Mapping the Space of Genomic Signatures

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An "image distance" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to $k$ (herein $k=9$) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence homology and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information.Comment: 14 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1307.375

Scenario analysis for programmatic tuberculosis control in Bangladesh: a mathematical modelling study

Tuberculosis (TB) is a major public health problem in Bangladesh. Although the National TB control program of Bangladesh is implementing a comprehensive expansion of TB control strategies, logistical challenges exist, and there is significant uncertainty concerning the disease burden. Mathematical modelling of TB is considered one of the most effective ways to understand the dynamics of infection transmission and allows quantification of parameters in different settings, including Bangladesh. In this study, we present a two-strain mathematical modelling framework to explore the dynamics of drug-susceptible (DS) and multidrug-resistant (MDR) TB in Bangladesh. We calibrated the model using DS and MDR-TB annual incidence data from Bangladesh from years 2001 to 2015. Further, we performed a sensitivity analysis of the model parameters and found that the contact rate of both strains had the largest influence on the basic reproduction numbers [Formula: see text] and [Formula: see text] of DS and MDR-TB, respectively. Increasingly powerful intervention strategies were developed, with realistic impact and coverage determined with the help of local staff. We simulated for the period from 2020 to 2035. Here, we projected the DS and MDR-TB burden (as measured by the number of incident cases and mortality) under a range of intervention scenarios to determine which of these scenario is the most effective at reducing burden. Of the single-intervention strategies, enhanced case detection is the most effective and prompt in reducing DS and MDR-TB incidence and mortality in Bangladesh and that with GeneXpert testing was also highly effective in decreasing the burden of MDR-TB. Our findings also suggest combining additional interventions simultaneously leads to greater effectiveness, particularly for MDR-TB, which we estimate requires a modest investment to substantially reduce, whereas DS-TB requires a strong sustained investment

Prevalence, antibiotic susceptibility profiles and ESBL production in Klebsiella pneumoniae and Klebsiella oxytoca among hospitalized patients

Background and Purpose: Klebsiella pneumoniae and Klebsiella oxytoca are the two most common pathogens causing nosocomial infections in humans and are of great concern for developing multidrug resistance. In the present study, K. pneumoniae and K. oxytoca from clinical samples were evaluated for their antibiotic sensitivity patterns against commonly used antibiotics and production of extended-spectrum beta-lactamase (ESBL). Materials and Methods: The isolates were obtained from tracheal swabs, sputum, wound swabs, pus, blood and urine samples of hospitalized patients. Klebsiella pneumoniae and Klebsiella oxytoca were identified by cultural and biochemical methods. Antibiotic sensitivity test was performed by modified Kirby-Bauer disc diffusion technique. ESBL production in Klebsiella spp. was confirmed by double disc synergy test. Results and Conclusion: Out of 500 clinical isolates, 120 were found positive for Klebsiella among which 108 were K. pneumoniae and 12 were K. oxytoca based on indole test. Prevalence rate of Klebsiella was found more prominent in males aged over 50 years, mostly in urine samples. Overall resistance pattern of Klebsiella isolates to Ampicillin, Amoxicillin, Ceftriaxone, Ciprofloxacin, Co-trimoxazole, Gentamicin, Nalidixic acid, Tetracycline was 100%, 90%, 45%, 40%, 45%, 25%, 50%, 35% respectively. Multidrug resistance was found more common in K. pneumoniae (56%) than in K. oxytoca (50%). Prevalence rate of ESBL producing Klebsiella was found 45% among which K. pneumoniae (50%) were found more prominent than K. oxytoca (25%). All the ESBL producing Klebsiella isolates were found to be multidrug resistant, showing 100% resistance to Ampicillin, Amoxicillin, Ceftriaxone and Ciprofloxacin

Relationship between inter-arm blood pressure differences and predicted future cardiovascular risk in hypertensive patients

Background: Hypertension stands as a widely recognized significant risk factor for cardiovascular disease. In clinical practice, it is advisable to measure blood pressure (BP) in both arms. The increasing attention on inter-arm blood pressure difference (IABPD) stems from its association with cardiovascular disease. This study aimed to assess the relationship between inter-arm blood pressure differences and predicted future cardiovascular risk in hypertensive patients. Methods: This cross-sectional study was conducted at the department of cardiology, Chittagong Medical College Hospital from July 2020 to June 2021. The study included 428 cases of previously or newly diagnosed hypertension, selected through convenient sampling. Data analysis was conducted using Microsoft Office tools and statistical package for the social sciences (SPSS) version 23.0. Results: In this study, 8.2% of patients exhibited noteworthy systolic IAD, and 2.3% demonstrated notable diastolic IAD. Median 10-year cardiovascular risk, assessed by Framingham and ASCVD calculators, was 21% and 11% respectively. A positive correlation was observed between sIAD and 10-year cardiovascular risk (p=0.003) and sIAD and 10-year ASCVD risk (p=0.041). Patients with significant sIAD had a higher incidence of ischemic heart disease compared to those without (p=0.041). Multiple regression analysis revealed a significant correlation between 10-year Framingham cardiovascular risk and sIAD (p=0.003). Conclusions: A significant difference in systolic blood pressure between arms is linked to a higher 10-year cardiovascular risk and the presence of cardiovascular disease in well-managed hypertensive patients. So, monitoring sIAD could be an additional factor in predicting future cardiovascular events in patients receiving hypertension treatment