Fin field-effect-transistor engineered sensor for detection of MDA-MB-231 breast cancer cells: A switching-ratio-based sensitivity analysis

The present study describes the utilization of a gallium-arsenide gate-stack gate-all-around (GaAs-GS-GAA) fin field-effect transistor (FinFET) to accomplish the electrical identification of the breast cancer cell MDA-MB-231 by monitoring the device switching ratio. The proposed sensor uses four nanocavities carved beneath the gate electrodes for enhanced detection sensitivity. MDA-MB-231 (cancerous) and MCF-10A (healthy) breast cells have a distinct dielectric constant, and it changes when exposed to microwave frequencies spanning across 200 MHz and 13.6 GHz, which modifies the electrical characteristics, allowing for early diagnosis. First, a percentage shift in the primary DC characteristics is presented to demonstrate the advantage of GS-GAA FinFET over conventional FinFET. The sensor measures the switching-ratio-based sensitivity, which comes out to be 99.72% for MDA-MB-231 and 47.78% for MCF-10A. The sensor was tested for stability and reproducibility and found to be repeatable and sufficiently stable with settling times of 55.51, 60.80, and 71.58 ps for MDA-MB-231 cells, MCF-10A cells, and air, respectively. It can distinguish between viable and nonviable cells based on electrical response alterations. The possibility of early detection of cancerous breast cells using Bruggeman's model is also discussed. Further, the impact of biomolecule occupancy and frequency variations on the device sensitivity is carried out. This study also explains how to maximize the sensing performance by adjusting the fin height, fin width, work function, channel doping, temperature, and drain voltage. Lastly, this article compared the proposed breast cancer cell detectors to existing literature to evaluate their performance and found considerable improvement. The findings of this research have the potential to establish GaAs-GS-GAA FinFET as a promising contender for MDA-MB-231 breast cancer cell detection.

Detection of biomolecules in dielectric modulated double metal below ferroelectric layer FET with improved sensitivity

In this work, we examined the double metal below ferroelectric layer FET that is double metal below negative capacitance field-effect transistor (DM-below-NCFET) for biosensing application and change in nanocavity gap with biomolecules as protein, ChO x (cholesterol oxidase), streptavidin, and uricase. For measuring the electrical characteristic and neutral biosensing such as threshold voltage, switching ratio (I on / I off ) of the device which is higher than one without molecules by 1.52 times, sensitivity of protein enhanced by 1.11 over without biomolecule, limit of detection of protein is higher by 1.012 times over without molecule, shift in potential have been researched for cavity length 10 nm. The biosensor indicated improved sensitivity for biomolecules with the rise in their dielectric parameter. Moreover, modulation of the length of the gap of cavity was too examined, exposing that its increment (from 8 to 12 nm) altogether upgraded the sensitivity of the proposed biosensor. Visual TCAD (Technology Computer-Aided Design) software is used for simulating all results. In general, the consequences of this examination represent that such DM-below-NCFET biosensors can display extreme sensitivity (1.11) at small drain voltage (0.4 V), empowering their utilization for biosensor applications to analyze different infections which involve low power, extreme density, and enhanced speed.

Assessment of distinct subcortical and cortical contributions to affect and approach/withdrawal behavior by means of resting-state functional connectivity approach

The relevance of subcortical structures and interhemispheric subcortical-cortical interactions among positive/negative affect and approach/withdrawal tendencies during resting-state are not fully understood. Gaining this knowledge may foster the know-how on their role in subsequent task-engagement and also on the interlinkage among affective measures and approach/withdrawal dichotomy. Here we performed a study based on Region of Interest (ROI)-based analysis and graph-theory estimates for global and subnetworks on a limited sample of healthy 50 male volunteers who recorded resting functional magnetic resonance imaging (fMRI) and self-reported measures of Positive and Negative Affect Schedule (PANAS) and BAS-BIS (Behavioral Activation System-Behavioral Inhibition System) scores. Our study's initial results of region of interest-to-region of interest (ROI-to-ROI) connectivity revealed the connectivity of subcortical neural substrates of PANAS and BAS-BIS scores with bilateralized cortical regions. However, on probing the lateralization of strength of degree measures of the cortical-regions vital for subcortical-cortical interaction, we found, for positive affect, a left-hemispheric proclivity. Further, higher connectivity within the left hemisphere was also observed for the left-lateralized critical cortical regions of negative affect. Our study also revealed the association of emotion and memory-related subcortical-cortical interactions in positive and negative affect. Right amygdala-right thalamus-frontotemporal cortical areas emanated in positive affect, and right putamen-left hippocampus-frontotemporal cortical regions network stemmed for negative affect. Then, we show the involvement of basal-ganglia structures in approach-withdrawal dichotomy with tight coupling of right-caudate, left-accumbens with anterior cingulate, and insular regions for withdrawal/inhibition system. Further, distinct involvement of the insula (posterior) in affective states while insula (anterior) in approach/withdrawal systems builds up for the existence of a feedback loop between affective and approach/withdrawal systems. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Effects of Neural Mechanisms of Pretask Resting EEG Alpha Information on Situational Awareness: A Functional Connectivity Approach

OBJECTIVE

In this study, the influence of pretask resting neural mechanisms on situational awareness (SA)-task is studied.

BACKGROUND

Pretask electroencephalography (EEG) information and Stroop effect are known to influence task engagement independently. However, neural mechanisms of pretask resting absolute alpha (PRAA) and pretask resting alpha frontal asymmetry (PRAFA) in influencing SA-task which is undergoing Stroop effect is still not understood.

METHOD

The study involved pretask resting EEG measurements from 18 healthy individuals followed by functional magnetic resonance imaging (fMRI) acquisition during SA-task. To understand the effect of pretask alpha information and Stroop effect on SA, a robust correlation between mean reaction time, SA Index, PRAA, and PRAFA were assessed. Furthermore, neural underpinnings of PRAA, PRAFA in SA-task, and functional connectivity were analyzed through the EEG-informed fMRI approach.

RESULTS

Significant robust correlation of reaction time was observed with SA Index (Pearson: r = .50, pcorr = .05) and PRAFA (Pearson: r = .63; pcorr = .01), respectively. Similarly, SA Index significantly correlated with PRAFA (Pearson: r = .56, pcorr = .01; Spearman: r = .61, pcorr = .007), and PRAA (Pearson: r = .59, pcorr = .005; Spearman: r = .59, pcorr = .002). Neural underpinnings of SA-task revealed regions involved in visual-processing and higher-order cognition. PRAA was primarily underpinned at frontal-temporal areas and functionally connected to SA-task regions pertaining to the emotional regulation. PRAFA has correlated with limbic and parietal regions, which are involved in integration of visual, emotion, and memory information of SA-task.

CONCLUSION

The results suggest a strong association of reaction time with SA-task and PRAFA and strongly support the hypothesis that PRAFA, PRAA, and associated neural mechanisms significantly influence the outcome of SA-task.

APPLICATION

It is beneficial to study the effect of pretask resting information on SA-task to improve SA.

Rapid detection of biomolecules in a dielectric modulated GaN MOSHEMT

Biosensors are the devices that find application in almost every field nowadays. In this paper, GaN MOSHEMT based biosensor is proposed for detection of biomolecules such as ChOx, protein, streptavidin and Uricase. The effect of biomolecule species on the performance parameters of the device has been studied. It has been observed that there is a significant increase in the drain current and gd is observed with the addition of biomolecule in the nanocavity. The electron concentration contour is studied which shows the rise of carrier concentration with biomolecule. Maximum positive shift is observed in threshold voltage for Uricase due to lowest dielectric constant. Similarly, the change in transconductance is also obtained with biomolecules. The effect of cavity dimensions on sensitivity is also studied. The maximum increase of 10% in channel potential is noted due biomolecule presence in the cavity. This device has shown good sensing and can be used for biosensing applications efficiently in addition to the high power performance of MOS-HEMTs.

Microstates-based resting frontal alpha asymmetry approach for understanding affect and approach/withdrawal behavior

The role of resting frontal alpha-asymmetry in explaining neural-mechanisms of affect and approach/withdrawal behavior is still debatable. The present study explores the ability of the quasi-stable resting EEG asymmetry information and the associated neurovascular synchronization/desynchronization in bringing more insight into the understanding of neural-mechanisms of affect and approach/withdrawal behavior. For this purpose, a novel frontal alpha-asymmetry based on microstates, that assess quasi-stable EEG scalp topography information, is proposed and compared against standard frontal-asymmetry. Both proposed and standard frontal alpha-asymmetries were estimated from thirty-nine healthy volunteers resting-EEG simultaneously acquired with resting-fMRI. Further, neurovascular mechanisms of these asymmetry measures were estimated through EEG-informed fMRI. Subsequently, the Hemodynamic Lateralization Index (HLI) of the neural-underpinnings of both asymmetry measures was assessed. Finally, the robust correlation of both asymmetry-measures and their HLI’s with PANAS, BIS/BAS was carried out. The standard resting frontal-asymmetry and its HLI yielded no significant correlation with any psychological-measures. However, the microstate resting frontal-asymmetry correlated significantly with negative affect and its neural underpinning’s HLI significantly correlated with Positive/Negative affect and BIS/BAS measures. Finally, alpha-BOLD desynchronization was observed in neural-underpinning whose HLI correlated significantly with negative affect and BIS. Hence, the proposed resting microstate-frontal asymmetry better assesses the neural-mechanisms of affect, approach/withdrawal behavior.