Characterization of the aggregation-induced enhanced emission of N,N'-bis(4-methoxysalicylide)benzene-1,4-diamine

© 2015 Springer Science+Business Media New York. N,N′-bis(4-methoxysalicylide)benzene-1,4-diamine (S1) was synthesized from 4-methoxysalicylaldehyde and p-phenylenediamine and it was found to exhibit interesting aggregation-induced emission enhancement (AIEE) characteristics. In aprotic solvent, S1 displayed very weak fluorescence, whilst strong emission was observed when in protic solvent. The morphology characteristics and luminescent properties of S1 were determined from the fluorescence and UV absorption spectra, SEM, fluorescence microscope and grading analysis. Analysis of the single crystal diffraction data infers that the intramolecular hydrogen bonding constitutes to a coplanar structure and orderly packing in aggregated state, which in turn hinders intramolecular C-N single bond rotation. Given that the three benzene rings formed a large plane conjugated structure, the fluorescence emission was significantly enhanced. The absolute fluorescence quantum yield and fluorescence lifetime also showed that radiation transition was effectively enhanced in the aggregated state. Moreover, the AIEE behavior of S1 suggests there is a potential application in the fluorescence sensing of some volatile organic solvents

Research on Strategies for Promoting Regional Modern Service Industry Development from the Perspective of Mobile E-commerce in Higher Vocational Education

With the rapid development of mobile e-commerce, higher vocational education plays a crucial role in promoting the development of the regional modern service industry. This paper, based on the perspective of mobile e-commerce, investigates the role and strategies of higher vocational education in regional modern service industry development. Firstly, it provides an overview of the current status of mobile e-commerce and higher vocational education, along with relevant research findings. Secondly, it explores the correlation between mobile e-commerce and higher vocational education, proposing strategies and measures for higher vocational education in nurturing mobile e-commerce talents. Furthermore, it analyzes the definition and characteristics of the regional modern service industry, elucidating the supportive role of higher vocational education in its development and suggesting specific strategies. Subsequently, through practical examples and case studies, it introduces cases of higher vocational education in specific regions and their impact on the development of the regional modern service industry, evaluating the implementation process and outcomes, summarizing experiences and insights. Finally, the paper presents policy recommendations and prospects, including government policy support and guidance for higher vocational education, directions and planning for higher vocational education in future mobile e-commerce and regional modern service industry development, as well as prospects for future research directions and application promotion. The aim of this paper is to provide theoretical and practical guidance for higher vocational education and the development of the regional modern service industry, promoting economic development and social progress

Research on Intelligent Design of Luxury Yacht

Unified model-driven and intelligent collaborative design has gradually become a new paradigm in luxury yacht design as the Internet of Things (IoT) and Big Data are gaining global momentum. This paper aims to initiate a research framework to systematically study feasibilities and challenges in developing and implementing this new paradigm. As the first step of this grand research endeavor, the paper investigates the state-of-the-art technological infrastructure to digitalization and automation in yacht production design, and conducts theoretic analysis of data integration and synergistic design collaboration as the backbone to this data-intensive, intelligent and collaborative design approach. The paper then conjectures the possible development trend of luxury yacht production in the intelligent design and manufacturing environment, and lays out a foundation to future research. (C) 2017 The Authors. Published by Elsevier Ltd.13th Global Congress on Manufacturing and Management (GCMM), NOV 28-30, 2016, Zhengzhou Univ, Zhengzhou, PEOPLES R CHINAhttps://doi.org/10.1016/j.proeng.2017.01.24

Protective Effects of Shen-Yuan-Dan, a Traditional Chinese Medicine, against Myocardial Ischemia/Reperfusion Injury<i>In Vivo</i>and<i>In Vitro</i>

Objectives.The study was to investigate the effects and mechanisms of Shen-Yuan-Dan (SYD) pharmacological postconditioning on myocardial ischemia/reperfusion (I/R) injury.Methods.In thein vivoexperiment, myocardial injury markers and histopathology staining were examined. In thein vitroexperiment, cell viability and cell apoptosis were, respectively, detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays and Hoechst 33342 fluorochrome staining. The protein expressions of Bcl-2 and Bax were determined by immunocytochemistry assay.Results.Both low and high doses of SYD protected myocardium against I/R injury in rat model by reducing lactic dehydrogenase (LDH) and creatine kinase-MB (CK-MB) activity and malondialdehyde (MDA) content, increasing superoxide dismutase (SOD) activity and attenuating histopathology injury. Meanwhile, in thein vitroexperiment, SYD promoted cell viability and inhibited the cardiomyocyte apoptosis. The level of Bcl-2 protein was restored to the normal level by SYD pharmacological postconditioning. In contrast, the Bax protein level was markedly reduced by SYD pharmacological postconditioning. These effects of SYD were inhibited by LY294002.Conclusions.The results of this study suggested that SYD pharmacological postconditioning has protective effects against myocardial I/R injury in bothin vivoandin vitromodels, which are related to activating the phosphatidylinositol 3-kinase/Akt (PI3K/Akt) pathway.</jats:p

Tumor Tissue Detection using Blood-Oxygen-Level-Dependent Functional MRI based on Independent Component Analysis

Accurate delineation of gliomas from the surrounding normal brain areas helps maximize tumor resection and improves outcome. Blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) has been routinely adopted for presurgical mapping of the surrounding functional areas. For completely utilizing such imaging data, here we show the feasibility of using presurgical fMRI for tumor delineation. In particular, we introduce a novel method dedicated to tumor detection based on independent component analysis (ICA) of resting-state fMRI (rs-fMRI) with automatic tumor component identification. Multi-center rs-fMRI data of 32 glioma patients from three centers, plus the additional proof-of-concept data of 28 patients from the fourth center with non-brain musculoskeletal tumors, are fed into individual ICA with different total number of components (TNCs). The best-fitted tumor-related components derived from the optimized TNCs setting are automatically determined based on a new template-matching algorithm. The success rates are 100%, 100% and 93.75% for glioma tissue detection for the three centers, respectively, and 85.19% for musculoskeletal tumor detection. We propose that the high success rate could come from the previously overlooked ability of BOLD rs-fMRI in characterizing the abnormal vascularization, vasomotion and perfusion caused by tumors. Our findings suggest an additional usage of the rs-fMRI for comprehensive presurgical assessment

Characterizing the Structural Pattern Predicting Medication Response in Herpes Zoster Patients Using Multivoxel Pattern Analysis

Herpes zoster (HZ) can cause a blistering skin rash with severe neuropathic pain. Pharmacotherapy is the most common treatment for HZ patients. However, most patients are usually the elderly or those that are immunocompromised, and thus often suffer from side effects or easily get intractable post-herpetic neuralgia (PHN) if medication fails. It is challenging for clinicians to tailor treatment to patients, due to the lack of prognosis information on the neurological pathogenesis that underlies HZ. In the current study, we aimed at characterizing the brain structural pattern of HZ before treatment with medication that could help predict medication responses. High-resolution structural magnetic resonance imaging (MRI) scans of 14 right-handed HZ patients (aged 61.0 ± 7.0, 8 males) with poor response and 15 (aged 62.6 ± 8.3, 5 males) age- (p = 0.58), gender-matched (p = 0.20) patients responding well, were acquired and analyzed. Multivoxel pattern analysis (MVPA) with a searchlight algorithm and support vector machine (SVM), was applied to identify the spatial pattern of the gray matter (GM) volume, with high predicting accuracy. The predictive regions, with an accuracy higher than 79%, were located within the cerebellum, posterior insular cortex (pIC), middle and orbital frontal lobes (mFC and OFC), anterior and middle cingulum (ACC and MCC), precuneus (PCu) and cuneus. Among these regions, mFC, pIC and MCC displayed significant increases of GM volumes in patients with poor response, compared to those with a good response. The combination of sMRI and MVPA might be a useful tool to explore the neuroanatomical imaging biomarkers of HZ-related pain associated with medication responses

Classification of temporal lobe epilepsy based on neuropsychological tests and exploration of its underlying neurobiology

ObjectiveTo assist improving long-term postoperative seizure-free rate, we aimed to use machine learning algorithms based on neuropsychological data to differentiate temporal lobe epilepsy (TLE) from extratemporal lobe epilepsy (extraTLE), as well as explore the relationship between magnetic resonance imaging (MRI) and neuropsychological tests.MethodsTwenty-three patients with TLE and 23 patients with extraTLE underwent neuropsychological tests and MRI scans before surgery. The least absolute shrinkage and selection operator were firstly employed for feature selection, and a machine learning approach with neuropsychological tests was employed to classify TLE using leave-one-out cross-validation. A generalized linear model was used to analyze the relationship between brain alterations and neuropsychological tests.ResultsWe found that logistic regression with the selected neuropsychological tests generated classification accuracies of 87.0%, with an area under the receiver operating characteristic curve (AUC) of 0.89. Three neuropsychological tests were acquired as significant neuropsychological signatures for the diagnosis of TLE. We also found that the Right-Left Orientation Test difference was related to the superior temporal and the banks of the superior temporal sulcus (bankssts). The Conditional Association Learning Test (CALT) was associated with the cortical thickness difference in the lateral orbitofrontal area between the two groups, and the Component Verbal Fluency Test was associated with the cortical thickness difference in the lateral occipital cortex between the two groups.ConclusionThese results showed that machine learning-based classification with the selected neuropsychological data can successfully classify TLE with high accuracy compared to previous studies, which could provide kind of warning sign for surgery candidate of TLE patients. In addition, understanding the mechanism of cognitive behavior by neuroimaging information could assist doctors in the presurgical evaluation of TLE