Are You a Panic Buyer? Observations from Consumers in Malaysia

Panic buying is an intriguing social phenomenon during a crisis. However, the existing literature primarily emphasises impulsive purchases and fails to address the objective of panic buying. A minimal study has examined panic buying, integrating variables within an S-O-R framework throughout a crisis. Therefore, this study bridges the existing gaps by examining the variables influencing panic buying behaviour in Malaysia. The quantitative and purposive sampling techniques were used to evaluate Malaysians aged 18 and above who have previously encountered panic buying. A total of 280 questionnaires were collected via distribution to social media platforms. Findings reveal that information overload impacts cyberchondria and perceived severity. Furthermore, price consciousness affects panic buying behaviour. No link is found between perceived severity and cyberchondria towards panic buying behavior. This study theoretically contributes to the literature on the variables influencing panic buying behaviour in Malaysia. This study enhances consumers' decision-making knowledge during a crisis. This study also provides insights to the government in ensuring product stability and business operators to undertake appropriate strategies pre- and post-crisis. Future research should consider the developed countries and different product categories

Multiple system atrophy

This is a practical guide to diagnosing and managing multiple system atrophy (MSA). We explain the newly published Movement Disorders Society Consensus Diagnostic Criteria, which include new ‘Clinically Established MSA’ and ‘Possible Prodromal MSA’ categories, hopefully reducing time to diagnosis. We then highlight the key clinical features of MSA to aid diagnosis. We include a list of MSA mimics with suggested methods of differentiation from MSA. Lastly, we discuss practical symptom management in people living with MSA, including balancing side effects, with the ultimate aim of improving quality of life

Predicting the catalytic sites of isopenicillin N synthase (IPNS) related non-haem iron-dependent oxygenases and oxidases (NHIDOX) through a structural superimposition and molecular docking approach

Isopenicillin N synthase (IPNS) related Non-haem iron-dependent oxygenases and oxidases (NHIDOX) demonstrated a striking structural conservativeness, even with low protein sequence homology. It is evident that these enzymes have an architecturally similar catalytic centre with active ligands lining the reactive pocket. Deacetoxycephalosporin C synthase (DAOCS), isopenicillin N synthase (IPNS), deacetylcephalosporin C synthase (DACS), clavaminate synthase 1 and 2 (CAS1 and 2) are important bacterial enzymes that catalyze the formation of β-lactam antibiotics belonging to this enzyme family. Most plant enzyme members within this subfamily namely flavonol synthase (FLS), leucoanthocyanidin dioxygenase (LDOX), anthocyanidin synthase (ANS), 1-aminocyclopropane-1-carboxylic acid oxidase (ACCO), gibberellin 20-oxidase (G20O), desacetoxyvindoline-4-hydroxylase (D4H), flavanone 3β-hydroxylase (F3H), and hyoscyamine 6β-hydroxylase (H6H) are involved in catalyzing the biosyntheses of plant secondary metabolites. With the advancement of protein structural analysis software, it is possible to predict the catalytic sites of protein that shared a structural resemblance. By exploiting the superimposition model of DAOCS-IPNS, DAOCS-IPNS-CAS, G20O-LDOX, FLS-LDOX, ACCO-LDOX, D4H-LDOX, F3H-LDOX and H6H-LDOX model; a computational protocol for predicting the catalytic sites of proteins is now made available. This study shows that without the crystallized or nuclear magnetic resonance (NMR) structures of most NHIDOX enzyme, the plausible catalytic sites of protein can be forecasted using this structural bioinformatics approach.Keywords: Enzyme, catalytic sites, isopenicillin N synthase, ligand

Principal component analysis on meteorological data in UTM KL

The high usage of fossil fuel to produce energy for the increasing demand of energy has been the primary culprit behind global warming. Renewable energies such as solar energy can be a solution in preventing the situation from worsening. Solar energy can be harnessed using available system such as solar thermal cogeneration systems. However, for the system to function smoothly and continuously, knowledge on solar radiation’s intensity several minutes in advance are required. Though there exist various solar radiation forecast models, most of the existing models requires high computational time. In this research, principal component analysis were applied on the meteorological data collected in Universiti Teknologi Malaysia Kuala Lumpur to reduce the dimension of the data. Dominant factors obtained from the analysis is expected to be useful for the development of solar radiation forecast model

Construct validity and reliability of Malay language-perception towards smoking questionnaire (BM-PTSQ) among secondary school adolescents

Multitude studies have demonstrated that perception is an integral factor associated with smoking. However, no such tool was available in the Malay language. In this study, we established a Bahasa Malaysia version of PTSQ (BM-PTSQ) and tested the validity and reliability among secondary school adolescents. The English version of PTSQ originally consists of 12 items. It was translated into Bahasa Malaysia and back-translated again into English to check for consistency. After face validity (face-to-face query) was determined among 20 secondary school adolescents, only 10 items were included in the survey. Construct validity was established from 407 school adolescents through random selection in the same locality. More than 60% of the respondents were female, while the majority of them (67.3%) were schooling in rural areas. Then, the reliability of the questionnaire was determined with Cronbach’s alpha. The Exploratory Factor Analysis (EFA) has grouped PTSQ into two components associated with either knowledge or attitude towards smoking. The variance and Cronbach’s alpha for the first and second components were 38.24% and 0.861 (7 items), 21.62% and 0.661 (3 items), respectively. The PTSQ showed good validity and reliability for measuring perception of smoking among secondary school-going adolescents in Malaysia. Hence, this is a viable measurement tool. But, more importantly, this study showed an urgent need to improve smoking education among adolescents in Malaysia

Differential Cytokine Responses in Hospitalized COVID-19 Patients Limit Efficacy of Remdesivir

A significant proportion of COVID-19 patients will progress to critical illness requiring invasive mechanical ventilation. This accentuates the need for a therapy that can reduce the severity of COVID-19. Clinical trials have shown the effectiveness of remdesivir in shortening recovery time and decreasing progression to respiratory failure and mechanical ventilation. However, some studies have highlighted its lack of efficacy in patients on high-flow oxygen and mechanical ventilation. This study uncovers some underlying immune response differences between responders and non-responders to remdesivir treatment. Immunological analyses revealed an upregulation of tissue repair factors BDNF, PDGF-BB and PIGF-1, as well as an increase in ratio of Th2-associated cytokine IL-4 to Th1-associated cytokine IFN-γ. Serological profiling of IgG subclasses corroborated this observation, with significantly higher magnitude of increase in Th2-associated IgG2 and IgG4 responses. These findings help to identify the mechanisms of immune regulation accompanying successful remdesivir treatment in severe COVID-19 patients

Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation

IntroductionPharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort.MethodsBuffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models’ performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites.ResultsOverall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model.DiscussionThe development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing

Baseline characteristics of participants in the Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) Program

OBJECTIVE: The Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) Program is a diabetes prevention trial comparing the diabetes conversion rate at 3 years between the intervention group, which receives the incentivized lifestyle intervention program with stepwise addition of metformin, and the control group, which receives the standard of care. We describe the baseline characteristics and compare Pre-DICTED participants with other diabetes prevention trials cohort. RESEARCH DESIGN AND METHODS: Participants were aged between 21 and 64 years, overweight (body mass index (BMI) ≥23.0 kg/m2), and had pre-diabetes (impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT)). RESULTS: A total of 751 participants (53.1% women) were randomized. At baseline, mean (SD) age was 52.5 (8.5) years and mean BMI (SD) was 29.0 (4.6) kg/m2. Twenty-three per cent had both IFG and IGT, 63.9% had isolated IGT, and 13.3% had isolated IFG. Ethnic Asian Indian participants were more likely to report a family history of diabetes and had a higher waist circumference, compared with Chinese and Malay participants. Women were less likely than men to meet the physical activity recommendations (≥150 min of moderate-intensity physical activity per week), and dietary intake varied with both sex and ethnicity. Compared with other Asian diabetes prevention studies, the Pre-DICTED cohort had a higher mean age and BMI. CONCLUSION: The Pre-DICTED cohort represents subjects at high risk of diabetes conversion. The study will evaluate the effectiveness of a community-based incentivized lifestyle intervention program in an urban Asian context.Peer reviewe

Teacher led school-based surveillance can allow accurate tracking of emerging infectious diseases - evidence from serial cross-sectional surveys of febrile respiratory illness during the H1N1 2009 influenza pandemic in Singapore

10.1186/1471-2334-12-336BMC Infectious Diseases12-BIDM

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis