Variation in brain connectivity during motor imagery and motor execution in stroke patients based on electroencephalography.

Objective: The objective of this study was to analyze the changes in connectivity between motor imagery (MI) and motor execution (ME) in the premotor area (PMA) and primary motor cortex (MA) of the brain, aiming to explore suitable forms of treatment and potential therapeutic targets. Methods: Twenty-three inpatients with stroke were selected, and 21 right-handed healthy individuals were recruited. EEG signal during hand MI and ME (synergy and isolated movements) was recorded. Correlations between functional brain areas during MI and ME were compared. Results: PMA and MA were significantly and positively correlated during hand MI in all participants. The power spectral density (PSD) values of PMA EEG signals were greater than those of MA during MI and ME in both groups. The functional connectivity correlation was higher in the stroke group than in healthy people during MI, especially during left-handed MI. During ME, functional connectivity correlation in the brain was more enhanced during synergy movements than during isolated movements. The regions with abnormal functional connectivity were in the 18th lead of the left PMA area. Conclusion: Left-handed MI may be crucial in MI therapy, and the 18th lead may serve as a target for non-invasive neuromodulation to promote further recovery of limb function in patients with stroke. This may provide support for the EEG theory of neuromodulation therapy for hemiplegic patients.

The effects of Lactobacillus reuteri microcapsules on radiation-induced brain injury by regulating the gut microenvironment.

A radiation-induced brain injury (RIBI) is a major adverse event following radiotherapy of malignant tumors. RIBI would affect cognitive function, leading to a series of complications and even death. However, the pathogenesis of RIBI is still unclear, and it still lacks specific therapeutic drugs. The gut-brain bidirectional communication may be mediated by various microbiota and metabolites in the gastrointestinal tract. Probiotics are closely related to physiological health. The theory of the gut-brain axis provides us with a new idea to improve the gut microenvironment by supplementing probiotics against RIBI. Here, Lactobacillus reuteri microcapsules (LMCs) were prepared, which were predominantly irregular spheres with a rough surface under a scanning electron microscope and a narrow size distribution ranging from 20 to 700 µm. The transmission electron microscopy images showed that the structure of microcapsules containing Lactobacillus reuteri (L. reuteri) was a core and shell structure. The survival of L. reuteri in microcapsules was significantly more than that of free L. reuteri in the simulated stomach environment of pH 1.2. 16S rDNA sequencing showed that LMCs observably increased the relative abundance of Lactobacillus in RIBI mice. More importantly, compared with the RIBI model mice, the behavior of RIBI mice treated with LMCs was significantly improved. In addition, LMCs greatly alleviated the pathological damage of the hippocampus and intestines in the mice after irradiation and reduced the level of TNF-α and IL-6 in vivo. Generally, LMCs are a promising oral preparation, which provide new ideas and methods for the treatment of RIBI.

Cannabidiol-loaded biomimetic macrophage membrane vesicles against post-traumatic stress disorder assisted by ultrasound.

Post-traumatic stress disorder (PTSD), which normally follows psychological trauma, has been increasingly studied as a brain disease. However, the blood-brain barrier (BBB) prevents conventional drugs for PTSD from entering the brain. Our previous studies proved the effectiveness of cannabidiol (CBD) against PTSD, but low water solubility, low brain targeting efficiency and poor bioavailability restricted its applications. Here, a bionic delivery system, camouflage CBD-loaded macrophage-membrane nanovesicles (CMNVs), was constructed via co-extrusion of CBD with macrophage membranes, which had inflammatory and immune escape properties. In vitro anti-inflammatory, cellular uptake and pharmacokinetic experiments respectively verified the anti-inflammatory, inflammatory targeting and immune escape properties of CMNVs. Brain targeting and excellent anti-PTSD effects of CMNVs had been validated in vivo by imaging and pharmacodynamics studies. In our study, the potential of ultrasound to open BBBs and improve the brain-targeted delivery of CBD was evaluated. In conclusion, this cell membrane bionic delivery system assisted with ultrasound had good therapeutic effect against PTSD mice, which is expected to help convey CBD to inflammatory areas within the brain and alleviate the symptoms of PTSD.

Advances in applications of head mounted devices (HMDs): Physical techniques for drug delivery and neuromodulation.

Head-mounted medical devices (HMDs) are disruptive inventions representing laboratories and clinical institutions worldwide are climbing the apexes of brain science. These complex devices are inextricably linked with a wide range knowledge containing the Physics, Imaging, Biomedical engineering, Biology and Pharmacology, particularly could be specifically designed for individuals, and finally exerting integrated bio-effect. The salient characteristics of them are non-invasive intervening in human brain's physiological structures, and alterating the biological process, such as thermal ablating the tumor, opening the BBB to deliver drugs and neuromodulating to enhance cognitive performance or manipulate prosthetic. The increasing demand and universally accepted of them have set off a dramatic upsurge in HMDs' studies, seminal applications of them span from clinical use to psychiatric disorders and neurological modulation. With subsequent pre-clinical studies and human trials emerging, the mechanisms of transcranial stimulation methods of them were widely studied, and could be basically came down to three notable approach: magnetic, electrical and ultrasonic stimulation. This review provides a comprehensive overviews of their stimulating mechanisms, and recent advances in clinic and military. We described the potential impact of HMDs on brain science, and current challenges to extensively adopt them as promising alternative treating tools.

Quercetin inclusion complex gels ameliorate radiation-induced brain injury by regulating gut microbiota.

Radiation-induced brain injury (RIBI) is a serious adverse effect of radiotherapy. RIBI has garnered considerable clinical attention owing to its powerful effects on brain function and cognition; however, no effective treatment is available. The microbiota-gut-brain axis theory is a novel concept of treating RIBI by regulating gut microbiota. Quercetin, a particularly common flavonoid compound, has a wide range of biological activities and can regulate gut microbiota; however, it has poor solubility and dispersibility. In the present study, oral gels of inclusion complex comprising quercetin and HP-ß-CD were prepared, which increased quercetin dispersion and extended its release time in the intestinal tract. First, the relative abundance and diversity of gut microbiota in RIBI mice changed after oral administration of quercetin inclusion complex gels (QICG). Second, the spontaneous activity behavior and short-term memory ability as well as anxiety level were improved. Third, changes in physical symptoms were observed, including a decrease in TNF-α and IL-6 levels. H&E staining revealed that gut epithelial injury and intestinal inflammation as well as hippocampal inflammation were ameliorated. Antibiotics treatment (Abx) mice were developed to disrupt the mice's original gut microbiota composition. No significant improvement was observed in behavior or histopathology after oral administration of QICG in Abx mice of RIBI, indicating that the effect of QICG on improving RIBI was regulated by intestinal microbiota. Finally, the QICG preparation is efficient, exerting a protective effect on RIBI by regulating gut microbiota via the microbiota-gut-brain axis, which provides a novel idea for RIBI treatment.

The Improved Brain-Targeted Drug Delivery of Edaravone Temperature-Sensitive Gels by Ultrasound for γ-ray Radiation-Induced Brain Injury.

Radiation-induced brain injury (RBI) is a common neurological disease caused by ionizing radiation (IR). Edaravone (EDA) is a free radical scavenger, has the potential to treat RBI. EDA loaded temperature-sensitive gels (TSGs) were prepared for subcutaneous injection to improve inconvenient administration of intravenous infusion. RBI mice model was established by irradiation of 60Co γ-ray on head. EDA TSGs could improve spontaneous behavior, learning and memory and anxiety of RBI mice by behavior tests, including the open field test, the novel object recognition test, the elevated plus maze test and the fear conditioning test. The therapeutic effects were enhanced with the assistance of ultrasound. Alleviative pathological changes, decreased the expression of Molondialdehyde (MDA) and Interleukin-6 (IL-6) in the hippocampus of brain, indicated reduced oxidative stress and inflammatory response with the treatment of EDA TSGs and ultrasound. Moreover, ultrasound was superior to the use of EDA TSGs. Safe and effective EDA TSGs were prepared for RBI, and the feasibility of brain-targeted drug delivery enhanced by ultrasound was preliminarily demonstrated in this study.

EEG decoding method based on multi-feature information fusion for spinal cord injury.

To develop an efficient brain-computer interface (BCI) system, electroencephalography (EEG) measures neuronal activities in different brain regions through electrodes. Many EEG-based motor imagery (MI) studies do not make full use of brain network topology. In this paper, a deep learning framework based on a modified graph convolution neural network (M-GCN) is proposed, in which temporal-frequency processing is performed on the data through modified S-transform (MST) to improve the decoding performance of original EEG signals in different types of MI recognition. MST can be matched with the spatial position relationship of the electrodes. This method fusions multiple features in the temporal-frequency-spatial domain to further improve the recognition performance. By detecting the brain function characteristics of each specific rhythm, EEG generated by imaginary movement can be effectively analyzed to obtain the subjects' intention. Finally, the EEG signals of patients with spinal cord injury (SCI) are used to establish a correlation matrix containing EEG channel information, the M-GCN is employed to decode relation features. The proposed M-GCN framework has better performance than other existing methods. The accuracy of classifying and identifying MI tasks through the M-GCN method can reach 87.456%. After 10-fold cross-validation, the average accuracy rate is 87.442%, which verifies the reliability and stability of the proposed algorithm. Furthermore, the method provides effective rehabilitation training for patients with SCI to partially restore motor function.

Nasal Delivery of Cinnarizine Thermo- and Ion-Sensitive In Situ Hydrogels for Treatment of Microwave-Induced Brain Injury.

(1) Background: When the body is exposed to microwave radiation, the brain is more susceptible to damage than other organs. However, few effective drugs are available for the treatment of microwave-induced brain injury (MIBI) because most drugs are difficult to cross the blood-brain barrier (BBB) to reach the brain. (2) Methods: Nasal cinnarizine inclusion complexes with thermo-and ion-sensitive hydrogels (cinnarizine ISGs) were prepared to treat MIBI and the characteristics of the inclusion complexes and their thermo-and ion-sensitive hydrogels were evaluated. (3) Results: Due to high viscosity, cinnarizine ISGs can achieve long-term retention in the nasal cavity to achieve a sustained release effect. Compared with the model, the intranasal thermo-and ion-sensitive cinnarizine ISGs significantly improved the microwave-induced spatial memory and spontaneous exploration behavior with Morris water maze and open field tests. Cinnarizine ISGs inhibited the expression of calcineurin and calpain 1 in the brain, which may be related to the inhibition of calcium overload by cinnarizine. (4) Conclusion: Intranasal thermo- and ion-sensitive cinnarizine ISGs are a promising brain-targeted pharmaceutical preparation against MIBI.

Therapeutic carrier based on solanesol and hyaluronate for synergistic tumor treatment.

The administration of nanodrugs can lead to metabolism related systemic toxicity due to the use of inert carriers in large quantities. Carrier materials that offer therapeutic effects are therefore a promising means of addressing this limitation. Herein, a hyaluronate-based nanocarrier was prepared from hyaluronic acid (HA) and solanesol. Solanesyl thiosalicylate (STS) derived from solanesol has certain antitumor effects and was used to modify HA. The conjugate (HA-STS) self-assembled into nanoparticles acting as a drug carrier. The synthesis of the conjugates was confirmed by 1H NMR spectroscopy. Doxorubicin (DOX) was loaded into the HA-STS nanoparticles with a relatively high content of 6.0%. pH-sensitive drug release behavior was achieved by introducing a hydroazone bond between STS and HA. A cytotoxicity assay indicated that the blank nanoparticles had an antitumor effect, which was enhanced by loading with an additional drug. Moreover, in vivo antitumor experiments indicated that the HA-STS-DOX showed superior tumor inhibition compared with free DOX, as well as lower cardiotoxicity and hepatotoxicity, demonstrating the advantages of the bioactive drug vehicles in cancer therapy.

A novel biochar electrode for efficient electroreduction of nitrate: Selective and regulation of halogen.

A novel biochar electrode Bio-Fe3O4/CF used for electroreduction of nitrate was prepared by the hydrothermal synthesis method. The results showed that the growth of spherical Fe3O4 on the surface of smooth biochar can significantly increase the nitrate reduction rate. Besides, the presence of Cl and Br in the solution could promote the conversion of NH4+ to N2, thereby regulating the element nitrogen in the solution. Mechanistic analysis showed that the interconversion of Fe (II) and Fe (III) facilitates the transfer of electrons to nitrate. This study not only provides a biochar electrode material for the efficient removal of nitrate but also simply reveals regulation of halogen in solution, which provides a particular theoretical and data basis for nitrate removal.

Parallel-slipped π-π electron-donor-acceptor in adsorption process: Molecular dynamics simulation.

Molecular dynamics simulation was used to study the adsorption of single wall carbon nanotubes (SCNT) in levofloxacin (LEV) solutions of different concentrations by Radial distribution function, mean square displacement and interaction energy. The results showed that levofloxacin molecules were adsorbed around the carbon nanotubes. The adsorption effect of large concentration solution was not as good as that of low concentration solution because of agglomeration. LEV molecules with different concentration were free diffusion within 15ns, and gradually agglomerated under the influence of adsorption. The energy change is proportional to the concentration of the molecule. The distance between benzene rings corresponding to the agglomeration effect of levofloxacin molecules was 0.4 nm, which should be the effect of parallel-slipped π-π electron-donor-acceptor (EDA) interactions. The simulation results are valuable to study the adsorption and removal of benzenes by adsorbent.

Combating the Infodemic: A Chinese Infodemic Dataset for Misinformation Identification.

Misinformation posted on social media during COVID-19 is one main example of infodemic data. This phenomenon was prominent in China when COVID-19 happened at the beginning. While a lot of data can be collected from various social media platforms, publicly available infodemic detection data remains rare and is not easy to construct manually. Therefore, instead of developing techniques for infodemic detection, this paper aims at constructing a Chinese infodemic dataset, "infodemic 2019", by collecting widely spread Chinese infodemic during the COVID-19 outbreak. Each record is labeled as true, false or questionable. After a four-time adjustment, the original imbalanced dataset is converted into a balanced dataset by exploring the properties of the collected records. The final labels achieve high intercoder reliability with healthcare workers' annotations and the high-frequency words show a strong relationship between the proposed dataset and pandemic diseases. Finally, numerical experiments are carried out with RNN, CNN and fastText. All of them achieve reasonable performance and present baselines for future works.

Insights on the mechanism of Fe doped ZnO for tightly-bound extracellular polymeric substances tribo-catalytic degradation: The role of hydration layers at the interface.

The control of interfacial microbial pollution is of great significance for water safety. Herein, the tribo-catalysis ability of zinc oxide (ZnO) has been investigated, which can realize the control of tightly-bound extracellular polymeric substances (T-EPS) in water under dark environment. The DFT calculation proves the Fe doping introduces the impurity level and decreases the work function from 5.071 eV to 5.045 eV, improves the charge separation of ZnO, and eventually enhances the catalytic reaction efficiency. Characterizing the catalytic reaction process by three-dimensional fluorescence (3D EEM) and fluorescence regional integration (FRI) method, it is found that the T-EPS solution can be degraded 75.8% by Fe-ZnO in 12 min, while ZnO can only degrade 32.2%. Combining with high-resolution scanning probe microscope (HR-SPM) and attenuated total reflection method (ATR-FTIR), hydration layers consist with hydroxyl layer (∼0.23 nm) and water molecular layer (∼0.27 nm) are observed at the interface between Fe-ZnO and T-EPS solution, and terminal hydroxyl group (OHt) is considered to be the active site for the generation of radicals. This study provides an idea for exploring the mechanism of tribo-catalytic reaction and shows its application prospect in the field of microbial inhibition in water.

An Updated Functional Annotation of Protein-Coding Genes in the Cucumber Genome.

Background: Although the cucumber reference genome and its annotation were published several years ago, the functional annotation of predicted genes, particularly protein-coding genes, still requires further improvement. In general, accurately determining orthologous relationships between genes allows for better and more robust functional assignments of predicted genes. As one of the most reliable strategies, the determination of collinearity information may facilitate reliable orthology inferences among genes from multiple related genomes. Currently, the identification of collinear segments has mainly been based on conservation of gene order and orientation. Over the course of plant genome evolution, various evolutionary events have disrupted or distorted the order of genes along chromosomes, making it difficult to use those genes as genome-wide markers for plant genome comparisons. Results: Using the localized LASTZ/MULTIZ analysis pipeline, we aligned 15 genomes, including cucumber and other related angiosperm plants, and identified a set of genomic segments that are short in length, stable in structure, uniform in distribution and highly conserved across all 15 plants. Compared with protein-coding genes, these conserved segments were more suitable for use as genomic markers for detecting collinear segments among distantly divergent plants. Guided by this set of identified collinear genomic segments, we inferred 94,486 orthologous protein-coding gene pairs (OPPs) between cucumber and 14 other angiosperm species, which were used as proxies for transferring functional terms to cucumber genes from the annotations of the other 14 genomes. In total, 10,885 protein-coding genes were assigned Gene Ontology (GO) terms which was nearly 1,300 more than results collected in Uniprot-proteomic database. Our results showed that annotation accuracy would been improved compared with other existing approaches. Conclusions: In this study, we provided an alternative resource for the functional annotation of predicted cucumber protein-coding genes, which we expect will be beneficial for the cucumber's biological study, accessible from http://cmb.bnu.edu.cn/functional_annotation. Meanwhile, using the cucumber reference genome as a case study, we presented an efficient strategy for transferring gene functional information from previously well-characterized protein-coding genes in model species to newly sequenced or "non-model" plant species.

The comparison of alternative splicing among the multiple tissues in cucumber.

BACKGROUND: Alternative splicing (AS) is an important post-transcriptional process. It has been suggested that most AS events are subject to tissue-specific regulation. However, the global dynamics of AS in different tissues are poorly explored. RESULTS: To analyse global changes in AS in multiple tissues, we identified the AS events and constructed a comprehensive catalogue of AS events within each tissue based on the genome-wide RNA-seq reads from ten tissues in cucumber. First, we found that 58% of the multi-exon genes underwent AS. We further obtained 565 genes with significantly more AS events compared with random genes. These genes were found significant enrichment in biological processes related to the regulation of actin filament length. Second, significantly different AS event profiles among ten tissues were found. The tissues with the same origin of development are more likely to have a relatively similar AS profile. Moreover, 7370 genes showed tissue-specific AS events and were highly enriched in biological processes related to the positive regulation of cellular component organization. Root-specificity AS genes were related to the cellular response to DNA damage stimulus. Third, the genes with different intron retention (IR) patterns among the ten tissues showed significant difference in GC percentages of the retained intron, and the number of exons and FPKM of the major transcripts. CONCLUSIONS: Our study provided a comprehensive view of AS in multiple tissues. We revealed novel insights into the patterns of AS in multiple tissues and the tissue-specific AS in cucumber.

A fast sequence assembly method based on compressed data structures.

Assembling a large genome using next generation sequencing reads requires large computer memory and a long execution time. To reduce these requirements, a memory and time efficient assembler is presented from applying FM-index in JR-Assembler, called FMJ-Assembler, where FM stand for FMR-index derived from the FM-index and BWT and J for jumping extension. The FMJ-Assembler uses expanded FM-index and BWT to compress data of reads to save memory and jumping extension method make it faster in CPU time. An extensive comparison of the FMJ-Assembler with current assemblers shows that the FMJ-Assembler achieves a better or comparable overall assembly quality and requires lower memory use and less CPU time. All these advantages of the FMJ-Assembler indicate that the FMJ-Assembler will be an efficient assembly method in next generation sequencing technology.

Accurate reconstruction for DNA sequencing by hybridization based on a constructive heuristic.

Sequencing by hybridization is a promising cost-effective technology for high-throughput DNA sequencing via microarray chips. However, due to the effects of spectrum errors rooted in experimental conditions, an accurate and fast reconstruction of original sequences has become a challenging problem. In the last decade, a variety of analyses and designs have been tried to overcome this problem, where different strategies have different trade-offs in speed and accuracy. Motivated by the idea that the errors could be identified by analyzing the interrelation of spectrum elements, this paper presents a constructive heuristic algorithm, featuring an accurate reconstruction guided by a set of well-defined criteria and rules. Instead of directly reconstructing the original sequence, the new algorithm first builds several accurate short fragments, which are then carefully assembled into a whole sequence. The experiments on benchmark instance sets demonstrate that the proposed method can reconstruct long DNA sequences with higher accuracy than current approaches in the literature.

An improved multi-label classification method and its application to functional genomics.

In this paper, a multi-label classification method based on label ranking and delicate boundary Support Vector Machine (SVM) is proposed for solving the functional genomics applications. Firstly, an improved probabilistic SVM with delicate decision boundary is used as scoring approach to obtain a proper label rank. Secondly, an instance-dependent thresholding strategy is proposed to decide classification results. A d-folds validation approach is utilised to determine a set of target thresholds for all training samples as teachers, then an appropriate instance-dependent threshold for each testing instance is obtained by applying k-Nearest Neighbours (KNN) strategy on this teacher threshold set.

Poisson approach to clustering analysis of regulatory sequences.

The presence of similar patterns in regulatory sequences may aid users in identifying co-regulated genes or inferring regulatory modules. By modelling pattern occurrences in regulatory regions with Poisson statistics, this paper presents a log likelihood ratio statistics-based distance measure to calculate pair-wise similarities between regulatory sequences. We employed it within three clustering algorithms: hierarchical clustering, Self-Organising Map, and a self-adaptive neural network. The results indicate that, in comparison to traditional clustering algorithms, the incorporation of the log likelihood ratio statistics-based distance into the learning process may offer considerable improvements in the process of regulatory sequence-based classification of genes.

A graph-based evolutionary algorithm: Genetic Network Programming (GNP) and its extension using reinforcement learning.

This paper proposes a graph-based evolutionary algorithm called Genetic Network Programming (GNP). Our goal is to develop GNP, which can deal with dynamic environments efficiently and effectively, based on the distinguished expression ability of the graph (network) structure. The characteristics of GNP are as follows. 1) GNP programs are composed of a number of nodes which execute simple judgment/processing, and these nodes are connected by directed links to each other. 2) The graph structure enables GNP to re-use nodes, thus the structure can be very compact. 3) The node transition of GNP is executed according to its node connections without any terminal nodes, thus the past history of the node transition affects the current node to be used and this characteristic works as an implicit memory function. These structural characteristics are useful for dealing with dynamic environments. Furthermore, we propose an extended algorithm, "GNP with Reinforcement Learning (GNPRL)" which combines evolution and reinforcement learning in order to create effective graph structures and obtain better results in dynamic environments. In this paper, we applied GNP to the problem of determining agents' behavior to evaluate its effectiveness. Tileworld was used as the simulation environment. The results show some advantages for GNP over conventional methods.