Controlling the Decoration of the Reduced Graphene Oxide Surface with Pyrene-Functionalized Gold Nanoparticles

We exploited a non‐covalent approach based on π‐stacking interactions to address the formation of hybrids between pyrene‐functionalized gold nanoparticles (PyAuNPs) and reduced graphene oxide (RGO), in which the former are distributed homogeneously on the surface of the latter with a high degree of coverage. We used water soluble PyAuNPs of two different average dimensions, namely 2 and 8 nm, in which the pendant pyrene moieties were introduced within a mixed monolayer with a choline derivative. The combination with RGO originates highly insoluble materials, in which microscopy evidences a complete adhesion of the PyAuNPs onto the carbon nanomaterial layers in a highly homogeneous fashion, with no traces of free particles, confirming the high affinity between pyrene‐functionalized species and conjugated carbon nanostructure surfaces

HUBUNGAN KUALITAS TIDUR DENGAN KADAR HEMOGLOBIN MAHASISWA FAKULTAS KEDOKTERAN UNDANA

Tidur adalah keadaan saat terjadinya proses pemulihan bagi tubuh dan otak serta sangat penting terhadap pencapaian kesehatan yang optimal. Padatnya aktifitas yang dilakukan mahasiswa menyebabkan lebih mudah mengalami gangguan tidur. Gejala penting dari gangguan tidur adalah kualitas tidur yang buruk. Faktor-faktor yang mempengaruhi kualitas tidur yang buruk yaitu status kesehatan, stres psikologis, diet, gaya hidup, lingkungan dan obat-obatan. Tujuan penelitian ini mengetahui hubungan kualitas tidur dengan kadar hemoglobin mahasiswa Fakultas Kedokteran Undana. Metode dari penelitian ini menggunakan observasional analitik dengan rancangan cross sectional regresi dengan teknik pengambilan sampel stratified random sampling dan didapatkan besar sampel 64 orang. Pengambilan data primer dari pengisian kuisoner Pittsburgh sleep quality index (PSQI) dan pengambilan darah kapiler.Analisis data yang dilakukan adalah univariat dan bivariat dengan uji Chi Square. Hasil penelitian uji analisis data dengan chi squareuntuk mengetahui hubungan kualitas tidur dengan kadar hemoglobin dan didapatkan nilai p=0,00. Kesimpulan penelitian ini terdapat hubungan yang bermakna antara kualitas tidur dengan kadar hemoglobin pada mahasiswa Fakultas Kedokteran Undan

Responding to Covid-19 via online learning: the relationship between Facebook intensity, community factors with social capital and academic performance

The rapid adoption of social media technologies has resulted in a fundamental shift in the way communication and collaboration take place. As staff and students use social media technologies in their personal lives, it is important to explore how social media technologies are being used as an educational tool especially during a pandemic where teaching and learning has to be done via mediated communication. However, the question arises as to how effective the use of social media in terms of Academic Performance and Social Capital of the students. Academic Performance and Social Capital of university students are two interrelated and critical issues which can define the efficacy of social and academic activities of students at their universities. However, few studies have adopted a holistic approachto determine the direct role of online social network activities such as Facebook Intensity, and Community Factors on both Academic Performance and Social Capital of university students. Thus, this study attempted to conduct a cross-sectional survey using self-administered questionnaires which were distributed to 518 undergraduate students at the University of Sirte, Libya. The data was analyzed using various analytical techniques including descriptive statistics, preliminary and inferential analyses by using SPSS and PLS-SEM. The results revealed that Facebook Intensity and Community Factors significantly relate to Social Capital and Academic Performance. This study concludes that the intensity of Facebook Usage among university students and the interactions maintained by students can be used to develop Social Capital. Also, university students with good social communications skills and high self-esteem will benefit from interactions with lecturers and peers and these benefits will certainly enhance their Academic Performance. This study also demonstrates the potential of using Facebook as a teaching aid during pandemic

Identification of chemokine receptors as potential modulators of endocrine resistance in oestrogen receptor–positive breast cancers

Introduction Endocrine therapies target oestrogenic stimulation of breast cancer (BC) growth, but resistance remains problematic. Our aims in this study were (1) to identify genes most strongly associated with resistance to endocrine therapy by intersecting global gene transcription data from patients treated presurgically with the aromatase inhibitor anastrazole with those from MCF7 cells adapted to long-term oestrogen deprivation (LTED) (2) to assess the clinical value of selected genes in public clinical data sets and (3) to determine the impact of targeting these genes with novel agents. Methods Gene expression and Ki67 data were available from 69 postmenopausal women with oestrogen receptor–positive (ER+) early BC, at baseline and 2 weeks after anastrazole treatment, and from cell lines adapted to LTED. The functional consequences of target genes on proliferation, ER-mediated transcription and downstream cell signalling were assessed. Results By intersecting genes predictive of a poor change in Ki67 with those upregulated in LTED cells, we identified 32 genes strongly correlated with poor antiproliferative response that were associated with inflammation and/or immunity. In a panel of LTED cell lines, C-X-C chemokine receptor type 7 (CXCR7) and CXCR4 were upregulated compared to their wild types (wt), and CXCR7, but not CXCR4, was associated with reduced relapse-free survival in patients with ER+ BC. The CXCR4 small interfering RNA variant (siCXCR4) had no specific effect on the proliferation of wt-SUM44, wt-MCF7 and their LTED derivatives. In contrast, siCXCR7, as well as CCX733, a CXCR7 antagonist, specifically suppressed the proliferation of MCF7-LTED cells. siCXCR7 suppressed proteins associated with G1/S transition and inhibited ER transactivation in MCF7-LTED, but not wt-MCF7, by impeding association between ER and proline-, glutamic acid– and leucine-rich protein 1, an ER coactivator. Conclusions These data highlight CXCR7 as a potential therapeutic target warranting clinical investigation in endocrine-resistant BC

Data-mining of potential antitubercular activities from molecular ingredients of traditional Chinese medicines

Background. Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of traditional Chinese medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of traditional Chinese medicines and accurate in-silico cheminformatics models for data mining for antitubercular agents and computational filters to prioritize molecules has prompted us to search for potential hits from these datasets.Results. We used a consensus approach to predict molecules with potential antitubercular activities from a large dataset of molecular ingredients of traditional Chinese medicines available in the public domain. We further prioritized 160 molecules based on five computational filters (SMARTSfilter) so as to avoid potentially undesirable molecules. We further examined the molecules for permeability across Mycobacterial cell wall and for potential activities against non-replicating and drug tolerant Mycobacteria. Additional in-depth literature surveys for the reported antitubercular activities of the molecular ingredients and their sources were considered for drawing support to prioritization.Conclusions. Our analysis suggests that datasets of molecular ingredients of traditional Chinese medicines offer a new opportunity to mine for potential biological activities. In this report, we suggest a proof-of-concept methodology to prioritize molecules for further experimental assays using a variety of computational tools. We also additionally suggest that a subset of prioritized molecules could be used for evaluation for tuberculosis due to their additional effect against non-replicating tuberculosis as well as the additional hepato-protection offered by the source of these ingredients

Attribute Specific Impacts of Stated Non-Attendance in Choice Experiments

In this paper, we generalise existing approaches to the treatment of stated attribute non‐attendance data in discrete choice experiments by allowing attribute specific impacts. We implement this approach by employing an extended hierarchical Bayes logit model specification. To illustrate this approach, we consider data collected to examine Indian consumers’ preferences for traditional aromatic rice varieties. Our results regarding stated attribute non‐attendance reveal that, our new approach shrinks marginal utilities of non‐attenders substantially compared to stated attenders, with significant differences in the shrinkage between some of the attributes. In addition, our results reveal the way in which non‐attendance of attributes interact with each other and the impact that this has on the distribution of willingness to pay estimates

Social Determinants of Smoking in Low- and Middle-Income Countries: Results from the World Health Survey

INTRODUCTION: Tobacco smoking is a leading cause of premature death and disability, and over 80% of the world's smokers live in low- or middle-income countries. The objective of this study is to assess demographic and socioeconomic determinants of current smoking in low- and middle-income countries. METHODS: We used data, from the World Health Survey in 48 low-income and middle-income countries, to explore the impact of demographic and socioeconomic factors on the current smoking status of respondents. The data from these surveys provided information on 213,807 respondents aged 18 years or above that were divided into 4 pooled datasets according to their sex and country income group. The overall proportion of current smokers, as well as the proportion by each relevant demographic and socioeconomic determinant, was calculated within each of the pooled datasets, and multivariable logistic regression was used to assess the association between current smoking and these determinants. RESULTS: The odds of smoking were not equal in all demographic or socioeconomic groups. Some factors were fairly stable across the four datasets studied: for example, individuals were more likely to smoke if they had little or no education, regardless of if they were male or female, or lived in a low or a middle income country. Nevertheless, other factors, notably age and wealth, showed a differential effect on smoking by sex or country income level. While women in the low-income country group were twice as likely to smoke if they were in the lowest wealth quintile compared with the highest, the association was absent in the middle-income country group. CONCLUSION: Information on how smoking is distributed among low- or middle-income countries will allow policy makers to tailor future policies, and target the most vulnerable populations

INTERFEROME: the database of interferon regulated genes.

INTERFEROME is an open access database of types I, II and III Interferon regulated genes (http://www.interferome.org) collected from analysing expression data sets of cells treated with IFNs. This database of interferon regulated genes integrates information from high-throughput experiments with annotation, ontology, orthologue sequences from 37 species, tissue expression patterns and gene regulatory information to enable a detailed investigation of the molecular mechanisms underlying IFN biology. INTERFEROME fulfils a need in infection, immunity, development and cancer research by providing computational tools to assist in identifying interferon signatures in gene lists generated by high-throughput expression technologies, and their potential molecular and biological consequences