290 research outputs found
Neighborhood Conditions and Psychosocial Outcomes Among Middle-Aged African Americans: A Cross-sectional Analysis
Objective: We examined associations between observed neighborhood conditions (good/adverse) and psychosocial outcomes (stress, depressive symptoms, resilience, and sense of control) among middle-aged and older African Americans. Methods: The sample included 455 middle-aged and older African Americans examined in Wave 10 of the African American Health (AAH) study. Linear regression was adjusted for attrition, self-selection into neighborhoods, and potential confounders, and stratified by the duration at current address (5 years at current residence despite being associated with better psychosocial outcomes
Cluster M Mycobacteriophages Bongo, PegLeg, and Rey with Unusually Large Repertoires of tRNA Isotopes
Genomic analysis of a large set of phages infecting the common hostMycobacterium smegmatis mc2155 shows that they span considerable genetic diversity. There are more than 20 distinct types that lack nucleotide similarity with each other, and there is considerable diversity within most of the groups. Three newly isolated temperate mycobacteriophages, Bongo, PegLeg, and Rey, constitute a new group (cluster M), with the closely related phages Bongo and PegLeg forming subcluster M1 and the more distantly related Rey forming subcluster M2. The cluster M mycobacteriophages have siphoviral morphologies with unusually long tails, are homoimmune, and have larger than average genomes (80.2 to 83.7 kbp). They exhibit a variety of features not previously described in other mycobacteriophages, including noncanonical genome architectures and several unusual sets of conserved repeated sequences suggesting novel regulatory systems for both transcription and translation. In addition to containing transfer-messenger RNA and RtcB-like RNA ligase genes, their genomes encode 21 to 24 tRNA genes encompassing complete or nearly complete sets of isotypes. We predict that these tRNAs are used in late lytic growth, likely compensating for the degradation or inadequacy of host tRNAs. They may represent a complete set of tRNAs necessary for late lytic growth, especially when taken together with the apparent lack of codons in the same late genes that correspond to tRNAs that the genomes of the phages do not obviously encode
Antifungal Activity of Bacillus Species Against Fusarium and Analysis of the Potential Mechanisms Used in Biocontrol
Fusarium is a complex genus of ascomycete fungi that consists of plant pathogens of agricultural relevance. Controlling Fusarium infection in crops that leads to substantial yield losses is challenging. These economic losses along with environmental and human health concerns over the usage of chemicals in attaining disease control are shifting focus toward the use of biocontrol agents for effective control of phytopathogenic Fusarium spp. In the present study, an analysis of the plant-growth promoting (PGP) and biocontrol attributes of four bacilli (Bacillus simplex 30N-5, B. simplex 11, B. simplex 237, and B. subtilis 30VD-1) has been conducted. The production of cellulase, xylanase, pectinase, and chitinase in functional assays was studied, followed by in silico gene analysis of the PGP-related and biocontrol-associated genes. Of all the bacilli included in this study, B. subtilis 30VD-1 (30VD-1) demonstrated the most effective antagonism against Fusarium spp. under in vitro conditions. Additionally, 100 μg/ml of the crude 1-butanol extract of 30VD-1’s cell-free culture filtrate caused about 40% inhibition in radial growth of Fusarium spp. Pea seed bacterization with 30VD-1 led to considerable reduction in wilt severity in plants with about 35% increase in dry plant biomass over uninoculated plants growing in Fusarium-infested soil. Phase contrast microscopy demonstrated distortions and abnormal swellings in F. oxysporum hyphae on co-culturing with 30VD-1. The results suggest a multivariate mode of antagonism of 30VD-1 against phytopathogenic Fusarium spp., by producing chitinase, volatiles, and other antifungal molecules, the characterization of which is underway
Anatomy of STEM Teaching in American Universities: A Snapshot from a Large-Scale Observation Study
National and local initiatives focused on the transformation of STEM teaching in higher education have multiplied over the last decade. These initiatives often focus on measuring change in instructional practices, but it is difficult to monitor such change without a national picture of STEM educational practices, especially as characterized by common observational instruments. We characterized a snapshot of this landscape by conducting the first large scale observation-based study. We found that lecturing was prominent throughout the undergraduate STEM curriculum, even in classrooms with infrastructure designed to support active learning, indicating that further work is required to reform STEM education. Additionally, we established that STEM faculty’s instructional practices can vary substantially within a course, invalidating the commonly-used teaching evaluations based on a one-time observation
Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities
Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities
De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome
Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here we identify the non-coding RNA RNU4-2 as a syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 base pair region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 115 individuals with NDD. Most individuals (77.4%) have the same highly recurrent single base insertion (n.64_65insT). In 54 individuals in whom it could be determined, the de novo variants were all on the maternal allele. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to RNU4-1 and other U4 homologues. Using RNA sequencing, we show how 5′ splice-site use is systematically disrupted in individuals with RNU4-2 variants, consistent with the known role of this region during spliceosome activation. Finally, we estimate that variants in this 18 base pair region explain 0.4% of individuals with NDD. This work underscores the importance of non-coding genes in rare disorders and will provide a diagnosis to thousands of individuals with NDD worldwide
Incorporating Genomics and Bioinformatics across the Life Sciences Curriculum
Undergraduate life sciences education needs an overhaul, as clearly described in the National Research Council of the National Academies’ publication BIO 2010: Transforming Undergraduate Education for Future Research Biologists. Among BIO 2010’s top recommendations is the need to involve students in working with real data and tools that reflect the nature of life sciences research in the 21st century [1]. Education research studies support the importance of utilizing primary literature, designing and implementing experiments, and analyzing results in the context of a bona fide scientific question [1–12] in cultivating the analytical skills necessary to become a scientist. Incorporating these basic scientific methodologies in undergraduate education leads to increased undergraduate and post-graduate retention in the sciences [13–16]. Toward this end, many undergraduate teaching organizations offer training and suggestions for faculty to update and improve their teaching approaches to help students learn as scientists, through design and discovery (e.g., Council of Undergraduate Research [www.cur.org] and Project Kaleidoscope [ www.pkal.org])
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