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Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.

Expanding upon recent work, a more comprehensive spectral model based on charge exchange induced X‐ray emission by ions precipitating into the Jovian atmosphere is used to provide new understanding of the polar auroras. In conjunction with the Xspec spectral fitting software, the model is applied to analyze observations from both Chandra and XMM‐Newton by systematically varying the initial precipitating ion parameters to obtain the best fit model for the observed spectra. In addition to the oxygen and sulfur ions considered previously, carbon is included to discriminate between solar wind and Jovian magnetospheric ion origins, enabled by the use of extensive databases of both atomic collision cross sections and radiative transitions. On the basis of fits to all the Chandra observations, we find that carbon contributes negligibly to the observed polar X‐ray emission suggesting that the highly accelerated precipitating ions are of magnetospheric origin. Most of the XMM‐Newton fits also favor this conclusion with one exception that implies a possible carbon contribution. Comparison among all the spectra from these two observatories in light of the inferred initial energies and relative abundances of precipitating ions from the modeling show that they are significantly variable in time (observation date) and space (north and south polar X‐ray auroras).

To understand the origin and magnitude of the present upper limit observations of Saturn's auroral X‐ray emission, we use simple models based on the mechanism that leads to analogous emission at Jupiter, charge transfer between ion precipitation and atmospheric gas. Several putative sources and characteristics of the precipitation are considered, namely, (1) highly charged solar wind ions with additional acceleration and (2) ambient, thermal ion population originating, for example, from Saturn's satellites, and then accelerated to high energies. Estimates obtained for each of these sources show the need for acceleration, either to focus the highly charged solar wind ions into the atmosphere or to enable stripping of the initially low‐charge state ambient ions to higher charges. The former yields a constraint on the existing accelerating potentials present at Saturn but can only account for about a tenth of the observed upper limit to the auroral luminosity, while the latter requires extremely low limits on the area (i.e., less than 100 km2) over which field‐aligned potentials are active and needed to produce the acceleration to generate the observational upper limit on the X‐ray luminosity. We therefore narrow the range of possible ion sources, the accelerating potentials required that are consistent with the present understanding of the magnetosphere, and model upper limit of X‐ray emission from ion precipitation.

The utility of circulating tumor DNA (ctDNA) analysis has not been well-established for disease detection and monitoring of childhood cancers, especially leukemias. We developed PeCan-Seq, a deep sequencing method targeting diverse somatic genomic variants in cell-free samples in childhood cancer. Plasma samples were collected at diagnosis from 233 children with hematologic, solid and brain tumors. All children with hematologic malignancy ( n  = 177) had detectable ctDNA at diagnosis. The median ctDNA fraction was 0.77, and 97% of 789 expected tumor variants were identified, including sequence mutations, copy number variations, and structural variations responsible for oncogenic fusions. In contrast, ctDNA was detected in 19 of 38 solid tumor patients and 1 of 18 brain tumor patients. Somatic variants from ctDNA were correlated with minimal residual disease levels as determined by flow cytometry in serial plasma samples from patients with B-cell acute lymphoblastic leukemia (B-ALL). We showcase multi-tumor detection by ctDNA analysis for a patient with concurrent B-ALL and neuroblastoma. In conclusion, PeCan-seq sensitively identified heterogeneous ctDNA alterations from 1 mL plasma for childhood hematologic malignancies and a subset of solid tumors. PeCan-seq provides a robust, non-invasive approach to augment comprehensive genomic profiling at diagnosis and mutation-specific detection during disease monitoring.

The utility of circulating tumor DNA (ctDNA) analysis has not been well-established for disease detection and monitoring of childhood cancers, especially leukemias. We developed PeCan-Seq, a deep sequencing method targeting diverse somatic genomic variants in cell-free samples in childhood cancer. Plasma samples were collected at diagnosis from 233 children with hematologic, solid and brain tumors. All children with hematologic malignancy (n = 177) had detectable ctDNA at diagnosis. The median ctDNA fraction was 0.77, and 97% of 789 expected tumor variants were identified, including sequence mutations, copy number variations, and structural variations responsible for oncogenic fusions. In contrast, ctDNA was detected in 19 of 38 solid tumor patients and 1 of 18 brain tumor patients. Somatic variants from ctDNA were correlated with minimal residual disease levels as determined by flow cytometry in serial plasma samples from patients with B-cell acute lymphoblastic leukemia (B-ALL). We showcase multi-tumor detection by ctDNA analysis for a patient with concurrent B-ALL and neuroblastoma. In conclusion, PeCan-seq sensitively identified heterogeneous ctDNA alterations from 1 mL plasma for childhood hematologic malignancies and a subset of solid tumors. PeCan-seq provides a robust, non-invasive approach to augment comprehensive genomic profiling at diagnosis and mutation-specific detection during disease monitoring.

Carriers of cancer predisposing variants are at an increased risk of developing subsequent malignant neoplasms among those who have survived childhood cancer. We aimed to investigate whether cancer predisposing variants contribute to the risk of subsequent malignant neoplasm-related late mortality (5 years or more after diagnosis). In this analysis, data were included from two retrospective cohort studies, St Jude Lifetime Cohort (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), with prospective follow-up of patients who were alive for at least 5 years after diagnosis with childhood cancer (ie, long-term childhood cancer survivors) with corresponding germline whole genome or whole exome sequencing data. Cancer predisposing variants affecting 60 genes associated with well-established autosomal-dominant cancer-predisposition syndromes were characterised. Subsequent malignant neoplasms were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 with modifications. Cause-specific late mortality was based on linkage with the US National Death Index and systematic cohort follow up. Fine-Gray subdistribution hazard models were used to estimate subsequent malignant neoplasm-related late mortality starting from the first biospecimen collection, treating non-subsequent malignant neoplasm-related deaths as a competing risk, adjusting for genetic ancestry, sex, age at diagnosis, and cancer treatment exposures. SJLIFE (NCT00760656) and CCSS (NCT01120353) are registered with ClinicalTrials.gov. 12 469 (6172 male and 6297 female) participants were included, 4402 from the SJLIFE cohort (median follow-up time since collection of the first biospecimen 7·4 years [IQR 3·1–9·4]) and 8067 from the CCSS cohort (median follow-up time since collection of the first biospecimen 12·6 years [2·2–16·6]). 641 (5·1%) of 12 469 participants carried cancer predisposing variants (294 [6·7%] in the SJLIFE cohort and 347 [4·3%] in the CCSS cohort), which were significantly associated with an increased severity of subsequent malignant neoplasms (CTCAE grade ≥4 vs grade <4: odds ratio 2·15, 95% CI 1·18–4·19, p=0·0085). 263 (2·1%) subsequent malignant neoplasm-related deaths (44 [1·0%] in the SJLIFE cohort; and 219 [2·7%] in the CCSS cohort) and 426 (3·4%) other-cause deaths (103 [2·3%] in SJLIFE; and 323 [4·0%] in CCSS) occurred. Cumulative subsequent malignant neoplasm-related mortality at 10 years after the first biospecimen collection in carriers of cancer predisposing variants was 3·7% (95% CI 1·2–8·5) in SJLIFE and 6·9% (4·1–10·7) in CCSS versus 1·5% (1·0–2·1) in SJLIFE and 2·1% (1·7–2·5) in CCSS in non-carriers. Carrying a cancer predisposing variant was associated with an increased risk of subsequent malignant neoplasm-related mortality (SJLIFE: subdistribution hazard ratio 3·40 [95% CI 1·37–8·43]; p=0·0082; CCSS: 3·58 [2·27–5·63]; p<0·0001). Identifying participants at increased risk of subsequent malignant neoplasms via genetic counselling and clinical genetic testing for cancer predisposing variants and implementing early personalised cancer surveillance and prevention strategies might reduce the substantial subsequent malignant neoplasm-related mortality burden. American Lebanese Syrian Associated Charities and US National Institutes of Health.

Auroral X‐ray emissions from Jupiter with a total power of about 1 GW have been observed by the Einstein Observatory, Roentgen satellite, Chandra X‐ray Observatory, and XMM‐Newton. Previous theoretical studies have shown that precipitating energetic sulfur and oxygen ions can produce the observed X‐rays. This study presents the results of a hybrid Monte Carlo (MC) model for sulfur and oxygen ion precipitation at high latitudes, looks at differences with the continuous slow‐down model, and compares the results to synthetic spectra fitted to observations. We concentrate on the effects of altitude on the observed spectrum. The opacity of the atmosphere to the outgoing X‐ray photons is found to be important for incident ion energies greater than about 1.2 MeV per nucleon for both sulfur and oxygen. Model spectra are calculated for intensities with and without any opacity effects. These synthetic spectra were compared with the results shown by Hui et al. (2010) which fit Chandra X‐ray Observatory observations for the north and south Jovian auroral emissions. Quenching of long‐lived excited states of the oxygen ions is found to be important. Opacity considerably diminishes the outgoing X‐ray intensity calculated, particularly when the viewing geometry is not favorable.

We have calculated the structures and the emergent spectra of stationary, geometrically thin accretion disks around intermediate mass black holes (IMBH) in both the Schwarzschild and extreme Kerr metrics. Equations of radiative transfer, hydrostatic equilibrium, energy balance, ionization equilibrium, and statistical equilibrium are solved simultaneously and consistently. The six most astrophysically abundant elements (H, He, C, N, O, and Fe) are included, as well as energy transfer by Comptonization. The observed spectrum as a function of viewing angle is computed, incorporating all general relativistic effects. We find that, in contrast with the predictions of the commonly used multicolor disk (MCD) model, opacity associated with photoionization of heavy elements can significantly alter the spectrum near its peak. These ionization edges can create spectral breaks visible in the spectra of slowly spinning black holes viewed from almost all angles and in the spectra of rapidly spinning black holes seen approximately face-on. For fixed mass and accretion rate relative to Eddington, both the black hole spin and the viewing angle can significantly shift the observed peak energy of the spectrum, particularly for rapid spin viewed edge-on. We present a detailed test of the approximations made in various forms of the MCD model. Linear limb-darkening is confirmed to be a reasonable approximation for the integrated flux but not for many specific frequencies of interest. To test if our atmosphere calculation would shed a new light in modeling observations of Ultra-Luminous X-ray sources (ULX) in which many researchers believe to harbor IMBHs, we have chosen 6 ULXs from the XMM-Newton archive whose spectra have high signal-to-noise and can be fitted solely with a disk model without requiring any power-law component. To estimate systematic errors in the inferred parameters, we fit every spectrum to two different disk models, one based on local blackbody emission (KERRBB) and one based on the detailed atmosphere calculation (BHSPEC). Both incorporate full general relativistic treatment of the disk surface brightness profile, photon Doppler shifts, and photon trajectories. We found in every case that they give almost identical fits and similar acceptable parameters and this indistinguishableness could be attributed to both low-level populations of unstripped heavy elements which generate the atomic features and strong Doppler shift which smears those atomic features. The best-fit value of the most interesting parameter, the mass of the central object, is between 23 and 73 [special characters omitted] in 5 of the 6 examples. In every case, the best-fit inclination angle and mass are correlated, in the sense that large mass corresponds to high inclination. Even after allowing for this degeneracy, we find that, with ≥ 99.9% formal statistical confidence, 3 of the 6 objects have mass ≥ 25 [special characters omitted]; for the other 3, these data are consistent with a wide range of masses. A mass greater than several hundred [special characters omitted] is unlikely for the 3 best-constrained objects. These fits also suggest comparatively rapid black hole spin in the 3 objects whose masses are relatively well-determined, but our estimate of the spin is subject to significant systematic error having to do with uncertainty in the underlying surface brightness profile.

Recent advancements in neutron and X-ray sources, instrumentation and data collection modes have significantly increased the experimental data size (which could easily contain 10\\(^8\\) -- 10\\(^10\\) data points), so that conventional volumetric visualization approaches become inefficient for both still imaging and interactive OpenGL rendition in a 3D setting. We introduce a new approach based on the unsupervised machine learning algorithm, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), to efficiently analyze and visualize large volumetric datasets. Here we present two examples of analyzing and visualizing datasets from the diffuse scattering experiment of a single crystal sample and the tomographic reconstruction of a neutron scanning of a turbine blade. We found that by using the intensity as the weighting factor in the clustering process, DBSCAN becomes very effective in de-noising and feature/boundary detection, and thus enables better visualization of the hierarchical internal structures of the neutron scattering data.