Influence of chemical oxidant on degradation of benzo[a]pyrene metabolites by the bacterium-Zoogloea sp.

It is neither comprehensive nor appropriate that the bioremediation of a benzo[a]pyrene (BaP)-contaminated environment be assessed only by its high degradation extent because its metabolites\u27 chemical structures are similar to the parent compound and maybe equally toxic. Therefore, further degradation of BaP metabolites is significant. Three methods, combining the Zoogloea sp. with potassium permanganate, combining the Zoogloea sp. with H2O2, Zoogloea sp. alone, were investigated to degrade cis-BP4,5-dihydrodiol and cis-BP7,8-dihydrodiol, which are the metabolites of BaP formed by bacterium-Zoogloea sp. Optimum parameters of degradation in the best method are that: of the three methods, coupling the Zoogloea sp. and KMnO4 is the best; compared with cis-BP7,8-dihydrodiol, cis-BP4,5-dihydrodiol is the more liable to be accumulated in pure cultures; the degradation effect of the two metabolites is optimal when the initial concentration of KMnO4 in the cultures is 0.05%; initial concentration of cis-BP4,5-dihydrodiol and cis-BP7,8-dihydrodiol is 4 mg L&minus;1, 8 mg L&minus;1, respectively; cometabolic substance is salicylic acid or sodium succinate. The degradation extent of cis-BP4,5-dihydrodiol and cis-BP7,8-dihydrodiol using combining the Zoogloea sp. and KMnO4 reach 76.1% and 85.9% after 12 days of cultivation, respectively, which were more than twice compared with conventional method.<br /

Network Analysis of RAD51 Proteins in Metazoa and the Evolutionary Relationships With Their Archaeal Homologs

The RAD51 (DNA repair protein RAD51) recombinases are essential for homologous recombination, DNA repair, and genome stability. Overexpression of RAD51 proteins has been observed in many cancer cells, such as thyroid carcinoma, breast cancer, pancreatic cancer, and others. In Metazoa, there are multiple members of RAD51 (RAD51, RAD51B, RAD51C, RAD51D, DMC1) (DNA meiotic recombinase 1), XRCC2 (X-ray repair cross-complementing 2), and XRCC3. In this study, we used a protein sequence similarity network (SSN) to analyze the evolutionary relationship within this protein family. The SSN based on the RAD51 proteins from Metazoa indicated that there are several proteins that have yet to be functionally defined. The SSN based on the distribution of the proteins supports the hypothesis that horizontal gene transfer plays an important role in the evolution of RAD51 proteins. Multiple sequence alignments with structural information revealed that the amino acid residues for ATP and Mg2+ are highly conserved. The seven RAD51 proteins in humans are under different selective pressure: RAD51 and DMC1 are under stringent negative selection, while other proteins are subject to relatively relaxed negative selection. Furthermore, the expression levels of the seven genes in different tissues showed that the genes in the same cluster in the phylogenetic tree showed similar expression profiles. Finally, the SSN based on the RAD51 proteins from both eukaryotes and prokaryotes suggested that the eukaryotic RAD51 recombinases share a common ancestor with the archaeal homologs, but XRCC2 may have a different origin. These findings expand the understanding of the evolution and diversity of RAD51 recombinases in Metazoa

Multiscale modelling and experimental analysis of ultrasonic-assisted drilling of GLARE fibre metal laminates

This study aims to evaluate the effectiveness of Ultrasonic-assisted drilling (UAD) of Glass laminate aluminium reinforced epoxy (GLARE) at high cutting speeds (Spindle speeds: 3000–7500 rpm; feed rates 300–750 mm/min) by analysing the thrust force and hole quality metrics (surface roughness, hole size, and burr formations. The research also presents numerical modelling of FMLs under conventional and UAD regimes to predict thrust force using ABAQUS/SIMULIA. The thrust force and exit burrs were reduced by up to 40.83 % and 80 %, respectively. The surface roughness metrics (Ra and Rz) were slightly higher using UAD but remained within the desirable limits of surface roughness for machined aeronautical structures. The discrepancy between the simulation and experimental results was adequate and did not exceed 15 %. The current study shows that it is feasible to drill holes in GLARE using higher cutting parameters and maintain excellent hole quality, which means increased productivity and reduced costs

A Multi-objective Optimization Algorithm of Task Scheduling in WSN

Sensing tasks should be allocated and processed among sensor nodes in minimum times so that users can draw useful conclusions through analyzing sensed data. Furthermore, finishing sensing task faster will benefit energy saving. The above needs form a contrast to the lower efficiency of task-performing caused by the  ailureprone sensor. To solve this problem, a multi-objective optimization algorithm of task scheduling is proposed for wireless sensor networks (MTWSN). This algorithm tries its best to make less makespan, but meanwhile, it also pay much more attention to the probability of task-performing and the lifetime of network. MTWSN avoids the task assigned to the failure-prone sensor, which effectively reducing the effect of failed nodes on task-performing. Simulation results show that the proposed algorithm can trade off these three objectives well. Compared with the traditional task scheduling algorithms, simulation experiments obtain better results

Analysis of the characteristics of intestinal microbiota after oral tolerance in infants with food protein–induced proctocolitis

ObjectiveTo understand the characteristics of the intestinal microbiota after oral tolerance in infants with food protein–induced proctocolitis (FPIAP) treated with amino acid formula and their differences from healthy children, aiming to provide a scientific basis for guiding the application of probiotics during treatment.MethodsFPIAP infants were prospectively enrolled, fecal specimens were obtained, and DNA was extracted for PCR amplification of the bacterial 16S rRNA gene V4 region. Library construction and sequencing were performed, and bioinformatic analysis was performed after obtaining valid data.ResultsThere were 36 patients in the FPIAP group: 20 males and 16 females, age 21.944 ± 13.277 months. Diarrhea with blood in the stool were the main symptom, with an average course of 14.83 ± 9.33 days. Thirty infants (83.33%) had mucus stool, 11.11% (4/36) of them experiencing vomiting, and 55.56% (20/36) of the infants displaying poor intake and weight gain, 28 (77.78%) patients with moderate eczema, 2 (5.6%) patients with chronic respiratory symptoms. The treatment time with amino acid formula was 5.51 ± 2.88 months. A control group comprising of 25 healthy infants who were full-term, natural delivery, bottle fed, and matched in terms of age (24.840 ± 12.680 months) and gender (15 males and 10 females) was selected. Anaerobic bacteria were less abundant in FPIAP infants than healthy infants (P = 4.811 × 10−5), but potentially pathogenic bacteria were more abundant (P = 0.000). The abundance of Actinobacteria was low in FPIAP infants, the abundance of Proteobacteria was high, and the abundance of Firmicutes was reduced. Bifidobacterium could be used as a bacterial genus to differentiate healthy and FPIAP infants. Both α-and β-diversity indicators of intestinal microbiota were lower in FPIAP infants. In FPIAP infants, glucose and energy metabolism and amino acid anabolism were decreased, and inflammation-related lipopolysaccharide synthesis pathways were increased.ConclusionCompared with healthy infants, FPIAP infants with oral tolerance after amino acid formula treatment had differences in the structure and diversity of intestinal microbiota, among which Bifidobacterium was significantly reduced. Trial RegistrationThis trial was registered on https://register.clinicaltrials.gov/

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, an