Comparative analysis of the lambda-interferons IL-28A and IL-29 regarding their transcriptome and their antiviral properties against hepatitis C virus.

Specific differences in signaling and antiviral properties between the different Lambda-interferons, a novel group of interferons composed of IL-28A, IL-28B and IL-29, are currently unknown. This is the first study comparatively investigating the transcriptome and the antiviral properties of the Lambda-interferons IL-28A and IL-29. Expression studies were performed by microarray analysis, quantitative PCR (qPCR), reporter gene assays and immunoluminometric assays. Signaling was analyzed by Western blot. HCV replication was measured in Huh-7 cells expressing subgenomic HCV replicon. All hepatic cell lines investigated as well as primary hepatocytes expressed both IFN-λ receptor subunits IL-10R2 and IFN-λR1. Both, IL-28A and IL-29 activated STAT1 signaling. As revealed by microarray analysis, similar genes were induced by both cytokines in Huh-7 cells (IL-28A: 117 genes; IL-29: 111 genes), many of them playing a role in antiviral immunity. However, only IL-28A was able to significantly down-regulate gene expression (n = 272 down-regulated genes). Both cytokines significantly decreased HCV replication in Huh-7 cells. In comparison to liver biopsies of patients with non-viral liver disease, liver biopsies of patients with HCV showed significantly increased mRNA expression of IL-28A and IL-29. Moreover, IL-28A serum protein levels were elevated in HCV patients. In a murine model of viral hepatitis, IL-28 expression was significantly increased. IL-28A and IL-29 are up-regulated in HCV patients and are similarly effective in inducing antiviral genes and inhibiting HCV replication. In contrast to IL-29, IL-28A is a potent gene repressor. Both IFN-λs may have therapeutic potential in the treatment of chronic HCV

The Extent of Genome Flux and Its Role in the Differentiation of Bacterial Lineages

Horizontal gene transfer (HGT) and gene loss are key processes in bacterial evolution. However, the role of gene gain and loss in the emergence and maintenance of ecologically differentiated bacterial populations remains an open question. Here, we use whole-genome sequence data to quantify gene gain and loss for 27 lineages of the plant-associated bacterium Pseudomonas syringae. We apply an extensive error-control procedure that accounts for errors in draft genome data and greatly improves the accuracy of patterns of gene occurrence among these genomes. We demonstrate a history of extensive genome fluctuation for this species and show that individual lineages could have acquired thousands of genes in the same period in which a 1% amino acid divergence accrues in the core genome. Elucidating the dynamics of genome fluctuation reveals the rapid turnover of gained genes, such that the majority of recently gained genes are quickly lost. Despite high observed rates of fluctuation, a phylogeny inferred from patterns of gene occurrence is similar to a phylogeny based on amino acid replacements within the core genome. Furthermore, the core genome phylogeny suggests that P. syringae should be considered a number of distinct species, with levels of divergence at least equivalent to those between recognized bacterial species. Gained genes are transferred from a variety of sources, reflecting the depth and diversity of the potential gene pool available via HGT. Overall, our results provide further insights into the evolutionary dynamics of genome fluctuation and implicate HGT as a major factor contributing to the diversification of P. syringae lineages

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

Flexible Architecture for Testing Connected Vehicles in Realistic Traffic

Connected vehicles have the potential to transform the way we commute and travel in a multitude of ways. Vehicles will cooperate and coordinate with each other to solve problems appropriate for the environment in which they are operating. In this paper, we focus on the development of test equipment that includes the infrastructure and vehicles to measure and record all of the information necessary to quantify the performance of cooperative driving algorithms in realistic scenarios. The system allows tests to include real vehicles on the track and virtual vehicles in a digital twin. Real and virtual vehicles interact through the road-side units and test facility network, allowing each test vehicle to receive messages from virtual vehicles as well as the infrastructure. Messages transmitted from the test vehicles are received in the digital twin, allowing the real vehicle to interact with virtual vehicles. This provides the capability to test algorithms in congested traffic without the expense and risk of conducting tests with many cars. The system is shown to allow for real-time operation of connected vehicles in closed loop operation using industry standard networks, along with a protocol for centralized traffic management, which is not currently standardized. Tests have been performed at highway speeds. The architecture has a low barrier to entry application programming interface for its vehicle to infrastructure network that utilizes the Robotic Operating System interface. The paper describes the development and integration of components and protocols, characterization of the network performance, methods for recording data referenced to a single clock, and demonstration of the repeatability of measurements made on test vehicles. The discussion at the end of the paper looks at current research on the impact of cooperative driving algorithms on energy efficiency and traffic flow

Genomic analysis and in vivo efficacy of Pediococcus acidilactici as a potential probiotic to prevent hyperglycemia, hypercholesterolemia and gastrointestinal infections

Abstract Lactic acid bacteria are the well acknowledged probiotics that can cure a variety of diseases. In this study, we observed the in vivo potentials of Pediococcus to treat hyperglycemia, hypercholesterolemia and gastrointestinal infections. A total of 77 Lactobacillus were isolated from the milk of 10 cows and 10 goats, four of those strains inhibited both carbohydrates-hydrolyzing enzymes, α-glucosidase, and α-amylase. They all showed antagonistic effects on pathogenic E. coli and S. Typhimurium which were confirmed by performing pathogen challenge test and visualizing on Electron microscopy. 16S rRNA gene sequence identified that all four strains belong to Pediococcus genus which were further distinguished as Pediococcus acidilactici by pheS gene sequence. Whole genome sequence analysis revealed their non-pathogenic properties for human and the presence of probiotic genes responsible for stress resistance, immunomodulation, adhesion, metal and drug resistance. In vivo trial with diabetes-induced mice ascertained that all Pediococcus acidilactici had significant potentials to reduce elevated glucose and low-density lipoprotein level in blood. Interestingly, two out of four strains were significantly more effective (p < 0.0001 each) than metformin in reducing the blood glucose level. This in vivo study demonstrated that Pediococcus acidilactici might be a promising probiotic to prevent hyperglycemia, hypercholesterolemia and gastrointestinal infections