Mehr Arbeitsplätze durch Subventionsabbau

In der Bundesrepublik Deutschland werden weit mehr Subventionen vergeben, als die offizielle Berichterstattung erkennen läßt. Sie haben im Jahr 1985 eine Höhe von rund 120 Mrd. DM erreicht und sich damit in den vergangenen zehn Jahren verdoppelt. Trotz aller Bekenntnisse zum Abbau haben die Subventionen auch in jüngster Zeit weiter kräftig zugenommen. Vor allem die Steuervergünstigungen sind rasch angestiegen. Die Ziele der Subventionspolitik sind zumeist unklar und, sofern sie erkennbar sind, oft widersprüchlich. Mit gesamtwirtschaftlichen Erfordernissen lassen sich Subventionen nicht begründen. Sie verzerren das Wettbewerbsgefüge zwischen Branchen und Unternehmen und begünstigen insbesondere strukturschwache Bereiche. Darüber hinaus fördern sie einen übermäßigen Kapitaleinsatz. Modellrechnungen zeigen: Würden die Subventionen um die Hälfte gekürzt, dann nähme die Zahl der Arbeitsplätze mittelfristig um rund eine Million zu. Außerdem könnte die Bruttowertschöpfung um (real) fast 3 vH höher ausfallen. Dies sind die Untergrenzen für die vorteilhaften Wirkungen eines Subventionsabbaus. Voraussetzung wäre, daß im gleichen Ausmaß wie die Subventionen auch die Steuern gekürzt würden. Zudem müßten die Tarifvertragsparteien zulassen, daß die Steuersenkungen bei den Unternehmen zu entsprechenden Kostenentlastungen führen. Vorgeschlagen wird ein stufenweises Programm zur gleichmäßigen Kürzung aller Subventionen um insgesamt 50 vH über fünf Jahre, kombiniert mit einer Senkung der Lohn- und Einkommensteuer sowie der Körperschaftsteuer. Bei einer linearen Verringerung der Steuersätze würde der Eingangssteuersatz bei der Lohn- und Einkommensteuer von jetzt 22 vH auf 15 vH, der Spitzensteuersatz von 56 vH auf 39 vH und die durchschnittliche steuerliche Belastung von 25 vH auf 18 vH sinken. Neue Subventionen sollten nur gewährt werden, wenn im Gegenzug alte gestrichen werden. Eine Kommission aus unabhängigen Experten könnte sowohl den Subventionsabbau als auch die Neuvergabe überwachen. Diese Aufgabe könnte auch den Rechnungshöfen übertragen werden. Außerdem sollte die Konkurrentenklage bei Subventionsentscheidungen zugelassen werden. --

Examination of Late Palaeolithic archaeological sites in northern Europe for the preservation of cryptotephra layers

We report the first major study of cryptotephra (non-visible volcanic ash layers) on Late Palaeolithic archaeological sites in northern Europe. Examination of 34 sites dating from the Last Termination reveals seven with identifiable cryptotephra layers. Preservation is observed in minerogenic and organic deposits, although tephra is more common in organic sediments. Cryptotephra layers normally occur stratigraphically above or below the archaeology. Nearby off-site palaeoclimate archives (peat bogs and lakes <0.3 km distant) were better locations for detecting tephra. However in most cases the archaeology can only be correlated indirectly with such cryptotephras. Patterns affecting the presence/absence of cryptotephra include geographic position of sites relative to the emitting volcanic centre; the influence of past atmospherics on the quantity, direction and patterns of cryptotephra transport; the nature and timing of local site sedimentation; sampling considerations and subsequent taphonomic processes. Overall, while tephrostratigraphy has the potential to improve significantly the chronology of such sites many limiting factors currently impacts the successful application

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies