αCP binding to a cytosine-rich subset of polypyrimidine tracts drives a novel pathway of cassette exon splicing in the mammalian transcriptome.

Alternative splicing (AS) is a robust generator of mammalian transcriptome complexity. Splice site specification is controlled by interactions of cis-acting determinants on a transcript with specific RNA binding proteins. These interactions are frequently localized to the intronic U-rich polypyrimidine tracts (PPT) located 5' to the majority of splice acceptor junctions. αCPs (also referred to as polyC-binding proteins (PCBPs) and hnRNPEs) comprise a subset of KH-domain proteins with high affinity and specificity for C-rich polypyrimidine motifs. Here, we demonstrate that αCPs promote the splicing of a defined subset of cassette exons via binding to a C-rich subset of polypyrimidine tracts located 5' to the αCP-enhanced exonic segments. This enhancement of splice acceptor activity is linked to interactions of αCPs with the U2 snRNP complex and may be mediated by cooperative interactions with the canonical polypyrimidine tract binding protein, U2AF65. Analysis of αCP-targeted exons predicts a substantial impact on fundamental cell functions. These findings lead us to conclude that the αCPs play a direct and global role in modulating the splicing activity and inclusion of an array of cassette exons, thus driving a novel pathway of splice site regulation within the mammalian transcriptome

Decoding covert somatosensory attention by a BCI system calibrated with tactile sensation

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Objective: We propose a novel calibration strategy to facilitate the decoding of covert somatosensory attention by exploring the oscillatory dynamics induced by tactile sensation. Methods: It was hypothesized that the similarity of the oscillatory pattern between stimulation sensation (SS, real sensation) and somatosensory attentional orientation (SAO) provides a way to decode covert somatic attention. Subjects were instructed to sense the tactile stimulation, which was applied to the left (SS-L) or the right (SS-R) wrist. The BCI system was calibrated with the sensation data and then applied for online SAO decoding. Results: Both SS and SAO showed oscillatory activation concentrated on the contralateral somatosensory hemisphere. Offline analysis showed that the proposed calibration method led to greater accuracy than the traditional calibration method based on SAO only. This is confirmed by online experiments, where the online accuracy on 15 subjects was 78.8±13.1%, with 12 subjects >70% and 4 subject >90%. Conclusion: By integrating the stimulus-induced oscillatory dynamics from sensory cortex, covert somatosensory attention can be reliably decoded by a BCI system calibrated with tactile sensation. Significance: Indeed, real tactile sensation is more consistent during calibration than SAO. This brain-computer interfacing approach may find application for stroke and completely locked-in patients with preserved somatic sensation.University Starter Grant of the University of Waterloo (No. 203859) National Natural Science Foundation of China (Grant No. 51620105002

Fibroblast Growth Factor-10 (FGF-10) Mobilizes Lung-resident Mesenchymal Stem Cells and Protects Against Acute Lung Injury.

FGF-10 can prevent or reduce lung specific inflammation due to traumatic or infectious lung injury. However, the exact mechanisms are poorly characterized. Additionally, the effect of FGF-10 on lung-resident mesenchymal stem cells (LR-MSCs) has not been studied. To better characterize the effect of FGF-10 on LR-MSCs, FGF-10 was intratracheally delivered into the lungs of rats. Three days after instillation, bronchoalveolar lavage was performed and plastic-adherent cells were cultured, characterized and then delivered therapeutically to rats after LPS intratracheal instillation. Immunophenotyping analysis of FGF-10 mobilized and cultured cells revealed expression of the MSC markers CD29, CD73, CD90, and CD105, and the absence of the hematopoietic lineage markers CD34 and CD45. Multipotency of these cells was demonstrated by their capacity to differentiate into osteocytes, adipocytes, and chondrocytes. Delivery of LR-MSCs into the lungs after LPS injury reduced the inflammatory response as evidenced by decreased wet-to-dry ratio, reduced neutrophil and leukocyte recruitment and decreased inflammatory cytokines compared to control rats. Lastly, direct delivery of FGF-10 in the lungs of rats led to an increase of LR-MSCs in the treated lungs, suggesting that the protective effect of FGF-10 might be mediated, in part, by the mobilization of LR-MSCs in lungs

Fast Recognition of BCI-Inefficient Users Using Physiological Features from EEG Signals: A Screening Study of Stroke Patients

Motor imagery (MI) based brain-computer interface (BCI) has been developed as an alternative therapy for stroke rehabilitation. However, experimental evidence demonstrates that a significant portion (10% to 50%) of subjects are BCI-illiterate users (accuracy less than 70%). Thus, predicting BCI performance prior to clinical BCI usage would facilitate the selection of suitable end-users and improve the efficiency of stroke rehabilitation. In the current study, we proposed two physiological variables, i.e., laterality index (LI) and cortical activation strength (CAS), to predict MI-BCI performance. Twenty-four stroke patients and ten healthy subjects were recruited for this study. Each subject was required to perform two blocks of left- and right-hand MI tasks. Linear regression analyses were performed between the BCI accuracies and two physiological predictors. Here, the predictors were calculated from the electroencephalography (EEG) signals during paretic hand MI tasks (5 trials; approximately one minute). LI values exhibited a statistically significant correlation with two-class BCI (left vs. right) performance (r=-0.732, p<0.001), and CAS values exhibited a statistically significant correlation with brain-switch BCI (task vs. idle) performance (r=0.641, p<0.001). Furthermore, the BCI-illiterate users were successfully recognized with a sensitivity of 88.2% and a specificity of 85.7% in the two-class BCI. The brain-switch BCI achieved a sensitivity of 100.0% and a specificity of 87.5% in the discrimination of BCI-illiterate users. These results demonstrated that the proposed BCI predictors were promising to promote the BCI usage in stroke rehabilitation and contribute to a better understanding of the BCI-illiteracy phenomenon in stroke patients.National Natural Science Foundation of China (Grant No. 51620105002) National High Technology Research and Development Program (863 Program) of China (Grant No.2015AA020501

Discriminating between disease-causing and neutral non-frameshifting micro-INDELs by support vector machines by means of integrated sequence- and structure-based features

poster abstractMicro-INDELs (insertions or deletions of ≤20 bp) constitute the second most frequent class of human gene mutation after single nucleotide variants. A significant portion of exonic INDELs are non-frameshifting (NFS), serving to insert or delete a discrete number of amino-acid residues. Despite the relative abundance of NFS-INDELs, their damaging effect on protein structure and function has gone largely unstudied whilst bioinformatics tools for discriminating between disease-causing and neutral NFS-INDELs remain to be developed. We have developed such a technique (DDIG-in; Detecting DIsease-causing Genetic variations due to INDELs) by comparing the properties of disease-causing NFS-INDELs from the Human Gene Mutation Database (HGMD) with putatively neutral NFS-INDELs from the 1,000 Genomes Project. Having considered 58 different sequence- and structure-based features, we found that predicted disordered regions around the NFS-INDEL region had the highest discriminative capability (disease versus neutral) with an Area Under the receiver-operating characteristic Curve (AUC) of 0.82 and a Matthews Correlation Coefficient (MCC) of 0.56. All features studied were combined by support vector machines (SVM) and selected by a greedy algorithm. The resulting SVM models were trained and tested by ten-fold cross-validation on the microdeletion dataset and independently tested on the microinsertion dataset and vice versa. The final SVM model for determining NFS-INDEL disease-causing probability was built on non-redundant datasets with a protein sequence identity cutoff of 35% and yielded an MCC value of 0.68, an accuracy of 84% and an AUC of 0.89. Predicted disease-causing probabilities exhibited a strong negative correlation with the average minor allele frequency (correlation coefficient, -0.84). DDIG-in, available at http://sparks.informatics.iupui.edu, can be used to estimate the disease-causing probability for a given NFS-INDEL

The effects of yam gruel on lowering fasted blood glucose in T2DM rats

© 2020 Xinjun Lin et al., published by De Gruyter 2020. There is increasing evidence of the linkage between type 2 diabetes mellitus (T2DM) and gut microbiota. Based on our previous studies, we investigated the hypoglycemic mechanisms of yam gruel to provide a scientific basis for its popularization and application. Wistar rats were randomly divided into control and T2DM model groups. Rats in the model group were stimulated by a high-sugar/high-fat diet combined with an intraperitoneal injection of streptozotocin to induce T2DM. The T2DM rats were further subdivided randomly into three groups: (1) DM, (2) DM + yam gruel, and (3) DM + metformin. After 4 weeks of intervention, the changes in gut microbiota, short-chain fatty acids (SCFAs) (acetic acid, propionic acid, and butyric acid), the expression of G protein-coupled receptor 43 (GPR43), glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and fasted blood glucose (FBG) levels were observed. Yam gruel intervention elevated the abundance of probiotic bacteria and increased the expression of SCFAs, GPR43 receptor, GLP-1, and PYY. It also reduced FBG levels. We conclude that yam gruel can lower FBG by promoting the growth of probiotic bacteria, increasing the content of SCFAs, and enhancing the expression of GPR43 receptor to increase the content of GLP-1 and PYY in serum

Performance of Brain-Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery

© 2017 IEEE.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A large proportion of users do not achieve adequate control using current non-invasive Brain-computer Interfaces (BCI). This issue has being coined “BCI-Illiteracy”, and is observed among BCI modalities. Here, we compare the performance and BCI-illiteracy rate of tactile selective sensation (SS) and motor imagery (MI) BCI, for large subject samples. We analyzed 80 experimental sessions from 57 subjects with two-class SS protocols. For SS, the group average performance was 79.8±10.6%, with 43 out of the 57 subjects (75.4%) exceeding the 70% BCI-illiteracy threshold for left and right hand SS discrimination. When compared to previous results, this tactile BCI outperformed all other tactile BCIs currently available. We also analyzed 63 experiment sessions from 43 subjects with two-class MI BCI protocols, where the group average performance was 77.2±13.3%, with 69.7% of the subjects exceeded the 70% performance threshold for left and right hand MI. For within-subject comparison, the 24 subjects who participated to both the SS and MI experiments, the BCI performance was superior with SS than MI especially in beta frequency band (p<0.05), with enhanced R2 discriminative information in the somatosensory cortex for the SS modality. Both SS and MI showed a functional dissociation between lower alpha ([8 10] Hz) and upper alpha ([10 13] Hz) bands, with BCI performance significantly better in the upper alpha than the lower alpha (p<0.05) band. In summary, we demonstrated that SS is a promising BCI modality with low BCI illiteracy issue, and has great potential in practical applications reaching large population.University Starter Grant of the University of Waterloo [No. 203859]National Natural Science Foundation of China [Grant No. 51620105002