Bioactivity-Guided Isolation of Anticancer Agents from Bauhinia Kockiana Korth.

Background: Flowers of Bauhinia kockiana were investigated for their anticancer properties.Methods: Gallic acid (1), and methyl gallate (2), were isolated via bioassay-directed isolation, and they exhibited anticancer properties towards several cancer cell lines, examined using MTT cell viability assay. Pyrogallol (3) was examined against the same cancer cell lines to deduce the bioactive functional group of the phenolic compounds.Results: The results showed that the phenolic compounds could exhibit moderate to weak cytotoxicity towards certain cell lines (GI50 30 - 86 μM), but were inactive towards DU145 prostate cancer cell (GI50 > 100 μM).Conclusion: It was observed that pyrogallol moiety was one of the essential functional structures of the phenolic compounds in exhibiting anticancer activity. Also, the carboxyl group of compound 1 was also important in anticancer activity. Examination of the PC-3 cells treated with compound 1 using fluorescence microscopy showed that PC-3 cells were killed by apoptosis.Key words: Gallic acid; Bauhinia kockiana; pyrogallol; anticancer; apoptosis

Talent flow analytics in online professional network

Singapore National Research Foundation under International Research Centres in Singapore Funding Initiativ

Higher Recovery and Better Energy Dissipation at Faster Strain Rates in Carbon Nanotube Bundles: An in-Situ Study

We report mechanical behavior and strain rate dependence of recoverability and energy dissipation in vertically aligned carbon nanotube (VACNT) bundles subjected to quasi-static uniaxial compression. We observe three distinct regimes in their stress–strain curves for all explored strain rates from 4 × 10^(–2) down to 4 × 10^(–4) /sec: (1) a short initial elastic section followed by (2) a sloped plateau with characteristic wavy features corresponding to buckle formation and (3) densification characterized by rapid stress increase. Load–unload cycles reveal a stiffer response and virtually 100% recoverability at faster strain rates of 0.04/sec, while the response is more compliant at slower rates, characterized by permanent localized buckling and significantly reduced recoverability. We propose that it is the kinetics of attractive adhesive interactions between the individual carbon nanotubes within the VACNT matrix that governs morphology evolution and ensuing recoverability. In addition, we report a 6-fold increase in elastic modulus and gradual decrease in recoverability (down to 50%) when VACNT bundles are unloaded from postdensification stage as compared with predensification. Finally, we demonstrate energy dissipation capability, as revealed by hysteresis in load–unload cycles. These findings, together with high thermal and electrical conductivities, position VACNTs in the “unattained-as-of-to-date-space” in the material property landscape

Talent Flow Analytics in Online Professional Network

Analyzing job hopping behavior is important for understanding job preference and career progression of working individuals. When analyzed at the workforce population level, job hop analysis helps to gain insights of talent flow among different jobs and organizations. Traditionally, surveys are conducted on job seekers and employers to study job hop behavior. Beyond surveys, job hop behavior can also be studied in a highly scalable and timely manner using a data driven approach in response to fast-changing job landscape. Fortunately, the advent of online professional networks (OPNs) has made it possible to perform a large-scale analysis of talent flow. In this paper, we present a new data analytics framework to analyze the talent flow patterns of close to 1 million working professionals from three different countries/regions using their publicly-accessible profiles in an established OPN. As OPN data are originally generated for professional networking applications, our proposed framework re-purposes the same data for a different analytics task. Prior to performing job hop analysis, we devise a job title normalization procedure to mitigate the amount of noise in the OPN data. We then devise several metrics to measure the amount of work experience required to take up a job, to determine that existence duration of the job (also known as the job age), and the correlation between the above metric and propensity of hopping. We also study how job hop behavior is related to job promotion/demotion. Lastly, we perform connectivity analysis at job and organization levels to derive insights on talent flow as well as job and organizational competitiveness.Comment: arXiv admin note: extension of arXiv:1711.05887, Data Science and Engineering, 201

The predominant learning approaches of medical students

Background By identifying medical students’ learning approaches and the factors that influence students’ learning approaches, medical schools and health care institutions are better equipped to intervene and optimize their learning experience. The aims of our study is to determine the predominant learning approach amongst medical students on a clinical posting in a hospital in Singapore and to examine the demographic factors that affect their learning approach. Methods The Approaches and Study Skills Inventory for Students (ASSIST) questionnaire was administered to 250 medical students from various medical schools on clinical attachment to the Obstetrics and Gynaecology (O&G) department of KK Women’s and Children’s Hospital (KKH) Singapore between March 2013 and May 2015 to determine students’ predominant learning approaches. Multinomial logistic regression was used to examine the association between demographic factors (age, gender and highest education qualification) and predominant learning approach. A cut-off of p \u3c 0.05 was used for statistical significance. Results Amongst 238 students with one predominant learning approach, 96 (40.3%) and 121 students (50.8%) adopted the deep and strategic approach respectively, whilst only 21 (8.8%) adopted the surface approach. Male students appeared less likely to adopt the strategic learning approach than female students (p value = 0.06). Predominant learning approaches were not influenced by demographic characteristics such as age, gender and highest educational qualifications. Conclusions This study provided insight into the learning approaches of a heterogeneous group of medical students in Singapore. While it is encouraging that the majority of students predominantly utilised the deep and strategic learning approach, there was a significant proportion of students who utilised the surface approach. Interventions can be explored to promote deeper learning amongst these students