85 research outputs found

    An algorithm for Monte-Carlo time-dependent radiation transfer

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    A new Monte-Carlo algorithm for calculating time-dependent radiative-transfer under the assumption of LTE is presented. Unlike flux-limited diffusion the method is polychromatic, includes scattering, and is able to treat the optically thick and free-streaming regimes simultaneously. The algorithm is tested on a variety of 1-d and 2-d problems, and good agreement with benchmark solutions is found. The method is used to calculate the time-varying spectral energy distribution from a circumstellar disc illuminated by a protostar whose accretion luminosity is varying. It is shown that the time lag between the optical variability and the infrared variability results from a combination of the photon travel time and the thermal response in the disc, and that the lag is an approximately linear function of wavelength.Comment: 10 pages, 10 figures, accepted for publication by MNRA

    Subduction or sagduction? Ambiguity in constraining the origin of ultramafic–mafic bodies in the Archean crust of NW Scotland

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    The Lewisian Complex of NW Scotland is a fragment of the North Atlantic Craton. It comprises mostly Archean tonalite–trondhjemite–granodiorite (TTG) orthogneisses that were variably metamorphosed and reworked in the late Neoarchean to Paleoproterozoic. Within the granulite facies central region of the mainland Lewisian Complex, discontinuous belts composed of ultramafic–mafic rocks and structurally overlying garnet–biotite gneiss (brown gneiss) are spatially associated with steeply-inclined amphibolite facies shear zones that have been interpreted as terrane boundaries. Interpretation of the primary chemical composition of these rocks is complicated by partial melting and melt loss during granulite facies metamorphism, and contamination with melts derived from the adjacent migmatitic TTG host rocks. Notwithstanding, the composition of the layered ultramafic–mafic rocks is suggestive of a protolith formed by differentiation of tholeiitic magma, where the ultramafic portions of these bodies represent the metamorphosed cumulates and the mafic portions the metamorphosed fractionated liquids. Although the composition of the brown gneiss does not clearly discriminate the protolith, it most likely represents a metamorphosed sedimentary or volcano-sedimentary sequence. For Archean rocks, particularly those metamorphosed to granulite facies, the geochemical characteristics typically used for discrimination of paleotectonic environments are neither strictly appropriate nor clearly diagnostic. Many of the rocks in the Lewisian Complex have ‘arc-like’ trace element signatures. These signatures are interpreted to reflect derivation from hydrated enriched mantle and, in the case of the TTG gneisses, partial melting of amphibolite source rocks containing garnet and a Ti-rich phase, probably rutile. However, it is becoming increasingly recognised that in Archean rocks such signatures may not be unique to a subduction environment but may relate to processes such as delamination and dripping. Consequently, it is unclear whether the Lewisian ultramafic–mafic rocks and brown gneisses represent products of plate margin or intraplate magmatism. Although a subduction-related origin is possible, we propose that an intraplate origin is equally plausible. If the second alternative is correct, the ultramafic–mafic rocks and brown gneisses may represent the remnants of intracratonic greenstone belts that sank into the deep crust due to their density contrast with the underlying partially molten low viscosity TTG orthogneisses

    Phenotypic and genetic spectrum of epilepsy with myoclonic atonic seizures

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    Objective: We aimed to describe the extent of neurodevelopmental impairments andidentify the genetic etiologies in a large cohort of patients with epilepsy with myoclonicatonic seizures (MAE).Methods: We deeply phenotyped MAE patients for epilepsy features, intellectualdisability, autism spectrum disorder, and attention-deficit/hyperactivity disorderusing standardized neuropsychological instruments. We performed exome analysis(whole exome sequencing) filtered on epilepsy and neuropsychiatric gene sets toidentify genetic etiologies.Results: We analyzed 101 patients with MAE (70% male). The median age of seizureonset was 34 months (range = 6-72 months). The main seizure types were myoclonicatonic or atonic in 100%, generalized tonic-clonic in 72%, myoclonic in 69%, absencein 60%, and tonic seizures in 19% of patients. We observed intellectual disability in62% of patients, with extremely low adaptive behavioral scores in 69%. In addition,24% exhibited symptoms of autism and 37% exhibited attention-deficit/hyperactivitysymptoms. We discovered pathogenic variants in 12 (14%) of 85 patients, includingfive previously published patients. These were pathogenic genetic variants inSYNGAP1 (n = 3), KIAA2022 (n = 2), and SLC6A1 (n = 2), as well as KCNA2,SCN2A, STX1B, KCNB1, and MECP2 (n = 1 each). We also identified three newcandidate genes, ASH1L, CHD4, and SMARCA2 in one patient each.Significance: MAE is associated with significant neurodevelopmental impairment.MAE is genetically heterogeneous, and we identified a pathogenic genetic etiologyin 14% of this cohort by exome analysis. These findings suggest that MAE is a manifestationof several etiologies rather than a discrete syndromic entity

    Cancer cell adaptation to chemotherapy

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    BACKGROUND: Tumor resistance to chemotherapy may be present at the beginning of treatment, develop during treatment, or become apparent on re-treatment of the patient. The mechanisms involved are usually inferred from experiments with cell lines, as studies in tumor-derived cells are difficult. Studies of human tumors show that cells adapt to chemotherapy, but it has been largely assumed that clonal selection leads to the resistance of recurrent tumors. METHODS: Cells derived from 47 tumors of breast, ovarian, esophageal, and colorectal origin and 16 paired esophageal biopsies were exposed to anticancer agents (cisplatin; 5-fluorouracil; epirubicin; doxorubicin; paclitaxel; irinotecan and topotecan) in short-term cell culture (6 days). Real-time quantitative PCR was used to measure up- or down-regulation of 16 different resistance/target genes, and when tissue was available, immunohistochemistry was used to assess the protein levels. RESULTS: In 8/16 paired esophageal biopsies, there was an increase in the expression of multi-drug resistance gene 1 (MDR1) following epirubicin + cisplatin + 5-fluorouracil (ECF) chemotherapy and this was accompanied by increased expression of the MDR-1 encoded protein, P-gp. Following exposure to doxorubicin in vitro, 13/14 breast carcinomas and 9/12 ovarian carcinomas showed >2-fold down-regulation of topoisomerase IIα (TOPOIIα). Exposure to topotecan in vitro, resulted in >4-fold down-regulation of TOPOIIα in 6/7 colorectal tumors and 8/10 ovarian tumors. CONCLUSION: This study suggests that up-regulation of resistance genes or down-regulation in target genes may occur rapidly in human solid tumors, within days of the start of treatment, and that similar changes are present in pre- and post-chemotherapy biopsy material. The molecular processes used by each tumor appear to be linked to the drug used, but there is also heterogeneity between individual tumors, even those with the same histological type, in the pattern and magnitude of response to the same drugs. Adaptation to chemotherapy may explain why prediction of resistance mechanisms is difficult on the basis of tumor type alone or individual markers, and suggests that more complex predictive methods are required to improve the response rates to chemotherapy
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