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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.

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.

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.

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

Background: Stroke is a disease with a high associated disability burden. Robotic-assisted gait training offers an opportunity for the practice intensity levels associated with good functional walking outcomes in this population. Neural interfacing technology, electroencephalography (EEG), or electromyography (EMG) can offer new strategies for robotic gait re-education after a stroke by promoting more active engagement in movement intent and/or neurophysiological feedback. Objectives: This study identifies the current state-of-the-art and the limitations in direct neural interfacing with robotic gait devices in stroke rehabilitation. Methods: A pre-registered systematic review was conducted using standardized search operators that included the presence of stroke and robotic gait training and neural biosignals (EMG and/or EEG) and was not limited by study type. Results: From a total of 8,899 papers identified, 13 articles were considered for the final selection. Only five of the 13 studies received a strong or moderate quality rating as a clinical study. Three studies recorded EEG activity during robotic gait, two of which used EEG for BCI purposes. While demonstrating utility for decoding kinematic and EMG-related gait data, no EEG study has been identified to close the loop between robot and human. Twelve of the studies recorded EMG activity during or after robotic walking, primarily as an outcome measure. One study used multisource information fusion from EMG, joint angle, and force to modify robotic commands in real time, with higher error rates observed during active movement. A novel study identified used EMG data during robotic gait to derive the optimal, individualized robot-driven step trajectory. Conclusions: Wide heterogeneity in the reporting and the purpose of neurobiosignal use during robotic gait training after a stroke exists. Neural interfacing with robotic gait after a stroke demonstrates promise as a future field of study. However, as a nascent area, direct neural interfacing with robotic gait after a stroke would benefit from a more standardized protocol for biosignal collection and processing and for robotic deployment. Appropriate reporting for clinical studies of this nature is also required with respect to the study type and the participants’ characteristics. Enterprise Ireland European Commission Horizon 2020

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.

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.

Reconstruction of the three-dimensional (3D) trajectory of an imagined limb movement using electro-encephalography (EEG) poses many challenges. However, if achieved, more advanced non-invasive brain-computer interfaces (BCIs) for the physically impaired could be realized. The most common motion trajectory prediction (MTP) BCI employs a time-series of band-pass filtered EEG potentials for reconstructing the 3D trajectory of limb movement using multiple linear regression (mLR). Most MTP BCI studies report the best accuracy using low delta (0.5–2Hz) band-pass filtered EEG potentials. In a recent study, we showed spatiotemporal power distribution of theta (4–8Hz), mu (8–12Hz), and beta (12–28Hz) EEG frequency bands contain richer information associated with movement trajectory. This finding is in line with the results in the extensive literature on traditional sensorimotor rhythm (SMR) based multiclass (MC) BCI studies, which report the best accuracy of limb movement classification using power values of mu and beta frequency bands. Here, we show the reconstruction of actual and imagined 3D limb movement trajectory with an MTP BCI using a time-series of bandpower values (BTS model). Furthermore, we show the proposed BTS model outperforms the standard potential time-series model (PTS model). The BTS model yielded best results in the mu and beta bands (R∼0.5 for actual and R∼0.2 for imagined movement reconstruction) and not in the low delta band, as previously reported for MTP studies using the PTS model. Our results show for the first time how mu and beta activity can be used for decoding imagined 3D hand movement from EEG.

Three dimensional (3D) limb motion trajectory is predictable with a non-invasive brain-computer interface (BCI). To date, most non-invasive motion trajectory prediction BCIs use potential values of electroencephalographic (EEG) signals as the input to a multiple linear regression (mLR) based kinetic data estimator. We investigated the possible improvement in accuracy of 3D hand movement prediction (i.e., the correlation of registered and reconstructed hand velocities) by replacing raw EEG potentials with spectrum power values of specific EEG bands. We also investigated if a non-linear neural network based estimator outperformed the mLR approach. The spectrum power model provided significantly higher accuracy (R∼0.60) compared to the similar EEG potentials based approach (R∼0.45). Additionally, when replacing the mLR based kinetic data estimation module with a feed-forward neural network (NN) we found the NN based spectrum power model provided higher accuracy (R∼0.70) compared to the similar mLR based approach (R∼0.60).

A motion trajectory prediction (MTP) - based brain-computer interface (BCI) aims to reconstruct the three-dimensional (3D) trajectory of upper limb movement using electroencephalography (EEG). The most common MTP BCI employs a time series of bandpass-filtered EEG potentials (referred to here as the potential time-series, PTS, model) for reconstructing the trajectory of a 3D limb movement using multiple linear regression. These studies report the best accuracy when a 0.5-2Hz bandpass filter is applied to the EEG. In the present study, we show that spatiotemporal power distribution of theta (4-8Hz), mu (8-12Hz), and beta (12-28Hz) bands are more robust for movement trajectory decoding when the standard PTS approach is replaced with time-varying bandpower values of a specified EEG band, ie, with a bandpower time-series (BTS) model. A comprehensive analysis comprising of three subjects performing pointing movements with the dominant right arm toward six targets is presented. Our results show that the BTS model produces significantly higher MTP accuracy (R~0.45) compared to the standard PTS model (R~0.2). In the case of the BTS model, the highest accuracy was achieved across the three subjects typically in the mu (8-12Hz) and low-beta (12-18Hz) bands. Additionally, we highlight a limitation of the commonly used PTS model and illustrate how this model may be suboptimal for decoding motion trajectory relevant information. Although our results, showing that the mu and beta bands are prominent for MTP, are not in line with other MTP studies, they are consistent with the extensive literature on classical multiclass sensorimotor rhythm-based BCI studies (classification of limbs as opposed to motion trajectory prediction), which report the best accuracy of imagined limb movement classification using power values of mu and beta frequency bands. The methods proposed here provide a positive step toward noninvasive decoding of imagined 3D hand movements for movement-free BCIs.

The indoleamine melatonin is ubiquitously distributed, and because of its small size and amphiphilic nature, it is able to reach easily all cellular compartments. The highest intracellular melatonin concentrations are found in the mitochondria, suggestive of local metabolism and/or direct participation in organelle function. In mitochondria cytochrome c (cyt c) could represent a melatonin target since it has the capability to oxidize organic molecules in the presence of H2O2, and mitochondria are the main site of H2O2 production in nonphagocytic cells. Therefore, we investigated oxidation of melatonin by cyt c/H2O2 couple as a potential pathway for its metabolism in the mitochondria. We found melatonin conversion into N(1)-acetyl-N(2)-formyl-5-methoxykynuramine via sequential steps that generate the intermediates 2-hydroxymelatonin and 2,3-dihydroxymelatonin. We experimentally excluded mediation by a Fenton/Haber-Weiss-type reaction and documented the dependence on oxoferryl heme for melatonin oxidation. Given the high mitochondrial concentrations of both melatonin and cyt c as well as the continuous generation of H2O2 during respiration, it is entirely possible that mitochondrial cyt c-mediated oxidation of melatonin may be a plausible pathway of its biotransformation in vivo.

In the present study we provide direct evidence for the involvement of rat microsomal cytochrome P450s in melatonin O-demethylation and hydroxylation at two different positions: 2 and 6, as well as generation of N(1)-acetyl-N(2)-formyl-5-methoxy-kynuramine (AFMK) and two unknown products. Moreover, we found that mitochondrial cytochrome P450s also converts melatonin into AFMK, N-acetylserotonin, 2-hydroxymelatonin, 6-hydroxymelatonin and the same two unknown products. Eadie-Hofstee plots for 6-hydroxylation and O-demethylation reactions were curvilinear for all tested fractions, suggestive of involvement of at least two components, one with a high affinity and low capacity, and another with a low affinity and high capacity. Mitochondrial cytochrome P450s exhibited higher affinity (suggesting lower K(m) value) and higher V(max) for melatonin 6-hydroxylation and O-demethylation for both high-affinity and low-affinity components as compared with microsomal enzymes. The intrinsic clearance for melatonin hydroxylation by high- and low-affinity components displayed the highest values in all tested fractions, indicating that both mitochondrial and microsomal cytochrome P450s metabolize melatonin principally by 6-hydroxylation, with O-demethylation representing a minor metabolic pathway.

Rationale: Myo-inositol is an isomer of glucose that is a precursor in the phosphatidylinositol (PIP) cycle, a source of two second messengers: diacylglycerol (DAG) and inositol triphosphate (IP3). Clinical studies have reported that inositol is effective in relieving symptoms of depression. Objective: The present study examined the effects of inositol on two animal models of depression: the Porsolt forced swim test, a behaviorally based model; and the reserpine-induced immobility model, a pharmacologically based model. Methods and results: Chronic inositol injections (daily for 14 days) of 1.2 g/kg (but not at lower doses) reduced immobility time and increased struggle time in the Porsolt test compared with control animals. The same dose and treatment schedule also reduced complete immobility time but did not affect ambulatory activity in the reserpine test compared with controls. Chronic oral treatment with inositol (10% in food for 14 days) had effects similar to IP inositol in the Porsolt test. Conclusions: The effect of inositol in animal models of depression supports its possible importance as a new treatment for the disorder, and permits research on its mechanisms of action.

Although the mechanism responsible for the clinical antiplaque efficacy of oral antiseptics is generally considered to be primarily one of bactericidal activity, it has been suggested that oral antiseptics may have additional effects on bacteria exposed to sublethal levels. Studies reported herein, investigated the effects of sublethal levels of an essential oil-containing antiseptic mouthrinse (Listerine Antiseptic, Warner-Lambert Co., Morris Plains, NJ) on selected activities of representative plaque microorganisms using in vitro models. These studies demonstrated that sublethal exposure to the tested oral antiseptic can have significant effects in reducing intergeneric coaggregation, increasing bacterial generation time, and extracting endotoxin from Gram-negative bacteria. These in vitro activities can be correlated with features of plaque formation and pathogenicity seen in vivo; however, additional studies will be necessary to confirm that these mechanisms are, in fact, operative clinically.

In this controlled clinical study, the authors examined the effect of subgingival irrigation and rinsing with an antiseptic mouthrinse before ultrasonic scaling of a quadrant containing inflamed gingivae. The results showed that pre-procedural subgingival irrigation and rinsing can significantly reduce the level of bacteremia associated with ultrasonic scaling. These results support the American Heart Association's recommendation of adjunctive subgingival irrigation prior to invasive procedures in patients at risk of developing bacterial endocarditis.