Ultrahigh spatial-frequency, high-contrast periodic structures produced by interference lithography

We have developed a process to produce high-aspect ratio, high- frequency periodic profiles recorded in a photoresist layer by interference lithography. We are able to independently control the period, duty cycle, and sidewall angle of the profiles. High-contrast diazonapthoquinone-based photoresist and single mode operation of the exposure laser are critical. The high-aspect ratio profiles are necessary for many applications such as transfer etch masks for etching oxides and field emitter array patterning. 5 refs., 5 figs

Genome-wide functional perturbation of human microsatellite repeats using engineered zinc finger transcription factors.

Repeat elements can be dysregulated at a genome-wide scale in human diseases. For example, in Ewing sarcoma, hundreds of inert GGAA repeats can be converted into active enhancers when bound by EWS-FLI1. Here we show that fusions between EWS and GGAA-repeat-targeted engineered zinc finger arrays (ZFAs) can function at least as efficiently as EWS-FLI1 for converting hundreds of GGAA repeats into active enhancers in a Ewing sarcoma precursor cell model. Furthermore, a fusion of a KRAB domain to a ZFA can silence GGAA microsatellite enhancers genome wide in Ewing sarcoma cells, thereby reducing expression of EWS-FLI1-activated genes. Remarkably, this KRAB-ZFA fusion showed selective toxicity against Ewing sarcoma cells compared with non-Ewing cancer cells, consistent with its Ewing sarcoma-specific impact on the transcriptome. These findings demonstrate the value of ZFAs for functional annotation of repeats and illustrate how aberrant microsatellite activities might be regulated for potential therapeutic applications

Remarkable preservation of microbial mats in Neoproterozoic siliciclastic settings : Implications for Ediacaran taphonomic models

The authors thank Duncan McIlroy and Alex Liu for their discussions, help, comments and field support, the National Trust for access to Longmyndian localities, and the staff of the British Geological Survey Palaeontology unit and the Oxford University Museum of Natural History for their assistance with access to materials. The comments and suggestions of two anonymous reviewers and Nora Noffke significantly improved the manuscript.Peer reviewedPostprin

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

Open data from the third observing run of LIGO, Virgo, KAGRA, and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Identification and subgrouping of Cucumber mosaic virus with mouse monoclonal antibodies

Using a mixture of isolates of Cucumber mosaic virus (CMV) from subgroups I and II as immunogens, 20 mouse hybridoma cell lines secreting monoclonal antibodies were produced. A reliable method for efficient detection and accurate subgrouping of CMV isolates has been developed. Tests with 12 well-characterized strains of CMV and other cucumoviruses demonstrated the presence of epitopes that were virus and subgroup specific. Analyses of 109 accessions of CMV isolates collected from various parts of the world revealed 70% were subgroup I, with 20% identified as subgroup II. Seven isolates (6%) did not react with group-specific antibodies but did react with antibodies that recognized all CMV isolates. Differential reactions among isolates suggested a total of 10 epitopes were recognized. The antigenic diversity among subgroup II CMVs was greater than for the subgroup I isolates, even though fewer subgroup II isolates were tested