were better than the performances of existing hERG-toxicity prediction models. The neural network model can predict hERG-related cardiotoxicity of chemical compounds with a high accuracy. Therefore, the model can be applied to virtual high-throughput screening for drug candidates that do not cause cardiotoxicity. The prediction tool is available as a web-tool at http://ssbio.cau.ac.kr/CardPred .

Three-dimensional (3D) bioprinting technology has emerged as a powerful biofabrication platform for tissue engineering because of its ability to engineer living cells and biomaterial-based 3D objects. Over the last few decades, droplet-based, extrusion-based, and laser-assisted bioprinters have been developed to fulfill certain requirements in terms of resolution, cell viability, cell density, etc. Simultaneously, various bio-inks based on natural–synthetic biomaterials have been developed and applied for successful tissue regeneration. To engineer more realistic artificial tissues/organs, mixtures of bio-inks with various recipes have also been developed. Taken together, this review describes the fundamental characteristics of the existing bioprinters and bio-inks that have been currently developed, followed by their advantages and disadvantages. Finally, various tissue engineering applications using 3D bioprinting are briefly introduced.

The detection of dopamine in a highly sensitive and selective manner is crucial for the early diagnosis of a number of neurological diseases/disorders. Here, a report on a new platform for the electrochemical detection of dopamine with a considerable accuracy that comprises a 3D porous graphene oxide (pGO)/gold nanoparticle (GNP)/pGO composite-modified indium tin oxide (ITO) is presented. The pGO was first synthesized and purified by ultrasonication and centrifugation, and it was then further functionalized on the surface of a GNP-immobilized ITO electrode. Remarkably, owing to the synergistic effects of the pGO and GNPs, the 3D pGO-GNP-pGO-modified ITO electrode showed a superior dopamine-detection performance compared with the other pGO- or GNP-modified ITO electrodes. The linear range of the newly developed sensing platform is from 0.1 μM to 30 μM with a limit of detection (LOD) of 1.28 μM, which is more precise than the other previously reported GO-functionalized electrodes. Moreover, the 3D pGO-GNP-pGO-modified ITO electrodes maintained their detection capability even in the presence of several interfering molecules (e.g., ascorbic acid, glucose). The proposed platform of the 3D pGO-GNP-pGO-modified ITO electrode could therefore serve as a competent candidate for the development of a dopamine-sensing platform that is potentially applicable for the early diagnosis of various neurological diseases/disorders.