19672 research outputs found
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Identification of potential anticancer protein targets in cytotoxicity mediated by tropical medicinal fern extracts
No full textBackground: Medicinal fern species represent a potentially important source for both food and medicinal applications. Previously, two underutilized tropical fern species (Blechnum orientale and Phymatopteris triloba) were reported with cytotoxic activities against selected cancer cell lines. However, the exact mechanism remains elusive. Objective: In this paper, we reported the identification of six differentially expressed proteins isolated from cancer cells, following exposure to the cytotoxic fern extracts. Materials and Methods: The identities of these cancer proteins were determined by matrix-assisted laser desorption ionization time-of-flight protein sequencing. Results: The cancer proteins were identified as follows: elongation factor 1-γ, glyceraldehydes-3-phosphate dehydrogenase, heat shock protein 90-β, heterogeneous nuclear ribonucleoprotein-A2/B1, truncated nucleolar phosphoprotein B23, and tubulin-β chain. To the best of our knowledge, this paper represents thefirst time these cancer proteins are being reported, following exposure to the aforementioned cytotoxic fern extracts. Conclusion: It is hoped that further efforts in this direction could lead to the identification and development of target-specific chemotherapeutic agents
A case-control study of breast cancer risk factors in 7,663 women in Malaysia
No full textBackground Breast cancer risk factors have been examined extensively in Western setting and more developed Asian cities/countries. However, there are limited data on developing Asian countries. The purpose of this study was to examine breast cancer risk factors and the change of selected risk factors across birth cohorts in Malaysian women. Methods An unmatched hospital based case-control study was conducted from October 2002 to December 2016 in Selangor, Malaysia. A total of 3,683 cases and 3,980 controls were included in this study. Unconditional logistic regressions, adjusted for potential confounding factors, were conducted. The breast cancer risk factors were compared across four birth cohorts by ethnicity. Results Ever breastfed, longer breastfeeding duration, a higher soymilk and soy product intake, and a higher level of physical activity were associated with lower risk of breast cancer. Chinese had the lowest breastfeeding rate, shortest breastfeeding duration, lowest parity and highest age of first full term pregnancy. Conclusions Our study shows that breastfeeding, soy intake and physical activity are modifiable risk factors for breast cancer. With the increasing incidence of breast cancer there is an urgent need to educate the women about lifestyle intervention they can take to reduce their breast cancer risk
Malaysian student leaders’ perception of their leadership styles
No full textStudent leadership is a distinct area in research and practice. This study explored the leadership styles of student leaders in Malaysian secondary and postsecondary schools based on the Bolman and Deal’s leadership orientations survey (LOS–self). Analysis was carried out on the four leadership styles: structural, human resource, political and symbolic. Student leaders’ demographics such as gender, age and ethnicity were identified. Findings revealed there exist different leadership styles between genders, those still studying in secondary school with postsecondary school and between the three main ethnic groups of student leaders. The human resource frame is the predominant frame followed by the structural frame. The significance of the findings and suggestions for further developing multi-frame leadership styles are proposed, as the use of multiple frames is linked to leadership effectiveness. This will help to increase the student leaders’ knowledge of leadership frames and their personal capabilities as leaders in their organisation
Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images
No full textIn this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determine an initial region of interest surrounding the heart, (ii) identify potential 2D objects of interest using an intensity-based segmentation, (iii) assess contraction/expansion, circularity, and proximity to lung tissue to score all objects of interest in terms of their likelihood of constituting part of the LV, and (iv) aggregate the objects into connected groups and construct the final LV blood pool volume and centroid. This algorithm was tested against 1140 datasets from the Kaggle Second Annual Data Science Bowl, as well as 45 datasets from the STACOM 2009 Cardiac MR Left Ventricle Segmentation Challenge. Correct LV localization was confirmed in 97.3% of the datasets. The mean absolute error between the gold standard and localization centroids was 2.8 to 4.7 mm, or 12 to 22% of the average endocardial radius
Nano-cellulose based nano-coating biomaterial dataset using corn leaf biomass: An innovative biodegradable plant biomaterial
No full textThe nanocellulose derived biodegradable plant biomaterial as nano-coating can be used in the medical, biomedical cosmetics, and bioengineering products. Bio-plastic and some synthetic derived materials are edible and naturally biodegradable. The study was conducted to investigate edible nano-biopolymer based nano-coating of capsules and drugs or other definite biomedical materials from corn leaf biomass. Corn leaf biomass was used as an innovative sample to produce edible nano-coating bioplastic for drug and capsule coating and other industrial uses. The data show the negligible water 0.01% absorbed by bio-plastic nanocoating. Odor represented by burning test was under the completely standard based on ASTM. Moreover, data on color coating, tensile strength, pH, cellulose content have been shown under standard value of ASTM (American standard for testing and materials) standard. In addition to that data on the chemical element test like K+, CO3 −−, Cl- Na+ exhibited positive data compared to the synthetic plastic in the laboratory using the EN (166)) standardization. Therefore, it can be concluded that both organic (cellulose and starch) based edible nano-coating bioplastic may be used for drug and capsule coating as biomedical and medical components in the pharmaceutical industries
Fabrication of capillary force induced DNA template Ag nanopatterns for sensitive and selective enzyme-free glucose sensors
No full textThe self-patterned silver (Ag) nanowires on Indium Tin Oxide (ITO) were developed and exploited as the enzyme-free sensor probes for glucose detection. Deoxyribonucleic acid (DNA) template increased the capillary force channels of Ag and facilitated the homogeneous and high mobility of Ag-DNA toward the scribe via the coffee ring effect. The subsequent removal of DNA template from Ag-DNA/ITO through the enzymatic hydrolysis process led to the formation of Ag nanowires on ITO. Under alkaline conditions, Ag nanopatterns developed on ITO realized the considerable enzyme-free glucose sensor performances. The fabricated sensor system is reproducible and stable and was pertained with an analysis of spiked human blood serum, where it provided excellent recoveries. Thus these findings have not only showered insights on the self assembly of Ag nanoparticles without the exploitation of any surfactants and harsh conditions but have also provided the fundamental perceptive on the influences of self-assembled nanowires in enzyme free glucose sensor applications
Is the Fama French Three-Factor Model Relevant? Evidence from Islamic Unit Trust Funds
No full textThe study tests the Fama and French three-factor model by using the newly created Islamic equity style indices. Based on a dataset from May 2006 to April 2011, the three-factor model is tested based on returns of Islamic unit trust funds using the Generalized Method of Moments (GMM) methodology. The sample period is also divided between periods before and after the Global Financial Crisis in August 2008 to test for robustness, and the Bai and Perron (2003) multiple structural break test was used to determine the structural break in the series. The analysis shows that the Fama and French model is valid for Islamic unit trust funds before and after the collapse of Lehman Brothers. The result further indicates the reversal of size effect. As for trading strategies, value funds outperform growth funds by annualized 3.13 percent for the full period. During pre-crisis period, value funds perform better than growth funds while in post-crisis, size factor yields better return than other strategies. As policy suggestion, fund managers need to be aware of the reversal of size effect, and they need to ensure a more transparent stock selection process so that investors can make an informed decision in their asset allocation
New approach for developing soft computational prediction models for moment and rotation of boltless steel connections
No full textThis study aims to minimize the expensive experimental testing of unique boltless steel connections using the prediction power of several computational techniques. Thirty-two tests were conducted on boltless steel connections using double-cantilever test method and their results were compared with developed models using Artificial Intelligence (AI) techniques. Linear Genetic Programming (LGP), Artificial Neural Networks (ANNs) and Adaptive Neuro Fuzzy Inference System (ANFIS) were applied to predict the moment-rotation (M-θ) behavior of boltless steel connections. The predictive performance of the models was assessed by comparing the values of co-efficient of determination (R2), mean square error (MSE) and root-mean-square error (RMSE). The LGP model well predicted the M-θ behavior as compared to the other models. The robustness of the LGP model was further proved by performing different statistical tests
Short-Term Forecasting of the Output Power of a Building-Integrated Photovoltaic System Using a Metaheuristic Approach
No full textThe rapidly increasing use of renewable energy resources in power generation systems in recent years has accentuated the need to find an optimum and efficient scheme for forecasting meteorological parameters, such as solar radiation, temperature, wind speed, and sun exposure. Integrating wind power prediction systems into electrical grids has witnessed a powerful economic impact, along with the supply and demand balance of the power generation scheme. Academic interest in formulating accurate forecasting models of the energy yields of solar energy systems has significantly increased around the world. This significant rise has contributed to the increase in the share of solar power, which is evident from the power grids set up in Germany (5 GW) and Bavaria. The Spanish government has also taken initiative measures to develop the use of renewable energy, by providing incentives for the accurate day-ahead forecasting. Forecasting solar power outputs aids the critical components of the energy market, such as the management, scheduling, and decision making related to the distribution of the generated power. In the current study, a mathematical forecasting model, optimized using differential evolution and the particle swarm optimization (DEPSO) technique utilized for the short-term photovoltaic (PV) power output forecasting of the PV system located at Deakin University (Victoria, Australia), is proposed. A hybrid self-energized datalogging system is utilized in this setup to monitor the PV data along with the local environmental parameters used in the proposed forecasting model. A comparison study is carried out evaluating the standard particle swarm optimization (PSO) and differential evolution (DE), with the proposed DEPSO under three different time horizons (1-h, 2-h, and 4-h). Results of the 1-h time horizon shows that the root mean square error (RMSE), mean relative error (MRE), mean absolute error (MAE), mean bias error (MBE), weekly mean error (WME), and variance of the prediction errors (VAR) of the DEPSO based forecasting is 4.4%, 3.1%, 0.03, −1.63, 0.16, and 0.01, respectively. Results demonstrate that the proposed DEPSO approach is more efficient and accurate compared with the PSO and DE
Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging
No full textObjectives: This study maps the lipid distributions based on magnetic resonance imaging (MRI) in-and opposed-phase (IOP) sequence and correlates the findings generated from lipid map to histological grading of glioma. Methods: Forty histologically proven glioma patients underwent a standard MRI tumour protocol with the addition of IOP sequence. The regions of tumour (solid enhancing, solid non-enhancing, and cystic regions) were delineated using snake model (ITK-SNAP) with reference to structural and diffusion MRI images. The lipid distribution map was constructed based on signal loss ratio (SLR) obtained from the IOP imaging. The mean SLR values of the regions were computed and compared across the different glioma grades. Results: The solid enhancing region of glioma had the highest SLR for both Grade II and III. The mean SLR of solid non-enhancing region of tumour demonstrated statistically significant difference between the WHO grades (grades II, III & IV) (mean SLRII = 0.04, mean SLRIII = 0.06, mean SLRIV = 0.08, & p <.01). A strong positive correlation was seen between WHO grades with mean SLR on lipid map of solid non-enhancing (ρ=0.68, p <.01). Conclusion: Lipid quantification via lipid map provides useful information on lipid landscape in tumour heterogeneity characterisation of glioma. This technique adds to the surgical diagnostic yield by identifying biopsy targets. It can also be used as an adjunct grading tool for glioma as well as to provide information about lipidomics landscape in glioma development