From Enzymatic Dopamine Biosensors to OECT Biosensors of Dopamine.

Neurotransmitters are an important category of substances used inside the nervous system, whose detection with biosensors has been seriously addressed in the last decades. Dopamine, a neurotransmitter from the catecholamine family, was recently discovered to have implications for cardiac arrest or muscle contractions. In addition to having many other neuro-psychiatric implications, dopamine can be detected in blood, urine, and sweat. This review highlights the importance of biosensors as influential tools for dopamine recognition. The first part of this article is related to an introduction to biosensors for neurotransmitters, with a focus on dopamine. The regular methods in their detection are expensive and require high expertise personnel. A major direction of evolution of these biosensors has expanded with the integration of active biological materials suitable for molecular recognition near electronic devices. Secondly, for dopamine in particular, the miniaturized biosensors offer excellent sensitivity and specificity and offer cheaper detection than conventional spectrometry, while their linear detection ranges from the last years fall exactly on the clinical intervals. Thirdly, the applications of novel nanomaterials and biomaterials to these biosensors are discussed. Older generations, metabolism-based or enzymatic biosensors, could not detect concentrations below the micro-molar range. But new generations of biosensors combine aptamer receptors and organic electrochemical transistors, OECTs, as transducers. They have pushed the detection limit to the pico-molar and even femto-molar ranges, which fully correspond to the usual ranges of clinical detection of human dopamine in body humors that cover 0.1 ÷ 10 nM. In addition, if ten years ago the use of natural dopamine receptors on cell membranes seemed impossible for biosensors, the actual technology allows co-integrate transistors and vesicles with natural receptors of dopamine, like G protein-coupled receptors. The technology is still complicated, but the uni-molecular detection selectivity is promising.

Current Status of Field-Effect Transistors for Biosensing Applications.

The latest novelties in electronic biosensors indicate an increased interest in the compatibilization between Field Effect Transistors (FETs) and bioreceptors, either enzymes, antibodies or cells, for the purpose of detecting the multiple analytes [...].

Low-Cost Antenna-Array-Based Metamaterials for Non-Invasive Early-Stage Breast Tumor Detection in the Human Body.

Microstrip patch antennas have been used in many applications since their appearance. Despite their great promise, their narrow bandwidth and the loss at high-frequency bands have limited their usage in medical applications. This work proposes a developed low-cost microstrip patch antenna suitable for microwave imaging (MWI) applications within the wideband frequency range. The proposed antenna is loaded with an artificial magnetic conductor (AMC) to improve the antenna performance. The simulated results obtained using computer simulation technology (CST) indicate that the presence of the AMC has improved the frequency selectivity of the antenna at 8.6 GHz with a peak realized gain of 9.90443 dBi and 10.61 dBi for simulated and measured results, respectively. The proposed microstrip antenna has been fabricated to validate the simulated results, and its performance is tested experimentally. Additionally, the fidelity factor of face-to-face (FtF) and side-by-side (SbS) scenarios have been presented. The breast phantom models with a tumor and the antenna operating as a transceiver have been numerically simulated for the application of cancer tumor cell detection. The work will have a significant impact on the design of electromagnetic biosensors.

Generalized Analytical Model for Enzymatic BioFET Transistors.

Software tools that are able to simulate the functionality or interactions of an enzyme biosensor with Metal Oxide Semiconductor (MOS), or any Field Effect Transistor (FET) as transducer, represent a gap in the market. Bio-devices, or Enzyme-FET, cannot be simulated by Atlas or equivalent software. This paper resolves this issue for the enzymatic block coupled with FETs' role within biosensors. The first block has the concentration of biological analyte as the input signal and concentration of ions from the enzymatic reaction as the output signal. The modeling begins from the Michaelis-Menten formalism and analyzes the time dependence of the product concentrations that become the input signal for the next FET block. Comparisons within experimental data are provided. The analytical model proposed in this paper represents a general analytical tool in the design stage for enzymatic transistors used in clinical practices.

Modeling of Enzyme-FET Biosensor Based on Experimental Glucose-Oxidase Receptor.

The modeling of biosensors is useful in the design stage. The main device simulator, like Silvaco, has poor software resources for bio-receptors simulations. The modeling is challenging due to the high complexity of the living matter. It requires complementary knowledge from biochemistry, biosensors technology and electronic devices, like FET - Field Effect Transistors. This paper presents an analytical model for the product concentrations versus the time for enzymatic FET based on zero, one or two-order reaction. The mathematical model is confronted with an experimental model tested on a glucose biosensor that uses glucose-oxidase receptor enzyme. The biosensor response time was 36 seconds for enzyme loading of 2µmol/l.Clinical Relevance- The analytical model proposed in this paper represents an analytical tool in the design stage, for any biosensor used in clinical practices. Their modeling is missing.

Optimized Technologies for Cointegration of MOS Transistor and Glucose Oxidase Enzyme on a Si-Wafer.

The biosensors that work with field effect transistors as transducers and enzymes as bio-receptors are called ENFET devices. In the actual paper, a traditional MOS-FET transistor is cointegrated with a glucose oxidase enzyme, offering a glucose biosensor. The manufacturing process of the proposed ENFET is optimized in the second iteration. Above the MOS gate oxide, the enzymatic bioreceptor as the glucose oxidase is entrapped onto the nano-structured TiO2 compound. This paper proposes multiple details for cointegration between MOS devices with enzymatic biosensors. The Ti conversion into a nanostructured layer occurs by anodization. Two cross-linkers are experimentally studied for a better enzyme immobilization. The final part of the paper combines experimental data with analytical models and extracts the calibration curve of this ENFET transistor, prescribing at the same time a design methodology.

Sulpho-Salicylic Acid Grafted to Ferrite Nanoparticles for n-Type Organic Semiconductors.

A disadvantage of the use of pentacene and typical organic materials in electronics is that their precursors are toxic for manufacturers and the environment. To the best of our knowledge, this is the first report of an n-type non-toxic semiconductor for organic transistors that uses sulpho-salicylic acid-a stable, electron-donating compound with reduced toxicity-grafted on a ferrite core-shell and a green synthesis method. The micro-physical characterization indicated a good dispersion stability and homogeneity of the obtained nanofilms using the dip-coating technique. The in-situ electrical characterization was based on a point-contact transistor configuration, and the increase in the drain current as the positive gate voltage increased proved the functionality of the n-type semiconductor.

Manufacture of a nothing on insulator nano-structure with two Cr/Au nanowires separated by 18 nm air gap.

Despite the huge number of previous studies of vacuum devices, nanoscale technologies open new paradigms. Vacuum nanodevices bring multiple advantages, such as air instead of a vacuum for the nanometric gap, strong non-linear characteristics, and a metal oxide semiconductor co-integration facility. This paper presents the manufacturing process and measured characteristics of a nano-device that uses a sub-36 nm gap between two Cr/Au nano-wires. In this way, the metal nano-wires replace the semiconductor nano-islands, while an air gap stands for the 'nothing' region of a first-time fabricated variant for a nothing on insulator device. The electron beam lithography mask-less technology is pushed to its technical limit to define a minimum 18 nm-wide gap between two Cr/Au nanowires. The main current-voltage curves are measured for this first real device called a nothing on insulator in the variant metal-air-metal, indicating 10 nA at 10 V as the optimal variant. The main connections between the measurements and technology are emphasized.

The sensitivity in the IR spectrum of the intact and pathological tissues by laser biophotometry.

In this paper, we use the laser biophotometry for in vivo investigations, searching the most sensitive interactions of the near-infrared spectrum with different tissues. The experimental methods are based on the average reflection coefficient (ARC) measurements. For healthy persons, ARC is the average of five values provided by the biophotometer. The probe is applied on dry skin with minimum pilosity, in five regions: left-right shank, left-right forearm, and epigastrium. For the pathological tissues, the emitting terminal is moved over the suspected area, controlling the reflection coefficient level, till a minimum value occurs, as ARC-Pathological. Then, the probe is moved on the symmetrical healthy region of the body to read the complementary coefficient from intact tissue, ARC-Intact, from the same patient. The experimental results show an ARC range between 67 and 59 mW for intact tissues and a lower range, up to 58-42 mW, for pathological tissues. The method is efficient only in those pathological processes accompanied by variable skin depigmentation, water retention, inflammation, thrombosis, or swelling. Frequently, the ARC ranges are overlapping for some diseases. This induces uncertain diagnosis. Therefore, a statistical algorithm is adopted for a differential diagnosis. The laser biophotometry provides a quantitative biometric parameter, ARC, suitable for fast diagnosis in the internal and emergency medicine. These laser biophotometry measurements are representatives for the Romanian clinical trials.