Detecting Fear of Heights Response to a Virtual Reality Environment Using Functional Near-Infrared Spectroscopy

To enable virtual reality exposure therapy (VRET) that treats anxiety disorders by gradually exposing the patient to fear using virtual reality (VR), it is important to monitor the patient's fear levels during the exposure. Despite the evidence of a fear circuit in the brain as reflected by functional near-infrared spectroscopy (fNIRS), the measurement of fear response in highly immersive VR using fNIRS is limited, especially in combination with a head-mounted display (HMD). In particular, it is unclear to what extent fNIRS can differentiate users with and without anxiety disorders and detect fear response in a highly ecological setting using an HMD. In this study, we investigated fNIRS signals captured from participants with and without a fear of height response. To examine the extent to which fNIRS signals of both groups differ, we conducted an experiment during which participants with moderate fear of heights and participants without it were exposed to VR scenarios involving heights and no heights. The between-group statistical analysis shows that the fNIRS data of the control group and the experimental group are significantly different only in the channel located close to right frontotemporal lobe, where the grand average oxygenated hemoglobin Δ[HbO] contrast signal of the experimental group exceeds that of the control group. The within-group statistical analysis shows significant differences between the grand average Δ[HbO] contrast values during fear responses and those during no-fear responses, where the Δ[HbO] contrast values of the fear responses were significantly higher than those of the no-fear responses in the channels located towards the frontal part of the prefrontal cortex. Also, the channel located close to frontocentral lobe was found to show significant difference for the grand average deoxygenated hemoglobin contrast signals. Support vector machine-based classifier could detect fear responses at an accuracy up to 70% and 74% in subject-dependent and subject-independent classifications, respectively. The results demonstrate that cortical hemodynamic responses of a control group and an experimental group are different to a considerable extent, exhibiting the feasibility and ecological validity of the combination of VR-HMD and fNIRS to elicit and detect fear responses. This research thus paves a way toward the a brain-computer interface to effectively manipulate and control VRET.

A Novel Insight into Screening for Antioxidant Peptides from Hazelnut Protein: Based on the Properties of Amino Acid Residues

This study used the properties of amino acid residues to screen antioxidant peptides from hazelnut protein. It was confirmed that the type and position of amino acid residues, grand average of hydropathy, and molecular weight of a peptide could be comprehensively applied to obtain desirable antioxidants after analyzing the information of synthesized dipeptides and BIOPEP database. As a result, six peptides, FSEY, QIESW, SEGFEW, IDLGTTY, GEGFFEM, and NLNQCQRYM were identified from hazelnut protein hydrolysates with higher antioxidant capacity than reduced Glutathione (GSH) against linoleic acid oxidation. The peptides having Tyr residue at C-terminal were found to prohibit the oxidation of linoleic acid better than others. Among them, peptide FSEY inhibited the rancidity of hazelnut oil very well in an oil-in-water emulsion. Additionally, quantum chemical parameters proved Tyr-residue to act as the active site of FSEY are responsible for its antioxidation. This is the first presentation of a novel approach to excavating desired antioxidant peptides against lipid oxidation from hazelnut protein via the properties of amino acid residues.

Electroencephalogram Source Imaging and Brain Network Based Natural Grasps Decoding

Studying the decoding process of complex grasping movement is of great significance to the field of motor rehabilitation. This study aims to decode five natural reach-and-grasp types using sources of movement-related cortical potential (MRCP) and investigate their difference in cortical signal characteristics and network structures. Electroencephalogram signals were gathered from 40 channels of eight healthy subjects. In an audio cue-based experiment, subjects were instructed to keep no-movement condition or perform five natural reach-and-grasp movements: palmar, pinch, push, twist and plug. We projected MRCP into source space and used average source amplitudes in 24 regions of interest as classification features. Besides, functional connectivity was calculated using phase locking value. Six-class classification results showed that a similar grand average peak performance of 49.35% can be achieved using source features, with only two-thirds of the number of channel features. Besides, source imaging maps and brain networks presented different patterns between each condition. Grasping pattern analysis indicated that the modules in the execution stage focus more on internal communication than in the planning stage. The former stage was related to the parietal lobe, whereas the latter was associated with the frontal lobe. This study demonstrates the superiority and effectiveness of source imaging technology and reveals the spread mechanism and network structure of five natural reach-and-grasp movements. We believe that our work will contribute to the understanding of the generation mechanism of grasping movement and promote a natural and intuitive control of brain–computer interface.

PERG adaptation for detection of retinal ganglion cell dysfunction in glaucoma: a pilot diagnostic accuracy study

It has been previously demonstrated that the adaptive phase changes of steady-state pattern electroretinogram (SS-PERG), recorded during 4-min presentation of patterned stimuli, are reduced in glaucoma suspects and patients compared to normal subjects. Our study aims at testing the hypothesis that adaptive changes of SS-PERG, recorded using the novel optimized Next Generation PERG (PERGx) protocol, differ between glaucoma patients and controls. In this pilot cross-sectional study, we included 28 glaucoma patients and 17 age-matched normal subjects. Both patients and controls underwent a full ophthalmologic examination, visual field testing, OCT and PERGx. The PERGx signal was sampled over 2 min (providing 1 noise and 9 signal packets) in response to alternating gratings generated on an OLED display. PERGx amplitude and phase were analyzed to quantify adaptive changes over recording time. Receiver operating characteristic (ROC) curves were used to study the diagnostic accuracy of PERGx parameters in distinguishing glaucoma patients from normal subjects. PERGx amplitude and phase data showed declining trends in both groups. PERGx amplitude slope and grand-average vector amplitude and phase were significantly different in patients compared to controls (p < 0.01), whereas phase angular dispersion was greater in patients but not significantly different between the two groups. The area under the ROC curves were 0.87 and 0.76 for PERGx amplitude slope and grand-average vector amplitude, and 0.62 and 0.87 for PERGx angular dispersion and grand-average vector phase, respectively. The PERGx paradigm resulted highly accurate in detecting the reduction of amplitude adaptive changes in glaucoma patients, presumably due to the loss of functional retinal ganglion cell autoregulation. Thus, PERG adaptation, recorded by this new protocol, might be helpful in the identification and diagnosis of early glaucomatous dysfunction.

Cloning, Amplified Expression and Bioinformatics Analysis of a Putative Nucleobase Cation Symporter-1 (NCS-1) Protein From Rhodococcus erythropolis

The Rhodococcus erythropolis gene DYC18_RS18060 (1437 bp) putatively codes for a secondary transporter of the Nucleobase Cation Symporter-1 (NCS-1) protein family (478 amino acids). The DYC18_RS18060 gene was successfully cloned from R. erythropolis genomic DNA with addition of EcoRI and PstI restriction sites at the 5′ and 3′ ends, respectively, using PCR technology. The amplified gene was introduced into IPTG-inducible plasmid pTTQ18 immediately upstream of the sequence coding for a His6-tag. The construct was transformed into Escherichia coli BL21(DE3), then amplified expression of the DYC18_RS18060-His6 protein was achieved with detection by SDS-PAGE and western blotting. Computational methods predicted that DYC18_RS18060 has a molecular weight of 51.1 kDa and isoelectric point of 6.58. The protein was predicted to be hydrophobic in nature (aliphatic index 113.24, grand average of hydropathicity 0.728) and to form twelve transmembrane spanning α-helices with both N- and C-terminal ends at the cytoplasmic side of the membrane. Whilst database sequence similarity searches and phylogenetic analysis suggested that the substrate of DYC18_RS18060 could be cytosine, this was not certain based on comparisons of residues involved in substrate binding in experimentally characterised NCS-1 proteins. This study has laid foundations for further structural and functional studies of DYC18_RS18060 and other NCS-1 proteins. Copyright(c) The Authors

GENOME-WIDE IDENTIFICATION AND COMPUTATIONAL CHARACTERIZATION OF THE NUCLEAR FACTOR-YC SUB-UNITS IN GRAIN AMARANTH (Amaranthus hypochondriacus)

Nuclear factor-Y (NF-Y) has been known as one of the plant-specific transcription factors that play key roles in numerous biological processes during the growth and development of plant species. In this study, a comprehensive analysis of NF-YC sub-units in grain amaranth (Amaranthus hypochondriacus) was carried out based on the bioinformatics approaches. Firstly, a total of five members of the NF-YC sub-units was reported in the grain amaranth. Its structural analyses revealed that the NF-YC sub-units were variable in physic-chemical properties, like protein sizes, molecular masses, isoelectric point, instability index, and grand average of hydropathy. Of our interest, the expression profiles of genes encoding NF-YC sub-units in various tissues\organs during the growth and development of grain amaranth. We found that three genes, including AhNF-YC01, AhNF-YC04, and AhNF-YC05 were highly expressed in leaf, root, floral, immature seed, and stem tissues. Interestingly, AhNF-YC05 was exclusively expressed in leaf and stem tissues. Taken together, our study could provide a solid understanding for further functional characterization of genes encoding NF-YC sub-units in grain amaranth.

Corticomuscular and Intermuscular Coupling in Simple Hand Movements to Enable a Hybrid Brain–Computer Interface

Hybrid Brain–Computer Interfaces (BCIs) for upper limb rehabilitation after stroke should enable the reinforcement of “more normal” brain and muscular activity. Here, we propose the combination of corticomuscular coherence (CMC) and intermuscular coherence (IMC) as control features for a novel hybrid BCI for rehabilitation purposes. Multiple electroencephalographic (EEG) signals and surface electromyography (EMG) from 5 muscles per side were collected in 20 healthy participants performing finger extension (Ext) and grasping (Grasp) with both dominant and non-dominant hand. Grand average of CMC and IMC patterns showed a bilateral sensorimotor area as well as multiple muscles involvement. CMC and IMC values were used as features to classify each task versus rest and Ext versus Grasp. We demonstrated that a combination of CMC and IMC features allows for classification of both movements versus rest with better performance (Area Under the receiver operating characteristic Curve, AUC) for the Ext movement (0.97) with respect to Grasp (0.88). Classification of Ext versus Grasp also showed high performances (0.99). All in all, these preliminary findings indicate that the combination of CMC and IMC could provide for a comprehensive framework for simple hand movements to eventually be employed in a hybrid BCI system for post-stroke rehabilitation.

Designing of a novel multisubunit vaccine against Nipah virus structural proteins: A reverse vaccinology approach

Background The significant public health risk posed by NiV zoonosis and the lack of effective countermeasures against the intermittent outbreaks of the disease in the South and Southeast Asia region have entailed an imperative search for a protective vaccine to prevent or mitigate its epidemic potentiality. This is an endeavor to design an effective, safe multisubunit vaccine using an in silico reverse vaccinology approach. Methods The epitopes used for the construction of the candidate vaccine were meticulously predicted from five viral structural proteins (G, F, M, N, P) using several immunoinformatics tools to assess different epitope characteristics, namely, VaxiJen server for antigenicity, IEDB immunogenicity tool for immunogenicity, AlgPred server for allergenicity, ToxinPred for toxigenicity, IFNepitope server for interferon-gamma induction, Protparam server for physicochemical properties, GROMACS for simulation and simulation dynamics analysis, and finally, SnapGene tool for molecular cloning. Results The proposed vaccine molecule consisted of 501 amino acids, encompassing 7 B cell epitopes, 14 CTL epitopes, and 4 HTL epitopes. The physiochemical parameters of the vaccine construct showed a molecular weight of 54.6 kDa, an acidic stable molecule with an instability index of 38.3, aliphatic index of 62.89, and grand average of hydropathicity of -0.476. Moreover, the docking results and simulation dynamics of the vaccine molecule and TLR-3 showed global energy of 1.58 Kcal/mol, atomic contact energy of 2.98 Kcal/mol, and RMSD of 0.65 nm. The radius gyration showed a relatively steady value throughout the simulation period. a suggestive result of a stable compact structure and a promisingly effective vaccine construct. Conclusion In summary, the overall results of the multi-subunit vaccine molecule are suggestive of a promisingly effective vaccine against NiV infection in humans with a relatively stable compact structure, however, further experimental validation and assessment of pathogenic priming and autoimmunity induction are recommended.

Decoding Different Reach-and-Grasp Movements Using Noninvasive Electroencephalogram

Grasping is one of the most indispensable functions of humans. Decoding reach-and-grasp actions from electroencephalograms (EEGs) is of great significance for the realization of intuitive and natural neuroprosthesis control, and the recovery or reconstruction of hand functions of patients with motor disorders. In this paper, we investigated decoding five different reach-and-grasp movements closely related to daily life using movement-related cortical potentials (MRCPs). In the experiment, nine healthy subjects were asked to naturally execute five different reach-and-grasp movements on the designed experimental platform, namely palmar, pinch, push, twist, and plug grasp. A total of 480 trials per subject (80 trials per condition) were recorded. The MRCPs amplitude from low-frequency (0.3–3 Hz) EEG signals were used as decoding features for further offline analysis. Average binary classification accuracy for grasping vs. the no-movement condition peaked at 75.06 ± 6.8%. Peak average accuracy for grasping vs. grasping conditions of 64.95 ± 7.4% could be reached. Grand average peak accuracy of multiclassification for five grasping conditions reached 36.7 ± 6.8% at 1.45 s after the movement onset. The analysis of MRCPs indicated that all the grasping conditions are more pronounced than the no-movement condition, and there are also significant differences between the grasping conditions. These findings clearly proved the feasibility of decoding multiple reach-and-grasp actions from noninvasive EEG signals. This work is significant for the natural and intuitive BCI application, particularly for neuroprosthesis control or developing an active human–machine interaction system, such as rehabilitation robot.

In Silico prediction and Comparative Modeling of proteins in Creeping Fig (Ficus pumila) plant

In the present study, the Ficus pumila have taken to analyze the proteins by their preliminary characters from the database and predicted vital role of different sequences. The F. pumila (Creeping fig) is a prostrate/climbing shrub, experiments proved various active phytochemicals and antioxidant, antimicrobial, antimutagenic, analgesic, anti-inflammatory, antiproliferative, hypoglycemic, hypolipidemic, antihyperprolactinemic, anticholinesterase, nephroprotective properties. In addition to all metabolites, it also constitutes specific proteins that were evaluated through insilico homology modeling. Though it is considered as a poisonous weed, the protein present in this plant is evaluated by physicochemical, phylogeny and amino acid proportions by protparam, Swiss model, SOPMA, Clustal omega tools to describe its structural features and to understand molecular function. The computed theoretical isoelectric point (pI) found to be more than 7 indicates basic nature of proteins. The aliphatic index ranges 67-113 indicates thermal stability of proteins. The predicted Grand average hydropathy(GRAVY) shows possibilities of enhanced interaction of these proteins with water by lowest value. Functional analysis of these proteins was performed by SOSUI server which predicted transmembrane helix and solubility. Secondary structure analysis was carried out by SOPMA revealed that Alpha helix and random coil dominated followed by extended strand, and beta turns among secondary structure elements. The modelling of three-dimensional structure of proteins was performed by Swiss model. The model was validated using protein structure checking tool- VADAR. Particularly, NAD(P)H –quinoneoxidoreductase and Glyceraldehyde-3-phosphate dehydrogenase structures were analysed by phylogenetic analysis to trace relationship and reported. The results suggesting its possible role in cellular and metabolic functions.