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A(syn)-U/T and G(syn)-C+ Hoogsteen (HG) base pairs (bps) are energetically more disfavored relative to Watson–Crick (WC) bps in A-RNA as compared to B-DNA by >1 kcal/mol for reasons that are not fully understood. Here, we used NMR spectroscopy, optical melting experiments, molecular dynamics simulations and modified nucleotides to identify factors that contribute to this destabilization of HG bps in A-RNA. Removing the 2′-hydroxyl at single purine nucleotides in A-RNA duplexes did not stabilize HG bps relative to WC. In contrast, loosening the A-form geometry using a bulge in A-RNA reduced the energy cost of forming HG bps at the flanking sites to B-DNA levels. A structural and thermodynamic analysis of purine-purine HG mismatches reveals that compared to B-DNA, the A-form geometry disfavors syn purines by 1.5–4 kcal/mol due to sugar-backbone rearrangements needed to sterically accommodate the syn base. Based on MD simulations, an additional penalty of 3–4 kcal/mol applies for purine-pyrimidine HG bps due to the higher energetic cost associated with moving the bases to form hydrogen bonds in A-RNA versus B-DNA. These results provide insights into a fundamental difference between A-RNA and B-DNA duplexes with important implications for how they respond to damage and post-transcriptional modifications.
A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012 are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations, and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO dataset is archived monthly from 2001–2012 on a grid of 5° longitude × 5° latitude × 1 km altitude, from the surface to 14 km altitude.
The mapping product has been carefully evaluated, by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less, and found to be less than 30 % for almost all cases. The trajectory-mapped CO dataset has also been validated by comparison profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %.
Maps are also compared with Version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. While agreement is good in the lowermost troposphere, the MOPITT CO profile shows negative biases of ∼ 20 % between 500 and 300 hPa. These upper troposphere biases are not related to the
mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS climatology column agrees with the MOPITT CO total column within ±5 %, which is consistent with previous reports.
The maps clearly show major regional CO sources such as biomass burning in the central and southern Africa and anthropogenic emissions in eastern China. The dataset shows the seasonal CO cycle over different latitude bands and altitude ranges that are representative of the regions as well as long-term trends over latitude bands. We observe a decline in CO over the Northern Hemisphere extratropics and the tropics consistent with that reported by previous studies.
Similar maps have been made using the concurrent O3 measurements by MOZAICIAGOS, as the global variation of O3–CO correlations can be a useful tool for the evaluation of ozone sources and transport in chemical transport models. We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO dataset as an a priori climatology for satellite retrieval, and for air quality model validation and initialization.
A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012, are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO data set is archived monthly from 2001 to 2012 on a grid of 5° longitude × 5° latitude × 1 km altitude, from the surface to 14 km altitude.
The mapping product has been carefully evaluated, firstly by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less and found to be less than 30 % for almost all cases. Secondly, the method has been validated by comparing profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %. Finally, the mapping product is compared with global MOZAIC-IAGOS cruise-level data, which were not included in the trajectory-mapped data set, and with independent data from the NOAA aircraft flask sampling program. The trajectory-mapped MOZAIC-IAGOS CO values show generally good agreement with both independent data sets.
Maps are also compared with version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. Both data sets clearly show major regional CO sources such as biomass burning in Central and southern Africa and anthropogenic emissions in eastern China. While the maps show similar features and patterns, and relative biases are small in the lowermost troposphere, we find differences of ∼ 20 % in CO volume mixing ratios between 500 and 300 hPa. These upper-tropospheric biases are not related to the mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS column is also higher than the MOPITT CO total column by 12–16 %.
The data set shows the seasonal CO cycle over different latitude bands and altitude ranges as well as long-term trends over different latitude bands. We observe a decline in CO over the northern hemispheric extratropics and the tropics consistent with that reported by previous studies using other data sources.
We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO data set as an a priori climatology for satellite retrieval and for air quality model validation and initialization.
A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.
A data-driven method was applied to Au+Au collisions at √sNN = 200 GeV made with the STAR detector at RHIC to isolate pseudorapidity distance η-dependent and η-independent correlations by using two- and four-particle azimuthal cumulant measurements. We identified a η-independent component of the correlation, which is dominated by anisotropic flow and flow fluctuations. It was also found to be independent of η within the measured range of pseudorapidity |η| < 1. In 20–30% central Au+Au collisions, the relative flow fluctuation was found to be 34%±2%(stat.)±3%(sys.) for particles with transverse momentum pT less than 2 GeV/c. The η-dependent part, attributed to nonflow correlations, is found to be 5% ± 2%(sys.) relative to the flow of the measured second harmonic cumulant at |η| > 0.7.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the Xchromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10-9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10-9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA Epilepsy study
(2019)
The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analyzed from 1,069 non-epileptic controls and 1,249 patients: temporal lobe epilepsy with hippocampal sclerosis (N=599), temporal lobe epilepsy with normal MRI (N=275), genetic generalized epilepsy (N=182) and nonlesional extratemporal epilepsy (N=193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fiber tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at p<0.001). Across “all epilepsies” lower fractional anisotropy was observed in most fiber tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. Less robust effects were seen with mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Those with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced differences in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and in mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of microstructural abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibers in a large multicentre study of epilepsy. Overall, epilepsy patients showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding new insights into pathological substrates that may be used to guide future therapeutic and genetic studies.
Background: Misconceptions about ADHD stigmatize affected people, reduce credibility of providers, and prevent/delay treatment. To challenge misconceptions, we curated findings with strong evidence base. Methods: We reviewed studies with more than 2000 participants or meta-analyses from five or more studies or 2000 or more participants. We excluded meta-analyses that did not assess publication bias, except for meta-analyses of prevalence. For network meta-analyses we required comparison adjusted funnel plots. We excluded treatment studies with waiting-list or treatment as usual controls. From this literature, we extracted evidence-based assertions about the disorder. Results: We generated 208 empirically supported statements about ADHD. The status of the included statements as empirically supported is approved by 80 authors from 27 countries and 6 continents. The contents of the manuscript are endorsed by 366 people who have read this document and agree with its contents. Conclusions: Many findings in ADHD are supported by meta-analysis. These allow for firm statements about the nature, course, outcome causes, and treatments for disorders that are useful for reducing misconceptions and stigma.
As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.