Evaluation of Chlorosulfonyl Pyridine for Protecting Wood from Soft-Rot Fungi Using A Tensile Strength Test

Laboratory evaluation of a promising new wood preservative, 2,3,5,6,-tetrachloro-4 methylsulfonyl pyridine, was conducted to determine its relative effectiveness against two soft-rot fungi using tensile strength as the measure of the protection value. One-sixteenth-inch sapwood specimens of three species: ponderosa pine (Pinus ponderosa Laws.), sweetgum (Liquidambar styraciflua L.), and pondcypress (Taxodium ascendens Bong.); were treated with various levels of preservative and exposed to Graphium sp. and Acremonium sp. in test tube incubation chambers for 14 days. Statistical comparison of strength values of treated sweetgum specimens exposed to Graphium sp. indicated no significant difference between the protective properties of chlorosulfonyl pyridine and pentachlorophenol. Multiple comparisons of the untreated unincubated specimen mean with treated specimen means, however, indicated that 0.05 pcf of chlorosulfonyl pyridine was required to provide the same protection as afforded by 0.03 pcf of pentachlorophenol. Results also revealed that Graphium sp. had a relatively high wood-deterioration capacity

Energy Value of Paraquat-Treated and Resin-Soaked Loblolly Pine

With a basal injector, loblolly pines were treated with 5% paraquat cation (weight weight basis) and harvested after 18 months. The resin acid, turpentine, moisture content (MC), and energy value were measured in three bolts of the stem. In bolt 1, the first 152 cm above the injection site, the increase in resin acids was 392% and in turpentine, 564%. Within the whole stem (the first two 152-cm bolts and the third bolt to a 7.6-cm inside-bark diameter), resin acids and turpentine increased 203 and 296%, respectively. Moisture content was reduced 9%, 8%, and 8% in bolts 1, 2, and 3, respectively. Turpentine from treated and untreated trees had an average heating value of 19,369 cal/g. When weighted for volume, net energy content was 7.8% greater for treated than control trees because of the increase in resin, including turpentine and the lowered MC

Complete Genome Sequences of Cluster A Mycobacteriophages BobSwaget, Fred313, KADY, Lokk, MyraDee, Stagni, and StepMih

Seven mycobacteriophages from distinct geographical locations were isolated, using Mycobacterium smegmatis mc2155 as the host, and then purified and sequenced. All of the genomes are related to cluster A mycobacteriophages, BobSwaget and Lokk in subcluster A2; Fred313, KADY, Stagni, and StepMih in subcluster A3; and MyraDee in subcluster A18, the first phage to be assigned to that subcluster

Monsoons: global energetics and local physics as drivers of past, present and future monsoons

Global constraints on momentum and energy govern the structure of the zonal mean tropical circulation and rainfall. The continental-scale monsoon systems are also facets of a momentum- and energy-constrained global circulation, but their modern and paleo variability deviates substantially from that of the longitudinal mean through mechanisms neither fully understood nor well simulated. A framework grounded in global constraints yet encompassing the complexities of monsoon dynamics is needed to identify the causes of mismatch between theory, models, and observations and, ultimately, improve regional climate projection. In a first step towards this goal, disparate regional processes must be distilled into gross measures of energy flow in and out of continents and from the surface to the tropopause, so that monsoon dynamics may be coherently diagnosed across modern and paleo observations and across idealized and comprehensive simulations. Accounting for zonal asymmetries in the circulation, land/ocean differences in surface fluxes, and the character of convective systems, such a monsoon framework would integrate our understanding at all relevant scales: from the fine details of how moisture and energy are lifted in the updrafts of thunderclouds, up to the global circulations

Measurements of ψ(2S) and X(3872) → J/ψπ+π− production in pp collisions at √s=8 TeV with the ATLAS detector

Differential cross sections are presented for the prompt and non-prompt production of the hidden-charm states X(3872) and ψ(2S), in the decay mode J/ψπ+π−, measured using 11.4 fb−1 of pp collisions at √s=8 TeV by the ATLAS detector at the LHC. The ratio of cross-sections X(3872)/ψ(2S) is also given, separately for prompt and non-prompt components, as well as the non-prompt fractions of X(3872) and ψ(2S). Assuming independent single effective lifetimes for non-prompt X(3872) and ψ(2S) production gives RB=B(B→X(3872)+any)B(X(3872)→J/ψπ+π−)B(B→ψ(2S)+any)B(ψ(2S)→J/ψπ+π−)=(3.95±0.32(stat)±0.08(sys))×10−2RB=B(B→X(3872)+any)B(X(3872)→J/ψπ+π−)B(B→ψ(2S)+any)B(ψ(2S)→J/ψπ+π−)=(3.95±0.32(stat)±0.08(sys))×10−2 separating short- and long-lived contributions, assuming that the short-lived component is due to Bc decays, gives RB = (3.57 ± 0.33(stat) ± 0.11(sys)) × 10−2, with the fraction of non-prompt X(3872) produced via Bc decays for pT(X(3872)) > 10 GeV being (25 ± 13(stat) ± 2(sys) ± 5(spin))%. The distributions of the dipion invariant mass in the X(3872) and ψ(2S) decays are also measured and compared to theoretical predictions

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

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 hospitalization2–4 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

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types