National Taipei University

Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer ( http://www.cellchat.org/ ) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.

It has been established that cancer can be promoted and/or exacerbated by inflammation and infections. Indeed, chronic inflammation orchestrates a tumor-supporting microenvironment that is an indispensable participant in the neoplastic process. The mechanisms that link infection, innate immunity, inflammation, and cancer are being unraveled at a fast pace. Important components in this linkage are the cytokines produced by activated innate immune cells that stimulate tumor growth and progression. In addition, soluble mediators produced by cancer cells recruit and activate inflammatory cells, which further stimulate tumor progression. However, inflammatory cells also produce cytokines that can limit tumor growth. Here we provide an overview of the current understanding of the role of inflammation-induced cytokines in tumor initiation, promotion, and progression.

Access to hierarchically porous carbons from polymers and biopolymers<italic>via</italic>a non-templating route has emerged as a promising strategy for a range of energy applications.

It is well accepted that umbilical cord blood has been a source for hematopoietic stem cells. However, controversy exists as to whether cord blood can serve as a source of mesenchymal stem cells, which can differentiate into cells of different connective tissue lineages such as bone, cartilage, and fat, and little success has been reported in the literature about the isolation of such cells from cord blood. Here we report a novel method to obtain single cell-derived, clonally expanded mesenchymal stem cells that are of multilineage differentiation potential by negative immunoselection and limiting dilution. The immunophenotype of these clonally expanded cells is consistent with that reported for bone marrow mesenchymal stem cells. Under appropriate induction conditions, these cells can differentiate into bone, cartilage, and fat. Surprisingly, these cells were also able to differentiate into neuroglial- and hepatocyte-like cells under appropriate induction conditions and, thus, these cells may be more than mesenchymal stem cells as evidenced by their ability to differentiate into cell types of all 3 germ layers. In conclusion, umbilical cord blood does contain mesenchymal stem cells and should not be regarded as medical waste. It can serve as an alternative source of mesenchymal stem cells to bone marrow.

Purpose The purpose of this study is to develop an original framework to explore the influences of green perceived value and green perceived risk on green purchase intentions and to discuss the mediation role of green trust. Design/methodology/approach This study applies four original concepts – green perceived value, green perceived risk, green trust, and green purchase intentions – to develop an integral model to enhance green purchase intentions. In addition, this research employs an empirical study by means of the questionnaire survey method to verify the hypotheses and to explore its managerial implications. Structural equation modeling (SEM) is applied to verify the research framework. Findings The empirical results show that green perceived value would positively affect green trust and green purchase intentions, while green perceived risk would negatively influence both of them. Furthermore, this study demonstrates that the relationships between green purchase intentions and their two antecedents – green perceived value and green perceived risk – are partially mediated by green trust. Hence, investing resources to increase green perceived value and to decrease green perceived risk is helpful to enhance green trust and green purchase intentions. Originality/value This study summarizes the literature on green marketing and relationship marketing into a new managerial framework of green purchase intentions. It utilizes four novel constructs – green perceived value, green perceived risk, green trust, and green purchase intentions – to develop an original research framework to enhance green purchase intentions. Although past research has highlighted the relevant issues about purchase intentions, none explores it about green management. Therefore, this paper develops the research framework of green purchase intentions to fill the research gap.

BACKGROUND: -mutated AML. METHODS: -mutated AML in a 2:1 ratio to receive either gilteritinib (at a dose of 120 mg per day) or salvage chemotherapy. The two primary end points were overall survival and the percentage of patients who had complete remission with full or partial hematologic recovery. Secondary end points included event-free survival (freedom from treatment failure [i.e., relapse or lack of remission] or death) and the percentage of patients who had complete remission. RESULTS: Of 371 eligible patients, 247 were randomly assigned to the gilteritinib group and 124 to the salvage chemotherapy group. The median overall survival in the gilteritinib group was significantly longer than that in the chemotherapy group (9.3 months vs. 5.6 months; hazard ratio for death, 0.64; 95% confidence interval [CI], 0.49 to 0.83; P<0.001). The median event-free survival was 2.8 months in the gilteritinib group and 0.7 months in the chemotherapy group (hazard ratio for treatment failure or death, 0.79; 95% CI, 0.58 to 1.09). The percentage of patients who had complete remission with full or partial hematologic recovery was 34.0% in the gilteritinib group and 15.3% in the chemotherapy group (risk difference, 18.6 percentage points; 95% CI, 9.8 to 27.4); the percentages with complete remission were 21.1% and 10.5%, respectively (risk difference, 10.6 percentage points; 95% CI, 2.8 to 18.4). In an analysis that was adjusted for therapy duration, adverse events of grade 3 or higher and serious adverse events occurred less frequently in the gilteritinib group than in the chemotherapy group; the most common adverse events of grade 3 or higher in the gilteritinib group were febrile neutropenia (45.9%), anemia (40.7%), and thrombocytopenia (22.8%). CONCLUSIONS: -mutated AML. (Funded by Astellas Pharma; ADMIRAL ClinicalTrials.gov number, NCT02421939.).

MicroRNAs (miRNAs) are noncoding RNAs with 18-26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA-target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update's critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3' untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.

To achieve security in wireless sensor networks, it is important to be able to encrypt and authenticate messages sent between sensor nodes. Before doing so, keys for performing encryption and authentication must be agreed upon by the communicating parties. Due to resource constraints, however, achieving key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and other public-key based schemes, are not suitable for wireless sensor networks due to the limited computational abilities of the sensor nodes. Predistribution of secret keys for all pairs of nodes is not viable due to the large amount of memory this requires when the network size is large.In this paper, we provide a framework in which to study the security of key predistribution schemes, propose a new key predistribution scheme which substantially improves the resilience of the network compared to previous schemes, and give an in-depth analysis of our scheme in terms of network resilience and associated overhead. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that communications between any additional nodes are compromised is close to zero. This desirable property lowers the initial payoff of smaller-scale network breaches to an adversary, and makes it necessary for the adversary to attack a large fraction of the network before it can achieve any significant gain.

Ongoing brain activity can be recorded as electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study applied machine-learning algorithms to categorize EEG dynamics according to subject self-reported emotional states during music listening. A framework was proposed to optimize EEG-based emotion recognition by systematically 1) seeking emotion-specific EEG features and 2) exploring the efficacy of the classifiers. Support vector machine was employed to classify four emotional states (joy, anger, sadness, and pleasure) and obtained an averaged classification accuracy of 82.29% +/- 3.06% across 26 subjects. Further, this study identified 30 subject-independent features that were most relevant to emotional processing across subjects and explored the feasibility of using fewer electrodes to characterize the EEG dynamics during music listening. The identified features were primarily derived from electrodes placed near the frontal and the parietal lobes, consistent with many of the findings in the literature. This study might lead to a practical system for noninvasive assessment of the emotional states in practical or clinical applications.

CONTEXT: Tumor recurrence is a major issue for patients with hepatocellular carcinoma (HCC) following curative liver resection. OBJECTIVE: To investigate the association between nucleoside analogue use and risk of tumor recurrence in patients with hepatitis B virus (HBV)--related HCC after curative surgery. DESIGN, SETTING, AND PARTICIPANTS: A nationwide cohort study between October 2003 and September 2010. Data from the Taiwan National Health Insurance Research Database. Among 100 938 newly diagnosed HCC patients, we identified 4569 HBV-related HCC patients who received curative liver resection for HCC between October 2003 and September 2010. MAIN OUTCOME MEASURES: The risk of first tumor recurrence was compared between patients not taking nucleoside analogues (untreated cohort, n = 4051) and patients taking nucleoside analogues (treated cohort, n = 518). Cumulative incidences and hazard ratios (HRs) were calculated after adjusting for competing mortality. RESULTS: The treated cohort had a higher prevalence of liver cirrhosis when compared with the untreated cohort (48.6% vs 38.7%; P < .001), but lower risk of HCC recurrence (n = 106 [20.5%] vs n = 1765 [43.6%]; P < .001), and lower overall death (n = 55 [10.6%] vs n = 1145 [28.3%]; P < .001). After adjusting for competing mortality, the treated cohort had a significantly lower 6-year HCC recurrence rate (45.6%; 95% CI, 36.5%-54.6% vs untreated, 54.6%; 95% CI, 52.5%-56.6%; P < .001). Six-year overall mortalities for treated cohorts were 29.0% (95% CI, 20.0%-38.0%) and for untreated 42.4% (95% CI, 40.0%-44.7%; P < .001). On modified Cox regression analysis, nucleoside analogue use (HR, 0.67; 95% CI, 0.55-0.81; P < .001), statin use (HR, 0.68; 95% CI, 0.53-0.87; P = .002), and nonsteroidal anti-inflammatory drugs or aspirin use (HR, 0.80; 95% CI, 0.73-0.88; P < .001) were independently associated with a reduced risk of HCC recurrence. Multivariable stratified analyses verified the association in all subgroups of patients, including those who were noncirrhotic (HR, 0.56; 95% CI, 0.42-0.76) and diabetic (HR, 0.52; 95% CI, 0.31-0.89). CONCLUSION: Nucleoside analogue use was associated with a lower risk of HCC recurrence among patients with HBV-related HCC after liver resection.

Food futurists accept that sustainability-minded humanity will increasingly incorporate insects as alternative protein. The most studied and easily reared species are not necessarily the most sustainable, acceptable, or delicious. Here, we review the literature on the black soldier fly, Hermetia illucens, which is capable of efficiently converting a wide variety of organic materials, from food waste to manure, into insect biomass. They can be grown and harvested without dedicated facilities and are not pestiferous. Their larvae are 42% crude protein and 29% fat, although they are higher in saturated fats than most insects. They do not concentrate pesticides or mycotoxins. They are already grown and recommended for use as animal feed, but with regional legal restrictions on how this is done. For commercial use in human foods, larvae could potentially be milled and converted into a textured protein with a strong flavor. Their biggest advantage over other insects is their ability to convert waste into food, generating value and closing nutrient loops as they reduce pollution and costs. This general advantage is also their greatest disadvantage, for the social stigmas and legal prohibitions against eating organisms that eat waste are added to extant taboos facing insect consumption.

The sudden outbreak of 2019 novel coronavirus (2019-nCoV, later named SARS-CoV-2) in Wuhan, China, which rapidly grew into a global pandemic, marked the third introduction of a virulent coronavirus into the human society, affecting not only the healthcare system, but also the global economy. Although our understanding of coronaviruses has undergone a huge leap after two precedents, the effective approaches to treatment and epidemiological control are still lacking. In this article, we present a succinct overview of the epidemiology, clinical features, and molecular characteristics of SARS-CoV-2. We summarize the current epidemiological and clinical data from the initial Wuhan studies, and emphasize several features of SARS-CoV-2, which differentiate it from SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), such as high variability of disease presentation. We systematize the current clinical trials that have been rapidly initiated after the outbreak of COVID-19 pandemic. Whereas the trials on SARS-CoV-2 genome-based specific vaccines and therapeutic antibodies are currently being tested, this solution is more long-term, as they require thorough testing of their safety. On the other hand, the repurposing of the existing therapeutic agents previously designed for other virus infections and pathologies happens to be the only practical approach as a rapid response measure to the emergent pandemic, as most of these agents have already been tested for their safety. These agents can be divided into two broad categories, those that can directly target the virus replication cycle, and those based on immunotherapy approaches either aimed to boost innate antiviral immune responses or alleviate damage induced by dysregulated inflammatory responses. The initial clinical studies revealed the promising therapeutic potential of several of such drugs, including favipiravir, a broad-spectrum antiviral drug that interferes with the viral replication, and hydroxychloroquine, the repurposed antimalarial drug that interferes with the virus endosomal entry pathway. We speculate that the current pandemic emergency will be a trigger for more systematic drug repurposing design approaches based on big data analysis.

BACKGROUND: This study examines the predictive value of a novel systemic immune-inflammation index (SII, platelet × neutrophil/lymphocyte ratio) in coronary artery disease (CAD) patients. METHODS: A total of 5602 CAD patients who had undergone a percutaneous coronary intervention (PCI) were enrolled. They were divided into two groups by baseline SII score (high SII vs low SII) to analyse the relationship between SII groups and the long-term outcome. The primary outcomes were major cardiovascular events (MACE) which includes nonfatal myocardial infarction (MI), nonfatal stroke and cardiac death. Secondary outcomes included a composite of MACE and hospitalization for congestive heart failure. RESULTS: was identified for MACE in the CAD training cohort (n = 373) and then verified in the second larger CAD cohort (n = 5602). Univariate and multivariate analyses showed that a higher SII score (≥694.3) was independently associated with increased risk of developing cardiac death (HR: 2.02; 95% CI: 1.43-2.86), nonfatal MI (HR: 1.42; 95% CI: 1.09-1.85), nonfatal stroke (HR: 1.96; 95% CI: 1.28-2.99), MACE (HR: 1.65; 95% CI: 1.36-2.01) and total major events (HR: 1.53; 95% CI: 1.32-1.77). In addition, the SII significantly improved risk stratification of MI, cardiac death, heart failure, MACE and total major events than conventional risk factors in CAD patients by the significant increase in the C-index (P < .001) and reclassification risk categories by significant NRI (P < .05) and IDI (P < .05). CONCLUSIONS: SII had a better prediction of major cardiovascular events than traditional risk factors in CAD patients after coronary intervention.

Support vector machines (SVMs) were originally designed for binary classification. How to effectively extend it for multiclass classification is still an ongoing research issue. Several methods have been proposed where typically we construct a multiclass classifier by combining several binary classifiers. Some authors also proposed methods that consider all classes at once. As it is computationally more expensive to solve multiclass problems, comparisons of these methods using large-scale problems have not been seriously conducted. Especially for methods solving multiclass SVM in one step, a much larger optimization problem is required so up to now experiments are limited to small data sets. In this paper we give decomposition implementations for two such "all-together" methods. We then compare their performance with three methods based on binary classifications: "one-against-all," "one-against-one," and directed acyclic graph SVM (DAGSVM). Our experiments indicate that the "one-against-one" and DAG methods are more suitable for practical use than the other methods. Results also show that for large problems methods by considering all data at once in general need fewer support vectors.

In the late 1970s and early 1980s, several important reviews of the literature failed to establish a clear consensus on the relationship between economic conditions and violent crime. The research presented here applies the procedures of meta-analysis to 34 aggregate data studies reporting on violent crime, poverty, and income inequality. These studies reported a total of 76 zero-order correlation coefficients for all measures of violent crime with either poverty or income inequality. Of the 76 coefficients, all but 2, or 97 percent, were positive. Of the positive coefficients, nearly 80 percent were of at least moderate strength (&gt;.25). It is concluded that poverty and income inequality are each associated with violent crime. The analysis, however, shows considerable variation in the estimated size of the relationships and suggests that homicide and assault may be more closely associated with poverty or income inequality than are rape and robbery.

OBJECTIVE: The aim of this study was to develop a self-administered scale based on the special features of smartphone. The reliability and validity of the Smartphone Addiction Inventory (SPAI) was demonstrated. METHODS: A total of 283 participants were recruited from Dec. 2012 to Jul. 2013 to complete a set of questionnaires, including a 26-item SPAI modified from the Chinese Internet Addiction Scale and phantom vibration and ringing syndrome questionnaire. There were 260 males and 23 females, with ages 22.9 ± 2.0 years. Exploratory factor analysis, internal-consistency test, test-retest, and correlation analysis were conducted to verify the reliability and validity of the SPAI. Correlations between each subscale and phantom vibration and ringing were also explored. RESULTS: Exploratory factor analysis yielded four factors: compulsive behavior, functional impairment, withdrawal and tolerance. Test-retest reliabilities (intraclass correlations = 0.74-0.91) and internal consistency (Cronbach's α = 0.94) were all satisfactory. The four subscales had moderate to high correlations (0.56-0.78), but had no or very low correlation to phantom vibration/ringing syndrome. CONCLUSION: This study provides evidence that the SPAI is a valid and reliable, self-administered screening tool to investigate smartphone addiction. Phantom vibration and ringing might be independent entities of smartphone addiction.

BACKGROUND: There are few cross-national comparisons of the rates of suicide ideation and attempts across diverse countries. Nine independently conducted epidemiological surveys using similar diagnostic assessment and criteria provided an opportunity to obtain that data. METHODS: Suicide ideation and attempts were assessed on the Diagnostic Interview Schedule in over 40000 subjects drawn from the United States, Canada, Puerto Rico, France, West Germany, Lebanon, Taiwan, Korea and New Zealand. RESULTS: The lifetime prevalence rates/100 for suicide ideation ranged from 2.09 (Beirut) to 18.51 (Christchurch, New Zealand). Lifetime prevalence rates/100 for suicide attempts ranged from 0.72 (Beirut) to 5.93 (Puerto Rico). Females as compared to males had only marginally higher rates of suicidal ideation in most countries, reaching a two-fold increase in Taiwan. Females as compared to males had more consistently higher rates for suicide attempts, reaching a two- to three-fold increase in most countries. Suicide ideation and attempts in most countries were associated with being currently divorced/separated as compared to currently married. CONCLUSIONS: While the rates of suicide ideation varied widely by country, the rates of suicide attempts were more consistent across most countries. The variations were only partly explained by variation in rates of psychiatric disorders, divorce or separation among countries and are probably due to cultural features that we do not, as yet, understand.

Exosomes are extracellular vesicles that share components of their parent cells and are attractive in biotechnology and biomedical research as potential disease biomarkers as well as therapeutic agents. Crucial to realizing this potential is the ability to manufacture high-quality exosomes; however, unlike biologics such as proteins, exosomes lack standardized Good Manufacturing Practices for their processing and characterization. Furthermore, there is a lack of well-characterized reference exosome materials to aid in selection of methods for exosome isolation, purification, and analysis. This review informs exosome research and technology development by comparing exosome processing and characterization methods and recommending exosome workflows. This review also provides a detailed introduction to exosomes, including their physical and chemical properties, roles in normal biological processes and in disease progression, and summarizes some of the on-going clinical trials.

BACKGROUND: Silent information regulator 1 (Sirt1), a class III histone deacetylase, retards aging and protects the heart from oxidative stress. We here examined whether Sirt1 is protective against myocardial ischemia/reperfusion (I/R). METHODS AND RESULTS: Protein and mRNA expression of Sirt1 is significantly reduced by I/R. Cardiac-specific Sirt1(-/-) mice exhibited a significant increase (44±5% versus 15±5%; P=0.01) in the size of myocardial infarction/area at risk. In transgenic mice with cardiac-specific overexpression of Sirt1, both myocardial infarction/area at risk (15±4% versus 36±8%; P=0.004) and terminal deoxynucleotidyl transferase dUTP nick end labeling-positive nuclei (4±3% versus 10±1%; P<0.003) were significantly reduced compared with nontransgenic mice. In Langendorff-perfused hearts, the functional recovery during reperfusion was significantly greater in transgenic mice with cardiac-specific overexpression of Sirt1 than in nontransgenic mice. Sirt1 positively regulates expression of prosurvival molecules, including manganese superoxide dismutase, thioredoxin-1, and Bcl-xL, whereas it negatively regulates the proapoptotic molecules Bax and cleaved caspase-3. The level of oxidative stress after I/R, as evaluated by anti-8-hydroxydeoxyguanosine staining, was negatively regulated by Sirt1. Sirt1 stimulates the transcriptional activity of FoxO1, which in turn plays an essential role in mediating Sirt1-induced upregulation of manganese superoxide dismutase and suppression of oxidative stress in cardiac myocytes. Sirt1 plays an important role in mediating I/R-induced increases in the nuclear localization of FoxO1 in vivo. CONCLUSIONS: These results suggest that Sirt1 protects the heart from I/R injury through upregulation of antioxidants and downregulation of proapoptotic molecules through activation of FoxO and decreases in oxidative stress.

Epithelial cells are the first line of mucosal defense. In the intestine, a single layer of epithelial cells must establish a selectively permeable barrier that supports nutrient absorption and waste secretion while preventing the leakage of potentially harmful luminal materials. Key to this is the tight junction, which seals the paracellular space and prevents unrestricted leakage. The tight junction is a protein complex established by interactions between members of the claudin, zonula occludens, and tight junction-associated MARVEL protein (TAMP) families. Claudins form the characteristic tight junction strands seen by freeze-fracture microscopy and create paracellular channels, but the functions of ZO-1 and occludin, founding members of the zonula occludens and TAMP families, respectively, are less well defined. Recent studies have revealed that these proteins have essential noncanonical (nonbarrier) functions that allow them to regulate epithelial apoptosis and proliferation, facilitate viral entry, and organize specialized epithelial structures. Surprisingly, neither is required for intestinal barrier function or overall health in the absence of exogenous stressors. Here, we provide a brief overview of ZO-1 and occludin canonical (barrier-related) functions, and a more detailed examination of their noncanonical functions.