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Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability
(2023)
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.
National greenhouse gas inventories (GHGIs) are submitted annually to the United Nations Framework Convention on Climate Change (UNFCCC). They are estimated in compliance with Intergovernmental Panel on Climate Change (IPCC) methodological guidance using activity data, emission factors and facility-level measurements. For some sources, the outputs from these calculations are very uncertain. Inverse modelling techniques that use high-quality, long-term measurements of atmospheric gases have been developed to provide independent verification of national GHGIs. This is considered good practice by the IPCC as it helps national inventory compilers to verify reported emissions and to reduce emission uncertainty. Emission estimates from the InTEM (Inversion Technique for Emission Modelling) model are presented for the UK for the hydrofluorocarbons (HFCs) reported to the UNFCCC (HFC-125, HFC-134a, HFC-143a, HFC-152a, HFC-23, HFC-32, HFC-227ea, HFC-245fa, HFC-43-10mee and HFC-365mfc). These HFCs have high global warming potentials (GWPs), and the global background mole fractions of all but two are increasing, thus highlighting their relevance to the climate and a need for increasing the accuracy of emission estimation for regulatory purposes. This study presents evidence that the long-term annual increase in growth of HFC-134a has stopped and is now decreasing. For HFC-32 there is an early indication, its rapid global growth period has ended, and there is evidence that the annual increase in global growth for HFC-125 has slowed from 2018. The inverse modelling results indicate that the UK implementation of European Union regulation of HFC emissions has been successful in initiating a decline in UK emissions from 2018. Comparison of the total InTEM UK HFC emissions in 2020 with the average from 2009–2012 shows a drop of 35 %, indicating progress toward the target of a 79 % decrease in sales by 2030. The total InTEM HFC emission estimates (2008–2018) are on average 73 (62–83) % of, or 4.3 (2.7–5.9) Tg CO2-eq yr−1 lower than, the total HFC emission estimates from the UK GHGI. There are also significant discrepancies between the two estimates for the individual HFCs.
National Greenhouse Gas Inventories (GHGI) are submitted annually to the United Nations Framework Convention on Climate Change (UNFCCC). They are estimated in compliance with Intergovernmental Panel on Climate Change (IPCC) methodological guidance using activity data, emission factors and facility-level measurements. For some sources, the outputs from these calculations are very uncertain. Inverse modelling techniques that use high-quality, long-term measurements of atmospheric gases have been developed to provide independent verification of national GHGI. This is considered good practice by the IPCC as it helps national inventory compilers to verify reported emissions and to reduce emission uncertainty. Emission estimates from the InTEM (Inversion Technique for Emissions Modelling) model are presented for the UK for the hydrofluorocarbons (HFCs) reported to the UNFCCC (HFC-125, HFC-134a, HFC-143a, HFC-152a, HFC-23, HFC-32, HFC-227ea, HFC-245fa, HFC-43-10mee and HFC-365mfc). These HFCs have high Global Warming Potentials (GWPs) and the global background mole fractions of all but two are increasing, thus highlighting their relevance to the climate and a need for increasing the accuracy of emission estimation for regulatory purposes. This study presents evidence that the long-term annual increase in growth of HFC-134a has stopped and is now decreasing. For HFC-32 there is an early indication its rapid global growth period has ended, and there is evidence that the annual increase in global growth for HFC-125 has slowed from 2018. The inverse modelling results indicate that the UK implementation of European Union regulation of HFC emissions has been successful in initiating a decline in UK emissions in the since 2018. Comparison of the total InTEM UK HFC emissions in 2020 with the average from 2009–2012 shows a drop of 35%, indicating progress toward the target of a 79% decrease in sales by 2030. The total InTEM HFC emission estimates (2008–2018) are on average 73 (62–83)% of, or 4.3 (2.7–5.9) Tg CO2-eq yr−1 lower than, the total HFC emission estimates from the UK GHGI inventory. There are also significant discrepancies between the two estimates for the individual HFCs.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
233U is the fissile nuclei in the Th-U fuel cycle with a particularily small neutron capture cross setion which is on average about one order of magnitude lower than its fission cross section. Hence, the measurement of the 233U(n, γ) cross section relies on a method to accurately distinguish between capture and fission γ-rays. A measurement of the 233U α-ratio has been performed at the n_TOF facility at CERN using a so-called fission tagging setup, coupling n_TOF 's Total Absorption Calorimeter with a novel fission chamber to tag the fission γ-rays. The experimental setup is described and essential parts of the analysis are discussed. Finally, a preliminary 233U α-ratio is presented.
The design and operation of innovative nuclear systems requires a better knowledge of the capture and fission cross sections of the Pu isotopes. For the case of capture on 242Pu, a reduction of the uncertainty in the fast region down to 8-12% is required. Moreover, aiming at improving the evaluation of the fast energy range in terms of average parameters, the OECD NEA High Priority Request List (HPRL) requests high-resolution capture measurements with improved accuracy below 2 keV. The current uncertainties also affect the thermal point, where previous experiments deviate from each other by 20%. A fruitful collaboration betwen JGU Mainz and HZ Dresden-Rossendorf within the EC CHANDA project resulted in a 242Pu sample consisting of a stack of seven fission-like targets making a total of 95(4) mg of 242Pu electrodeposited on thin (11.5 μm) aluminum backings. This contribution presents the results of a set of measurements of the 242Pu(n, γ) cross section from thermal to 500 keV combining different neutron beams and techniques. The thermal point was determined at the Budapest Research Reactor by means of Neutron Activation Analysis and Prompt Gamma Analysis, and the resolved (1 eV - 4 keV) and unresolved (1 - 500 keV) resonance regions were measured using a set of four Total Energy detectors at the CERN n_TOF-EAR1.
Objective: TGF-β2 (TGF-β, transforming growth factor beta), the less-investigated sibling of TGF-β1, is deregulated in rodent and human liver diseases. Former data from bile duct ligated and MDR2 knockout (KO) mouse models for human cholestatic liver disease suggested an involvement of TGF-β2 in biliary-derived liver diseases.
Design: As we also found upregulated TGFB2 in liver tissue of patients with primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC), we now fathomed the positive prospects of targeting TGF-β2 in early stage biliary liver disease using the MDR2-KO mice. Specifically, the influence of TgfB2 silencing on the fibrotic and inflammatory niche was analysed on molecular, cellular and tissue levels.
Results: TgfB2-induced expression of fibrotic genes in cholangiocytes and hepatic stellate cellswas detected. TgfB2 expression in MDR2-KO mice was blunted using TgfB2-directed antisense oligonucleotides (AON). Upon AON treatment, reduced collagen deposition, hydroxyproline content and αSMA expression as well as induced PparG expression reflected a significant reduction of fibrogenesis without adverse effects on healthy livers. Expression analyses of fibrotic and inflammatory genes revealed AON-specific regulatory effects on Ccl3, Ccl4, Ccl5, Mki67 and Notch3 expression. Further, AON treatment of MDR2-KO mice increased tissue infiltration by F4/80-positive cells including eosinophils, whereas the number of CD45-positive inflammatory cells decreased. In line, TGFB2 and CD45 expression correlated positively in PSC/PBC patients and localised in similar areas of the diseased liver tissue.
Conclusions: Taken together, our data suggest a new mechanistic explanation for amelioration of fibrogenesis by TGF-β2 silencing and provide a direct rationale for TGF-β2-directed drug development.
233U is of key importance among the fissile nuclei in the Th-U fuel cycle. A particularity of 233U is its small neutron capture cross-section, which is on average about one order of magnitude lower than the fission cross-section. The accuracy in the measurement of the 233U capture cross-section depends crucially on an efficient capture-fission discrimination, thus a combined set-up of fission and γ-detectors is needed. A measurement of the 233U capture cross-section and capture-to-fission ratio was performed at the CERN n_TOF facility. The Total Absorption Calorimeter (TAC) of n_TOF was employed as γ-detector coupled with a novel compact ionization chamber as fission detector. A brief description of the experimental set-up will be given, and essential parts of the analysis procedure as well as the preliminary response of the set-up to capture are presented and discussed.