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Objective: This study aimed to identify differentially expressed genes (DEGs) by transcriptome analysis to elucidate a potential mechanism by which governor vessel electroacupuncture (GV-EA) promotes neuronal survival, axonal regeneration, and functional recovery after complete transection spinal cord injury (SCI).Methods: Sham, control, or GV-EA group adult female Sprague Dawley rats underwent a complete transection SCI protocol. SCI area RNA-seq investigated the DEGs of coding and noncoding RNAs 7 days post-SCI. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were used to classify DEGs functions, to explain a possible molecular mechanism. Immunofluorescence and BBB (Basso, Beattie, and Bresnahan) score were used to verify a GV-EA treatment effect following SCI.Results: GV-EA treatment could regulate the expression of 173 mRNA, 260 lncRNA, and 153 circRNA genes among these DEGs resulted by SCI. GO enrichment analysis showed that the DEGs were most enriched in membrane, actin binding, and regulation of Toll-like receptor signaling pathway. KEGG pathway analysis showed enriched pathways (e.g. , Toll-like receptors, MAPK, Hippo signaling). According to the ceRNA network, miR-144-3p played a regulatory role by interacting with lncRNA and circRNA. GV-EA also promoted the injured spinal cord neuron survival, axonal regeneration, and functional improvement of hind limb locomotion.Conclusion: Results of our RNA-seq suggest that post-SCI GV-EA may regulate characteristic changes in transcriptome gene expression, potential critical genes, and signaling pathways, providing clear directions for further investigation into the mechanism of GV-EA in subacute SCI treatment. Moreover, we found that GV-EA promotes neuronal survival, nerve fiber extension, and motor function recovery in subacute SCI.

N4-methylcytosine (4mC) is a type of DNA modification which could regulate several biological progressions such as transcription regulation, replication and gene expressions. Precisely recognizing 4mC sites in genomic sequences can provide specific knowledge about their genetic roles. This study aimed to develop a deep learning-based model to predict 4mC sites in the Escherichia coli. In the model, DNA sequences were encoded by word embedding technique 'word2vec'. The obtained features were inputted into 1-D convolutional neural network (CNN) to discriminate 4mC sites from non-4mC sites in Escherichia coli genome. The examination on independent dataset showed that our model could yield the overall accuracy of 0.861, which was about 4.3% higher than the existing model. To provide convenience to scholars, we provided the data and source code of the model which can be freely download from https://github.com/linDing-groups/Deep-4mCW2V.

A readily available chiral cyclohexanediamine-derived bifunctional tertiary amine-squaramide catalyst is more effective for the asymmetric dearomative 1,3-dipolar cycloaddition of 2-nitrobenzofurans and N-2,2,2-trifluoroethylisatin ketimines. A range of structurally diverse spiro-fused polyheterocyclic compounds containing oxindole, pyrrolidine, and hydrobenzofuran motifs were smoothly obtained in excellent results (up to 99% yield,20:1 dr in all cases and up to 99% ee). This method features high efficiency, mild reaction conditions, exquisite asymmetric induction, wide functional group tolerance, great potential for scale-up synthesis, and attractive product diversification.

Kendall, BJ, Siekirk, NJ, and Lai, Q. Effects of acute high-intensity interval training on information processing speed. J Strength Cond Res XX(X): 000-000, 2021-This study investigated the effects of acute exercise on reaction time (RT), premotor time (i.e., central processing), and motor time (i.e., peripheral processing) using surface electromyography to fractionate RT. Fifty-eight young adults (27 men, 31 women) between the age of 18 and 40 years participated in 2 testing sessions. During visit one, subjects performed a simple RT task under regular (i.e., consistent timing) and irregular (i.e., variable timing) foreperiods. Subjects were then randomized to either an aerobic-only high-intensity interval training (HIIT) group (HIIT-A), an aerobic/resistance HIIT group (HIIT-AR), or a resting control group (CG). Both exercise groups performed a 20-minute, digital video disc-delivered HIIT exercise protocol. After exercise or rest, when controlling for cardiovascular fitness, no statistical differences were observed for the regular foreperiod conditions (p > 0.05). For the irregular foreperiod conditions, the HIIT-A group (M = 219.8, SE = 6.5) and the HIIT-AR group (M = 218.2, SE = 5.8) had significantly faster mean RTs than the CG (M = 248.1, SE = 8.1). In addition, the HIIT-A (M = 172.1, SE = 4.6) and HIIT-AR exercise groups (M = 171.3, SE = 4.8) had significantly faster mean PMTs than the CG (M = 189.7, SE = 5.7). These findings suggest that tasks dependent on central processing may benefit from an acute bout of exercise.

Graphical abstract, Highlights • An computational method was developed to identify Cyclin Protein. • Several kinds of features were proposed to formulate protein samples. • A fusion feature set could produce a high accuracy., Cyclin proteins are capable to regulate the cell cycle by forming a complex with cyclin-dependent kinases to activate cell cycle. Correct recognition of cyclin proteins could provide key clues for studying their functions. However, their sequences share low similarity, which results in poor prediction for sequence similarity-based methods. Thus, it is urgent to construct a machine learning model to identify cyclin proteins. This study aimed to develop a computational model to discriminate cyclin proteins from non-cyclin proteins. In our model, protein sequences were encoded by seven kinds of features that are amino acid composition, composition of k-spaced amino acid pairs, tri peptide composition, pseudo amino acid composition, geary correlation, normalized moreau-broto autocorrelation and composition/transition/distribution. Afterward, these features were optimized by using analysis of variance (ANOVA) and minimum redundancy maximum relevance (mRMR) with incremental feature selection (IFS) technique. A gradient boost decision tree (GBDT) classifier was trained on the optimal features. Five-fold cross-validated results showed that our model would identify cyclins with an accuracy of 93.06% and AUC value of 0.971, which are higher than the two recent studies on the same data.

Eukaryotic cells can expand their coding ability by using their splicing machinery, spliceosome, to process precursor mRNA (pre-mRNA) into mature messenger RNA. The mega-macromolecular spliceosome contains multiple subcomplexes, referred to as small nuclear ribonucleoproteins (snRNPs). Among these, U1 snRNP and its central component, U1-70K, are crucial for splice site recognition during early spliceosome assembly. The human U1-70K has been linked to several types of human autoimmune and neurodegenerative diseases. However, its phylogenetic relationship has been seldom reported. To this end, we carried out a systemic analysis of 95 animal U1-70K genes and compare these proteins to their yeast and plant counterparts. Analysis of their gene and protein structures, expression patterns and splicing conservation suggest that animal U1-70Ks are conserved in their molecular function, and may play essential role in cancers and juvenile development. In particular, animal U1-70Ks display unique characteristics of single copy number and a splicing isoform with truncated C-terminal, suggesting the specific role of these U1-70Ks in animal kingdom. In summary, our results provide phylogenetic overview of U1-70K gene family in vertebrates. In silico analyses conducted in this work will act as a reference for future functional studies of this crucial U1 splicing factor in animal kingdom.

The mechanism underlying neurogenesis during embryonic spinal cord development involves a specific ligand/receptor interaction, which may be help guide neuroengineering to boost stem cell-based neural regeneration for the structural and functional repair of spinal cord injury. Herein, we hypothesized that supplying spinal cord defects with an exogenous neural network in the NT-3/fibroin-coated gelatin sponge (NF-GS) scaffold might improve tissue repair efficacy. To test this, we engineered tropomyosin receptor kinase C (TrkC)-modified neural stem cell (NSC)-derived neural network tissue with robust viability within an NF-GS scaffold. When NSCs were genetically modified to overexpress TrkC, the NT-3 receptor, a functional neuronal population dominated the neural network tissue. The pro-regenerative niche allowed the long-term survival and phenotypic maintenance of the donor neural network tissue for up to 8 weeks in the injured spinal cord. Additionally, host nerve fibers regenerated into the graft, making synaptic connections with the donor neurons. Accordingly, motor function recovery was significantly improved in rats with spinal cord injury (SCI) that received TrkC-modified NSC-derived neural network tissue transplantation. Together, the results suggested that transplantation of the neural network tissue formed in the 3D bioactive scaffold may represent a valuable approach to study and develop therapies for SCI., Graphical abstract Scheme 1. A neurotrophin-3 (NT-3) sustained-release bioscaffold supports the formation of tyrosine kinase receptor C (TrkC)-modified neural stem cell-derived neural network tissue with efficacy in repairing spinal cord injury.Image 1, Highlights • A NT-3 sustained-release scaffold confers a microenvironment partially simulating the developmental spinal cord. • The NT-3 microenvironment boosts neuronal differentiation of TrkC-modified NSCs by interactions between ligand and receptor. • TrkC-NSCs is self-organized into a neural network tissue with typical neural excitability in 3D bioactive scaffold in vitro. • The grafted neural network tissue can survive and maintain neural property, and improve motor function of paralyzed rats.

Milad T Jannesari,1 Zhongming Wang,2 Jianzhuang Zheng,1 Wenwu Xie,1 Qin Lai,1 Lu Wu1 1School of Business, Zhejiang University City College, Hangzhou, People’s Republic of China; 2School of Management, Zhejiang University, Hangzhou, People’s Republic of ChinaCorrespondence: Milad T JannesariSchool of Business, Zhejiang University City College, Hangzhou, People’s Republic of ChinaEmail miladjannesari@gmail.comPurpose: This study answer calls for research on host country nationals (HCNs) by examining factors that may influence HCN task performance and contextual performance during work with their self-initiated expatriate (SIE) colleagues.Participants and Methods: Data on personality traits (extraversion, openness), socialization self-efficacy, and frequency of interaction, task, and contextual performance were collected by surveying 373 Chinese HCNs. The first author recruited the HCNs through SIEs working and living in China. SIEs who participated in this project provided the email addresses of HCNs with whom they worked.Results: The frequency of interactions fully mediated the relationship between (a) extraversion with task and contextual performance and (b) openness with task and contextual performance. Only socialization self-efficacy moderated the mediating effects of extraversion on task performance via the frequency of interaction; it also moderated the mediating effects of openness on contextual performance via the frequency of interactions, but not in the hypothesized direction.Conclusion: This study investigated the neglected stakeholder in the expatriation process, namely, HCNs, and what factors may impact HCNs’ performance during work and collaboration with their SIE colleagues.Keywords: host country nationals, expatriates, career, personality, socialization self-efficacy

Axon regeneration and remyelination of the damaged region is the most common repair strategy for spinal cord injury. However, achieving good outcome remains difficult. Our previous study showed that porcine decellularized optic nerve better mimics the extracellular matrix of the embryonic porcine optic nerve and promotes the directional growth of dorsal root ganglion neurites. However, it has not been reported whether this material promotes axonal regeneration in vivo. In the present study, a porcine decellularized optic nerve was seeded with neurotrophin-3-overexpressing Schwann cells. This functional scaffold promoted the directional growth and remyelination of regenerating axons. In vitro, the porcine decellularized optic nerve contained many straight, longitudinal channels with a uniform distribution, and microscopic pores were present in the channel wall. The spatial micro topological structure and extracellular matrix were conducive to the adhesion, survival and migration of neural stem cells. The scaffold promoted the directional growth of dorsal root ganglion neurites, and showed strong potential for myelin regeneration. Furthermore, we transplanted the porcine decellularized optic nerve containing neurotrophin-3-overexpressing Schwann cells in a rat model of T10 spinal cord defect in vivo. Four weeks later, the regenerating axons grew straight, the myelin sheath in the injured/transplanted area recovered its structure, and simultaneously, the number of inflammatory cells and the expression of chondroitin sulfate proteoglycans were reduced. Together, these findings suggest that porcine decellularized optic nerve loaded with Schwann cells overexpressing neurotrophin-3 promotes the directional growth of regenerating spinal cord axons as well as myelin regeneration. All procedures involving animals were conducted in accordance with the ethical standards of the Institutional Animal Care and Use Committee of Sun Yat-sen University (approval No. SYSU-IACUC-2019-B034) on February 28, 2019.

T-cadherin functions as a suppressor gene, which is frequently inactivated by aberrant promoter methylation in several human cancers, but its methylation status in oral squamous cell carcinoma (OSCC) has been scarcely studied. Thus this study aimed at exploring the clinical significance and prognostic value of T-cadherin methylation in sera of patients with OSCC. Methylation-specific PCR (MSP) and bisulfate sequencing PCR (BSP) was performed to examine the methylation status of T-cadherin. Then, the associations between methylation status of T-cadherin and various clinicopathological variables or patient survival were investigated in 202 patients with OSCC and 68 controls. T-cadherin methylation was detected in 62 out of 202 (30.7%) patients with OSCC, and the methylation status of T-cadherin in corresponding tissues was confirmed by BSP. Methylation of T-cadherin was significantly associated with advanced tumor T-stage (P < 0.001) and N-stage (P = 0.003), positive lymphatic metastasis (P = 0.004) and tumor recurrence (P = 0.001). In addition, patients with methylation of T-cadherin had worse overall survival (P = 0.018) and progression-free survival (P < 0.001) than patients without, and methylation of T-cadherin in sera was an independent prognostic factor for worse overall survival (HR: 3.626, 95% CI: 1.112-9.624, P = 0.007) and progression-free survival (HR: 4.201, 95% CI: 1.562-10.038, P < 0.001) of patients with OSCC. These results demonstrated that methylation of T-cadherin was frequently detected in sera of patients with OSCC, which was associated with risk factors of poor outcomes, and may act as a potential independent prognostic marker for patients with OSCC.

A sudden blow or jolt to the human brain called traumatic brain injury (TBI) is one of the most common injuries recorded in the health insurance claim. Generally, computed tomography (CT) or magnetic resonance imaging (MRI) is required to identify the trauma’s severity. Unfortunately, CT and MRI equipment are bulky, expensive, and not always available, limiting their use in TBI detection. Therefore, as an alternative, this study presents a novel classification architecture that can classify non-severe TBI patients from healthy subjects by using resting-state electroencephalogram (EEG) as the input. The proposed architecture employs a convolutional neural network (CNN), and error-correcting output codes support vector machine (ECOC-SVM) to perform automated feature extraction and multi-class classification. In this architecture, complex feature selection and extraction steps are avoided. The proposed architecture attained a high-performance classification accuracy of 99.76%, potentially being used as a classification approach to preventing healthcare insurance fraud. The proposed method is compared to existing studies in the literature. The outcome from the comparisons indicates that the proposed method has outperformed the benchmarked methods by presenting the highest classification accuracy and precision.

Background: Epidemiologic studies have shown that persons suffering from psychotic disorders are at increased risk of violent behavior. Several factors have been shown to predict violent behavior among persons with psychosis. However, prior research is limited in that these factors have not been explored simultaneously within the same study. Methods: The current study, therefore, aimed to determine which demographic, clinical, cognitive, and developmental characteristics were associated with an increased likelihood of violence among patients diagnosed with a psychotic disorder and which combination of these best predicted a history of violence. Participants (n=53) completed measures of demographics, violence risk, psychotic and personality symptoms, trauma, psychopathy and cognitive functioning. Results: Bivariate relationships were conducted to compare the history of violent behavior between all variables. Additionally, a binary logistic regression was run predicting participants’ history of violence. Several demographic, cognitive, clinical, and developmental factors were associated with increased odds of having a history of violence. The overall correct classification rate for the model was 92.2%, with 87.5% of participants without a history of violence and 91.4% with a history of violence being correctly classified. The model included antisocial personality traits, poor behavioral controls, head injury, not accepting responsibility, lacking goals, prior supervision failures, and HCR-20 total score. Conclusion: The binary logistic regression model showed good accuracy in predicting a history of violence in persons with psychosis. These findings are consistent with prior research and can inform efforts at risk assessment and identification of treatment targets for people with a psychotic disorder who are at highest risk of violence.

Diabetes is a metabolic disorder caused by insufficient insulin secretion and insulin secretion disorders. From health to diabetes, there are generally three stages: health, pre-diabetes and type 2 diabetes. Early diagnosis of diabetes is the most effective way to prevent and control diabetes and its complications. In this work, we collected the physical examination data from Beijing Physical Examination Center from January 2006 to December 2017, and divided the population into three groups according to the WHO (1999) Diabetes Diagnostic Standards: normal fasting plasma glucose (NFG) (FPG6.1 mmol/L), mildly impaired fasting plasma glucose (IFG) (6.1 mmol/L ≤ FPG7.0 mmol/L) and type 2 diabetes (T2DM) (FPG7.0 mmol/L). Finally, we obtained1,221,598 NFG samples, 285,965 IFG samples and 387,076 T2DM samples, with a total of 15 physical examination indexes. Furthermore, taking eXtreme Gradient Boosting (XGBoost), random forest (RF), Logistic Regression (LR), and Fully connected neural network (FCN) as classifiers, four models were constructed to distinguish NFG, IFG and T2DM. The comparison results show that XGBoost has the best performance, with AUC (macro) of 0.7874 and AUC (micro) of 0.8633. In addition, based on the XGBoost classifier, three binary classification models were also established to discriminate NFG from IFG, NFG from T2DM, IFG from T2DM. On the independent dataset, the AUCs were 0.7808, 0.8687, 0.7067, respectively. Finally, we analyzed the importance of the features and identified the risk factors associated with diabetes.

We investigated the effect of sense of status on undergraduate students' international entrepreneurial intention as well as the possible influences of risk propensity and having a global mindset on this relationship. Data were collected by surveying 265 students at 19 universities in Eastern China. As hypothesized, sense of status was positively related to the students' international entrepreneurial intention, and this relationship was mediated by risk propensity. Further, having a global mindset moderated the mediating effect of risk propensity on the relationship between sense of status and international entrepreneurial intention. This study demonstrates the value to international business study of examining the previously neglected association between sense of status and international entrepreneurial intention among undergraduates in China, as well as how risk propensity may influence international entrepreneurial intention.

Background: RNA methylation is a reversible post-transcriptional modification involving numerous biological processes. Ribose 2'-O-methylation is part of RNA methylation. It has shown that ribose 2'-O-methylation plays an important role in immune recognition and other pathogenesis. Objective: We aim to design a computational method to identify 2'-O-methylation. Methods: Different from the experimental method, we propose a computational workflow to identify the methylation site based on the multi-feature extracting algorithm. Results: With a voting procedure based on 7 best feature-classifier combinations, we achieved Accuracy of 76.5% in 10-fold cross-validation. Furthermore, we optimized features and input the optimized features into SVM. As a result, the AUC reached to 0.813. Conclusion: The RNA sample, especially the negative samples, used in this study are more objective and strict, so we obtained more representative results than state-of-arts studies.

A molecular NiFe complex (Cyclen@Ni0.5Fe0.5) was incorporated into the framework of COF (NH4@COF-SO3) by a one-pot post-synthesis method. The use of cyclen that can strongly chelate metal ions enables the formation of completely isolated metal sits uniformly distributed on the framework of COF. The resulting single-site heterogeneous catalyst ((Cyclen@Ni0.5Fe0.5)@COF-SO3) exhibits outstanding oxygen evolution reaction (OER) activity because of the maximum atom-utilization efficiency and significant bimetallic synergy effect. The TOF value at the overpotential of 300 mV reaches as high as 0.69 s−1, which is superior to most of the recently reported efficient OER electrocatalysts. Moreover, the catalyst is stable and reusable without the loss of current density during a 25 h long-term test. The combination of advantages of molecular catalysts (metal complex) similar to homogeneous catalysts and solid COF materials for the fabrication of single-site heterogeneous catalysts first reported in this work can bring new avenues to develop highly efficient and stable COF-based catalysts in different catalytic fields.

The incidence and disability rate of spinal cord injury (SCI) worldwide are high, imposing a heavy burden on patients. Considerable research efforts have been directed toward identifying new strategies to effectively treat SCI. Governor Vessel electro-acupuncture (GV-EA), used in traditional Chinese medicine, combines acupuncture with modern electrical stimulation. It has been shown to improve the microenvironment of injured spinal cord (SC) by increasing levels of endogenous neurotrophic factors and reducing inflammation, thereby protecting injured neurons and promoting myelination. In addition, axons extending from transplanted stem cell-derived neurons can potentially bridge the two severed ends of tissues in a transected SC to rebuild neuronal circuits and restore motor and sensory functions. However, every single treatment approach to severe SCI has proven unsatisfactory. Combining different treatments-for example, electro-acupuncture (EA) with adult stem cell transplantation-appears to be a more promising strategy. In this review, we have summarized the recent progress over the past two decades by our team especially in the use of GV-EA for the repair of SCI. By this strategy, we have shown that EA can stimulate the nerve endings of the meningeal branch. This would elicit the dorsal root ganglion neurons to secrete excess amounts of calcitonin gene-related peptide centrally in the SC. The neuropeptide then activates the local cells to secrete neurotrophin-3 (NT-3), which mediates the survival and differentiation of donor stem cells overexpressing the NT-3 receptor, at the injury/graft site of the SC. Increased local production of NT-3 facilitates reconstruction of host neural tissue such as nerve fiber regeneration and myelination. All this events in sequence would ultimately strengthen the cortical motor-evoked potentials and restore the motor function of paralyzed limbs. The information presented herein provides a basis for future studies on the clinical application of GV-EA and adult stem cell transplantation for the treatment of SCI.