Application of higher order statistics for atrial arrhythmia classification

Atrial fibrillation (AF) and atrial flutter (AFL) are the two common atrial arrhythmia encountered in the clinical practice. In order to diagnose these abnormalities the electrocardiogram (ECG) is widely used. The conventional linear time and frequency domain methods cannot decipher the hidden complexity present in these signals. The ECG is inherently a non-linear, non-stationary and non-Gaussian signal. The non-linear models can provide improved results and capture minute variations present in the time series. Higher order spectra (HOS) is a non-linear dynamical method which is highly rugged to noise. In the present study, the performances of two methods are compared: (i) 3rd order HOS cumulants and (ii) HOS bispectrum. The 3rd order cumulant and bispectrum coefficients are subjected to dimensionality reduction using independent component analysis (ICA) and classified using classification and regression tree (CART), random forest (RF), artificial neural network (ANN) and k-nearest neighbor (KNN) classifiers to select the best classifier. The ICA components of cumulant coefficients have provided the average accuracy, sensitivity, specificity and positive predictive value of 99.50%, 100%, 99.22% and 99.72% respectively using KNN classifier. Similarly, the ICA components of HOS bispectrum coefficients have yielded the average accuracy, sensitivity, specificity and PPV of 97.65%, 98.16%, 98.75% and 99.53% respectively using KNN. So, the ICA performed on the 3rd order HOS cumulants coupled with KNN classifier performed better than the HOS bispectrum method. The proposed methodology is robust and can be used in mass screening of cardiac patients.     

ECG beat classification using PCA,LDA, ICA and Discrete Wavelet Transform

Electrocardiogram (ECG) is the P-QRS-T wave, representing the cardiac function. The information concealed in the ECG signal is useful in detecting the disease afflicting the heart. It is very difficult to identify the subtle changes in the ECG in time and frequency domains. The Discrete Wavelet Transform (DWT) can provide good time and frequency resolutions and is able to decipher the hidden complexities in the ECG. In this study, five types of beat classes of arrhythmia as recommended by Association for Advancement of Medical Instrumentation (AAMI) were analyzed namely: non-ectopic beats, supra-ventricular ectopic beats, ventricular ectopic beats, fusion betas and unclassifiable and paced beats. Three dimensionality reduction algorithms; Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA) were independently applied on DWT sub bands for dimensionality reduction. These dimensionality reduced features were fed to the Support Vector Machine (SVM), neural network (NN) and probabilistic neural network (PNN) classifiers for automated diagnosis. ICA features in combination with PNN with spread value (σ) of 0.03 performed better than the PCA and LDA. It has yielded an average sensitivity, specificity, positive predictive value (PPV) and accuracy of 99.97%, 99.83%, 99.21% and 99.28% respectively using ten-fold cross validation scheme.     

Unintended polar metabolite profiling of carotenoid-biofortified transgenic rice reveals substantial equivalence to its non-transgenic counterpart

Substantial equivalence is a critical concept for biosafety assessment of genetically modified (GM) crops. To investigate substantial equivalence among carotenoid-biofortified GM rice and five conventional rice cultivars having common white (three) and red (two) grain colors, profiles of 52 polar metabolites were analyzed using gas chromatography time-of-flight mass spectrometry. The results were compared to evaluate the differences among GM and non-GM rice cultivars using principal components analysis. The GM rice is more comparable to its non-transgenic counterpart rice variety according to the closer co-separation than for other cultivars tested. This suggests that profiling of unintended polar metabolites could be a useful tool to reveal substantial equivalence of GM rice.     

Development of cyan fluorescent protein (CFP) reporter system in green alga Chlamydomonas reinhardtii and macroalgae Pyropia sp.

Various fluorescent proteins have been developed for in vivo reporter systems in diverse prokaryotes and eukaryotes. However, few in vivo imaging systems have been reported for the model algae Chlamydomonas reinhardtii or Pyropia sp. In this study, an effective imaging system using cyan fluorescent protein (CFP) was developed for the green alga C. reinhardtii, and its application was also successful in the red macroalgae Pyropia tenera and P. yezoensis. For optimization of CFP expression in C. reinhardtii and Pyropia sp., we modified codon usage in the CFP gene (CFP), generating PtCrCFP (Pyropia tenera/Chlamydomonas reinhardtii CFP). PtCrCFP was successfully expressed in PtCrCFP-expressing UVM11 transgenic lines, and high accumulation levels of PtCrCFP were found by western blotting. Consistent with these results, PtCrCFP fluorescence was clearly detected with a low level of chlorophyll background fluorescence in PtCrCFP-expressing UVM11 transgenic lines. In Pyropia sp. gametophytic cells, transient expression of PtCrCFP fluorescence was distinctly visualized. PtCrCFP fluorescence was also observed during the regeneration of monospores and young gametophytes from PtCrCFP-expressing P. yezoensis gametophytic cells. These results suggest that PtCrCFP may be useful as an in vivo reporter in green algae due to the short emission wavelength of CFP, which provides a low level of chlorophyll background fluorescence. This study also presents the possibility of PtCrCFP’s use as a visible selection marker for the generation of transgenic lines in the red algae Pyropia sp. Thus, PtCrCFP as an in vivo visualization tool may offer new opportunities for the functional analysis of genetic studies in both green and red algae.     

Evolutionary History of HIV-1 Subtype B and CRF01_AE Transmission Clusters among Men Who Have Sex with Men (MSM) in Kuala Lumpur,Malaysia

HIV-1 epidemics among men who have sex with men (MSM) continue to expand in developed and developing countries. Although HIV infection in MSM is amongst the highest of the key affected populations in many countries in Southeast Asia, comprehensive molecular epidemiological study of HIV-1 among MSM remains inadequate in the region including in Malaysia. Here, we reported the phylodynamic profiles of HIV-1 genotypes circulating among MSM population in Kuala Lumpur, Malaysia. A total of n = 459 newly-diagnosed treatment-naïve consenting subjects were recruited between March 2006 and August 2012, of whom 87 (18.9%) were self-reported MSM. Transmitted drug resistance mutations were absent in these isolates. Cumulatively, phylogenetic reconstructions of the pro-rt gene (HXB2∶2253–3275) showed that HIV-1 subtype B and CRF01_AE were predominant and contributed to approximately 80% of the total HIV-1 infection among MSM. In addition to numerous unique transmission lineages within these genotypes, twelve monophyletic transmission clusters of different sizes (2–7 MSM sequences, supported by posterior probability value of 1) were identified in Malaysia. Bayesian coalescent analysis estimated that the divergence times for these clusters were mainly dated between 1995 and 2005 with four major transmission clusters radiating at least 12 years ago suggesting that active spread of multiple sub-epidemic clusters occurred during this period. The changes in effective population size of subtype B showed an exponential growth within 5 years between 1988 and 1993, while CRF01_AE lineage exhibited similar expansion between 1993 and 2003. Our study provides the first insight of the phylodynamic profile of HIV-1 subtype B and CRF01_AE circulating among MSM population in Kuala Lumpur, Malaysia, unravelling the importance of understanding transmission behaviours as well as evolutionary history of HIV-1 in assessing the risk of outbreak or epidemic expansion.     

Is Dynamic Autocrine Insulin Signaling Possible? A Mathematical Model Predicts Picomolar Concentrations of Extracellular Monomeric Insulin within Human Pancreatic Islets

Insulin signaling is essential for -cell survival and proliferation in vivo. Insulin also has potent mitogenic and anti-apoptotic actions on cultured -cells, with maximum effect in the high picomolar range and diminishing effect at high nanomolar doses. In order to understand whether these effects of insulin are constitutive or can be subjected to physiological modulation, it is essential to estimate the extracellular concentration of monomeric insulin within an intact islet. Unfortunately, the in vivo concentration of insulin monomers within the islet cannot be measured directly with current technology. Here, we present the first mathematical model designed to estimate the levels of monomeric insulin within the islet extracellular space. Insulin is released as insoluble crystals that exhibit a delayed dissociation into hexamers, dimers, and eventually monomers, which only then can act as signaling ligands. The rates at which different forms of insulin dissolve in vivo have been estimated from studies of peripheral insulin injection sites. We used this and other information to formulate a mathematical model to estimate the local insulin concentration within a single islet as a function of glucose. Model parameters were estimated from existing literature. Components of the model were validated using experimental data, if available. Model analysis predicted that the majority of monomeric insulin in the islet is that which has been returned from the periphery, and the concentration of intra-islet monomeric insulin varies from 50–300 pM when glucose is in the physiological range. Thus, our results suggest that the local concentration of monomeric insulin within the islet is in the picomolar ‘sweet spot’ range of insulin doses that activate the insulin receptor and have the most potent effects on -cells in vitro. Together with experimental data, these estimations support the concept that autocrine/paracrine insulin signalling within the islet is dynamic, rather than constitutive and saturated.     

Oral Ingestion of Transgenic RIDL Ae. aegypti Larvae Has No Negative Effect on Two Predator Toxorhynchites Species

Dengue is the most important mosquito-borne viral disease. No specific treatment or vaccine is currently available; traditional vector control methods can rarely achieve adequate control. Recently, the RIDL (Release of Insect carrying Dominant Lethality) approach has been developed, based on the sterile insect technique, in which genetically engineered ‘sterile’ homozygous RIDL male insects are released to mate wild females; the offspring inherit a copy of the RIDL construct and die. A RIDL strain of the dengue mosquito, Aedes aegypti, OX513A, expresses a fluorescent marker gene for identification (DsRed2) and a protein (tTAV) that causes the offspring to die. We examined whether these proteins could adversely affect predators that may feed on the insect. Aedes aegypti is a peri-domestic mosquito that typically breeds in small, rain-water-filled containers and has no specific predators. Toxorhynchites larvae feed on small aquatic organisms and are easily reared in the laboratory where they can be fed exclusively on mosquito larvae. To evaluate the effect of a predator feeding on a diet of RIDL insects, OX513A Ae. aegypti larvae were fed to two different species of Toxorhynchites (Tx. splendens and Tx. amboinensis) and effects on life table parameters of all life stages were compared to being fed on wild type larvae. No significant negative effect was observed on any life table parameter studied; this outcome and the benign nature of the expressed proteins (tTAV and DsRed2) indicate that Ae. aegypti OX513A RIDL strain is unlikely to have any adverse effects on predators in the environment.     

Identification of a Novel Human Papillomavirus by Metagenomic Analysis of Samples from Patients with Febrile Respiratory Illness

As part of a virus discovery investigation using a metagenomic approach, a highly divergent novel Human papillomavirus type was identified in pooled convenience nasal/oropharyngeal swab samples collected from patients with febrile respiratory illness. Phylogenetic analysis of the whole genome and the L1 gene reveals that the new HPV identified in this study clusters with previously described gamma papillomaviruses, sharing only 61.1% (whole genome) and 63.1% (L1) sequence identity with its closest relative in the Papillomavirus episteme (PAVE) database. This new virus was named HPV_SD2 pending official classification. The complete genome of HPV-SD2 is 7,299 bp long (36.3% G/C) and contains 7 open reading frames (L2, L1, E6, E7, E1, E2 and E4) and a non-coding long control region (LCR) between L1 and E6. The metagenomic procedures, coupled with the bioinformatic methods described herein are well suited to detect small circular genomes such as those of human papillomaviruses.