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Background : The study examines the effectiveness of both neurofeedback and motor-imagery brain-computer interface (BCI) training, which promotes self-regulation of brain activity, using low-cost electroencephalography (EEG)-based wearable neurotechnology outside a clinical setting, as a potential treatment for post-traumatic stress disorder (PTSD) in Rwanda. Methods : Participants received training/treatment sessions along with a pre- and post- intervention clinical assessment, (N = 29; control n = 9, neurofeedback (NF, 7 sessions) n = 10, and motor-imagery (MI, 6 sessions) n = 10). Feedback was presented visually via a game. Participants were asked to regulate (NF) or intentionally modulate (MI) brain activity to affect/control the game. Results : The NF group demonstrated an increase in resting-state alpha (8-12Hz) bandpower following individual training sessions, termed alpha ‘rebound’ (Pz channel, p = 0.025, all channels, p = 0.024), consistent with previous research findings. This alpha ‘rebound’, unobserved in the BCI group, produced a clinically relevant reduction in symptom severity in NF group, as revealed in four of seven clinical outcome measures: PCL-5 (p = 0.005), PTSD screen (p = 0.005), HTQ (p = 0.005), and CD-RISC (p = 0.041). Limitations : Data collection took place in environments that posed difficulties in controlling environmental factors. Nevertheless, this limitation improves ecological validity, as neurotechnology treatments must be deployable outside controlled environments, to be a feasible technological treatment. Conclusions : The study produced the first evidence to support low-cost, neurotechnological solution for neurofeedback as an effective treatment of PTSD for victims of acute trauma in conflict zones in a developing country.

The formation of complexes may be used for the development of delivery systems in foods field. The aim of this study was to explore the interaction mechanism between Lentinus edodes mycelia polysaccharide (LMP) and bovine lactoferrin (BLF), and the activity of LMP-BLF complex to inhibit oxidative stress in islet β cells. The interaction mechanisms of LMP with BLF were investigated with multi-spectroscopic techniques. The multi-spectroscopic analysis result showed that LMP bound with BLF by van der Waals force and hydrogen bond. The quenching mechanism of BLF with LMP was static quenching. Cell viability, reactive oxygen species (ROS) level, apoptosis and the related signaling pathways were detected with thiazolyl blue tetrazolium bromide (MTT) assay, 2,7-Dichlorofluorescin diacetate (DCFH-DA) staining, Hoechst 33258 staining and Western blot methods respectively. The complex alleviated apoptosis induced by hydrogen peroxide (H2O2), and inhibited oxidative stress via MAPK pathways in MIN6 cells. In addition, the complex was able to promote glucose uptake in HepG2 cells. These results will broaden our understanding of LMP-BLF complexes and the applications of polysaccharide-protein complexes in the foods field.

Background: Electroencephalography (EEG) -based motor-imagery brain-computer interface (MI-BCI) systems can facilitate training of wilful modulation of sensorimotor oscillations in patients with prolonged disorders of consciousness, potentially enabling empirical assessment of awareness and movement independent responses and question answering. Methods: A multistage, ten session, protocol was evaluated with twenty-four (N = 24) patients who have prolonged disorders of consciousness (PDoC) (unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS)) or locked-in syndrome (LIS). Phase one assessed capacity to modulate brain activity and thus detect awareness, phase two involved motor-imagery training with neurofeedback, and phase three assessed patients’ motor-imagery response to closed questions, categorised to assess biographical, numerical, logical, and situational awareness. Results: Patients from all groups show significant capacity to modulate brain activity and respond to closed questions with motor imagery. A conservative approach to statistical testing was necessarily taken, due to a limited sample size and uneven groups. However, significant group differences were observed indicating patients with LIS outperform patients with PDoC. As patients diagnosed with UWS present evidence of command following in this protocol and thus could have MCS, significant differences between UWS and MCS across a range of tests were inconclusive although, in general, group performances are correlated with the level of awareness associated with clinical diagnosis. Conclusions: We conclude that the proposed multistage protocol involving progression from motor imagery training with neurofeedback to closed question responses under the correct conditions may be effective for movement-independent consciousness profiling in prolonged disorders of consciousness.

Background The brain–computer interface (BCI) race at the Cybathlon championship, for people with disabilities, challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and results of the Ulster University BCI Team pilot who has tetraplegia and was trained to use an electroencephalography (EEG)-based BCI intermittently over 10 years, to compete in three Cybathlon events. Methods A multi-class, multiple binary classifier framework was used to decode three kinesthetically imagined movements (motor imagery of left arm, right arm, and feet), and relaxed state. Three game paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon Race: BrainDriver. An evaluation of the pilot’s performance is presented for two Cybathlon competition training periods—spanning 20 sessions over 5 weeks prior to the 2019 competition, and 25 sessions over 5 weeks in the run up to the 2020 competition. Results Having participated in BCI training in 2009 and competed in Cybathlon 2016, the experienced pilot achieved high two-class accuracy on all class pairs when training began in 2019 (decoding accuracy > 90%, resulting in efficient NeuroSensi and Triad game control). The BrainDriver performance (i.e., Cybathlon race completion time) improved significantly during the training period, leading up to the competition day, ranging from 274–156 s (255 ± 24 s to 191 ± 14 s mean ± std), over 17 days (10 sessions) in 2019, and from 230–168 s (214 ± 14 s to 181 ± 4 s), over 18 days (13 sessions) in 2020. However, on both competition occasions, towards the race date, the performance deteriorated significantly. Conclusions The training regime and framework applied were highly effective in achieving competitive race completion times. The BCI framework did not cope with significant deviation in electroencephalography (EEG) observed in the sessions occurring shortly before and during the race day. Changes in cognitive state as a result of stress, arousal level, and fatigue, associated with the competition challenge and performance pressure, were likely contributing factors to the non-stationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration not registered

The ongoing discussion on the diagnosis and tactics of surgical treatment of painful forms of adhesions of the abdominal cavity and adhesive intestinal obstruction testifies to the persistent urgency of this problem. The presence of a postoperative scar and recurrent abdominal pain are interpreted by surgeons and gastroenterologists as adhesive disease, with the appointment of the same type of treatment. At the same time, patients have a reduced critical attitude to their condition, which leads them to late seeking medical help. For the occurrence of the adhesion process, a long-term effect of a complex of factors is necessary, an important place among which is blood supply, oxygen access to tissues and peristalsis in the early postoperative period. The most effective methods of treatment and prevention of intestinal obstruction are low-traumatic surgical technologies. There was no statistically significant difference between open and laparoscopic adhesiolysis in the number of intraoperative intestinal injuries, wound infections and mortality. Laparoscopic operations have fewer general and pulmonary complications than open ones. Reducing fibroblast proliferation, minimizing hypoxia and inflammation are a new preventive solution to the problem of adhesion formation.

The problem of adhesion after surgical diseases on the abdominal organs remains extremely relevant despite the rapid development of new medical technologies and approaches to the diagnosis and treatment of surgical diseases. The formation of adhesions occurs during open surgical interventions and will differ only in the degree of severity and clinical manifestations. The article is devoted to the study of oxygenation of the peritoneal tissue in experimental adhesions of the abdominal cavity. Experimental studies were carried out on 95 outbred guinea pigs with simulated adhesive disease of the abdominal cavity. As a result of performing direct oximetry on the surface of the peritoneum in conditions of modeling adhesions of the abdominal cavity in laboratory animals, it was revealed that any of the models causes, to a greater or lesser degree, hypoxic changes in the peritoneum, thereby creating favorable conditions for the maturation of coarse-fibrous connective tissue. The impact on the peritoneum of any of the modeling factors caused a decrease in the partial pressure of oxygen in the intestinal wall by an average of 45%. The leveling of hypoxic changes on the surface of the peritoneum in the postoperative period is a method of preventing adhesions of the abdominal cavity.

This article is devoted to the problem of adhesions of the abdominal cavity, as one of the most important and poorly studied problems of abdominal surgery. As a result of a series of experiments on 85 laboratory animals, an analysis of the effectiveness and representativeness of various models of the adhesions of the abdominal cavity was carried out. It was revealed that the isolated modeling effect has a small effect on the occurrence of the adhesive process and, as a consequence, adhesive disease. In terms of the number of adhesions formed, the prevalence of the adhesive process, the method of modeling with talc followed by adhesiolysis is the most equivalent to human adhesive disease.

Robotic-Assisted Gait training (RAGT) offers an innovative therapeutic option for restoration of functional gait in stroke survivors, complementing existing physical rehabilitation strategies. However, there is a limited understanding of the neurophysiological response induced by this training in end-users. Neural desynchronization and Cortico-Muscular Coherence (CMC) are two biomarkers that define the level of muscle-cortex association during gait phases and can be used to estimate induced user’s adaptation during RAGT. In this study, we measure Event-Related Spectral Perturbation (ERSP) and CMC from three healthy individuals and three stroke survivors during overground-gait with and without an exoskeleton. Results show that (1) the use of the exoskeleton in healthy individuals is associated with a different and more refined motor-control represented in a highθ-desynchronization, (2) altered and noisy ERSP and lower and non-focalβ-CMC patterns are observed in Stroke patients when performing overground-gait both with and without the Exoskeleton, and (3) Exoskeleton use in stroke survivors is associated with a reduction in swing-time during gait-cycle, but this effect is not correlated with an increment ofθ-desynchronization and/orβ-CMC. ERSP and CMC demonstrated evidence of neural modulation in able-bodied users during RAGT, which could not be detected in subacute stroke survivors during RAGT. These results suggest that the gait-parameters changes observed during exoskeleton use in subacute stroke survivors are unlikely to be neurally driven.

Background: The brain-computer interface (BCI) race at the Cybathlon championship for athletes with disabilities challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and results of the Ulster University BCI Team pilot who is tetraplegic and has trained to use an electroencephalography (EEG)-based BCI intermittently over 10 years, to compete in three Cybathlon events. Methods: A multi-class, multiple binary classifier framework was used to decode three kinesthetically imagined movements (motor imagery) (left (L) and right (R) arm and feet (F)) as well as relax state (X). Three games paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon: BrainDriver. An evaluation of the pilot’s performance is presented for two Cybathlon competition training periods – spanning 20 sessions over 5 weeks prior to the 2019 competition, and 25 sessions over 5 weeks in the run up to the 2020 competition.Results: Having participated in BCI training in 2009 and competed in Cybathlon 2016, the experienced pilot achieved high two-class accuracy on all class pairs when training began in 2019 (decoding accuracy >90%, resulting in efficient NeuroSensi and Triad game control). The BrainDriver performance (i.e., Cybathlon race completion time) improved significantly during the training period, leading up to the competition day, ranging from 274s - 156s (255±24s to 191±14s mean±std), over 17 days (10 sessions) in 2019, and from 230s - 168s (214±14s to 181±4s), over 18 days (13 sessions) in 2020. However, on both competition occasions, towards the race date, the performance deteriorated significantly.Conclusions: The training regime and framework applied were highly effective in achieving competitive race completion times. The BCI framework did not cope with significant deviation in electroencephalography (EEG) observed in the sessions occurring shortly before and during the race day. Stress, arousal level and fatigue, associated with the competition challenge and performance pressure resulting in cognitive state changes, were likely contributing factors to the nonstationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration: not registered

The prevalence of feeding problems is over 20% in typically developing children and over 70% in children with developmental disabilities. Oral motor therapy targeting feeding disorders may have secondary/indirect positive effects on co-morbid articulation disorders in young children. The purpose of this study was to examine such indirect effects. Seven young children with feeding problems were assessed via a known standardized articulation test upon admission for feeding therapy. They received a 4-week oral motor treatment protocol toward the development of age-appropriate feeding and swallowing, consisting of the application of tongue pressure and therapeutic spoon placement. At the conclusion of the oral motor feeding therapy, the participants' articulatory skills were tested again. Results indicated a significant difference in the pre- and post-treatment scores on the articulation test as well as on parents' reports on their child's speech intelligibility.

Classification of electroencephalography (EEG) signals corresponding to imagined speech production is important for the development of a direct-speech brain&ndash, computer interface (DS-BCI). Deep learning (DL) has been utilized with great success across several domains. However, it remains an open question whether DL methods provide significant advances over traditional machine learning (ML) approaches for classification of imagined speech. Furthermore, hyperparameter (HP) optimization has been neglected in DL-EEG studies, resulting in the significance of its effects remaining uncertain. In this study, we aim to improve classification of imagined speech EEG by employing DL methods while also statistically evaluating the impact of HP optimization on classifier performance. We trained three distinct convolutional neural networks (CNN) on imagined speech EEG using a nested cross-validation approach to HP optimization. Each of the CNNs evaluated was designed specifically for EEG decoding. An imagined speech EEG dataset consisting of both words and vowels facilitated training on both sets independently. CNN results were compared with three benchmark ML methods: Support Vector Machine, Random Forest and regularized Linear Discriminant Analysis. Intra- and inter-subject methods of HP optimization were tested and the effects of HPs statistically analyzed. Accuracies obtained by the CNNs were significantly greater than the benchmark methods when trained on both datasets (words: 24.97%, p &lt, 1 &times, 10&ndash, 7, chance: 16.67%, vowels: 30.00%, p &lt, 7, chance: 20%). The effects of varying HP values, and interactions between HPs and the CNNs were both statistically significant. The results of HP optimization demonstrate how critical it is for training CNNs to decode imagined speech.

Citizen Journalism kerap ikut andil dalam menyampaikan aspirasi di media massa. Hal ini serupa dengan Citizen Jounalism yang ada di meda online Tribun Pekanbaru, mereka mengirimkan peristiwa yang terjadi disekitar lingkungan ke media Tribunpekanbaru.com guna untuk menginformasikan kepada masyarakat. Permasalahan dalam penelitian ini adalah Partisipasi Citizen Journalism di Media Online Tribun Pekanbaru. Bertujuan untuk mengetahui Bagimana Partisipasi Citizen Journalism di Media Online Tribun Pekanbaru. Metode yang digunakan adalah deskriptif kualitatif dengan pengumpulan data wawancara, dokumentasi dan observasi. Hasil penelitian ini dapat diketahui bahwa Tribun Pekanbaru menyediakan tempat untuk Citizen Journalism yaitu topik Citizen Report di laman Citizen Journalism, yang bertujuan untuk menyampaikan aspirasi-aspirasi maupun informasi yang ada di lingkungan sekitar. Dengan adanya tempat penyampaian aspirasi untuk Citizen Journalism kini media online Trbibun Pekanbaru memuat 250-300 berita pertahun khusus berita yang dikirim oleh Citizen Journalsm

Objective: To date, motion trajectory prediction (MTP) of a limb from non-invasive electroencephalography (EEG) has relied, primarily, on band-pass filtered samples of EEG potentials i.e., the potential time-series model. Most MTP studies involve decoding 2D and 3D arm movements i.e., executed arm movements. Decoding of observed or imagined 3D movements has been demonstrated with limited success and only reported in a few studies. MTP studies normally use EEG potentials filtered in the low delta (~1 Hz) band for reconstructing the trajectory of an executed or an imagined/observed movement. In contrast to MTP, multiclass classification based sensorimotor rhythm brain-computer interfaces aim to classify movements using the power spectral density of mu (8–12 Hz) and beta (12–28 Hz) bands. Approach: We investigated if replacing the standard potentials time-series input with a power spectral density based bandpower time-series improves trajectory decoding accuracy of kinesthetically imagined 3D hand movement tasks (i.e., imagined 3D trajectory of the hand joint) and whether imagined 3D hand movements kinematics are encoded also in mu and beta bands. Twelve naïve subjects were asked to generate or imagine generating pointing movements with their right dominant arm to four targets distributed in 3D space in synchrony with an auditory cue (beep). Main results: Using the bandpower time-series based model, the highest decoding accuracy for motor execution was observed in mu and beta bands whilst for imagined movements the low gamma (28–40 Hz) band was also observed to improve decoding accuracy for some subjects. Moreover, for both (executed and imagined) movements, the bandpower time-series model with mu, beta, and low gamma bands produced significantly higher reconstruction accuracy than the commonly used potential time-series model and delta oscillations. Significance: Contrary to many studies that investigated only executed hand movements and recommend using delta oscillations for decoding directional information of a single limb joint, our findings suggest that motor kinematics for imagined movements are reflected mostly in power spectral density of mu, beta and low gamma bands, and that these bands may be most informative for decoding 3D trajectories of imagined limb movements.