ANTAGONISTIC POTENTIAL OF FLUORESCENT Pseudomonas AND ITS IMPACT ON GROWTH OF TOMATO CHALLENGED WITH PHTOPATHOGENS

This study focused on the antagonistic potential of fluorescent Pseudomonas in vitro, and its inoculation effect on growth performance of Lycopersicon esculentum in Fusarium oxysporum and Rhizoctonia solani infested soil. Biochemical characteristics of fluorescent Pseudomonas showed that all ten isolates were positive to catalase, amylase, gelatinase and siderophore production. While three isolates (Pf5, Pf6 and Pf9) were oxidase positive, nine isolates (Pf1, Pf2, Pf3, Pf4, Pf6, Pf7, Pf8, Pf9, and Pf10) were tolerant to 6.5% NaCl. Isolates Pf5 and Pf6 were resistant to all the test antibiotics; in contrast, the remaining eight isolates responded differently to different antibiotics. Isolates Pf5 and Pf6 were antagonistic against 14 bacterial species, and two pathogenic fungi (F. oxysporum and R. solani). Inoculation with fulorescent Pseudomonas Pf5 induced a significant increase in root and shoot length, and dry weight. Treatment of plants with either F. oxysporum or R. solani drastically reduced the root and shoot length and dry weight of the plant. However, in the presence of fluorescent Pseudomonas the adverse effect of the pathogens on growth of L. esculentum was alleviated.Cette \ue9tude a port\ue9 sur le potentiel antagonistique du Pseudomonas fluorescent, in vitro et les effets de son inoculation sur la performance en croissance du Lycopersicon esculentum dans le sol infest\ue9 par le Fusarium oxysporum et le Rhizoctonia solani . Les caract\ue9ristiques biochemiques du Pseudomonas fluorescent ont montr\ue9 que tous les dix isolats \ue9taient positives eu \ue9gard \ue0 la production de catalase, amylase, g\ue9latinase et sid\ue9rophore. Alors que trois isolats (Pf5, Pf6 and Pf9) \ue9taient oxidase positifs, neuf isolats (Pf1, Pf2, Pf3, Pf4, Pf6, Pf7, Pf8, Pf9, et Pf10) \ue9taient tolerant au 6.5% NaCl. Les isolats Pf5 et Pf6 \ue9taient r\ue9sistants \ue0 tous les test antibiotiques; au contraire, les huit isolats restants ont r\ue9pondu diff\ue9remment aux diff\ue9rents antibiotiques. Les isolats Pf5 et Pf6 \ue9taient antagonistiques contre 14 esp\ue8ces de bact\ue9ries, et deux champignons pathogeniques (F. oxysporum et R. solani). L\u2019inoculation avec Pseudomonas fulorescent Pf5 a induit une augmentation significative des raciness et de la longueur des tiges, ainsi que du poids sec. Le traitement de plants avec du F. oxysporum ou du R. solani ont radicalement r\ue9duit la longueur des raciness et tiges ainsi que le poids sec du plant. Cependant, en pr\ue9sence du Pseudomonas fluorescent, l\u2019effet adverse du pathog\ue8ne sur la croissance du L. esculentum \ue9tait allevi\ue9

Effect of a 2-week interruption in methotrexate treatment on COVID-19 vaccine response in people with immune-mediated inflammatory diseases (VROOM study): a randomised, open label, superiority trial

Background: Methotrexate is the first-line treatment for immune-mediated inflammatory diseases and reduces vaccine-induced immunity. We evaluated if a 2-week interruption of methotrexate treatment immediately after COVID-19 booster vaccination improved antibody response against the S1 receptor binding domain (S1-RBD) of the SARS-CoV-2 spike protein and live SARS-CoV-2 neutralisation compared with uninterrupted treatment in patients with immune-mediated inflammatory diseases. Method: We did a multicentre, open-label, parallel-group, randomised, superiority trial in secondary-care rheumatology and dermatology clinics in 26 hospitals in the UK. Adults (aged ≥18 years) with immune-mediated inflammatory diseases taking methotrexate (≤25 mg per week) for at least 3 months, who had received two primary vaccine doses from the UK COVID-19 vaccination programme were eligible. Participants were randomly assigned (1:1) using a centralised validated computer program, to temporarily suspend methotrexate treatment for 2 weeks immediately after COVID-19 booster vaccination or continue treatment as usual. The primary outcome was S1-RBD antibody titres 4 weeks after COVID-19 booster vaccination and was assessed masked to group assignment. All randomly assigned patients were included in primary and safety analyses. This trial is registered with ISRCTN, ISRCTN11442263; following a pre-planned interim analysis, recruitment was stopped early. Finding: Between Sept 30, 2021, and March 7, 2022, we screened 685 individuals, of whom 383 were randomly assigned: to either suspend methotrexate (n=191; mean age 58·8 years [SD 12·5], 118 [62%] women and 73 [38%] men) or to continue methotrexate (n=192; mean age 59·3 years [11·9], 117 [61%] women and 75 [39%] men). At 4 weeks, the geometric mean S1-RBD antibody titre was 25 413 U/mL (95% CI 22 227–29 056) in the suspend methotrexate group and 12 326 U/mL (10 538–14 418) in the continue methotrexate group with a geometric mean ratio (GMR) of 2·08 (95% CI 1·59–2·70; p<0·0001). No intervention-related serious adverse events occurred. Interpretation: 2-week interruption of methotrexate treatment in people with immune-mediated inflammatory diseases enhanced antibody responses after COVID-19 booster vaccination that were sustained at 12 weeks and 26 weeks. There was a temporary increase in inflammatory disease flares, mostly self-managed. The choice to suspend methotrexate should be individualised based on disease status and vulnerability to severe outcomes from COVID-19. Funding: National Institute for Health and Care Research

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation

Open data from the third observing run of LIGO, Virgo, KAGRA, and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of binary black hole coalescences confidently observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include the effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that have already been identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total source-frame mass M > 70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz emitted gravitational-wave frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place a conservative upper limit for the merger rate density of high-mass binaries with eccentricities 0 < e ≤ 0.3 at 16.9 Gpc−3 yr−1 at the 90% confidence level

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

Identification of potential biomarkers of head and neck squamous cell carcinoma using iTRAQ based quantitative proteomic approach

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers in India. Despite improvements in treatment strategy, the survival rates of HNSCC patients remain poor. Thus, it is necessary to identify biomarkers that can be used for early detection of disease. In this study, we employed iTRAQ-based quantitative mass spectrometry analysis to identify dysregulated proteins from a panel of head and neck squamous cell carcinoma (HNSCC) cell lines. We identified 2468 proteins, of which 496 proteins were found to be dysregulated in at least two out of three HNSCC cell lines compared to immortalized normal oral keratinocytes. We detected increased expression of replication protein A1 (RPA1) and heat shock protein family H (Hsp110) member 1 (HSPH1), in HNSCC cell lines compared to control. The differentially expressed proteins were further validated using parallel reaction monitoring (PRM) and western blot analysis in HNSCC cell lines. Immunohistochemistry-based validation using HNSCC tissue microarrays revealed overexpression of RPA1 and HSPH1 in 15.7% and 32.2% of the tested cases, respectively. Our study illustrates quantitative proteomics as a robust approach for identification of potential HNSCC biomarkers. The proteomic data has been submitted to ProteomeXchange Consortium (http://www.proteomecentral.proteomexchange.org) via the PRIDE public data repository accessible using the data identifier - PXD009241. Keywords: HNSCC, iTRAQ, Parallel reaction monitoring, Mass spectrometry, OKF6/TERT