O1 Channels Research Articles

Occupancy Analysis of Water Molecules inside Channels within 25 Å Radius of the Oxygen-Evolving Center of Photosystem II in Molecular Dynamics Simulations.

At room temperature and neutral pH, the oxygen-evolving center (OEC) of photosystem II (PSII) catalyzes water oxidation. During this process, oxygen is released from the OEC, while substrate waters are delivered to the OEC and protons are passed from the OEC to the lumen through water channels known as the narrow or the O4 channel, broad or the Cl1 channel, and large or the O1 channel. Protein residues lining the surfaces of these channels play a critical role in stabilizing the hydrogen-bonding networks that assist in the process. We carried out an occupancy analysis to better understand the structural and possible substrate water dynamics in full PSII monomer molecular dynamics (MD) trajectories in both the S1 and S2 states. We find that the equilibrated positions of water molecules derived from MD-derived electron density maps largely match the experimentally observed positions in crystallography. Furthermore, the occupancy reduction in MD simulations of some water molecules inside the single-filed narrow channel also correlates well with the crystallographic data during a structural transition when the S1 state of the OEC advances to the S2 state. The overall reduced occupancies of water molecules are the source of their "vacancy-hopping" dynamic nature inside these channels, unlike water molecules inside an ice lattice where all water molecules have a fixed unit occupancy. We propose on the basis of findings in our structural and molecular dynamics analysis that the water molecule occupying a pocket formed by D1-D61, D1-S169, and O4 of the OEC could be the last steppingstone to enter into the OEC and that the broad channel may be favored for proton transfer.

Evolutionary diversity of proton and water channels on the oxidizing side of photosystem II and their relevance to function.

One of the reasons for the high efficiency and selectivity of biological catalysts arise from their ability to control the pathways of substrates and products using protein channels, and by modulating the transport in the channels using the interaction with the protein residues and the water/hydrogen-bonding network. This process is clearly demonstrated in Photosystem II (PS II), where its light-driven water oxidation reaction catalyzed by the Mn4CaO5 cluster occurs deep inside the protein complex and thus requires the transport of two water molecules to and four protons from the metal center to the bulk water. Based on the recent advances in structural studies of PS II from X-ray crystallography and cryo-electron microscopy, in this review we compare the channels that have been proposed to facilitate this mass transport in cyanobacteria, red and green algae, diatoms, and higher plants. The three major channels (O1, O4, and Cl1 channels) are present in all species investigated; however, some differences exist in the reported structures that arise from the different composition and arrangement of membrane extrinsic subunits between the species. Among the three channels, the Cl1 channel, including the proton gate, is the most conserved among all photosynthetic species. We also found at least one branch for the O1 channel in all organisms, extending all the way from Ca/O1 via the 'water wheel' to the lumen. However, the extending path after the water wheel varies between most species. The O4 channel is, like the Cl1 channel, highly conserved among all species while having different orientations at the end of the path near the bulk. The comparison suggests that the previously proposed functionality of the channels in T. vestitus (Ibrahim et al., Proc Natl Acad Sci USA 117:12624-12635, 2020; Hussein et al., Nat Commun 12:6531, 2021) is conserved through the species, i.e. the O1-like channel is used for substrate water intake, and the tighter Cl1 and O4 channels for proton release. The comparison does not eliminate the potential role of O4channel as a water intake channel. However, the highly ordered hydrogen-bonded water wire connected to the Mn4CaO5 cluster via the O4 may strongly suggest that it functions in proton release, especially during the S0 → S1 transition (Saito et al., Nat Commun 6:8488, 2015; Kern et al., Nature 563:421-425, 2018; Ibrahim et al., Proc Natl Acad Sci USA 117:12624-12635, 2020; Sakashita et al., Phys Chem Chem Phys 22:15831-15841, 2020; Hussein et al., Nat Commun 12:6531, 2021).

Assessment of electroencephalography modification by antipsychotic drugs in patients with schizophrenia spectrum disorders using frontier orbital theory: A preliminary study.

Schizophrenia is characterized by an abnormality in electroencephalography (EEG), which can be affected by antipsychotic drugs. Recently, the mechanism underlying these EEG alterations in schizophrenia patients was reframed from the perspective of redox abnormalities. The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) can be calculated using a computational method and may be useful for evaluating the antioxidant/prooxidant effect of antipsychotic drugs. Thus, we examined the association between the effects of antipsychotic monotherapy on quantitative EEG and HOMO/LUMO energy. We used medical report data including EEG results of psychiatric patients admitted to Hokkaido University Hospital. We extracted the EEG records of patients diagnosed with a schizophrenia spectrum disorder undergoing antipsychotic monotherapy during the natural course of treatment (n=37). We evaluated the HOMO/LUMO energy of all antipsychotic drugs using computational methods. Multiple regression analyses were used to examine the relationship between the HOMO/LUMO energy of all antipsychotic drugs and spectral band power in all patients. Statistical significance was set at p < 6.25 × 10-4 adjusted with Bonferroni correction. We showed that the HOMO energy of all antipsychotic drugs had weak positive correlations with delta- and gamma-band power (e.g., standardized β=0.617 for delta in the F3 channel, p=6.6 × 10-5 ; standardized β=0.563 for gamma in the O1 channel, p=5.0 × 10-4 ). Although there may be unexpected bias and confounding factors, our findings suggest that the effect of antipsychotic drugs on EEG may be related to their antioxidant actions.

A deep learning method for classification of steady-state visual evoked potentials in a brain-computer interface speller

ABSTRACT The main drawback of SSVEP-based BCIs is the lack of a classifier that categorizes SSVEPs with high accuracy and Information Transfer Rate (ITR). Addressing this, we proposed a deep convolutional neural network (CNN) for classifying a 40-class SSVEP. Time windows of length 2 and 3.5 seconds were used for training and testing the model by leave-one-subject-out cross-validation, using nine, three, and single-channel EEG. The proposed model reached 88.5% average accuracy for the nine-channel EEG with the mean and max ITR of 72 and 91.23 bpm, respectively. It outperformed the previous deep learning methods for SSVEP-based BCIs, in terms of accuracy and ITR. In the three-channel experiment the mean accuracy and ITR were 76.02% and 40.1 bpm. In single-channel implementation, O1 channel achieved 77.38 % average accuracy (highest) and the mean ITR was 57.51 bpm. The model showed promising performance to put this technology forward and make it more practical.

EEG Parameter Selection Reflecting the Characteristics of Internet Gaming Disorder While Playing League of Legends.

Game playing is an accessible leisure activity. Recently, the World Health Organization officially included gaming disorder in the ICD-11, and studies using several bio-signals were conducted to quantitatively determine this. However, most EEG studies regarding internet gaming disorder (IGD) were conducted in the resting state, and the outcomes appeared to be too inconsistent to identify a general trend. Therefore, this study aimed to use a series of statistical processes with all the existing EEG parameters until the most effective ones to identify the difference between IGD subjects IGD and healthy subjects was determined. Thirty subjects were grouped into IGD (n = 15) and healthy (n = 15) subjects by using the Young's internet addition test (IAT) and the compulsive internet use scale (CIUS). EEG data for 16 channels were collected while the subjects played League of Legends. For the exhaustive search of parameters, 240 parameters were tested in terms of t-test, factor analysis, Pearson correlation, and finally logistic regression analysis. After a series of statistical processes, the parameters from Alpha, sensory motor rhythm (SMR), and MidBeta ranging from the Fp1, C3, C4, and O1 channels were found to be best indicators of IGD symptoms. The accuracy of diagnosis was computed as 63.5-73.1% before cross-validation. The most interesting finding of the study was the dynamics of EEG relative power in the 10-20 Hz band. This EEG crossing phenomenon between IGD and healthy subjects may explain why previous research showed inconsistent outcomes. The outcome of this study could be the referential guide for further investigation to quantitatively assess IGD symptoms.

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ABSTRACT Introduction Applying the problem-based learning (PBL) method to the teaching of sports physiology. Objective This study explored the mechanism of the PBL method to improve the interest and learning effectiveness of students. Methods Twenty male students at the Physical Education College of Hubei Minzu University were randomly divided into a PBL group (10) and a traditional teaching method group (TTM). During the test, the subjects in the TTM group sat quietly listening to the experienced teacher, while the subjects in PBL group sat quietly and participated in a 20-minute group discussion under the guidance of the experienced teacher. Transcutaneous partial pressure of oxygen (TcPO2), microcirculatory blood perfusion (MBP), and alpha- and beta-band power were monitored at the beginning of and during the test. Results The mean of the PBL-group quiz score was significantly higher than that of the TTM group. In the PBL group, the alpha power of the students decreased statistically in the F3, T3, P3, and O1 channels and the beta power of the students increased statistically in the F7, F3, T3, C3, P3, and O1 as compared to the baseline values. Conclusion PBL can be an effective learning mechanism, since the students are actively engaged in the teaching of sports physiology. Level of Evidence I; Therapeutic studies - Investigating treatment results.

Structural dynamics in the water and proton channels of photosystem II during the S2 to S3 transition

Light-driven oxidation of water to molecular oxygen is catalyzed by the oxygen-evolving complex (OEC) in Photosystem II (PS II). This multi-electron, multi-proton catalysis requires the transport of two water molecules to and four protons from the OEC. A high-resolution 1.89 Å structure obtained by averaging all the S states and refining the data of various time points during the S2 to S3 transition has provided better visualization of the potential pathways for substrate water insertion and proton release. Our results indicate that the O1 channel is the likely water intake pathway, and the Cl1 channel is the likely proton release pathway based on the structural rearrangements of water molecules and amino acid side chains along these channels. In particular in the Cl1 channel, we suggest that residue D1-E65 serves as a gate for proton transport by minimizing the back reaction. The results show that the water oxidation reaction at the OEC is well coordinated with the amino acid side chains and the H-bonding network over the entire length of the channels, which is essential in shuttling substrate waters and protons.

Single-Channel Selection for Detecting Steady-State Visual Evoked Potentials in a Brain-Computer Interface Speller

Purpose: Brain-Computer Interface (BCI) provides a secondary communication pathway for patients with neuromuscular diseases such as amyotrophic lateral sclerosis (ALS) or brainstem stroke in which they are almost incapacitated to move or talk. BCI enacts neural oscillations to generate a command signal for machines to operate desired tasks instead of patients. Steady-State Visual Evoked Potential (SSVEP) is the brain response to a visual stimulus, with the same frequency as its eliciting signal (or its harmonics), that has been widely used in BCI environments. In order to provide a more convenient situation for BCI users, we aim to find the best single-channel EEG, which results in the highest accuracy for detecting SSVEP. Materials and Methods: We developed a Deep Convolutional Neural Network with single-channel EEG as input to classify a 40-class SSVEP; each class represents a stimulus, which has been acquired from 35 subjects. We used 3.5 s windows of the data (Trials of 3.5 seconds length for each class) to train our model and leave-one-subject-out cross-validation for the testing. Results: The proposed method resulted in the average classification accuracy of 74.30%±20.85 and Information Transfer Rate (ITR) of 57.51 bpm which outperforms the previous single-channel SSVEP BCIs in terms of ITR. Also, the O1 channel achieved the best performance criteria among the channels in the occipital and parietal lobes, which seems reasonable according to previous researches for finding the location of neurons, responsible for visual tasks in the brain. Conclusion: In this study, we dedicated our efforts to reduce the number of EEG channels to a single channel while proposing a deep learning strategy for an SSVEP-based BCI speller to make it more feasible for patients whose lives are dependent on such systems. The overall results, although not ideal, open a new promising window toward a feasible BCI system.

Power Spectral Changes of Quantitative EEG in the Subjective Cognitive Decline: Comparison of Community Normal Control Groups.

PurposeThe purpose of this study is to compare and analyze the power spectral changes between subjective cognitive decline (SCD) subjects and normal controls (NC) while checking the preclinical stage of AD in the SCD subjects and to use the derived data for biomarker research that can diagnose early-stage AD in the future.MethodsWe recruited 23 SCD patients and 23 normal control subjects and QEEG analysis including power spectral density (PSD) and source-level analysis were performed. An automated preprocessing procedure and statistical analysis were performed by iSync Brain® (iMediSync Inc., Republic of Korea) (https://isyncbrain.com/) using the international standard 10–20 system (19 electrodes).ResultsAbsolute PSD, there was no statistically significant difference in all of the EEG power measurements of the 19 channels. In the relative PSD analysis, the average delta band power of the SCD group was significantly higher in Fp2, F4, and F8 than NC. Alpha1 band power of the O1 channel was 22.56±16.05 for the SCD group and 33.19±19.05 for the NC (p-value <0.05). Source-level analysis did not show a statistically significant difference.ConclusionSCD subjects showed a partial increase of delta waves in the frontal lobe region and a partial decrease in alpha1, a fast wave in the occipital region, compared to the NC. SCD is considered one of the earliest clinical symptoms of AD and it is predicted to be related to minor nerve damage. We were able to observe the power spectral changes in SCD subjects in this cross-sectional study, a large number of subjects and longitudinal studies are needed to evaluate their predictability for future deterioration such as conversion to MCI.

An Event-related Potential Study of Second Language Semantic and Syntactic Processing: Evidence From the Declarative/Procedural Model.

Introduction:This study examined the effect of proficiency level on the second Language (L2) syntactic and semantic processing by addressing the role of procedural and declarative memory systems in light of the Declarative/Procedural (DP) model. The primary purpose was to determine to what extent proficiency accounts for native-like language processing in L2 in adult bilinguals who learned English (L2) after the age of 15 under explicit instruction.Methods:Using a mixed-method design and an oddball violation paradigm, we examined the functional neural correlates of syntactic and semantic processing in two groups of Persian-English bilinguals (L1=Persian, L2=English; N=10 high-proficient, N=10 pre-intermediate levels; Gender= Female; mean age=25.50 years, SD = 5.09 years, age range = 19–35 years of age) across 6 different conditions. They included a visual stimulus task of 240 English sentences with three different experimental conditions (violated regular past forms or phrase structure rules or final-word semantic violation) and three control conditions (sets of correct sentences for each experimental condition). Both groups started learning English late (age of onset=15+) and under an explicit learning context. To evaluate the effect of L2 proficiency, Event-related potentials (ERPs) to target words in each condition were elicited across the N400 time window (300–500 ms) and the P600 time window (500–700 ms).Results:Results showed different cortical responses in the two groups. Upon processing the violated forms, high-proficient subjects showed more native-like patterns of scalp activity in both lexical-semantic and syntactic processing. In contrast, less proficient learners have shown delayed onsets and or peaks of components, reduced amplitudes, or absent components in some regions. For instance, the difference in N400 amplitude for the incorrect regular past conditions was observed only in the pre-intermediate (PI) subjects in the O1 channel. This finding is compatible with the DP Model in that at lower levels of L2 proficiency, the participants show N400s or N400-like posterior negativities instead of Anterior Negativities (ANs). This finding shows the initial reliance on the declarative memory system for syntactic processing at lower levels of L2.Conclusion:Our findings suggest that attained proficiency was a more determinant factor in the L1-like cortical representation of L2 than the age of acquisition and or the type of instruction/context. Several brain areas, similar to those observed for L1, were activated during L2 syntactic processing in high-proficient subjects addressing their reliance on the procedural memory system for syntactic processing to gain more proficiency. For instance, our results showed a significant difference in N400 amplitude for the incorrect regular past conditions in O1 for the PI subjects, which shows the initial reliance on the declarative memory system for syntactic processing at lower levels of L2.

Fractal Dimension and Power Spectrum of Electroencephalography Signals of Sleep Inertia State

Human brain functions and behaviors during the transition state between sleep and wakefulness are not similar to these at alert wakefulness state. The transition state, which is called sleep inertia, has many unpleasant and dangerous effects on many situations that require full attention and fast response, such as driving. Within 30 minutes after waking up from sleep, the driver’s performance might be impaired due to the sleep inertia effects. Groups of drivers that may drive within a short period after waking up are: workers who travel early in the morning; secondary drivers of long distance bus who sleep in the bus before taking over the job from the primary drivers; night travelers; and long haul truck drivers who stop at the rest area to sleep for a while and continue driving. Previous research used subjective self-report measurement, eye tracker, and a driving simulator to analyze the driver’s performance during sleep inertia state. The physiological measures of the drivers, such as their brain signals have also been studied. However, the brain signals which are recorded in Electroencephalography (EEG) are typically analyzed in perspective of the power spectrum. This study proposes a hybrid of EEG features, which are fractal dimension and power spectrum, supported by behavioral data which is the driver’s reaction time. This study finds the features that significantly differentiate between normal and sleep inertia drivers based on the classification accuracy and p-value of the statistical ANOVA. This study compares the results with other features (power spectrum, variance, sample entropy), and between EEG channel. This study record the EEG from the Fz, T7, Cz, Pz, and O1 channels. This study uses subjective and behavioral measurements to support the results. The results show that the hybrid of fractal dimension estimated by Katz’s algorithm at the O1 channel and delta power from the Fz channel, and alpha power from the O1 channel, have better classifications than the power spectrum alone. Furthermore, the reaction time recorded from the LED reaction time task shows a significant difference between drivers with sleep inertia and normal (alert) drivers.

Using Theme-based Narrative Construct of Images as Passwords: Implementation and Assessment of Remembered Sequences

Secret keys connecting users to the system is the heart of cryptographic systems. With the recent wars, several cryptographic systems that use alpha-numeric passwords have been known to be vulnerable to many attacks. Image based password systems were introduced to add more complexity and security. This paper employs human uniqueness of narrative skills on an image-based password system with focus on theme in the password generation process. To generate the secret password, a specially designed computer game was used. We used narrative constructs composed of cartoon image sequences to generate user-specific secret key. The durability of generated passwords and the authentication process while assessing the reconstruction process by a potential hacker was verified. Under imposed psychological duress, users failed retrieving the password sequence suggesting the reliability as an anti-coercive attack cybersecurity tool. A set of experiments were used to analyze user behavior behind the image-based password system. EEG measurements demonstrated increased activity of α rhythms in F3 and FC5 channel bins and augmented levels of β rhythms in F3 and O1 channels, suggesting users added personalization to authentication more than in alpha-numeric password-based logins.

Measurement of Visual Eeg Signals Stimulated By Yellow Color Photons of Specific Wave Length At Different Intensities

Electroencephalography (EEG) is a diagnostic tool that records the electrical activity of the brain using numerous electrodes placed on various regions to the scalp, or in special cases on the cortex. The resulting traces are known as an electroencephalogram and represent so-called brainwaves.There are many types of stimulators (physical, chemical , and mechanical )that are affect the special senses sensitive areas in the brain which are collected as electrical signals. This research is concerned with photo stimulator (yellow color with frequency of ≈ 515 THz that is transmitted by visual nerve and the generated electrical signal waves are recorded by EEG. The sample of the research consists of 18 normal vision volunteers divided equally between males and females. All precautions of wave interference or artifacts that are due to physiological or external electrical source are taken into account and minimized into the ignored level.The results clearly showed that, the mean relative action potential amplitude recorded from O2 for males were the same in low and higher intensities ; when intensity was increased than that recorded from O1, and O2 channel for females also the same at low intensities then increased with increasing intensity than that recorded from O1.The fitting equation of the mean relative action potential amplitude versus the intensity of O1 and O2 channels for males are y = 0.053x2-3.161x + 47.23 with R2 = 0.969 and y = 0.044x2- 2.619x + 39.19 with R2 = 0.987, and for females are y = 0.046x2 – 2.693x + 39.60 with R2 = 0.894 and y = 0.043x2- 2.483x + 36.59 with R2 = 0.880 respectively.To compare the EEG electrical signals that are recorded from O1 and O2 channels for males and females, the mean relative action potential amplitudes are higher in males than in females for both channels. The deduced fitting curves for males O1 channel is y =0.046x2 – 2.693x + 39.60 with R2 = 0.894 and for females, O1 channel y =0.043x2 - 2.483x + 36.59 with R2 = 0.880 and that for male O2 channel is y = 0.044x2 – 2.619x + 39.19 with R2 = 0.987 and for female O2 channel y = 0.05x2 – 3.61x + 47.23 with R2 = 0.969.

Detrended fluctuation analysis of resting EEG in depressed outpatients and healthy controls

Objective Recent findings have demonstrated that the EEG possesses long-range temporal (auto-) correlations (LRTC) in the dynamics of broad band oscillations. The analysis of LRTC provides a quantitative index of statistical dependencies in oscillations on different time scales. We analyzed LRTC in resting EEG signals in depressed outpatients and healthy controls. Methods The participants in this study were 11 non-depressed, age-matched controls, and 11 unmedicated unipolar depressed patients. EEG data were obtained from each participant during 5-min resting baseline periods with eyes closed and then analyzed with detrended fluctuation analysis (DFA), a scaling analysis method that quantifies a simple parameter to represent the correlation properties of a time series. The scaling exponent, the result of DFA, provides a quantitative measure of LRTC from the EEG. Results The present study demonstrates that all the scaling exponents in depressed patients and healthy controls were greater than 0.5 and less than 1.0, regardless of condition. Furthermore, the scaling exponents of depressed patients have relatively higher values in whole brain regions compared to healthy controls, with significant differences at F3, C3, T3, T4 and O1 channels ( p < 0.05). Finally, a significant linear correlation was observed between the severity of depression and the scaling exponent over most of the channels, except O2. Conclusions These results suggest that the brain affected by a major depressive disorder shows slower decay of the LRTC, and that the persistence of the LRTC of EEG in depressed patients was associated with the severity of depression over most of the cortical areas. Significance The DFA method may broaden our understanding of the psychophysiological basis of depression.