Credit Card Fraud Detection Using Machine Learning As Data Mining Technique

The rapid participation in online based transactional activities raises the fraudulent cases all over the world and causes tremendous losses to the individuals and financial industry. Although there are many criminal activities occurring in financial industry, credit card fraudulent activities are among the most prevalent and worried about by online customers. Thus, countering the fraud activities through data mining and machine learning is one of the prominent approaches introduced by scholars intending to prevent the losses caused by these illegal acts. Primarily, data mining techniques were employed to study the patterns and characteristics of suspicious and non-suspicious transactions based on normalized and anomalies data. On the other hand, machine learning (ML) techniques were employed to predict the suspicious and non-suspicious transactions automatically by using classifiers. Therefore, the combination of machine learning and data mining techniques were able to identify the genuine and non-genuine transactions by learning the patterns of the data. This paper discusses the supervised based classification using Bayesian network classifiers namely K2, Tree Augmented Naïve Bayes (TAN), and Naïve Bayes, logistics and J48 classifiers. After preprocessing the dataset using normalization and Principal Component Analysis, all the classifiers achieved more than 95.0% accuracy compared to results attained before preprocessing the dataset

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

COVID-19 Antibody Surveillance Among Healthcare Workers in A Non-COVID designated Cardiology Centre

BACKGROUND: Reports on healthcare worker antibody response to COVID-19 infection are scarce. We aim to determine theCOVID-19 antibody prevalence among healthcare workers in a cardiology centre and the relationship between case definitioncriteria with the COVID-19 antibody result. METHODS: Convenience sampling was applied. Healthcare workers in SarawakHeart Centre (SHC) cardiology, radiology, and emergency unit were recruited. A survey form on clinical symptoms and closecontact history was distributed. HEALGEN COVID-19 IgG/IgM rapid test was performed using serum/ whole blood specimen.Staff with positive COVID-19 antibody results were referred to the infectious disease specialist for assessment. RESULTS: Atotal of 310 staff were screened. 220(71%) were female, and the mean age was 36±7.7 years old. 46(14.8%) staff reported havingclinical symptoms at some stage from the end of January 2020 to the time of this surveillance. Number of staff who had a historyof overseas travel, close contact with confirmed COVID-19 patients, or had visited places with identified COVID-19 clusterswere 4(1.3%), 24(7.7%) and 24(7.7%) respectively. There were 14 staff (4.5%) with positive tests positive, 2 for IgM, and 12for IgG. All those with positive antibody were subsequently tested negative with RT-PCR test. The history of having clinicalsymptoms and exposure to COVID-19 cluster area were independently associated with a positive IgG result. CONCLUSION:The application of COVID-19 antibody serology rapid tests could determine true exposure of staff to the infection and allowus to reassess existing measures of infection control within the hospital

Clinical Outcomes and Predictors of Improved Left Ventricular Ejection Fraction in Heart Failure with Reduced Ejection Fraction due to Non-Ischemic Cardiomyopathy

Background: Left ventricular ejection fraction (LVEF) improvement is the cornerstone of LV reverse remodelling. It prognosticates heart failure with reduced ejection fraction (HFrEF). There is limited data on the clinical factors that predict LVEF improvement among non-ischemic cardiomyopathy (NICM) patients in Malaysia. Objective: To determine the 3-year outcomes and predictors of LVEF improvement in patients with (NICM) and HFrEF. Materials & Methods: We recruited patients with NICM and HFrEF (LVEF <40%) between 2016 and 2018. NICM was defined as HF with 1) normal coronary arteries or 2) any coronary artery stenosis not involving the proximal left anterior descending artery (LAD) and without transmural fibrosis in the LAD territory from cardiac magnetic resonance (CMR) imaging to account for the impaired LVEF. Clinical and imaging parameters were assessed using logistic regression statistics to determine the predictors of LVEF improvement. LVEF improvement is defined as a recovery of EF to > 40% with at least a 10-point increment from baseline. The clinical outcomes at three year were 1) change in NYHA class and 2) composite of all-cause mortality, unscheduled clinic or emergency department visits, readmission and/or ventricular arrhythmia. Results: 43 patients were recruited. The mean duration of follow-up and echocardiographic assessment interval were 46 and 23 months, respectively. The cohort had a mean age of 46±13 years, and were mostly male (72%). More patients had NYHA 1 at the end of the study (37% vs 86%). 11 patients (25%) recorded composite outcomes. 62.8% had LVEF improvement. Patients with LVEF improvement had a lower incidence of late gadolinium enhancement (51.7% vs 85.7%, odds 5.6 ,p=0.045) and midwall fibrosis on CMR (18.5% vs 62.5%, odds 7.3, p=0.003). LVEF improvement did not affect the functional NYHA recovery (92% vs 81%, p=0.28). Patients with less LVEF improvement had higher incidence of composite outcome (18.5% vs 37.5%, p=0.168). Other characteristics were not significantly different between the groups. Conclusion: Patients with NICM and LVEF improvement had lower composite outcome. Absence of late gadolinium enhancement, particularly midwall fibrosis was an independant predictor of LVEF improvement. This underscores the importance of CMR tissue characterisation to refine the prognostication of NICM patients

Characterizing and Prognosticating Heart Failure with Improved Ejection Fraction Using NT-proBNP, Growth Differentiation Factor 15 and Global Longitudinal Strain

Background: Heart failure with improved ejection fraction (HFiEF) is a novel heart failure (HF) subgroup. There are sparse data on using NT-proBNP, growth differentiation factor 15 (GDF15) and global longitudinal strain (GLS) to characterize and prognosticate HFiEF patients. Objectives: (1) To determine the level and correlation between NT-proBNP, GDF-15 and GLS in HFiEF patients. (2) To examine the correlation of each marker with NYHA, MAGGIC prognostic score, HF etiologies, comorbidities status, degree of LVEF/ LV end-diastolic diameter change from baseline and diastolic dysfunction. (3) To look for association of each marker with follow-up LVEF change and 1-year composite mortality or HF events outcome. Materials & Methods: This was a cross-sectional observational study in Sarawak Heart Centre HF clinic. 53 HfiEF patients who had NT-proBNP and GDF15 tests performed were selected. This cohort had no HF events in the past 6 months during the blood tests. Clinical characteristics, echocardiography parameters, and 1-year composite clinical outcome were analyzed retrospectively. Results: The mean age of the cohort was 52 years old and 81% were male. The cohort was highly comorbid (hypertension 71%; diabetes 45.3%; AF 17.3%). Most of the patients (87%) were asymptomatic by NYHA (I) and low rate of composite outcome was observed, 5.7%. The mean NT-proBNP, GDF-15, GLS were 357 pg/ml, 1572 pg/ml, and -12.1% respectively. There were significant moderate correlation between GDF15 with NT-proBNP (r=0.414) and NT-proBNP with GLS (r=-0.351). Higher NT-proBNP and GDF15 levels were associated with poorer MAGGIC prognostic scores (r=0.549, 0.41 respectively). NT-proBNP was the only marker associated with a higher degree of LVEF improvement compare to baseline echocardiography. NT-proBNP was also related to severe diastolic echo parameters. Hypertension and diabetes were strongly associated with higher elevated GDF15 levels. The lower mean GLS level was significantly associated with the presence of composite outcome (-6.45% vs -12.47%, p=0.0). Patients with NT-proBNP levels below the median cutoff had favourable follow-up LVEF improvement (+9.73%, p=0.035). Conclusion: In our HFiEF study cohort, NT-proBNP best correlate and prognosticate future LV remodelling. GDF15 was closely related to systemic illnesses such as diabetes. The role of GLS in our HFiEF cohort remains uncertain

Prognostic Value of Leucocyte Telomere Length in Acute Myocardial Infarction

Introduction: Leucocyte telomere length (LTL) has been described as a marker of biological age, endothelial dysfunction and atherosclerosis. The association between LTL and clinical characteristics of Asian patients, and their outcomes following acute myocardial infarction (AMI) have been inconclusive. Objective: To investigate the relationship between LTL and developing AMI, the association of LTL with inpatient and 30-day mortality, and the comparison to LTL with established AMI risk scores in predicting these outcomes. Methodology: 100 patients aged 30-70 years admitted with an AMI to a tertiary referral center between May-Oct 2017 were enrolled; these were matched with 100 non-AMI ('healthy') controls for gender and age (+/- 1 year). Clinical data was obtained prospectively; inpatient and 30-day outcomes documented. LTL was reflected by a well described variable called a tis ratio (TSR). The TSR was measured at enrolment using a quantitative PCR-based methods (qPCR) and results blinded to the clinician

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

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of an association with T2D for PEPD5 and HNF4A6,7 has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D