1,501 research outputs found
Minimum Tillage Corn Trial
Minimum tillage practices have tremendous potential to reduce expenses and potential negative environmental effects caused by intensive cropping operations. Conventional tillage practices require heavy machinery to work and groom the soil surface in preparation for the planter. The immediate advantage of reduced tillage for the farm operator is less fuel expense, equipment, time, and labor required. It’s also clear that intensive tillage potentially increases nutrient and soil losses to our surface waterways. By turning the soil and burying surface residue, more soil particles are likely to detach from the soil surface and run off from agricultural fields. Reducing the amount and intensity of tillage can help build soil structure and reduce soil erosion
Minimum Tillage Corn Trial
Minimum tillage practices have significant potential to reduce expenses and the potential negative environmental effects caused by intensive tillage operations. Conventional tillage practices require heavy machinery to work and groom the soil surface in preparation for the planter. The immediate advantage of reduced tillage for the farm operator is less fuel expense, equipment, time, and labor required. It’s also clear that intensive tillage potentially increases nutrient and soil losses to our surface waterways. By turning the soil and burying surface residue, more soil particles are likely to detach from the soil surface and increase the potential for run off from agricultural fields. Reducing the amount and intensity of tillage can help build soil structure and reduce soil erosion
An improved Plasmodium cynomolgi genome assembly reveals an unexpected methyltransferase gene expansion.
Background: Plasmodium cynomolgi, a non-human primate malaria parasite species, has been an important model parasite since its discovery in 1907. Similarities in the biology of P. cynomolgi to the closely related, but less tractable, human malaria parasite P. vivax make it the model parasite of choice for liver biology and vaccine studies pertinent to P. vivax malaria. Molecular and genome-scale studies of P. cynomolgi have relied on the current reference genome sequence, which remains highly fragmented with 1,649 unassigned scaffolds and little representation of the subtelomeres.
Methods: Using long-read sequence data (Pacific Biosciences SMRT technology), we assembled and annotated a new reference genome sequence, PcyM, sourced from an Indian rhesus monkey. We compare the newly assembled genome sequence with those of several other Plasmodium species, including a re-annotated P. coatneyi assembly.
Results: The new PcyM genome assembly is of significantly higher quality than the existing reference, comprising only 56 pieces, no gaps and an improved average gene length. Detailed manual curation has ensured a comprehensive annotation of the genome with 6,632 genes, nearly 1,000 more than previously attributed to P. cynomolgi. The new assembly also has an improved representation of the subtelomeric regions, which account for nearly 40% of the sequence. Within the subtelomeres, we identified more than 1300 Plasmodium interspersed repeat (pir) genes, as well as a striking expansion of 36 methyltransferase pseudogenes that originated from a single copy on chromosome 9.
Conclusions: The manually curated PcyM reference genome sequence is an important new resource for the malaria research community. The high quality and contiguity of the data have enabled the discovery of a novel expansion of methyltransferase in the subtelomeres, and illustrates the new comparative genomics capabilities that are being unlocked by complete reference genomes
Clonal and microclonal mutational heterogeneity in high hyperdiploid acute lymphoblastic leukemia.
High hyperdiploidy (HD), the most common cytogenetic subtype of B-cell acute lymphoblastic leukemia (B-ALL), is largely curable but significant treatment-related morbidity warrants investigating the biology and identifying novel drug targets. Targeted deep-sequencing of 538 cancer-relevant genes was performed in 57 HD-ALL patients lacking overt KRAS and NRAS hotspot mutations and lacking common B-ALL deletions to enrich for discovery of novel driver genes. One-third of patients harbored damaging mutations in epigenetic regulatory genes, including the putative novel driver DOT1L (n=4). Receptor tyrosine kinase (RTK)/Ras/MAPK signaling pathway mutations were found in two-thirds of patients, including novel mutations in ROS1, which mediates phosphorylation of the PTPN11-encoded protein SHP2. Mutations in FLT3 significantly co-occurred with DOT1L (p=0.04), suggesting functional cooperation in leukemogenesis. We detected an extraordinary level of tumor heterogeneity, with microclonal (mutant allele fraction <0.10) KRAS, NRAS, FLT3, and/or PTPN11 hotspot mutations evident in 31/57 (54.4%) patients. Multiple KRAS and NRAS codon 12 and 13 microclonal mutations significantly co-occurred within tumor samples (p=4.8x10-4), suggesting ongoing formation of and selection for Ras-activating mutations. Future work is required to investigate whether tumor microheterogeneity impacts clinical outcome and to elucidate the functional consequences of epigenetic dysregulation in HD-ALL, potentially leading to novel therapeutic approaches
Etiology of hospital mortality in children living in low- and middle-income countries:a systematic review and meta-analysis
In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2,000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1,000 admissions with 95% confidence intervals (95% CI). Our search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95% CI 3.4%–4.7%]. The most common causes of mortality (deaths/1,000 admissions) were infectious [12 (95% CI 9–14)]; respiratory [9 (95% CI 5–13)]; and gastrointestinal [9 (95% CI 6–11)]. Common causes of admission (cases/1,000 admissions) were respiratory [255 (95% CI 231–280)]; infectious [214 (95% CI 193–234)]; and gastrointestinal [166 (95% CI 143–190)]. We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation
The NEWFIRM Medium-band Survey: Photometric Catalogs, Redshifts and the Bimodal Color Distribution of Galaxies out to z~3
We present deep near-infrared (NIR) medium-bandwidth photometry over the
wavelength range 1-1.8 microns in the All-wavelength Extended Groth strip
International Survey (AEGIS) and Cosmic Evolution Survey (COSMOS) fields. The
observations were carried out as part of the NEWFIRM Medium-Band Survey (NMBS),
an NOAO survey program on the Mayall 4m telescope on Kitt Peak using the NOAO
Extremely Wide-Field Infrared Imager (NEWFIRM). In this paper, we describe the
full details of the observations, data reduction and photometry for the survey.
We also present a public K-selected photometric catalog, along with accurate
photometric redshifts. The redshifts are computed with 37 (20) filters in the
COSMOS (AEGIS) fields, combining the NIR medium-bandwidth data with existing
ultraviolet (UV; Galaxy Evolution Explorer), visible and NIR
(Canada-France-Hawaii Telescope and Subaru) and mid-IR (Spitzer/IRAC) imaging.
We find excellent agreement with publicly available spectroscopic redshifts,
with sigma_z/(1+z)~1-2% for ~4000 galaxies at z=0-3. The NMBS catalogs contain
~13,000 galaxies at z>1.5 with accurate photometric redshifts and rest-frame
colors. Due to the increased spectral resolution obtained with the five NIR
medium-band filters, the median 68% confidence intervals of the photometric
redshifts of both quiescent and star-forming galaxies are a factor of ~2 times
smaller when comparing catalogs with medium-band NIR photometry to NIR
broadband photometry. We show evidence for a clear bimodal color distribution
between quiescent and star-forming galaxies that persists to z~3, a higher
redshift than has been probed so far.Comment: All NMBS data products and a high resolution version of paper are
available for download at http://www.astro.yale.edu/nmbs; Accepted for
publication in ApJ; 24 pages, 21 figures, 4 table
Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression
Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation
The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020
Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology
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