Deformed graphene FET biosensor on textured glass coupled with dielectrophoretic trapping for ultrasensitive detection of GFAP

Numerous efforts have been undertaken to mitigate the Debye screening effect of FET biosensors for achieving higher sensitivity. There are few reports that show sub-femtomolar detection of biomolecules by FET mechanisms but they either suffer from significant background noise or lack robust control. In this aspect, deformed/crumpled graphene has been recently deployed by other researchers for various biomolecule detection like DNA, COVID-19 spike proteins and immunity markers like IL-6 at sub-femtomolar levels. However, the chemical vapor deposition (CVD) approach for graphene fabrication suffers from various surface contamination while the transfer process induces structural defects. In this paper, an alternative fabrication methodology has been proposed where glass substrate has been initially texturized by wet chemical etching through the sacrificial layer of synthesized silver nanoparticles, obtained by annealing of thin silver films leading to solid state dewetting. Graphene has been subsequently deposited by thermal reduction technique from graphene oxide solution. The resulting deformed graphene structure exhibits higher sensor response towards glial fibrillary acidic protein (GFAP) detection with respect to flat graphene owing to the combined effect of reduced Debye screening and higher surface area for receptor immobilization. Additionally, another interesting aspect of the reported work lies in the biomolecule capture by dielectrophoretic (DEP) transport on the crests of the convex surfaces of graphene in a coplanar gated topology structure which has resulted in 10 aM and 28 aM detection limits of GFAP in buffer and undiluted plasma respectively, within 15 min of application of analyte. The detection limit in buffer is almost four decades lower than that documented for GFAP using biosensors which is is expected to pave way for advancing graphene FET based sensors towards ultrasensitive point-of-care diagnosis of GFAP, a biomarker for traumatic brain injury.

Molecularly Imprinted Polymer Interface on Screen-Printed ZnO Nanorod Field Effect Transistors for Serotonin Detection in Clinical Samples

Ultrasensitive detection of serotonin is crucial for the early diagnosis of several diseases like Parkinson's and Alzheimer's. Most of the existing detection strategies are still not suitable for sensitive point-of-care applications. This study presents direct molecular imprinting of serotonin on the surface of three-dimensional zinc oxide (ZnO) nanorod devices connected in a field effect transistor (FET) configuration to achieve ultrasensitive, real-time, and rapid detection with a convenient and affordable approach, which has significant potential for translation to clinical settings. This strategy has enabled pushing the detection limit to 0.1 fM in a physiological analyte in real time with screen-printed electrodes, thereby resulting in the convenient batch fabrication of sensors for clinical validation. The response of the sensor with the clinical sample has been correlated with that of the gold standard and has been observed to be statistically similar.

Competitive Impedance Spectroscopy in a Schottky-Contacted ZnO Nanorod Structure for Ultrasensitive and Specific Biosensing in a Physiological Analyte

To enable detection and discovery of biomarkers, development of label-free, ultrasensitive, and specific sensors is the need of the hour. For addressing this requirement, here, a Schottky-contacted ZnO nanorod biosensor has been demonstrated, which explores the interplay between Schottky junction capacitance and solution resistance, resulting in an interesting sensing principle of competitive impedance spectroscopy. When the transition of dominating impedance occurs from solution resistance to junction capacitance, a notch or a peak appears in the impedance response at a particular frequency (referred to as the corner frequency) depending on the charge of the target molecule. The appearance of the peak or notch acts like an electronic label for selectivity since it is visible only for target molecules even at ultralow concentrations in the physiological analyte, where the magnitude of impedance change overlaps with that for nonspecific molecules. This phenomenon has been successfully applied for the positively charged vascular endothelial growth factor (VEGF) and the negatively charged hepatitis B surface antigen (HBsAg), where the shifts in the higher corner frequencies for 1 aM concentration of the target molecules have been observed to be more than 3 times the changes in the impedance magnitude. Further, the area of the ZnO nanorods was segmented into two zones corresponding to the lower and higher concentration regimes, thereby expanding the dynamic range. To summarize, an ultralow detection limit of 1 aM with a dynamic range up to 1 pM was achieved for VEGF and HBsAg, which is 4 orders of magnitude and 20 times lower than their most sensitive label-free reports, respectively.

Modeling the Effective Conductance Drop Due to a Particle in a Solid State Nanopore Towards Optimized Design

An understanding of the current change in a solid state nanopore due to particle movement or capture is crucial for improvement of nanopore based sensing technologies. For lower aspect ratio pores, which are gaining importance due to their high sensitivity, there is interplay between access and pore resistance and the existing theories for computation of access resistance cannot explain most of the experimental observations. Hence, there is a need to develop a comprehensive model for calculating the effective conductance drop in presence of particles in a solid state nanopore. In this paper, we develop analytical models to calculate both the access and pore resistance in presence of particle at different positions during translocation and also when captured by receptors in functionalized nanopores. A wide range of pore geometry and molar strength has been investigated. Taking into consideration the positional uncertainty during particle translocation, the effective resistance sensitivity has been found to agree very well with the experimental observations in low aspect ratio pore. Additionally, we observe that in functionalized nanopores, a pore of higher diameter results in around 50% increase in sensitivity compared to a pore with half its diameter, which indicates the scope of design optimization in such systems.

Liquid gated ZnO nanorod FET sensor for ultrasensitive detection of Hepatitis B surface antigen with vertical electrode configuration

Detection of the Hepatitis-B surface antigen at the attomolar level is demonstrated using antibody functionalized liquid gated ZnO nanorods field effect transistor (FET) biosensor with vertical electrode configuration. The sensor is operated in heterodyne mode at high frequency to overcome the problem of Debye screening effect in physiological analyte. Enhanced penetration of the electric field lines through the nanorods enables significant improvement in the limit of detection and sensitivity compared to that of the conventional lateral electrode configuration. The combined effect of the probable change in the threshold voltage and the carrier mobility for vertical electrode configuration lead to a sensitivity of around 75% at 1 fM (which is an enhancement by 200%) and a detection limit of 20 aM with a dynamic range from 20 aM to 1 pM. The detection limit which is achieved with the proposed label free sensor in physiological analyte using antibodies is lowered by more than three orders of magnitude compared to the existing reports.

Label-Free Biomolecule Detection in Physiological Solutions With Enhanced Sensitivity Using Graphene Nanogrids FET Biosensor

Recently, graphene nanogrid sensor has been reported to be capable of sub-femtomolar sensing of Hepatitis B (Hep-B) surface antigen in buffer. However, for such low concentration of Hep-B in serum, it has been observed during real-time operation that there is an overlap of around 50% in the drain-source current sensitivity values between different concentrations of the target biomolecule, in the range from 0.1 to 100 fM. This has been attributed to the fact that the concentration of non-specific antigen in serum being significantly higher than that of the target antigen, there is a considerable deviation in the number of captured target antigen for the same concentration. Further, this degree of overlap varies from one set to another set of sensor, depending on the statistical variations in the sensor fabrication process. This phenomenon challenges the quantification of target antigen for ultralow limit in physiological analyte. In this paper, we introduce probabilistic neural network (PNN) for quantification of Hep-B down to 0.1 fM in serum using graphene nanogrids field-effect transistor biosensor. The sensor has been operated in heterodyne mode in the frequency range of 100 kHz to 1 MHz applied between drain and source to overcome the problem of Debye screening effect. The application of PNN limits the quantification error within 10% in the range of 0.1 to 100 fM in contrast to 77% and 66% using polynomial fit and static neural network models, respectively. Further, the proposed methodology lowers the detection limit of Hep-B in serum by more than three orders of magnitude compared with the state-of-the-art, real-time, label-free sensors.

Risk prediction for oral potentially malignant disorders using fuzzy analysis of cytomorphological and autofluorescence alterations in habitual smokers

AIM

This study aims to develop a novel noninvasive method for early cancer trend diagnosis in habitual smokers by corroborating cytomorphological and autofluorescence alterations.

MATERIALS & METHODS

A total of 120 subjects were included and categorized into nonsmoker, smoker and clinically diagnosed oral potentially malignant disorder (OPMD) patients. Oral exfoliative epithelial cells were studied through differential interference contrast and fluorescence microscopy. Fuzzy trend analysis was performed using measured parameters for determining the risk factors among smokers.

RESULTS

The risk assessment in this study showed a positive correlation of smoking duration with early cancer risk factors with a correlation co-efficient of 0.86.

CONCLUSION

Alterations in cellular morphology and autofluorescence intensities showed positive correlation with OPMD. The present study will benefit to investigate early prediction of OPMD among susceptible individuals.

Graphene Nanogrids FET Immunosensor: Signal to Noise Ratio Enhancement

Recently, a reproducible and scalable chemical method for fabrication of smooth graphene nanogrids has been reported which addresses the challenges of graphene nanoribbons (GNR). These nanogrids have been found to be capable of attomolar detection of biomolecules in field effect transistor (FET) mode. However, for detection of sub-femtomolar concentrations of target molecule in complex mixtures with reasonable accuracy, it is not sufficient to only explore the steady state sensitivities, but is also necessary to investigate the flicker noise which dominates at frequencies below 100 kHz. This low frequency noise is dependent on the exposure time of the graphene layer in the buffer solution and concentration of charged impurities at the surface. In this paper, the functionalization strategy of graphene nanogrids has been optimized with respect to concentration and incubation time of the cross linker for an enhancement in signal to noise ratio (SNR). It has been interestingly observed that as the sensitivity and noise power change at different rates with the functionalization parameters, SNR does not vary monotonically but is maximum corresponding to a particular parameter. The optimized parameter has improved the SNR by 50% which has enabled a detection of 0.05 fM Hep-B virus molecules with a sensitivity of around 30% and a standard deviation within 3%. Further, the SNR enhancement has resulted in improvement of quantification accuracy by five times and selectivity by two orders of magnitude.

A review on amperometric-type immunosensors based on screen-printed electrodes

In this brief review, we summarize the recent research activities involved in the development of amperometric-type immunosensors based on screen-printed electrodes (SPEs). We focus on the underlying principle involved in these types of sensors, their fabrication and electrode surface modification. We also discuss the various factors involved in the designing of such immunosensors and how they affect their performances. Finally we provide an insight into the drawbacks associated with these SPEs.

Noise spectroscopy as an efficient tool for impedance based sub-femtomolar toxin detection in complex mixture using nanoporous silicon oxide

In this paper we demonstrate an efficient and non-interfering computational method for sub-femtomolar food toxin detection in complex mixture based on nanoporous silicon oxide impedance immunosensor by employing noise spectroscopy analysis at the peak frequency. It has been observed that the peak frequency (fp) values obtained from steady state impedance measurements cannot distinguish between solution with only the specific toxin, which is aflatoxin B1 (AfB1) and mixture of AfB1 with other non-specific toxins (NSTs), thus leading to erroneous quantification of AfB1 in complex mixture. On the other hand, the first cut-off frequency (fc) ranges obtained from noise spectroscopy analysis can qualitatively differentiate between solution containing only AfB1, AfB1 and NSTs and no AfB1. However fc values being very close for different concentration of AfB1 in pure solution and being overlapping for different mixtures cannot quantify AfB1 either in pure solution or in complex mixture. To address this problem, the proposed computational method first clusters the fp and fc values in 11 categories each using k-means clustering algorithm and then applies a simple combinational digital logic on the clusters of fps and fcs to obtain the final output, realizable with standard NAND-NOR gates. The output digital word differs only with AfB1 concentration and not with concentration of NSTs and is found to be capable of detecting sub-femtomolar AfB1 range down to 0.1 fg/ml not only in pure solution but also in complex mixture with as high as 1000 ng/ml NSTs. This is the most sensitive and selective report so far on electrochemical food toxin immunosensors.