Publications by authors named "Pushpendra Singh"

102 Publications

An efficient method for identification of epileptic seizures from EEG signals using Fourier analysis.

Phys Eng Sci Med 2021 Mar 29. Epub 2021 Mar 29.

Indian Institute of Technology Indore, Indore, India.

Epilepsy is a disease recognized as the chronic neurological dysfunction of the human brain which is described by the sudden and excessive electrical discharges of the brain cells. Electroencephalogram (EEG) is a prime tool applied for the diagnosis of epilepsy. In this study, a novel and effective approach is introduced to decompose the non-stationary EEG signals using the Fourier decomposition method. The concept of position, velocity, and acceleration has been employed on the EEG signals for feature extraction using [Formula: see text] norms computed from Fourier intrinsic band functions (FIBFs). The proposed scheme comprises three main sections. In the first section, the EEG signal is decomposed into a finite number of FIBFs. In the second stage, the features are extracted from FIBFs and relevant features are selected by using the Kruskal-Wallis test. In the last stage, the significant features are passed on to the support vector machine (SVM) classifier. By applying 10-fold cross-validation, the proposed method provides better results in comparison to the state-of-the-art methods discussed in the literature, with an average classification accuracy of 99.96% and 99.94% for classification of EEG signals from the BONN dataset and the CHB-MIT dataset, respectively. It can be implemented using the computationally efficient fast Fourier transform (FFT) algorithm.
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http://dx.doi.org/10.1007/s13246-021-00995-3DOI Listing
March 2021

Generalized SIR (GSIR) epidemic model: An improved framework for the predictive monitoring of COVID-19 pandemic.

ISA Trans 2021 Feb 15. Epub 2021 Feb 15.

SBILab, Department of ECE, Indraprastha Institute of Information Technology Delhi, Delhi, India. Electronic address:

Novel coronavirus respiratory disease COVID-19 has caused havoc in many countries across the globe. In order to contain infection of this highly contagious disease, most of the world population is constrained to live in a complete or partial lockdown for months together with a minimal human-to-human interaction having far reaching consequences on countries' economy and mental well-being of their citizens. Hence, there is a need for a good predictive model for the health advisory bodies and decision makers for taking calculated proactive measures to contain the pandemic and maintain a healthy economy. This paper extends the mathematical theory of the classical Susceptible-Infected-Removed (SIR) epidemic model and proposes a Generalized SIR (GSIR) model that is an integrative model encompassing multiple waves of daily reported cases. Existing growth function models of epidemic have been shown as the special cases of the GSIR model. Dynamic modeling of the parameters reflect the impact of policy decisions, social awareness, and the availability of medication during the pandemic. GSIR framework can be utilized to find a good fit or predictive model for any pandemic. The study is performed on the COVID-19 data for various countries with detailed results for India, Brazil, United States of America (USA), and World. The peak infection, total expected number of COVID-19 cases and thereof deaths, time-varying reproduction number, and various other parameters are estimated from the available data using the proposed methodology. The proposed GSIR model advances the existing theory and yields promising results for continuous predictive monitoring of COVID-19 pandemic.
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http://dx.doi.org/10.1016/j.isatra.2021.02.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7883688PMC
February 2021

SARS-CoV-2 antibody seroprevalence in India, August-September, 2020: findings from the second nationwide household serosurvey.

Lancet Glob Health 2021 03 27;9(3):e257-e266. Epub 2021 Jan 27.

ICMR, New Delhi, India.

Background: The first national severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey in India, done in May-June, 2020, among adults aged 18 years or older from 21 states, found a SARS-CoV-2 IgG antibody seroprevalence of 0·73% (95% CI 0·34-1·13). We aimed to assess the more recent nationwide seroprevalence in the general population in India.

Methods: We did a second household serosurvey among individuals aged 10 years or older in the same 700 villages or wards within 70 districts in India that were included in the first serosurvey. Individuals aged younger than 10 years and households that did not respond at the time of survey were excluded. Participants were interviewed to collect information on sociodemographics, symptoms suggestive of COVID-19, exposure history to laboratory-confirmed COVID-19 cases, and history of COVID-19 illness. 3-5 mL of venous blood was collected from each participant and blood samples were tested using the Abbott SARS-CoV-2 IgG assay. Seroprevalence was estimated after applying the sampling weights and adjusting for clustering and assay characteristics. We randomly selected one adult serum sample from each household to compare the seroprevalence among adults between the two serosurveys.

Findings: Between Aug 18 and Sept 20, 2020, we enrolled and collected serum samples from 29 082 individuals from 15 613 households. The weighted and adjusted seroprevalence of SARS-CoV-2 IgG antibodies in individuals aged 10 years or older was 6·6% (95% CI 5·8-7·4). Among 15 084 randomly selected adults (one per household), the weighted and adjusted seroprevalence was 7·1% (6·2-8·2). Seroprevalence was similar across age groups, sexes, and occupations. Seroprevalence was highest in urban slum areas followed by urban non-slum and rural areas. We estimated a cumulative 74·3 million infections in the country by Aug 18, 2020, with 26-32 infections for every reported COVID-19 case.

Interpretation: Approximately one in 15 individuals aged 10 years or older in India had SARS-CoV-2 infection by Aug 18, 2020. The adult seroprevalence increased approximately tenfold between May and August, 2020. Lower infection-to-case ratio in August than in May reflects a substantial increase in testing across the country.

Funding: Indian Council of Medical Research.
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http://dx.doi.org/10.1016/S2214-109X(20)30544-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906675PMC
March 2021

Green synthesis of silver nanoparticles using Indian male fern (), operational parameters, characterization and bioactivity on venom neutralization.

Toxicol Res (Camb) 2020 Sep 15;9(5):706-713. Epub 2020 Oct 15.

Department of Biological Science and Engineering, Maulana Azad National Institute of Technology, Bhopal 462003, Madhya Pradesh, India.

Snakebite is considered as one of the acute severe medical problems across the world. Snake venoms composed of various group of toxins, enzymes and non-toxic enzymes. Phospholipases A present in snake venom plays a significant role in lipid signalling and contributes to different inflammation in the human body. rhizomes have antioxidant, antimicrobial property and used to treat lesions, gonorrhoea, sores, muscular pain, rheumatic and also useful in dog and snake bites. In this study, Indian male fern rhizomes have been used for green synthesis of silver nanoparticles with the aim to increase the bioactivity of plant extract and to evaluate snake venom inhibition activity of prepared nanoparticles. Green synthesized nanoparticles were characterized with the help of ultraviolet-visible spectroscopy, Fourier-transform infrared spectroscopy, X-ray powder diffraction and atomic force microscopy. venom inhibition activity of nanoparticles was performed using phospholipases A assay and tissue damage activity. The results showed that surface plasmon resonance maxima peaks of nanoparticles were observed at 424 nm. Average particle size was around 35 nm, with a spherical shape. Neutralization results exhibited that synthesized silver nanoparticles from decreased percentage of tissue damage, resulting in significant inhibition of phospholipase A and snake venom. Results concluded that green synthesized silver nanoparticles from rhizome neutralize snake venom activity.
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http://dx.doi.org/10.1093/toxres/tfaa070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7640931PMC
September 2020

Comparison of target enrichment strategies for ancient pathogen DNA.

Biotechniques 2020 12 2;69(6):455-459. Epub 2020 Nov 2.

Institute for Archaeological Sciences, Archaeo- & Palaeogenetics, University of Tübingen, 72070 Tübingen, Germany.

In ancient DNA research, the degraded nature of the samples generally results in poor yields of highly fragmented DNA; targeted DNA enrichment is thus required to maximize research outcomes. The three commonly used methods - array-based hybridization capture and in-solution capture using either RNA or DNA baits - have different characteristics that may influence the capture efficiency, specificity and reproducibility. Here we compare their performance in enriching pathogen DNA of and from 11 ancient and 19 modern samples. We find that in-solution approaches are the most effective method in ancient and modern samples of both pathogens and that RNA baits usually perform better than DNA baits.
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http://dx.doi.org/10.2144/btn-2020-0100DOI Listing
December 2020

Potential Inhibitors for SARS-CoV-2 and Functional Food Components as Nutritional Supplement for COVID-19: A Review.

Plant Foods Hum Nutr 2020 Dec 10;75(4):458-466. Epub 2020 Oct 10.

Department of Biological Science & Engineering, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, 462003, India.

The severe acute respiratory syndrome is a viral respiratory infection and commonly called as COVID-19, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). It widely transmitted through direct or indirect contact. Currently, no specific treatment against SARS-CoV-2 are available; only prevention and supportive strategy are the preventive measures. The present review emphasizes the latest research related to COVID-19 and SARS-CoV-2 virus as well as the current status of potential inhibitors identified. Recent interest in SARS-CoV-2 has focused on transmission, symptoms, structure, and its structural proteins that exhibit promising therapeutics targets for rapid identification of potential inhibitors. The quick identification of potential inhibitors and immune-boosting functional food ingredients are crucial to combat this pandemic disease. We also tried to give an overview of the functional food components as a nutritional supplement, which helps in boosting our immune system and could be useful in preventing the COVID-19 and/or to improve the outcome during therapy.
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http://dx.doi.org/10.1007/s11130-020-00861-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7546941PMC
December 2020

Molecular epidemiology of leprosy: An update.

Infect Genet Evol 2020 12 4;86:104581. Epub 2020 Oct 4.

Laboratory of Molecular Biology Applied to Mycobacteria - Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil. Electronic address:

Molecular epidemiology investigations are notoriously challenging in the leprosy field mainly because the inherent characteristics of the disease as well as its yet uncultivated causative agents, Mycobacterium leprae and M. lepromatosis. Despite significant developments in understanding the biology of leprosy bacilli through genomic approaches, the exact mechanisms of transmission is still unclear and the factors underlying pathological variation of the disease in different patients remain as major gaps in our knowledge about leprosy. Despite these difficulties, the last two decades have seen the development of genotyping procedures based on PCR-sequencing of target loci as well as by the genome-wide analysis of an increasing number of geographically diverse isolates of leprosy bacilli. This has provided a foundation for molecular epidemiology studies that are bringing a better understanding of strain evolution associated with ancient human migrations, and phylogeographical insights about the spread of disease globally. This review discusses the advantages and drawbacks of the main tools available for molecular epidemiological investigations of leprosy and summarizes various methods ranging from PCR-based genotyping to genome-typing techniques. We also describe their main applications in analyzing the short-range and long-range transmission of the disease. Finally, we summarise the current gaps and challenges that remain in the field of molecular epidemiology of leprosy.
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http://dx.doi.org/10.1016/j.meegid.2020.104581DOI Listing
December 2020

A novel approach for automated alcoholism detection using Fourier decomposition method.

J Neurosci Methods 2020 12 7;346:108945. Epub 2020 Sep 7.

Department of Electronics and Communication Engineering, National Institute of Technology, Hamirpur, India.

Background: The identification of alcoholism is of prime importance because of its adverse effects on the central nervous system. Moreover, people suffering from alcoholism are susceptible to various health problems such as cardiomyopathy, immune system disorder, high blood pressure, cirrhosis, brain anomalies, and heart problems.

New Method: This study presents a novel approach, based on Fourier theory, known as Fourier decomposition method (FDM) for automatic identification of alcoholism using electroencephalogram (EEG) signals. The FDM approach is employed to decompose EEG signals into a set of desired orthogonal components, commonly referred as Fourier intrinsic band functions (FIBFs), obtained by dividing the complete bandwidth of EEG signal under analysis into equal frequency bands. Time-domain features such as Hjorth parameters, kurtosis, inter-quartile range, and median frequency are extracted from FIBFs. To reduce the complexity, Kruskal-Wallis (KW) statistical test, is performed to adopt the most significant features.

Results: Simulation results are obtained using different classification methods, namely, k-nearest neighbor (kNN), support vector machine (SVM), and linear discriminant analysis (LDA). The proposed approach with the SVM classifier using radial basis function provides average accuracy of 99.98%, sensitivity of 99.99% and specificity of 99.97%. Performance is also tested in the presence of noise.

Comparison With Existing Method(s): Classification results highlight the superior performance of our method in comparison to existing works.

Conclusions: The proposed scheme provides an efficient approach and can be employed in real-time alcoholism detection.
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http://dx.doi.org/10.1016/j.jneumeth.2020.108945DOI Listing
December 2020

Novel generalized Fourier representations and phase transforms.

Authors:
Pushpendra Singh

Digit Signal Process 2020 Nov 10;106:102830. Epub 2020 Aug 10.

Department of ECE, National Institute of Technology Hamirpur, India.

The Fourier representations (FRs) are indispensable mathematical formulations for modeling and analysis of physical phenomena and engineering systems. This study presents a new set of generalized Fourier representations (GFRs) and phase transforms (PTs). The PTs are special cases of the GFRs and true generalizations of the Hilbert transforms. In particular, the Fourier transform based kernel of the PT is derived and its various properties are discussed. The time derivative and integral, including fractional order, of a signal are obtained using the GFR. It is demonstrated that the general class of time-invariant and time-variant filtering operations, analog and digital modulations can be obtained from the proposed GFR. A narrowband Fourier representation for the time-frequency analysis of a signal is also presented using the GFR. A discrete cosine transform based implementation, to avoid end artifacts due to discontinuities present in the both ends of a signal, is proposed. A fractional-delay in a discrete-time signal using the FR is introduced. The fast Fourier transform implementation of all the proposed representations is developed. Moreover, using the analytic wavelet transform, a wavelet phase transform (WPT) is proposed to obtain a desired phase-shift in a signal under-analysis. A wavelet quadrature transform (WQT) is also presented which is a special case of the WPT with a phase-shift of radians. Thus, a wavelet analytic signal representation is derived from the WQT. Theoretical analysis and numerical experiments are conducted to evaluate effectiveness of the proposed methods.
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http://dx.doi.org/10.1016/j.dsp.2020.102830DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416779PMC
November 2020

Biophysical characterization of polydisperse liposomal adjuvant formulations.

Biochem Biophys Res Commun 2020 08 1;529(2):362-365. Epub 2020 Jul 1.

U.S. Military HIV Research Program, Walter Reed Army Institute of Research, 503 Robert Grant Ave, Silver Spring, MD, 20910, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD, 20817, USA. Electronic address:

Army Liposome Formulations (ALF) are potent adjuvants, of which there are two primary forms, lyophilized ALF (ALFlyo) containing monophosphoryl lipid A (MPLA) and ALF containing MPLA and QS21 (ALFQ). ALFlyo and ALFQ adjuvants are essential constituents of candidate vaccines for bacterial, viral, and parasitic diseases. They have been widely used in preclinical immunogenicity studies in small animals and non-human primates and are progressing to phase I/IIa clinical trials. ALFQ was prepared by adding saponin QS21 to small unilamellar liposome vesicles (SUVs) of ALF55 that contain 55 mol% cholesterol, whereas ALFlyo was created by reconstituting lyophilized SUVs of ALF43, consisting of 43 mol% cholesterol, in aqueous buffer solution. These formulations display heterogenous particle size distribution. Since biophysical characteristics of liposomes may impact their adjuvant potential, we characterized the particle size distribution and lamellarity of the individual liposome particles in ALFlyo and ALFQ formulations using cryo-electron microscopy and a newly developed MANTA technology. ALFlyo and ALFQ exhibited similar particle size distributions with liposomes ranging from 50 nm to several μm. However, fundamental differences were observed in the lamellar structures of the liposomes. ALFlyo displayed a greater number of multilamellar and multivesicular liposome particles, as compared to that in ALFQ, which was predominately unilamellar.
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http://dx.doi.org/10.1016/j.bbrc.2020.05.156DOI Listing
August 2020

Identification of bioactive molecule from (Ashwagandha) as SARS-CoV-2 main protease inhibitor.

J Biomol Struct Dyn 2020 Jul 8:1-14. Epub 2020 Jul 8.

Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.

SARS-CoV-2 is the causative agent of COVID-19 and has been declared as pandemic disease by World Health Organization. Lack of targeted therapeutics and vaccines for COVID-2019 have triggered the scientific community to develop new vaccines or drugs against this novel virus. Many synthetic compounds and antimalarial drugs are undergoing clinical trials. The traditional medical practitioners widely use Indian medicinal plant (Ashwagandha) natural constituents, called withanolides for curing various diseases. The main protease (M) of SARS-CoV-2 plays a vital role in disease propagation by processing the polyproteins which are required for its replication. Hence, it denotes a significant target for drug discovery. In the present study, we evaluate the potential of 40 natural chemical constituents of Ashwagandha to explore a possible inhibitor against main protease of SARS-CoV-2 by adopting the computational approach. The docking study revealed that four constituents of Ashwagandha; Withanoside II (-11.30 Kcal/mol), Withanoside IV (-11.02 Kcal/mol), Withanoside V (-8.96 Kcal/mol) and Sitoindoside IX (-8.37 Kcal/mol) exhibited the highest docking energy among the selected natural constituents. Further, MD simulation study of 100 ns predicts Withanoside V possess strong binding affinity and hydrogen-bonding interactions with the protein active site and indicates its stability in the active site. The binding free energy score also correlates with the highest score of -87.01 ± 5.01 Kcal/mol as compared to other selected compounds. In conclusion, our study suggests that Withanoside V in Ashwagandha may be serve as a potential inhibitor against M of SARS-CoV-2 to combat COVID-19 and may have an antiviral effect on nCoV. Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1790425DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7441797PMC
July 2020

Modeling and prediction of COVID-19 pandemic using Gaussian mixture model.

Chaos Solitons Fractals 2020 Sep 16;138:110023. Epub 2020 Jun 16.

Department of Electrical Engineering, Indian Institute of Technology Delhi, Delhi, India.

COVID-19 is caused by a novel coronavirus and has played havoc on many countries across the globe. A majority of the world population is now living in a restricted environment for more than a month with minimal economic activities, to prevent exposure to this highly infectious disease. Medical professionals are going through a stressful period while trying to save the larger population. In this paper, we develop two different models to capture the trend of a number of cases and also predict the cases in the days to come, so that appropriate preparations can be made to fight this disease. The first one is a mathematical model accounting for various parameters relating to the spread of the virus, while the second one is a non-parametric model based on the Fourier decomposition method (FDM), fitted on the available data. The study is performed for various countries, but detailed results are provided for the India, Italy, and United States of America (USA). The turnaround dates for the trend of infected cases are estimated. The end-dates are also predicted and are found to agree well with a very popular study based on the classic susceptible-infected-recovered (SIR) model. Worldwide, the total number of expected cases and deaths are 12.7 × 10 and 5.27 × 10, respectively, predicted with data as of 06-06-2020 and 95% confidence intervals. The proposed study produces promising results with the potential to serve as a good complement to existing methods for continuous predictive monitoring of the COVID-19 pandemic.
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http://dx.doi.org/10.1016/j.chaos.2020.110023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296328PMC
September 2020

Population Genomics of Reveals a New Genotype in Madagascar and the Comoros.

Front Microbiol 2020 11;11:711. Epub 2020 May 11.

Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

Human settlement of Madagascar traces back to the beginning of the first millennium with the arrival of Austronesians from Southeast Asia, followed by migrations from Africa and the Middle East. Remains of these different cultural, genetic, and linguistic legacies are still present in Madagascar and other islands of the Indian Ocean. The close relationship between human migration and the introduction and spread of infectious diseases, a well-documented phenomenon, is particularly evident for the causative agent of leprosy, . In this study, we used whole-genome sequencing (WGS) and molecular dating to characterize the genetic background and retrace the origin of the strains circulating in Madagascar ( = 30) and the Comoros ( = 3), two islands where leprosy is still considered a public health problem and monitored as part of a drug resistance surveillance program. Most strains (97%) from Madagascar and Comoros belonged to a new genotype as part of branch 1, closely related to single nucleotide polymorphism (SNP) type 1D, named 1D-Malagasy. Other strains belonged to the genotype 1A (3%). We sequenced 39 strains from nine other countries, which, together with previously published genomes, amounted to 242 genomes that were used for molecular dating. Specific SNP markers for the new 1D-Malagasy genotype were used to screen samples from 11 countries and revealed this genotype to be restricted to Madagascar, with the sole exception being a strain from Malawi. The overall analysis thus ruled out a possible introduction of leprosy by the Austronesian settlers and suggests a later origin from East Africa, the Middle East, or South Asia.
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http://dx.doi.org/10.3389/fmicb.2020.00711DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233131PMC
May 2020

Inter-comparisons and applicability of CMIP5 GCMs, RCMs and statistically downscaled NEX-GDDP based precipitation in India.

Sci Total Environ 2019 Dec 30;697:134163. Epub 2019 Aug 30.

National Institute of Hydrology, Roorkee 247667, Uttarakhand, India.

The applicability of GCMs (produced at 2° to 4°) and RCMs (produced at ~0.5°) vary and they might produce lots of ambiguity in their outcomes, because of their resolutions. This is true fact and already been reported in several studies. In this study, we have explored the precipitation variabilities in India involved in different resolution climate model based data-sets such as GCMs and RCMs under two extreme Representation Concentration Pathway (RCP) experiments (e.g. RCP4.5 and RCP8.5). Precipitation inter-comparisons have been done between different resolution datasets (e.g. GCMs, RCMs, NEX-GDDP and observed precipitation) to explore precipitation ambiguity (or variabilities) and their applicability in a long-term period (1951-2100) across the India. The observed gridded precipitation (1951-2005) and NEX-GDDP datasets (2006-2100) have been used as a reference data-sets to assess the accuracy of GCMs and RCMs. Variations in precipitation trends have been explored at each grid scale utilizing non-parametric Mann-Kendall test and statistical p-value test at 95% confidence interval. Inter-comparison analysis results showed that a significant diversity existed in the precipitation amounts among all climate model datasets, which have been non-uniformly distributed across the India. Results from model inter-comparisons, percentage of change analysis and Q-Q analysis performed between GCMs versus observed precipitation, RCM versus observed precipitation, GCMs versus RCMs and RCMs versus NEX-GDDP models showed a high variability existed in precipitation amount across the India during1951-2100. In opposite, at several locations a good association in precipitation between different resolution datasets was observed. GCMs based precipitation was underestimated and RCMs showed overestimation across the India. Overall, RCMs based rainfalls have found comparatively closer to observed and NEX-GDDP based rainfalls, yet RCMs have highly overestimated in several regions of India. Seasonal trends uncertainty estimation showed a better correlation in precipitation between NEX-GDDP and RCMs, especially during monsoon and pre-monsoon season.
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http://dx.doi.org/10.1016/j.scitotenv.2019.134163DOI Listing
December 2019

The double burden of malnutrition among adults in India: evidence from the National Family Health Survey-4 (2015-16).

Epidemiol Health 2019 18;41:e2019050. Epub 2019 Dec 18.

Tata Institute of Social Sciences, Mumbai, India.

Objectives: India still faces the burden of undernutrition and communicable diseases, and the prevalence of overweight/obesity is steadily increasing. The discourse regarding the dual burden of underweight and overweight/obesity has not yet been widely explored in both men and women. The present study assessed the determinants of underweight and overweight/obesity in India among adult men and women aged 15-49.

Methods: Population-based cross-sectional and nationally representative data from the National Family Health Survey-4 (2015-16), consisting of a sample of men and women, were analyzed. Stratified 2-stage sampling was used in the NFHS-4 study protocol. In the present study, bivariate and adjusted multinomial logistic regression analyses were performed to determine the correlates of underweight and overweight/obesity.

Results: The results suggested a persistently high prevalence of underweight coexisting with an increased prevalence of overweight/obesity in India. The risk of underweight was highest in the central and western regions and was also relatively high among those who used either smoking or smokeless tobacco. Overweight/obesity was more prevalent in urban areas, in the southern region, and among adults aged 35-49. Furthermore, level of education and wealth index were positively associated with overweight/obesity. More educated and wealthier adults were less likely to be underweight.

Conclusions: In India, underweight has been prevalent, and the prevalence of overweight/obesity is increasing rapidly, particularly among men. The dual burden of underweight and overweight/obesity is alarming and needs to be considered; public health measures to address this situation must also be adopted through policy initiatives.
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http://dx.doi.org/10.4178/epih.e2019050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976728PMC
January 2020

Percolation Characteristics of Conductive Additives for Capacitive Flowable (Semi-Solid) Electrodes.

ACS Appl Mater Interfaces 2020 Feb 22;12(5):5866-5875. Epub 2020 Jan 22.

Electrochemical Energy Systems Laboratory Department of Mechanical Engineering and Mechanics , Drexel University , Philadelphia , Pennsylvania 19104 , United States.

Understanding the percolation characteristics of multicomponent conducting suspensions is critical for the development of flowable (semi-solid) electrochemical systems for energy storage and capacitive deionization with optimal electrochemical and rheological performance. Despite its significance, not much is known about the impact of the selected particle morphology on the agglomeration kinetics and the state of dispersion in flowable electrodes. In this study, the impact of the conductive additive morphology on the electrochemical and rheological response of capacitive flowable electrodes has been systematically investigated. Critical viscosity limits have been determined for common carbon additives that offer slurry formulations with improved electrochemical and rheological performance. For instance, at the same electrical conductivity of 60 mS cm, higher aspect ratio particles, such as graphene and carbon nanotubes, offered 4 and 2.4 times lower viscosity compared to carbon black due to the improved packing and conformity of the high aspect ratio particles. On the other hand, thixotropic measurements showed that the flowable electrodes with carbon black exhibit the fastest agglomeration kinetics, offering 25 % less time to recover from the applied shear due to spherical morphology and facile agglomeration kinetics. Overall, our findings show that the particle morphology has a significant impact on the electrochemical and rheological performance of flowable electrodes with up to 40 % difference in capacitance for similar viscosity suspensions. Furthermore, a direct correlation between the rheological and the electrochemical properties was established, offering morphology-independent practical guidelines for formulating slurries with optimal performance. In this manner, particles that can achieve the highest density of packing before the critical limit were found to offer the optimal balance between electrochemical and rheological performance.
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http://dx.doi.org/10.1021/acsami.9b19739DOI Listing
February 2020

Isolation of Mycobacterium lepromatosis and Development of Molecular Diagnostic Assays to Distinguish Mycobacterium leprae and M. lepromatosis.

Clin Infect Dis 2020 Nov;71(8):e262-e269

US Department of Health and Human Services, Health Resources and Services Administration, Healthcare Systems Bureau, National Hansen's Disease Program, Baton Rouge, Louisiana, USA.

Background: Mycobacterium leprae was thought to be the exclusive causative agent of leprosy until Mycobacterium lepromatosis was identified in a rare form of leprosy known as diffuse lepromatous leprosy (DLL).

Methods: We isolated M. lepromatosis from a patient with DLL and propagated it in athymic nude mouse footpads. Genomic analysis of this strain (NHDP-385) identified a unique repetitive element, RLPM, on which a specific real-time quantitative polymerase chain reaction assay was developed. The RLPM assay, and a previously developed RLEP quantitative polymerase chain reaction assay for M. leprae, were validated as clinical diagnostic assays according to Clinical Laboratory Improvement Amendments guidelines. We tested DNA from archived histological sections, patient specimens from the United States, Philippines, and Mexico, and US wild armadillos.

Results: The limit of detection for the RLEP and RLPM assays is 30 M. leprae per specimen (0.76 bacilli per reaction; coefficient of variation, 0.65%-2.44%) and 122 M. lepromatosis per specimen (3.05 bacilli per reaction; 0.84%-2.9%), respectively. In histological sections (n = 10), 1 lepromatous leprosy (LL), 1 DLL, and 3 Lucio reactions contained M. lepromatosis; 2 LL and 2 Lucio reactions contained M. leprae; and 1 LL reaction contained both species. M. lepromatosis was detected in 3 of 218 US biopsy specimens (1.38%). All Philippines specimens (n = 180) were M. lepromatosis negative and M. leprae positive. Conversely, 15 of 47 Mexican specimens (31.91%) were positive for M. lepromatosis, 19 of 47 (40.43%) were positive for M. leprae, and 2 of 47 (4.26%) contained both organisms. All armadillos were M. lepromatosis negative.

Conclusions: The RLPM and RLEP assays will aid healthcare providers in the clinical diagnosis and surveillance of leprosy.
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http://dx.doi.org/10.1093/cid/ciz1121DOI Listing
November 2020

Particle size analyses of polydisperse liposome formulations with a novel multispectral advanced nanoparticle tracking technology.

Int J Pharm 2019 Jul 6;566:680-686. Epub 2019 Jun 6.

U.S. Military HIV Research Program, Henry M. Jackson Foundation for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD, USA; Laboratory of Adjuvant and Antigen Research, U S Military HIV Research Program, Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD, USA. Electronic address:

Liposomes are potent adjuvant constituents for licensed vaccines and vaccine candidates and carriers for drug delivery. Depending on the method of preparation, liposomes vary in size distribution, either forming uniform small size vesicles or a heterogeneous mixture of small to large vesicles. Importantly, differences in liposomal size have been demonstrated to induce differential immune responses. Determination of particle size distribution could therefore be crucial for the efficacy and stability of vaccine formulations. We compared the techniques of dynamic light scattering, laser diffraction, and conventional nanoparticle tracking analysis with a novel multispectral advanced nanoparticle tracking analysis (MANTA) for particle size determination of mono- and polydisperse liposomes. MANTA reported an average 146 nm size of monodisperse liposomes but showed a multimodal distribution of polydisperse liposomes with continuous sizes from 50 to 2000 nm. However, approximately 95% of particles were in the size range of 50-1500 nm and only few particles were identified in the 1500-2000 nm range for the investigated volume. Based on our results, we conclude that MANTA is the most suitable approach and can serve as stand-alone technique for particle size characterization of heterogeneous liposome samples in the 50-2000 nm size range.
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http://dx.doi.org/10.1016/j.ijpharm.2019.06.013DOI Listing
July 2019

Drug-Eluting Stent Use Among Low-Income Patients in Maharashtra After Statewide Price Reductions.

Circ Cardiovasc Interv 2019 04;12(4):e007757

Michigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine (B.G., K.S., B.K.N.), University of Michigan, Ann Arbor.

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http://dx.doi.org/10.1161/CIRCINTERVENTIONS.118.007757DOI Listing
April 2019

I-BLEND, a campus-scale commercial and residential buildings electrical energy dataset.

Sci Data 2019 02 19;6:190015. Epub 2019 Feb 19.

Computer Science and Engineering, OKhla Phase III, IIIT Delhi, New Delhi, 110020 India.

Efficient energy consumption at the building level is vital for sustainability. Providing energy efficient systems and solutions requires an understanding of how energy gets consumed. However, there is a general lack of large-scale open datasets about the energy consumption of buildings, which hinders the research. The recent emergence of smart energy meters makes it possible to collect such data, which can then be used for analysis. In this paper, we release I-BLEND, 52 months of electrical energy dataset at a one-minute sampling rate from commercial and residential buildings of an academic institute campus in an emerging economy, India. Also, we provide occupancy datasets at a 10-minute sampling rate for each of the campus buildings. To the best of our knowledge, this is the first such dataset from India. Public availability of such fine-granular data will allow users to perform different research tasks such as analyzing the impact of weather or occupancy schedule on energy consumption, detecting anomalies, and developing algorithms for predictive maintenance.
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http://dx.doi.org/10.1038/sdata.2019.15DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6422068PMC
February 2019

Epidemiology of technology addiction among school students in rural India.

Asian J Psychiatr 2019 Feb 24;40:30-38. Epub 2019 Jan 24.

Department of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh, India. Electronic address:

Objective: Penetration of mobile technology is rapidly rising. Excessive use leads to Technology addiction, which often start early in adolescence. The purpose of the present study was to assess Technology addiction and its correlates among school students in rural India.

Methods: This cross sectional study was conducted among 885 school students in north India. Four schools were selected and participants aged 13-18 years, were enrolled randomly. A self-designed 45 item questionnaire was used to evaluate dependence syndrome (intense desire, impaired control, tolerance, withdrawal, persistence despite harm, neglect of alternate pleasure) as used for substance dependence in ICD-10. Screening for depression and anxiety was done by using patient health questionnaire (PHQ-9) and generalized anxiety disorder scale (GAD-7) respectively. Descriptive and logistic regression analyses were done.

Results: The mean age of the study participants was 15.1 years. Among the participants, 30.3% (95% Confidence Interval = 27.2%-33.3%) met the dependence criteria. One-third (33%) of the students stated that their grades had gone down due to gadget use. Technology addiction was more among male students (odds ratio = 2.82, 95% CI = 1.43, 5.59), those having a personal mobile phone (2.98, (1.52-5.83), use smart phone (2.77, 1.46-5.26), use one additional gadget (2.12, 1.14-3.94) and those who were depressed (3.64, 2.04-6.49).

Conclusion: Increased mobile phone access in rural India is leading to technology addiction among school students. Certain demographic and gadget specific factors predict addiction. The technology addiction possibly contributes to poor academic performance and depression. This warrants studies on a larger scale, with interventions for judicious use of gadgets.
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http://dx.doi.org/10.1016/j.ajp.2019.01.009DOI Listing
February 2019

Novel Fourier quadrature transforms and analytic signal representations for nonlinear and non-stationary time-series analysis.

Authors:
Pushpendra Singh

R Soc Open Sci 2018 Nov 28;5(11):181131. Epub 2018 Nov 28.

School of Engineering and Applied Sciences, Bennett University, Greater Noida, India.

The Hilbert transform (HT) and associated Gabor analytic signal (GAS) representation are well known and widely used mathematical formulations for modelling and analysis of signals in various applications. In this study, like the HT, to obtain quadrature component of a signal, we propose novel discrete Fourier cosine quadrature transforms (FCQTs) and discrete Fourier sine quadrature transforms (FSQTs), designated as Fourier quadrature transforms (FQTs). Using these FQTs, we propose 16 Fourier quadrature analytic signal (FQAS) representations with following properties: (1) real part of eight FQAS representations is the original signal, and imaginary part of each representation is FCQT of real part; (2) imaginary part of eight FQAS representations is the original signal, and real part of each representation is FSQT of imaginary part; (3) like the GAS, Fourier spectrum of all FQAS representations has only positive frequencies; however, unlike the GAS, real and imaginary parts of FQAS representations are not orthogonal. The Fourier decomposition method (FDM) is an adaptive data analysis approach to decompose a signal into a set Fourier intrinsic band functions. This study also proposes new formulations of the FDM using discrete cosine transform with GAS and FQAS representations, and demonstrates its efficacy for improved time-frequency-energy representation and analysis of many real-life nonlinear and non-stationary signals.
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http://dx.doi.org/10.1098/rsos.181131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6281917PMC
November 2018

Saturated phospholipids are required for nano- to micron-size transformation of cholesterol-containing liposomes upon QS21 addition.

J Liposome Res 2019 Sep 23;29(3):247-250. Epub 2018 Nov 23.

b Laboratory of Adjuvant and Antigen Research, U.S. Military HIV Research Program, Walter Reed Army Institute of Research , 503 Robert Grant Avenue , Silver Spring , MD 20910 , USA.

Liposomes containing cholesterol and monophosphoryl lipid A (such as ALFQ and AS01B) are vaccine adjuvants. During construction of the formulations, addition of QS21 to nano-size (50-100 nm) liposomes resulted in extremely large (up to ∼30 µm) liposomes in ALFQ, but AS01B liposomes remained small nano-vesicles. Here, we show that saturation of phospholipid chains is essential for production of large liposomes by QS21.
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http://dx.doi.org/10.1080/08982104.2018.1538239DOI Listing
September 2019

Is India ready for mental health apps (MHApps)? A quantitative-qualitative exploration of caregivers' perspective on smartphone-based solutions for managing severe mental illnesses in low resource settings.

PLoS One 2018 19;13(9):e0203353. Epub 2018 Sep 19.

Department of Computer Science, IIIT-Delhi, Delhi, India.

Background: Mobile application based delivery of psycho-social interventions may help reduce the treatment gap for severe mental illnesses (SMIs) and decrease the burden on caregivers. Apps developed in high income settings show effectiveness, but they suffer from lack of applicability in low resource scenarios due to the difference in technology penetration, affordability, and acceptance.

Objective: This study aimed to understand health technology usage, perceived needs, and acceptability of app based interventions in patients with SMIs to improve illness management and reduce caregiver burden.

Methods: The study was conducted in inpatient and outpatient settings of a tertiary care center in North India. A cross-sectional survey assessed smartphone and health app usage. Further, three focus group discussions evaluated the needs and apprehensions in using apps in management of SMIs.

Results: A total of 176 participants including 88 patients and 88 caregivers completed the survey. Smartphone ownership was similar to the national average (30%) in both caregivers (38.6%) and in patients (31.8%). Although subjects regularly used a third party app, health app usage was very low. Cost, unfamiliarity, and language were significant barriers to adoption. The focus group discussions provided insight into the various apprehensions of caregivers in using and in allowing patients to use smartphones and such apps. Caregivers wanted mobile apps for accessing information regarding services and resources available for people with SMI, and they felt such apps can be helpful if they could automate some of their routine caregiving activities. However, the significant difficulty was perceived in regards to the cost of the device, language of the medium, and unfamiliarity in using technology. Apprehensions that SMI patients might misuse technology, or damage the device were also prevalent.

Conclusions: The study systematically looks into the scope, design considerations and limitations of implementing a mobile technology based intervention for low resource settings. With only one-third of the patients and caregivers having access to smartphones and internet, parallel outreach strategies like IVRS should be actively considered while designing interventions. The difficulty of understanding and searching in a non-native language needs to be addressed. Hand holding of caregivers and frequent encouragement from treating doctors might significantly help in technology adoption and in surmounting the apprehensions related to using technology. To make the solution acceptable and useful to the already over-burdened caregivers, developers need to work closely with patients' family members and follow a ground-up collaborative approach to app development. The scope of delivering mental health services through technology is immense in resource constrained settings like India, provided we, researchers, appreciate and accept the fact that in the varied landscape of a divergent economic, educational, and cultural milieu, a single solution will never suffice for all, and intervention modality matching with end user capacity will be of paramount importance in determining the success of the endeavor.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0203353PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145572PMC
February 2019

{-[2-(Butyl-selan-yl)benz-yl]-,-di-methyl-ethane-1,2-di-amine}-dichlorido-mercury(II).

Acta Crystallogr E Crystallogr Commun 2018 Aug 27;74(Pt 8):1151-1154. Epub 2018 Jul 27.

Department of Chemistry, Howard University, 525 College Street NW, Washington, DC 20059, USA.

In the title compound, [HgCl(CHNSe)], the primary geometry around the Se and Hg atoms is distorted trigonal-pyramidal and distorted square-pyramidal, respectively. The distortion of the mol-ecular geometry in the complex is caused by the steric demands of the ligands attached to the Se atom. The Hg atom is coordinated through two chloride anions, an N atom and an Se atom, making up an unusual HgNSeCl coordination sphere with an additional long Hg⋯N inter-action. Inter-molecular C-H⋯Cl inter-actions are the only identified inter-molecular hydrogen-bonding inter-actions that seem to be responsible for the self assembly. These relatively weak C-H⋯Cl hydrogen bonds possess the required linearity and donor-acceptor distances. They act as mol-ecular associative forces that result in a supra-molecular assembly along the axis direction in the solid state of the title compound.
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http://dx.doi.org/10.1107/S2056989018010423DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072982PMC
August 2018

A Review on Venom Enzymes Neutralizing Ability of Secondary Metabolites from Medicinal Plants.

J Pharmacopuncture 2017 Sep 30;20(3):173-178. Epub 2017 Sep 30.

Department of Biological Science and Engineering, Maulana Azad National Institute of Technology, Bhopal, India.

Objectives: Medicinal plants are vital sources of bioactive compounds that are useful for the treatment of patients with snake bites or are indirectly applicable for boosting the effects of conventional serum therapy. These plants are being used traditionally by local healers and tribes for the treatment of patients with snake bites and therefore can be used as an alternative against snake envenomation. Scientifically, using the secondary metabolites of plants to neutralize venom enzymes has an extra benefit of being based on traditional knowledge; also, the use of such metabolites for the treatment of patients with snake bites is cheaper and the treatment can be started sooner.

Methods: All the available information on various secondary metabolites exhibiting venom neutralizing ability were collected via electronic search (using Google books, Pubmed, SciFinder, Scirus, Google Scholar, and Web of Science) and articles of peer-reviewed journals.

Results: Recent interest in different plant has focused on isolating and identifying of different phytoconstituents that exhibit Phospholipase A2 activity and other venom enzyme neutralizing ability. In this support convincing evidence in experimental animal models are available.

Conclusion: Secondary metabolites are naturally present, have no side effect, are stable for a long time, can be easily stored, and can neutralize a wide range of snake enzymes, such as phospholipase A2, hyaluronidase, protease, L-amino acid oxidase, 5'nucleotidase, etc. The current review presents a compilation of important plant secondary metabolites that are effective against snake venom due to enzyme neutralization.
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http://dx.doi.org/10.3831/KPI.2017.20.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633669PMC
September 2017

Survival outcomes post percutaneous coronary intervention: Why the hype about stent type? Lessons from a healthcare system in India.

PLoS One 2018 24;13(5):e0196830. Epub 2018 May 24.

Institute of Genomics and Integrative Biology, New Delhi, India.

A prospective, multicenter study was initiated by the Government of Maharashtra, India, to determine predictors of long-term outcomes of percutaneous coronary intervention (PCI) for coronary artery disease, and to compare the effectiveness of drug-eluting stents (DESs) and bare-metal stents (BMSs) in patients undergoing PCI under government-funded insurance. The present analysis included 4595 patients managed between August 2012 and November 2016 at any of 110 participating centers. Using the classical multivariable regression and propensity-matching approach, we found age to be the most important predictor of 1-year mortality and target lesion revascularization at 1 year post-PCI. However, using machine learning methods to account for unmeasured confounders and bias in this large observational study, we determined total stent length and number of stents deployed as the most important predictors of 1-year survival, followed by age and employment status. The unadjusted death rates were 5.0% and 3.8% for the BMS and DES groups, respectively (p = 0.185, log-rank test). The rate of re-hospitalization (p<0.001) and recurrence of unstable angina (p = 0.08) was significantly lower for DESs than for BMSs. Increased use of DES after 2015 (following establishment of a price cap on DESs) was associated with a sharp decrease in adjusted hazard ratios of DESs versus BMSs (from 0.94 in 2013 to 0.58 in 2016), suggesting that high price was limiting DES use in some high-risk patients. Since stented length and stent number were the most important predictors of survival outcomes, adopting an ischemia-guided revascularization strategy is expected to help improve outcomes and reduce procedural costs. In the elderly, PCI should be reserved for cases where the benefits outweigh the higher risk of the procedure. As unemployed patients had poorer long-term outcomes, we expect that implementation of a post-PCI cardiovascular rehabilitation program may improve long-term outcomes.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0196830PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5967815PMC
July 2018

A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals.

IEEE Trans Neural Syst Rehabil Eng 2018 05;26(5):925-935

This paper presents a signal modeling-based new methodology of automatic seizure detection in EEG signals. The proposed method consists of three stages. First, a multirate filterbank structure is proposed that is constructed using the basis vectors of discrete cosine transform. The proposed filterbank decomposes EEG signals into its respective brain rhythms: delta, theta, alpha, beta, and gamma. Second, these brain rhythms are statistically modeled with the class of self-similar Gaussian random processes, namely, fractional Brownian motion and fractional Gaussian noises. The statistics of these processes are modeled using a single parameter called the Hurst exponent. In the last stage, the value of Hurst exponent and autoregressive moving average parameters are used as features to design a binary support vector machine classifier to classify pre-ictal, inter-ictal (epileptic with seizure free interval), and ictal (seizure) EEG segments. The performance of the classifier is assessed via extensive analysis on two widely used data set and is observed to provide good accuracy on both the data set. Thus, this paper proposes a novel signal model for EEG data that best captures the attributes of these signals and hence, allows to boost the classification accuracy of seizure and seizure-free epochs.
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http://dx.doi.org/10.1109/TNSRE.2018.2818123DOI Listing
May 2018

Ancient genomes reveal a high diversity of Mycobacterium leprae in medieval Europe.

PLoS Pathog 2018 05 10;14(5):e1006997. Epub 2018 May 10.

Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.

Studying ancient DNA allows us to retrace the evolutionary history of human pathogens, such as Mycobacterium leprae, the main causative agent of leprosy. Leprosy is one of the oldest recorded and most stigmatizing diseases in human history. The disease was prevalent in Europe until the 16th century and is still endemic in many countries with over 200,000 new cases reported annually. Previous worldwide studies on modern and European medieval M. leprae genomes revealed that they cluster into several distinct branches of which two were present in medieval Northwestern Europe. In this study, we analyzed 10 new medieval M. leprae genomes including the so far oldest M. leprae genome from one of the earliest known cases of leprosy in the United Kingdom-a skeleton from the Great Chesterford cemetery with a calibrated age of 415-545 C.E. This dataset provides a genetic time transect of M. leprae diversity in Europe over the past 1500 years. We find M. leprae strains from four distinct branches to be present in the Early Medieval Period, and strains from three different branches were detected within a single cemetery from the High Medieval Period. Altogether these findings suggest a higher genetic diversity of M. leprae strains in medieval Europe at various time points than previously assumed. The resulting more complex picture of the past phylogeography of leprosy in Europe impacts current phylogeographical models of M. leprae dissemination. It suggests alternative models for the past spread of leprosy such as a wide spread prevalence of strains from different branches in Eurasia already in Antiquity or maybe even an origin in Western Eurasia. Furthermore, these results highlight how studying ancient M. leprae strains improves understanding the history of leprosy worldwide.
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http://dx.doi.org/10.1371/journal.ppat.1006997DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944922PMC
May 2018

Differential growth of Mycobacterium leprae strains (SNP genotypes) in armadillos.

Infect Genet Evol 2018 08 14;62:20-26. Epub 2018 Apr 14.

Health Resources and Services Administration (HRSA), National Hansen's Disease Program (NHDP), Baton Rouge, LA, USA. Electronic address:

Leprosy (Hansen's Disease) has occurred throughout human history, and persists today at a low prevalence in most populations. Caused by Mycobacterium leprae, the infection primarily involves the skin, mucosa and peripheral nerves. The susceptible host range for Mycobacterium leprae is quite narrow. Besides humans, nine banded armadillos (Dasypus novemcinctus) and red squirrels (Sciurus vulgaris) are the only other natural hosts for M. leprae, but only armadillos recapitulate the disease as seen in humans. Armadillos across the Southern United States harbor a single predominant genotypic strain (SNP Type-3I) of M. leprae, which is also implicated in the zoonotic transmission of leprosy. We investigated, whether the zoonotic strain (3I) has any notable growth advantages in armadillos over another genetically distant strain-type (SNP Type-4P) of M. leprae, and if M. leprae strains manifest any notably different pathology among armadillos. We co-infected armadillos (n = 6) with 2 × 10 highly viable M. leprae of both strains and assessed the relative growth and dissemination of each strain in the animals. We also analyzed 12 additional armadillos, 6 each individually infected with the same quantity of either strain. The infections were allowed to fulminate and the clinical manifestations of the disease were noted. Animals were humanely sacrificed at the terminal stage of infection and the number of bacilli per gram of liver, spleen and lymph node tissue were enumerated by Q-PCR assay. The growth of M. leprae strain 4P was significantly higher (P < 0.05) than 3I when each strain was propagated individually in armadillos. Significantly (P < 0.0001) higher growth of the 4P strain also was confirmed among animals co-infected with both 3I and 4P strain types using whole genome sequencing. Interestingly, the zoonotic strain does not exhibit any growth advantage in these non-human hosts, but the varied proliferation of the two M. leprae strains within armadillos suggest there are notable pathological variations between M. leprae strain-types.
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http://dx.doi.org/10.1016/j.meegid.2018.04.017DOI Listing
August 2018