Genetic plasticity of the Shigella virulence plasmid is mediated by intra- and inter-molecular events between insertion sequences

Acquisition of a single copy, large virulence plasmid, pINV, led to the emergence of Shigella spp. from Escherichia coli. The plasmid encodes a Type III secretion system (T3SS) on a 30kb pathogenicity island (PAI), and is maintained in a bacterial population through a series of toxin:antitoxin (TA) systems which mediate post-segrega tional killing (PSK). The T3SS imposes a significant cost on the bacterium, and strains which have lost the plasmid and/or genes encoding the T3SS grow faster than wild-type strains in the laboratory, and fail to bind the indicator dye Congo Red (CR). Our aim was to define the molecular events in Shigella flexneri that cause loss of Type III secretion (T3S), and to examine whether TA systems exert positional effects on pINV. During growth at 37°C, we found that deletions of regions of the plasmid including the PAI lead to the emergence of CR-negative colonies; deletions occur through intra-molecula r recombination events between insertion sequences (ISs) flanking the PAI. Furthermore, by repositioning MvpAT (which belongs to the VapBC family of TA systems) near the PAI, we demonstrate that the location of this TA system alters the rearrangements that lead to loss of T3S, indicating that MvpAT acts both globally (by reducing loss of pINV through PSK) as well as locally (by preventing loss of adjacent sequences). During growth at environmental temperatures, we show for the first time that pINV spontaneously integrates into different sites in the chromosome, and this is mediated by inter-molecular events involving IS 1294. Integration leads to reduced PAI gene expression and impaired secretion through the T3SS, while excision of pINV from the chromosome restores T3SS function. Therefore, pINV integration provides a reversible mechanism for Shigella to circumvent the metabolic burden imposed by pINV. Intra- and inter-molecular events between ISs, which are abundant in Shigella spp., mediate plasticity of S. flexneri pINV

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global burden of 87 risk factors in 204 countries and territories, 1990�2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk�outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk�outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk�outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51�12·1) deaths (19·2% 16·9�21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12�9·31) deaths (15·4% 14·6�16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253�350) DALYs (11·6% 10·3�13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0�9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10�24 years, alcohol use for those aged 25�49 years, and high systolic blood pressure for those aged 50�74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

The ability of two different Vibrio spp. bacteriophages to infect Vibrio harveyi, Vibrio cholerae and Vibrio mimicus

Aims: To determine the host range of the Vibrio harveyi myovirus-like bacteriophage (VHML) and the cholera toxin conversion bacteriophage (CTX Φ) within a range of Vibrio cholerae and V. mimicus and V. harveyi, V. cholerae and V. mimicus isolates respectively.\ud \ud Methods and Results: Three V. harveyi, eight V. cholerae and five V. mimicus isolates were incubated with VHML and CTX Φ. Polymerase chain reaction (PCR) was used to determine the presence of VHML and CTX Φ in infected isolates. We demonstrated that it was possible to infect one isolate of V. cholerae (isolate ACM #2773/ATCC #14035) with VHML. This isolate successfully incorporated VHML into its genome as evident by positive PCR amplification of the sequence coding part of the tail sheath of VHML. Attempts to infect all other V. cholerae and V. mimicus isolates with VHML were unsuccessful. Attempts to infect V. cholerae non-01, V. harveyi andV. mimicus isolates with CTX Φ were unsuccessful.\ud \ud Conclusions: Bacteriophage infection is limited by bacteriophage-exclusion systems operating within bacterial strains and these systems appear to be highly selective. One system may allow the co-existence of one bacteriophage while excluding another. VHML appears to have a narrow host range which may be related to a common receptor protein in such strains. The lack of the vibrio pathogenicity island bacteriophage (VPI Φ) in the isolates used in this study may explain why infections with CTX Φ were unsuccessful.\ud \ud Significance and Impact of the Study: The current study has demonstrated that Vibrio spp. bacteriophages may infect other Vibrio spp.\u

Relationship of microalbuminuria with different clinical and biochemical parameters in newly detected diabetes mellitus cases

This study was conducted to assess the presence of microalbuminuria in newly detected diabetes mellitus (DM) cases in a small group of Bangladeshi population attending BIRDEM out patient department and to find out the relationship (if any) of microalbuminuria with different clinical and biochemical parameters. Out of 110 DM cases, 10 (9.1%) were found to have microalbuminuria. Blood pressure, both systolic (r=0.190) and diastolic (r = 0.30) had significant positive correlation with urinary albumin. There was no association of microalbuminuria with waist circumference, waist to hip ratio, serum triglycerides, HDL cholesterol, fasting blood glucose, age, sex, weight, height or BMI. This suggests that all newly detected diabetes mellitus should be screened for raised blood pressure and if found positive be given the same importance as blood glucose. They should be treated meticulously to revert or prevent microalbuminuria and thus prevent complications. Ibrahim Med. Coll. J. 2010; 4(1): 21-2

A comparative analysis to forecast carbon dioxide emissions

Despite the growing knowledge and commitment to climate change, carbon dioxide (CO2) emissions continue to rise dramatically throughout the planet. In recent years, the consequences of climate change have become more catastrophic and have attracted widespread attention globally. CO2 emissions from the energy industry have lately been highlighted as one of the world's most pressing concerns for all countries. This paper examines the relationships between CO2 emissions, electrical energy consumption, and gross domestic product (GDP) in Bangladesh from 1972 to 2019 in the first section. In this purpose, we applied the fully modified ordinary least squares (FMOLS) approach. The findings indicate that CO2 emissions, electrical energy consumption, and GDP have a statistically significant long-term cointegrating relationship. Developing an accurate CO2 emissions forecasting model is crucial for tackling it safely. This leads to the second step, which involves formulating the multivariate time series CO2 emissions forecasting challenges considering its influential factors. Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN-LSTM), long short-term memory (LSTM), and dense neural network (DNN). The root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) are used to analyze and compare the performances of the predictive models. The prediction errors in MAPE of the CNN, CNN-LSTM, LSTM, and DNN are 15.043, 5.065, 5.377, and 3.678, respectively. After evaluating those deep learning models, a multivariate polynomial regression has also been employed to forecast CO2 emissions. It seems to have nearly similar accuracy as the LSTM model, having a MAPE of 5.541. 2022 The AuthorsThe publication of this article was funded by Qatar National Library .Scopu

Factors associated with moderate wasting among marginalized 6 to 23-month aged children in Bangladesh: Findings of the Suchana program baseline survey data

Suchana—a large-scale, 7-year nutrition program that started in 2015—is being implemented in 250,000 households in the marginalized segment in north-east Bangladesh, with the aim of improving childhood nutrition status. Untreated childhood moderate wasting may develop to severe wasting, which is associated with a 10-fold higher risk of mortality compared to children of normal weight relative to height/length. Identifying the diverse, age-specific risk factors for moderate wasting may help such programs to formulate tailored interventions to prevent and treat childhood malnutrition in rural communities. The objective of this study was to identify the age-specific factors associated with moderate wasting among 6–23-month-old children in beneficiary households. Cross-sectional data on 4,400 children was collected through systematic sampling between November 2016 and February 2017 using the Suchana beneficiary list. In total, 8.1% of 6–11 month-olds and 10.3% of 12– 23 month-olds suffered moderate wasting; 12–23-month-olds had a 1.3-fold higher risk of moderate wasting than 6–11-month-olds. Our results of logistic regression models suggest that larger household size, higher maternal body mass index (BMI), and maternal food consumption status more than usual during the recent pregnancy were associated with a reduced risk of moderate wasting among 6–11-month-olds. Higher maternal BMI, normal maternal food consumption status during last pregnancy, being female and maternal knowledge on diarrheal management, were associated with a reduced risk of moderate wasting among 12–23-month-olds. In conclusion, beyond maternal BMI and maternal food consumption status during the last pregnancy, the factors associated with moderate wasting among 6–23-month-olds in the poorest households in Bangladesh are age-specific