Simultaneous two-color imaging in digital holographic microscopy

We demonstrate the use of two-color digital holographic microscopy (DHM) for imaging microbiological subjects. The use of two wavelengths significantly reduces artifacts present in the reconstructed data, allowing us to image weakly scattering objects in close proximity to strongly-scattering objects. We demonstrate this by reconstructing the shape of the flagellum of a single-cell eukaryotic parasite Leishmania mexicana in close proximity to a more strongly-scattering cell body. Our approach also yields a reduction of approximately one third in the axial position uncertainty when tracking the motion of swimming cells at low magnification, which we demonstrate with a sample of Escherichia coli bacteria mixed with polystyrene beads. The two-wavelength system that we describe introduces minimal additional complexity into the optical system, and provides significant benefits

RSAT™ process development for post-combustion CO2 capture: Scale-up from laboratory and pilot test data to commercial process design

AbstractIt is believed that a RSAT™ (Regenerable Solvent Absorption Technology) process is the most viable nearterm technology for post-combustion CO2 capture from power plant flue gas. The Babcock & Wilcox Power Generation Group, Inc. (B&W) has deployed a suite of research tools to evaluate and develop the CO2 scrubbing technology, including laboratory, pilot-scale, and simulation modeling capabilities. Since the construction and operation of test facilities require significant resources, it is essential to effectively utilize these research tools by choosing a scale-up approach which provides robust design data for a commercial process while minimizing the amount of experimentation required.The scale-up protocol used for RSAT CO2 scrubbing processes was rigorously developed using rate-based modeling concurrent with acquiring fundamental laboratory and pilot plant data for process validation. These development activities were not conducted in series but rather overlapped to yield an optimized commercial CO2 scrubbing process in a reasonable time frame with a high degree of design confidence [1,2].This paper presents the scale-up protocol used in evaluating the RSAT process which encompasses both laboratory and pilot-scale testing as well as rate-based modeling to achieve a commercial-scale RSAT process design. This document demonstrates the qualification of test data from a packed tower scale-up point of view. Solvent screening research activities recently conducted within B&W successfully demonstrate the scale-up protocol used for RSAT process development. The time and cost of process development can be significantly reduced through rigorous rate-based modeling in conjunction with laboratory experiments and pilot plant validation

Spatial arrangement of several flagellins within bacterial flagella improves motility in different environments

Bacterial flagella are helical proteinaceous fibers, composed of the protein flagellin, that confer motility to many bacterial species. The genomes of about half of all flagellated species include more than one flagellin gene, for reasons mostly unknown. Here we show that two flagellins (FlaA and FlaB) are spatially arranged in the polar flagellum of Shewanella putrefaciens, with FlaA being more abundant close to the motor and FlaB in the remainder of the flagellar filament. Observations of swimming trajectories and numerical simulations demonstrate that this segmentation improves motility in a range of environmental conditions, compared to mutants with single-flagellin filaments. In particular, it facilitates screw-like motility, which enhances cellular spreading through obstructed environments. Similar mechanisms may apply to other bacterial species and may explain the maintenance of multiple flagellins to form the flagellar filament

DAS181 treatment of severe lower respiratory tract parainfluenza virus infection in immunocompromised patients: A phase 2 randomized, placebo-controlled study

BACKGROUND: There are no antiviral therapies for parainfluenza virus (PIV) infections. DAS181, a sialidase fusion protein, has demonstrated activity in in vitro and in animal models of PIV. METHODS: Adult immunocompromised patients diagnosed with PIV lower respiratory tract infection (LRTI) who required oxygen supplementation were randomized 2:1 to nebulized DAS181 (4.5 mg/day) or matching placebo for up to 10 days. Randomization was stratified by need for mechanical ventilation (MV) or supplemental oxygen (SO). The primary endpoint was the proportion of patients reaching clinical stability survival (CSS) defined as returning to room air (RTRA), normalization of vital signs for at least 24 hours, and survival up to day 45 from enrollment. RESULTS: A total of 111 patients were randomized to DAS181 (n = 74) or placebo (n = 37). CSS was achieved by 45.0% DAS181-treated patients in the SO stratum compared with 31.0% for placebo (P = .15), whereas patients on MV had no benefit from DAS181. The proportion of patients achieving RTRA was numerically higher for SO stratum DAS181 patients (51.7%) compared with placebo (34.5%) at day 28 (P = .17). In a post hoc analysis of solid organ transplant, hematopoietic cell transplantation within 1 year, or chemotherapy within 1 year, more SO stratum patients achieved RTRA on DAS181 (51.8%) compared with placebo (15.8%) by day 28 (P = .012). CONCLUSIONS: The primary endpoint was not met, but post hoc analysis of the RTRA component suggests DAS181 may have clinical activity in improving oxygenation in select severely immunocompromised patients with PIV LRTI who are not on mechanical ventilation. Clinical Trials Registration. NCT01644877

Advanced Hydrogen Transport Membranes for Vision 21 Fossil Fuel Plants

Seeks to economically eliminate the environmental concerns associated with the use of fossil fuels

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

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

Circulating microRNAs in sera correlate with soluble biomarkers of immune activation but do not predict mortality in ART treated individuals with HIV-1 infection: A case control study

Introduction: The use of anti-retroviral therapy (ART) has dramatically reduced HIV-1 associated morbidity and mortality. However, HIV-1 infected individuals have increased rates of morbidity and mortality compared to the non-HIV-1 infected population and this appears to be related to end-organ diseases collectively referred to as Serious Non-AIDS Events (SNAEs). Circulating miRNAs are reported as promising biomarkers for a number of human disease conditions including those that constitute SNAEs. Our study sought to investigate the potential of selected miRNAs in predicting mortality in HIV-1 infected ART treated individuals. Materials and Methods: A set of miRNAs was chosen based on published associations with human disease conditions that constitute SNAEs. This case: control study compared 126 cases (individuals who died whilst on therapy), and 247 matched controls (individuals who remained alive). Cases and controls were ART treated participants of two pivotal HIV-1 trials. The relative abundance of each miRNA in serum was measured, by RTqPCR. Associations with mortality (all-cause, cardiovascular and malignancy) were assessed by logistic regression analysis. Correlations between miRNAs and CD4+ T cell count, hs-CRP, IL-6 and D-dimer were also assessed. Results: None of the selected miRNAs was associated with all-cause, cardiovascular or malignancy mortality. The levels of three miRNAs (miRs -21, -122 and -200a) correlated with IL-6 while miR-21 also correlated with D-dimer. Additionally, the abundance of miRs -31, -150 and -223, correlated with baseline CD4+ T cell count while the same three miRNAs plus miR- 145 correlated with nadir CD4+ T cell count. Discussion: No associations with mortality were found with any circulating miRNA studied. These results cast doubt onto the effectiveness of circulating miRNA as early predictors of mortality or the major underlying diseases that contribute to mortality in participants treated for HIV-1 infection

Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe