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The MR signal is sensitive to diffusion. This effect can be increased by the use of large, balanced bipolar gradients. The gradient systems of MR scanners are calibrated at installation and during regular servicing visits. Because the measured apparent diffusion constant (ADC) depends on the square of the amplitude of the diffusion sensitizing gradients, errors in the gradient calibration are exaggerated. If the error is varying among the different gradient axes, it will affect the estimated degree of anisotropy. To assess the gradient calibration accuracy in a whole-body MRI scanner, ADC values were calculated for a uniform water phantom along each gradient direction while monitoring the temperature. Knowledge of the temperature allows the expected diffusion constant of water to be calculated independent of the MRI measurement. It was found that the gradient axes (±x, ±y, ±z) were calibrated differently, resulting in offset ADC values. A method is presented to rescale the amplitude of each of the six principal gradient axes within the MR pulse sequence. The scaling factor is the square root of the ratio of the expected and observed diffusion constants. In addition, fiber tracking results in the human brain were noticeably affected by improving the gradient system calibration. Magn Reson Med 58:763–768, 2007. © 2007 Wiley-Liss, Inc. Keywords: diffusion tensor imaging, apparent diffusion constant, magnetic field gradient, fibre tracking, anisotropy
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented, and used with simulations from the HadCM3 and FAMOUS climate models to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Global modelled (BIOME4) biome distributions over time generally agree well with those inferred from pollen data. The two climate models show good agreement in global net primary productivity (NPP). NPP is strongly influenced by atmospheric carbon dioxide (CO2) concentrations through CO2 fertilization. The combined effects of modelled changes in vegetation and (via a simple model) soil carbon result in a global terrestrial carbon storage at the Last Glacial Maximum that is 210–470 Pg C less than in pre-industrial time. Without the contribution from exposed glacial continental shelves the reduction would be larger, 330–960 Pg C. Other intervals of low terrestrial carbon storage include stadial intervals at 108 and 85 kaBP, and between 60 and 65 kaBP during Marine Isotope Stage 4. Terrestrial carbon storage, determined by the balance of global NPP and decomposition, influences the stable carbon isotope composition (δ 13C) of seawater because terrestrial organic carbon is depleted in 13C. Using a simple carbon-isotope mass balance equation we find agreement in trends between modelled ocean δ 13C based on modelled land carbon storage, and palaeo-archives of ocean δ 13C, confirming that terrestrial carbon storage variations may be important drivers of ocean δ 13 C changes.
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.
Rare copy-number variation (CNV) is an important source of risk for autism spectrum disorders (ASDs). We analyzed 2,446 ASD-affected families and confirmed an excess of genic deletions and duplications in affected versus control groups (1.41-fold, p = 1.0 × 10(-5)) and an increase in affected subjects carrying exonic pathogenic CNVs overlapping known loci associated with dominant or X-linked ASD and intellectual disability (odds ratio = 12.62, p = 2.7 × 10(-15), ∼3% of ASD subjects). Pathogenic CNVs, often showing variable expressivity, included rare de novo and inherited events at 36 loci, implicating ASD-associated genes (CHD2, HDAC4, and GDI1) previously linked to other neurodevelopmental disorders, as well as other genes such as SETD5, MIR137, and HDAC9. Consistent with hypothesized gender-specific modulators, females with ASD were more likely to have highly penetrant CNVs (p = 0.017) and were also overrepresented among subjects with fragile X syndrome protein targets (p = 0.02). Genes affected by de novo CNVs and/or loss-of-function single-nucleotide variants converged on networks related to neuronal signaling and development, synapse function, and chromatin regulation.
Background: Since sorafenib has shown activity in different tumour types and gemcitabine regimens improved the outcome for biliary tract cancer (BTC) patients, we evaluated first-line gemcitabine plus sorafenib in a double-blind phase II study.
Patients and methods: 102 unresectable or metastatic BTC patients with histologically proven adenocarcinoma of gallbladder or intrahepatic bile ducts, Eastern Cooperative Oncology Group (ECOG) 0–2 were randomised to gemcitabine (1000 mg/m2 once weekly, first 7-weeks + 1-week rest followed by once 3-weeks + 1-week rest) plus sorafenib (400 mg twice daily) or placebo. Treatment continued until progression or unacceptable toxicity. Tumour samples were prospectively stained for sorafenib targets and potential biomarkers. Serum samples (first two cycles) were measured for vascular endothelial growth factors (VEGFs), vascular endothelial growth factor receptor 2 (VEGFR-2) and stromal cell-derived factor 1 (SDF1)α by enzyme-linked immunosorbent assay (ELISA).
Results: Gemcitabine plus sorafenib was generally well tolerated. Four and three patients achieved partial responses in the sorafenib and placebo groups, respectively. There was no difference in the primary end-point, median progression-free survival (PFS) for gemcitabine plus sorafenib versus gemcitabine plus placebo (3.0 versus 4.9 months, P = 0.859), and no difference for median overall survival (OS) (8.4 versus 11.2 months, P = 0.775). Patients with liver metastasis after resection of primary BTC survived longer with sorafenib (P = 0.019) compared to placebo. Patients who developed hand-foot syndrome (HFS) showed longer PFS and OS than patients without HFS. Two sorafenib targets, VEGFR-2 and c-kit, were not expressed in BTC samples. VEGFR-3 and Hif1α were associated with lymph node metastases and T stage. Absence of PDGFRβ expression correlated with longer PFS.
Conclusion: The addition of sorafenib to gemcitabine did not demonstrate improved efficacy in advanced BTC patients. Biomarker subgroup analysis suggested that some patients might benefit from combined treatment.
The purpose of this study was to investigate which social groups are perceived as a threat target and which are perceived as a threat source during the COVID-19 outbreak. In a German sample (N = 1454) we examined perceptions of social groups ranging from those that are psychologically close and smaller (family, friends, neighbors) to those that are more distal and larger (people living in Germany, humankind). We hypothesized that psychologically closer groups would be perceived as less affected by COVID-19 as well as less threatening than more psychologically distal groups. Based on social identity theorizing, we also hypothesized that stronger identification with humankind would change these patterns. Furthermore, we explored how these threat perceptions relate to adherence to COVID-19 health guidelines. In line with our hypotheses, latent random-slope modelling revealed that psychologically distal and larger groups were perceived as more affected by COVID-19 and as more threatening than psychologically closer and smaller groups. Including identification with humankind as a predictor into the threat target model resulted in a steeper increase in threat target perception patterns, whereas identification with humankind did not predict differences in threat source perceptions. Additionally, an increase in threat source perceptions across social groups was associated with more adherence to health guidelines, whereas an increase in threat target perceptions was not. We fully replicated these findings in a subgroup from the original sample (N = 989) four weeks later. We argue that societal recovery from this and other crises will be supported by an inclusive approach informed by a sense of our common identity as human beings.