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Exploring Responsible Tourism: How Small Actions Make a Big Impact
No full textIn conjunction with World Tourism Day, let’s explore the concept of responsible tourism. It can be traced back to the early root that initiate to promote environmental conservation that related to ecotourism, it has since then expanded to three aspects: environment, economy, and society, aiming to create a healthier tourism ecosystem for both tourists and hosts
Drivers of trade openness, exchange rates, and production efficiency: firm and country level study.
Get PDFThis research focuses on the factors influencing trade openness and their flow-through effect on the production efficiency of both firms and countries. It further explores how enhanced production efficiency can lead to increased financial inflows into a country and examines the resultant impact on the nation's currency exchange rates. This thesis aims to bridge the existing knowledge gaps in the field of trade openness by conducting a comprehensive analysis across several pivotal areas. Firstly, it investigates the relationship between trade openness and associated factors. Secondly, it explores the impact of trade openness on improving production efficiency at the firm level. Thirdly, the study examines the flow through effects of trade openness on countries' productivity. Lastly, it assesses how enhanced production efficiency influences trade flows, subsequently leading to financial inflows that have a bearing on currency exchange rates. Data from the World Trade Organization (WTO) was collected for the period spanning 1995 to 2020, covering 101 nations categorized into three groups based on their levels of trade openness (high, moderate, and low). Additionally, a sample of 600 manufacturing companies from economies with high and low trade openness was included for the period between 2010 and 2019. The study employed several statistical methods, such as stepwise regression, ordinary least squares (OLS), fixed/random effect methods, and fully modified least squares (FMOLS) to estimate the results. The Granger Causality test was also utilized to determine the direction of causality. Regarding the first objective, the findings reveal a positive relationship between trade openness drivers and level of trade openness. The study specifically identifies gross national savings, trade reserves, per capita income, net flows of foreign direct investment and exchange rate as significant factors driving trade openness. In contrast, per capita income is recognized as having the most considerable influence on trade openness. The findings related to the second objective suggest that firms in economies with high trade openness witness a more significant positive effect on their total factor productivity, primarily due to improvements in efficiency and technology, in comparison to firms in economies with lower levels of trade openness. Furthermore, the analysis reveals a unidirectional relationship between technological changes and total factor productivity. In relation to the third objective, the research findings demonstrate that the growth in total factor productivity for 20 countries engaged in open trading is at 10 percent. When comparing the two distinct groups, the study reveals that the average total factor productivity in ten countries with a high level of trade openness stands at 16 percent, a figure that is threefold higher than in ten countries characterized by lower trade openness. The results related to the fourth objective reveal that trade reserves have a significantly negative effect on exchange rates across the full spectrum and in three distinct categories of trade openness. It is particularly noteworthy that economies with low trade openness display the most substantial influence of trade reserves on their exchange rates, whereas economies with high and moderate trade openness exhibit a lesser impact
Screening of synthesized nanoparticle and antineoplastics cytotoxicity against drug resistant breast cancer cells
Get PDFBreast cancer is regarded as a major global health issue due to its high incidence and mortality rate. They are also becoming harder to treat due to the emergence of multidrug resistance (MDR), rendering anticancer drugs less sensitive than ever. Therapeutic nanoparticles and novel bio-derived drugs can be used as a potential replacement for chemo-drug-resistant breast cancer. This study was performed to investigate the resistance of breast cancer cells against a multitude of drugs, as well as to evaluate whether certain nanoparticles could induce cytotoxicity. Four antineoplastic agents, Cisplatin (CDDP), Paclitaxel (PTX), Alpha-Mangostin (A-MG), and Andrographolide (Andr-G), as well as three nanoparticles, synthesized gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and graphene oxide (GO), were investigated for cytotoxicity against non-chemo-resistant breast cancer MCF-7, chemo-resistant MCF-7-CR, and MDR MDA-MB-231 cell lines. AuNPs and AgNPs were synthesized via chemical reduction using reducing agents NaBH4 and ascorbic acid, where they were further characterized. Treatment of GO was coupled with UV-B irradiation to determine the influence on cytotoxicity against breast cancer cells. It was found that PTX was the most potent yet easiest to be desensitized among all four drugs, whereas A-MG and Andr-G were less prone to be desensitized in longer duration treatment, with 25 µM of A-MG resulting in about 20% cell viability. Ascorbic acid-reduced AuNPs were found to be spherical with a size of 170 nm, zeta potential of -36 mV, and polydispersity index of about 17%. NaBH4-reduced AgNPs were also characterized to have irregular shapes at around 680 nm in size and a zeta potential of -21 mV. AgNPs and AuNPs were less potent against drug-resistant breast cancer cells. In MCF-7 cells, ascorbic acid-reduced AgNPs and NaBH4-reduced AuNPs caused 50% and 25% cell death using 10 µM, respectively. GO was observed to be toxic to both MCF-7 and MDA-MB-231, with viability observed at 70% on MCF-7 for 100 µg/mL GO. UV-B irradiation influenced cytotoxicity in MCF-7 by increasing potency from 80% to 50% cell viability after 3h of GO incubation and 10 mJ/cm2 exposure. GO was more toxic on MCF-7 and MDA-MB-231 cells, whereas MCF-7-CR was more susceptible to both AgNPs and AuNPs. Further studies on the mechanism of action between nanoparticles, drugs, and cancer cells are necessary. The inclusion of different drug-resistant breast cancer cells as well as normal cells is also necessary to further compound the potential therapeutic importance of the study
Malaysian Carrageenophyte Kappapphycus species inhibit Lipopolysaccharides-induced Neuroinflammation by suppressing the AKT/NFxB and ERK signaling pathways in BV2 Microglia
No full textNeuroinflammation is normally caused by the stimulation of microglia and astrocytes with the production of proinflammatory mediators such as inducible nitric oxide synthase (iNOS), nitric oxide (NO), and cyclooxygenase-2 (COX-2), as well as the generation of proinflammatory cytokines, including tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6. Unregulated activities and overproduction of proinflammatory mediators and cytokines will cause neuronal death, which will trigger the development of neurodegenerative diseases. Kappaphycus alvarezii and Kappaphycus malesianus are red algae cultivated in Semporna, Sabah, East Malaysia. They are remarkable with their k-carrageenans, which have been widely used as a thickening agent in food, cosmetics, and the nutraceutical industry. Kappaphycus spp. have been reported with several pharmacological effects, including antioxidant, anti-viral, and anti-cancer effects. However, limited research has focused on their neurological effects. Therefore, it is our interest to explore and compare the bioactivity of K. alvarezii and K. malesianus from the neuroprotective aspect. This study aimed to investigate the anti-neuroinflammatory activity in K. alvarezii and K. malesianus crude extracts (ethyl acetate, ethanol, and methanol extracts) on lipopolysaccharides (LPS)-induced BV2 microglial cell line and their underlying mechanisms. Cell viability assay (MTT assay) was used to examine the percentage of viable BV2 microglial cell line after treating with the respective K. alvarezii and K. malesianus crude extracts. Nitric oxide inhibition assay (Griess assay) was used to investigate the nitric oxide inhibitory activity of all crude extracts, while the crude extract with the highest nitric oxide inhibitory activity was used for western blot and ELISA analyses to investigate the proinflammatory mediators (iNOS and COX-2) and cytokines (TNF-⍺, IL-6 and IL-1β) expression in LPS-induced BV2 microglial cell line. The potential compound(s) in the extract with the highest promising anti-neuroinflammatory effect were identified using the liquid chromatography-mass spectrometry (LC-MS) analysis. Our results indicated that all extracts of both seaweeds had maintained cell viability above 80% at the concentration of 2.5 mg/mL, except for K. malesianus ethanol extract (69.7% ± 0.31 mg/mL). K. alvarezii ethyl acetate extract and K. malesianus methanol extract indicated the highest nitric oxide inhibitory activity without showing significant cytotoxicity towards the BV2 microglial cell line. Thus, K. alvarezii ethyl acetate and K. malesianus methanol extract were selected to further evaluate their proinflammatory mediators and proinflammatory cytokines expressions, and signaling pathways. The results disclosed that K. malesianus methanol extract demonstrated higher inhibitory activity in the formation of proinflammatory mediators and cytokines via AKT/NF-B and ERK pathways. According to the LC-MS analysis for K. malesianus methanol extract, three known bioactive compounds were identified with anti-neuroinflammatory activities, namely, 2,6-nonadien-1-ol, prosopinine, and eplerenone. In conclusion, all K. alvarezii and K. malesianus extracts showed inhibitory
activity on nitric oxide and proinflammatory cytokines production, which may contribute
to the anti-neuroinflammatory activity. Moreover, western blot results explained that K.
Alvarezii and K. malesianus extracts had contributed to anti-neuroinflammatory activity
through inhibiting iNOS and COX-2 production via AKT/NF-B and ERK pathways. K. malesianus methanol extract is the most potent extract and may act as a potent anti-neuroinflammatory therapy in the prevention of neurodegenerative disorders
Examining mediator effects within multilevel perspectives: a comprehensive analysis of job uncertainty and job stress
No full textJob stress is a growing problem in the work literature as employees continue to keep up with the demands of a growing and competitive environment due to globalization and the Industrial Revolution 4.0. Coupled with job uncertainty due to unpredictable environments that interrupt regular workflow, the issue of job stress in the workforce is further escalated as employees face ambiguity in predicting the direction of the future of their work. The present study aims to understand the relationships between environmental factors (i.e., technological uncertainty), organisational factors (i.e., clan culture and learning opportunities), individual factors (i.e., emotional intelligence and proactive personality), and individual resources (i.e., problem-solving skills, entrepreneurship skills, and technological readiness) that contributes to job uncertainty, and consequently job stress as initially proposed by Robbins and colleagues (2009). In addressing the lack of studies on how technological uncertainty and clan culture relate to learning opportunities as well as how emotional intelligence and proactive personality relate to problem-solving skills, entrepreneurship skills, and technological readiness, and how these constructs further relate to job uncertainty and job stress, this study employs a successive independent samples research design to address the limitations of the cross-sectional design and longitudinal design. In Study 1, the relationships between job uncertainty and job stress, technological uncertainty, clan culture, and learning opportunities, as well as emotional intelligence, proactive personality, problem-solving skills, entrepreneurship skills, and technological readiness is tested at an individual level for 252 employees aged 18-years old and above (M = 30.75 years; SD = 8.7 years). In Study 2, the relationships between these constructs by collecting another set of data, recruiting 240 employees from 36 teams aged 18-years old and above (M = 38.0 years; SD = 8.6 years), targeting teams from organisations with technological uncertainty and clan culture as multilevel constructs to further examine if they have cross-level relationships on job uncertainty. To analyse the results, hierarchical linear regression analysis was used for Study 1 while hierarchical linear modelling analysis was used for Study 2. The general results showed that job uncertainty significantly predicts job stress in a positive direction, learning opportunities significantly negatively predicts job uncertainty, and technological uncertainty and clan culture positively affect learning opportunities. Specifically, in Study 1, emotional intelligence was found to significantly predict entrepreneurship skills, and proactive personality was found to predict entrepreneurship skills and technological readiness. In Study 2, emotional intelligence was found to significantly predict problem solving skills and entrepreneurship skills, while proactive personality was found to predict problem-solving skills, entrepreneurship skills, and technological readiness. Mediation analyses were also conducted to further understand the relationships between the variables in the study. Implications and recommendations for future studies are discussed with regard to leadership and organisational management whereby a more supportive leadership like clan culture is beneficial in dealing with job uncertainty and job stress, emphasizing the multilevel nature of the issue of job uncertainty and job stress. The study also highlights the importance of learning opportunities in organisational training and development in the context of technological uncertainty and job uncertainty
Herbs Used for the Management of Hypertension: A Systematic Review
No full textBackground: Hypertension is characterized by persistent high blood pressure and has emerged as a critical risk factor for severe cardiovascular diseases. Although several drugs have been designated to reduce blood pressure, these drugs can potentially cause side effects for patients. Therefore, medicinal plants are used to complement conventional drugs to treat various ailments.
Methods: This study reviews the anti-hypertensive potential of herbs and plants and their mechanism of action in reducing blood pressure at their evaluated effective doses. Databases such as PubMed, Scopus, Science Direct, and Google Scholar were used to search articles from January 2016 to Sept 2022. The key search terms included “hypertension”, “lowers blood pressure”, “antihypertensive”, and “plants”. These generated 807 documents and using the PRISMA guidelines, thirty plants were identified for this review. Research studies with similar plant parts extracted from similar solvents, more than one dose, and animal models with a positive control were considered in this review. Studies that did not show significant blood pressure reduction were excluded.
Results: Based on this criterion, the mechanism of actions of these plants was thematically grouped into three categories, namely 1) antioxidant, 2) angiotensin-converting enzyme (ACE) inhibition, and 3) calcium influx in vascular smooth muscle. The effective doses, plant parts used, and traditional medicine usage are presented in this review.
Conclusion: Further research is highly recommended to identify the active compounds and to potentially develop them into anti-hypertensive drugs as well as to establish the safe doses and standardization of these plant extracts. This review is partially funded by grants from the Ministry of Higher Education
Dietary exposure to acrylamide among the Malaysian adult population
No full textThis study aimed to estimate the Malaysian adult population's current dietary exposure and margin of exposure (MOE) to the carcinogenic processing contaminant, acrylamide. A total of 448 samples from 11 types of processed foods were collected randomly throughout Malaysia in the year 2015 and 2016. Acrylamide was analysed in samples using Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) with a limit of detection (LOD) of 10 μg/kg and a limit of quantification (LOQ) of 25 μg/kg. The highest average level of acrylamide (772 ± 752 μg/kg) was found in potato crisps, followed by French fries (415 ± 914 μg/kg) and biscuits (245 ± 195 μg/kg). The total acrylamide exposure for the adult Malaysian was 0.229 and 1.77 μg/kg body weight per day for average and high consumers, respectively. The MOE were 741 and 1875 for the average consumer based on cancer and non-cancer effects of acrylamide, respectively. Meanwhile, for high consumers, the MOE is 96 for cancer and 243 for non-cancer effects. These findings indicate potential carcinogenic risks from acrylamide exposure among Malaysian adults, especially in Malay and other Bumiputra groups compared to Chinese, Indian, and other ethnic groups, while non-cancer effects appeared less concerning
An advanced deep learning model for predicting water quality index
No full textPredicting a water quality index (WQI) is important because it serves as an important metric for assessing the overall health and safety of water bodies. Our paper develops a new hybrid model for predicting the WQI. The study uses a combination of a convolutional neural network (CNN), clockwork recurrent neural network (Clockwork RNN), and M5 Tree (CNN-CRNN-M5T) to predict a WQI. The M5T model lacks advanced operators for extracting meaningful data from water quality parameters, so the new model enhances its ability to analyze intricate patterns. The general linear model analysis of variance (GLM-ANOVA) is an improved version of the ANOVA. Our study uses the GLM-ANOVA to determine significant inputs. As all input variables had p < 0.050, they were defined as significant variables. Results showed that NH-NL and PH had the highest and lowest impact, respectively. Our study used the CNN-CRNN-M5T, CNN-CRNN, CRNN-M5T, CNN-M5T, CRNN, CNN, and M5T models to predict the WQI of a large basin in Malaysia. The CNN-CRNN decreased testing mean absolute error (MAE) of the CRNN, CNN, and M5T models by 2.1 %, 12 %, and 15 %, respectively. The CNN-CRNN-M5T model increased Nash–Sutcliffe efficiency coefficient of the other models by 4–20 % and 2.1–19 %, respectively. The CNN-CRNN-M5T model was a reliable tool for spatial and temporal predictions of WQI
Planting the seeds to grow a safer society
No full textAs an educator who is deeply concerned about the pervasive issue of violence in our society. I've come to realise that our approach to preventing intimate partner violence (IPV) needs a significant shift. "Love should be pain-free" (The Star, Aug 13).
While our efforts to protect and empower women and girls are undeniably crucial, they are only half the equation. To truly make a difference, we must broaden our focus and actively engage boys and men in this critical conversation
Operating Room Nurse Burnout: A Global Challenge With SDG Solutions
No full textBuilding a support network, sharing best practices, and crafting collective solutions can pave the way for reducing burnout rates and improving health care.
In the high-stakes world of health care, operating room nurses play a pivotal role in safeguarding lives. Yet, these unsung heroes are facing a silent crisis: occupational burnout