20 research outputs found
An Extracted Fraction of Pseudomonas Oleovorans Can Inhibit Viral Entry and RNA Replication of Hepatitis C Virus in Cell Culture
The emergence and distribution of Hepatitis C virus (HCV) infection is still considered as an unsolved problem. Due
to side effects, many synthetic drugs have been avoided and replaced by new biologically derived ones. Aim of this study
was to use Pseudomonas oleovorans’ extract as HCV viral replication inhibition agent in cell culture system. Several factors were studied and the optimum growth conditions were selected for maximum production of antiviral substance.
Pseudomonas oleovorans’ extract was fractionated using different concentrations of chloroform: methanol on silica gel
columns. Analysis of potent fraction by GC/MS showed of tetradecanoic and hexadecanoic acid methyl esters. The selected fraction was tested against HCV in vitro using two different protocols: viral attachment entry inhibition (Pre-incubation) and viral replication inhibition (Post infection). 0.1 µg / ml of the selected antiviral fraction resulted in inhibition
of viral replication in Huh 7.5 cells. However, higher concentration of 100 µg / ml did not cause any viral inhibition. The
selected bacterial fraction containing tetradecanoic acid and hexadecanoic acid methyl esters could be used as a promising candidate to inhibit viral HCV entry and replication of HCV
Core Microbial Functional Activities in Ocean Environments Revealed by Global Metagenomic Profiling Analyses
Metagenomics-based functional profiling analysis is an effective means of gaining deeper insight into the composition of marine microbial populations and developing a better understanding of the interplay between the functional genome content of microbial communities and abiotic factors. Here we present a comprehensive analysis of 24 datasets covering surface and depth-related environments at 11 sites around the world's oceans. The complete datasets comprises approximately 12 million sequences, totaling 5,358 Mb. Based on profiling patterns of Clusters of Orthologous Groups (COGs) of proteins, a core set of reference photic and aphotic depth-related COGs, and a collection of COGs that are associated with extreme oxygen limitation were defined. Their inferred functions were utilized as indicators to characterize the distribution of light- and oxygen-related biological activities in marine environments. The results reveal that, while light level in the water column is a major determinant of phenotypic adaptation in marine microorganisms, oxygen concentration in the aphotic zone has a significant impact only in extremely hypoxic waters. Phylogenetic profiling of the reference photic/aphotic gene sets revealed a greater variety of source organisms in the aphotic zone, although the majority of individual photic and aphotic depth-related COGs are assigned to the same taxa across the different sites. This increase in phylogenetic and functional diversity of the core aphotic related COGs most probably reflects selection for the utilization of a broad range of alternate energy sources in the absence of light.This work was supported by King Abdullah University for Science and Technology Global Collaborative Partners (GCR) program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed
Comparison of Safety and Efficacy of Al-Hijama (Cupping) and Conventional Medical Therapy for Sinusitis (I)
Systematic Review on the Efficacy, Effectiveness, Safety, and Immunogenicity of Monkeypox Vaccine
Background: The variation in the reported vaccine safety and effectiveness could contribute to the high rates of vaccine hesitancy among the general population and healthcare workers in areas where monkeypox (mpox) is circulating. In this review, our objective was to evaluate the safety, immunogenicity, effectiveness, and efficacy of the mpox vaccines. Methods: An extensive search for articles across multiple databases was performed, including searching six databases (PubMed Central, PubMed Medline, Scopus, Web of Science, Cochrane, ProQuest), two pre-print databases (European PMC Preprint and MedRxiv), and Google Scholar. Results: A total of 4290 citations were retrieved from the included databases. Following the removal of duplicates and the initial screening of records, a total of 36 studies were included into the analysis. Additionally, we identified five more studies through manual searches, resulting in a total of 41 eligible articles for qualitative synthesis. The study findings revealed that mpox vaccines demonstrate the ability to generate adequate antibodies; however, their effectiveness may decrease over time, exhibiting varying safety profiles. Most of the included studies consistently reported substantial levels of effectiveness and efficacy against mpox. Interestingly, the number of vaccine doses administered was found to influence the degree of immunogenicity, subsequently impacting the overall effectiveness and efficacy of the vaccines. Furthermore, we found that smallpox vaccines exhibited a form of cross-protection against mpox. Conclusions: Vaccines can be used to prevent mpox and effectively control its spread
Abundance ratios of photic to aphotic related COGs.
<p>(<b>A</b>) Mean abundance ratios of photic to aphotic related COGs for datasets from the reference water columns, the Iquique water column, and from single-depth datasets. This analysis was initially determined using the 82-COG global-core, depth-related reference set, as described in Materials and Methods. Applying the ratios for the photic and aphotic datasets from the reference water columns, ratio ranges (mean±two SD) were established to indicate photic or aphotic functional genomic content enrichment. Mean abundance ratios for the Iquique water column and the single-depth datasets were calculated to verify their balance between photic and aphotic related biological functions. The arrows at the top of the diagram indicate the approximate depth of the boundary between photic and aphotic zones in each water column (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097338#pone-0097338-g001" target="_blank">fig. 1B</a>). (<b>B</b>) Normalized abundance of the deoxyribodipyrimidine photolyase gene (COG0415; <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097338#pone.0097338.s004" target="_blank">table S4A in file S1</a>) in the 24 datasets obtained from the indicated depths. The average normalized abundance was calculated for the photic and for the aphotic groups of datasets. The bars represent two SD of the mean.</p
Clustering of the 176 depth-related COGs.
<p>(<b>A</b>) Hierarchical clustering of the 176 depth-related COGs in the 24 datasets. Clustering analysis is based on the normalized abundance profile of the 176 depth-related COGs that were shared by the three reference water columns (ATII, ALOHA and BATS) and significantly differed in abundance within at least one of them (details in Materials and Methods). The height indicates the relative distance between datasets. Bootstrap confidence values above 60 for the nodes are shown. The heatmap is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097338#pone.0097338.s003" target="_blank">fig. S3A</a>. (<b>B</b>) Location of the boundary between the photic and aphotic zones in each of the four water columns. The arrows indicate the depth at which PAR reaches 1% of the level at the surface. (<b>C</b>) Hierarchical clustering of the photic/aphotic global-core depth-related COGs. 82 COGs that showed statistically significant difference (Welch's test, FDR-corrected, p≤1E-04) in their normalized abundance between the photic and the aphotic groups of datasets were selected to establish a photic/aphotic global-core, depth-related reference set. 54 COGs had significantly higher abundance in the photic datasets (Group I, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097338#pone.0097338.s004" target="_blank">table S4A in file S1</a>); contrary to the remaining 28 aphotic related COGs (Group II, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097338#pone.0097338.s004" target="_blank">table S4B in file S1</a>). Bootstrap confidence values for the major nodes are shown. Heatmap coloring reflects the Z score of normalized abundances of each COG across all clustered datasets (details in Materials and Methods).</p