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Down syndrome is associated with genome-wide perturbation of gene expression, which may be mediated by epigenetic changes. We perform an epigenome-wide association study on neonatal bloodspots comparing 196 newborns with Down syndrome and 439 newborns without Down syndrome, adjusting for cell-type heterogeneity, which identifies 652 epigenome-wide significant CpGs (P

MLL gene rearrangements (MLLr) are a common cause of aggressive, incurable acute lymphoblastic leukemias (ALL) in infants and children, most of which originate in utero. The most common MLLr produces an MLL-AF4 fusion protein. MLL-AF4 promotes leukemogenesis by activating key target genes, mainly through recruitment of DOT1L and increased histone H3 lysine-79 methylation (H3K79me2/3). One key MLL-AF4 target gene is PROM1, which encodes CD133 (Prominin-1). CD133 is a pentaspan transmembrane glycoprotein that represents a potential pan-cancer target as it is found on multiple cancer stem cells. Here we demonstrate that aberrant PROM1/CD133 expression is essential for leukemic cell growth, mediated by direct binding of MLL-AF4. Activation is controlled by an intragenic H3K79me2/3 enhancer element (KEE) leading to increased enhancer-promoter interactions between PROM1 and the nearby gene TAPT1. This dual locus regulation is reflected in a strong correlation of expression in leukemia. We find that in PROM1/CD133 non-expressing cells, the PROM1 locus is repressed by polycomb repressive complex 2 (PRC2) binding, associated with reduced expression of TAPT1, partially due to loss of interactions with the PROM1 locus. Together, these results provide the first detailed analysis of PROM1/CD133 regulation that explains CD133 expression in MLLr ALL.

We present a mathematical model that describes thermo-mechanical deformations and thermal gradients on the unsteady burning of a heterogeneous solid propellant. A scaling study shows that the deformations in solid at combustion timescales can be treated as quasi-static. The resulting thermo-mechanical formulation is formulated on a Cartesian grid and makes use of a weak form of Chorin-type projection method to deal with large difference in shear modulus of constituent materials. A one-dimensional verification study is carried out by comparing numerical simulations with those of an analytical model. In addition, convergence studies for a two-dimensional propellant sandwich configuration are presented for the stress, velocity, and reference map components. Finally, simulations are carried out for a two-dimensional random propellant pack and the time-averaged burn rate and strains are reported.

Resonant soft X-ray scattering (RSoXS) leverages chemical specificity to characterize thin films but is limited near the nitrogen edge. The challenge is that commercially available X-ray transparent substrates are composed of Si 3 N 4 and thereby absorb incident X-rays and generate incoherent fluorescence. To overcome this challenge, we designed and fabricated Al 2 O 3 free-standing films for use as RSoXS windows. Al 2 O 3 films offer higher X-ray transmittance and minimal fluorescence near the nitrogen edge. As an example, Al 2 O 3 windows allow for nitrogen RSoXS of conjugated block copolymer thin films that reveal domain spacings, which are not apparent with commercially available Si 3 N 4 substrates.

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

To investigate if retinal thickness has predictive utility in COVID-19 outcomes by evaluating the statistical association between retinal thickness using OCT and of COVID-19-related mortality. Secondary outcomes included associations between retinal thickness and length of stay (LoS) in hospital. In this retrospective cohort study, OCT scans from 230 COVID-19 patients admitted to the Intensive Care Unit (ITU) were compared with age and gender-matched patients with pneumonia from before March 2020. Total retinal, GCL + IPL, and RNFL thicknesses were recorded, and analysed with systemic measures collected at the time of admission and mortality outcomes, using linear regression models, Pearson's R correlation, and Principal Component Analysis. Retinal thickness was significantly associated with all-time mortality on follow up in the COVID-19 group (p = 0.015), but not 28-day mortality (p = 0.151). Retinal and GCL + IPL layer thicknesses were both significantly associated with LoS in hospital for COVID-19 patients (p = 0.006 for both), but not for patients with pneumonia (p = 0.706 and 0.989 respectively). RNFL thickness was not associated with LoS in either group (COVID-19 p = 0.097, pneumonia p = 0.692). Retinal thickness associated with LoS in hospital and long-term mortality in COVID-19 patients, suggesting that retinal structure could be a surrogate marker for frailty and predictor of disease severity in this group of patients, but not in patients with pneumonia from other causes. [ABSTRACT FROM AUTHOR]

Water quality indicator algorithms often separate marine and freshwater systems, introducing artificial boundaries and artifacts in the freshwater to ocean continuum. Building upon the Ocean Colour- (OC) and Lakes Climate Change Initiative (CCI) projects, we propose an improved tool to assess the interactions across river–sea transition zones. Fuzzy clustering methods are used to generate optical water types (OWT) representing spectrally distinct water reflectance classes, occurring within a given region and period (here 2016–2021), which are then utilized to assign membership values to every OWT class for each pixel and seamlessly blend optimal in-water algorithms across the region. This allows a more flexible representation of water provinces across transition zones than classic hard clustering techniques. Improvements deal with expanded sensor spectral band-sets, such as Sentinel-3 OLCI, and increased spatial resolution with Sentinel-2 MSI high-resolution data. Regional clustering was found to be necessary to capture site-specific characteristics, and a method was developed to compare and merge regional cluster sets into a pan-regional representative OWT set. Fuzzy clustering OWT timeseries data allow unique insights into optical regime changes within a lagoon, estuary, or delta system, and can be used as a basis to improve WQ algorithm performance. [ABSTRACT FROM AUTHOR]

Introduction : Cutaneous abscess incision and drainage and foreign body removal are 2 common procedures in a variety of outpatient settings. The goal of this project was to create a novel, clean, reusable task trainer that could more accurately reproduce all the steps necessary to perform cutaneous abscess drainage or foreign body removal including ultrasound to identify the abscess cavity or foreign body. Methods : The novel task trainer was constructed using silicone for both the base and the top skin. Toothpaste mixed with saline was used for the abscess material as this produced an ultrasound image that mimicked purulent material. A piece of a metal paper clip was imbedded in the top skin to mimic a cutaneous foreign body. Physician assistant (PA) students given a didactic lecture then used the novel task trainer as part of a clinical skills course. Results : After the activity, the PA students were asked to voluntarily complete a brief preretrospective/postretrospective survey comprised 8 questions that addressed their self-perceived knowledge and skills using a 5-point Likert scale. Survey data from an initial cohort of PA students at one university show effectiveness of the models when used with the associated curriculum. Discussion : This study demonstrates the feasibility of constructing a practical, low-cost, non-animal-based task trainer for the purpose of training incision and drainage of cutaneous abscesses and removal of cutaneous foreign bodies. This novel task trainer allows for ultrasound skill development and provides realistic imaging experience. [ABSTRACT FROM AUTHOR]

Little is known of primary production in dark hypersaline ecosystems despite the prevalence of such environments on Earth today and throughout its geologic history. Here, we generated and analyzed metagenome-assembled genomes (MAGs) organized as operational taxonomic units (OTUs) from three depth intervals along a 30-cm sediment core from the north arm of Great Salt Lake, Utah. The sediments and associated porewaters were saturated with NaCl, exhibited redox gradients with depth, and harbored nitrogen-depleted organic carbon. Metabolic predictions of MAGs representing 36 total OTUs recovered from the core indicated that communities transitioned from aerobic and heterotrophic at the surface to anaerobic and autotrophic at depth. Dark CO2 fixation was detected in sediments and the primary mode of autotrophy was predicted to be via the Wood–Ljungdahl pathway. This included novel hydrogenotrophic acetogens affiliated with the bacterial class Candidatus Bipolaricaulia. Minor populations were dependent on the Calvin cycle and the reverse tricarboxylic acid cycle, including in a novel Thermoplasmatota MAG. These results are interpreted to reflect the favorability of and selectability for populations that operate the lowest energy requiring CO2-fixation pathway known, the Wood–Ljungdahl pathway, in anoxic and hypersaline conditions that together impart a higher energy demand on cells. [ABSTRACT FROM AUTHOR]

Introduction: Understanding genetic contributors to sarcopenia (age-related loss of muscle strength and mass) is key to finding effective therapies. Variants of the bradykinin receptor 2 (BDKRB2) have been linked to athletic and muscle performance. The rs1799722–9 and rs5810761 T alleles have been shown to be overrepresented in endurance athletes, possibly due to increased transcriptional rates of the receptor. These variants have been rarely studied in older people or people with sarcopenia. Methods: We performed a post hoc sub-study of the Leucine and ACE (LACE) inhibitor trial, which enrolled 145 participants aged ≥70 years with low grip strength and low gait speed. Participants' blood samples were genotyped for rs179972 using TaqMan and rs5810761 by amplification through Hotstar Taq. Genotypes were compared with outcomes of physical performance and body composition measures. Results: Data from 136 individuals were included in the analysis. For rs1799722 the genotype frequency (TT: 17, CC: 48, CT: 71) remained in Hardy-Weinberg Equilibrium (HWE p = 0.248). There was no difference between the genotypes for six-Minute Walk Distance (6MWD) or Short Physical Performance Battery (SPPB). Men with the TT genotype had a significantly greater 6MWD than other genotypes (TT 400m vs CT 310m vs CC 314m, p = 0.027), and greater leg muscle mass (TT 17.59kg vs CT 15.04kg vs CC 15.65kg, p = 0.007). For rs5810761, the genotype frequency (-9-9: 31, +9+9: 43, -9+9: 60) remained in HWE (p = 0.269). The +9+9 genotype was associated with a significant change in SPPB score at 12 months (-9-9 0 vs -9+9 0 vs +9+9–1, p<0.001), suggesting an improvement. In men, the -9-9 genotype was associated with lower arm fat (-9-9 2.39kg vs -9+9 2.72kg vs +9+9 2.76kg, p = 0.019). Conclusion: In men, the rs1799722 TT genotype was associated with longer 6MWD and greater leg muscle mass, while the rs5810761 -9-9 genotype was associated with lower arm fat mass. [ABSTRACT FROM AUTHOR]

Course evaluations can be used for curriculum improvement and have the potential to better the student learning experience. However, because most are based on Likert scales and open-ended feedback, understanding diversity in student opinion and uncovering optimal options for course change and improvement are often difficult. Alternatively, Q-methodology can be used to investigate patterns of thought within a group and may offer greater potential for course reform. This manuscript offers a tutorial-based explanation of the three components of Q-methodology studies (1) survey instrument development, (2) data collection, and (3) analysis and interpretation, then demonstrates, via case study, the use of Q-methodology to evaluate a fourth-year undergraduate pathoanatomy course. The goal of this article is to enable the reader to broadly apply Q-methodology in other courses to gain insight and feedback beyond that offered by traditional Likert scale methods. As demonstrated through the pathoanatomy case study, Q-methodology highlights groups (denoted by factors) of like-minded students that share opinions, preferences, and values. Overall, Q-methodology analyses support course instructors in identifying areas of course strength and improvement in an evidence-based way. This alternative to traditional Likert scales represents a promising solution to ongoing course evaluation limitations.