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We propose a new method to estimate and isolate the localization of knowledge spillovers due to the physical presence of a person, using after-application but pre-grant deaths of differently located coinventors of the same patent. The approach estimates the differences in local citations between the deceased and still-living inventors at increasingly distant radii. Patents receive 26 percent fewer citations from within a radius of 20 miles around the deceased, relative to still-living coinventors. Differences attenuate with time and distance, are stronger when still-living coinventors live farther from the deceased, and hold for a subsample of possibly premature deaths. (JEL O31, O33, O34, R32)

Much work on innovation strategy assumes or theorizes that competition in innovation elicits duplication of research and that disclosure decreases such duplication. We validate this empirically using the American Inventors Protection Act (AIPA), three complementary identification strategies, and a new measure of blocked future patent applications. We show that AIPA-intended to reduce duplication, through default disclosure of patent applications 18 months after filing-reduced duplication in the U.S. and European patent systems. The blocking measure provides a clear and micro measure of technological competition that can be aggregated to facilitate the empirical investigation of innovation, firm strategy, and the positive and negative externalities of patenting.

Abstract Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Objective: The cardiac inwardly rectifying potassium current IK1 and its molecular correlates Kir2.1 and Kir2.2 play an important role in cardiac repolarisation and in the pathogenesis of hereditary long-QT syndrome (LQTS-7). Protein kinases A (PKA) and C (PKC) are key enzymes in adrenergic signal transduction, inducing arrhythmias in heart disease. This study investigated the regulation of Kir2.2 (KCNJ12) by PKA. Methods: Cloned Kir2.2 channels were expressed heterologously in Xenopus oocytes and currents were measured with the double-electrode voltage–clamp technique. Results: After activation of PKA by forskolin (100 μmol/l) or Ro-20-1724 (100 μmol/l), wild type currents at -120 mV were increased by 93.7% and 79.0%, respectively. Coapplication of the PKA inhibitor KT-5720 (2.5 μmol/l) attenuated this effect. No significant changes were apparent after mutation of the single PKA consensus site S430. In addition, removal of all four PKC consensus sites in Kir2.2 induced a phorbolester-mediated current increase which could be suppressed by PKA inhibitors H-89 (50 μmol/l) and KT-5720 (2.5 μmol/l). Conclusions: This study demonstrates antagonistic effects of PKA and PKC in the regulation of Kir2.2. Phosphorylation by PKC has been shown to cause an inhibition of Kir2.2 currents, whereas activation of PKA leads to current upregulation. [Copyright &y& Elsevier]

Background: MicroRNAs are regulators of gene expression, which act mainly by decreasing mRNA levels of their multiple targets. Deregulated microRNA expression has been shown for acute myeloid leukemia, a disease also characterized by altered gene expression associated with distinct genomic aberrations such as nucleophosmin (NPM1) mutations. To shed further light on the role of deregulated microRNA and gene expression in cytogenetically normal acute myeloid leukemia with NPM1 mutation we performed an integrative analysis of microRNA and mRNA expression data sets., Design and Methods: Both microRNA and gene expression profiles were investigated in samples from a cohort of adult cytogenetically normal acute myeloid leukemia patients (n=43; median age 46 years, range 23-60 years) with known NPM1 mutation status (n=23 mutated, n=20 wild-type) and the data were integratively analyzed. Putative microRNA-mRNA interactions were validated by quantitative reverse transcriptase polymerase chain reaction, western blotting and luciferase reporter assays. For selected microRNAs, sensitivity of microRNA-overexpressing cells to cytarabine treatment was tested by FACS viability and cell proliferation assays., Results: Our integrative approach of analyzing both microRNA- and gene expression profiles in parallel resulted in a refined list of putative target genes affected by NPM1 mutation-associated microRNA deregulation. Of 177 putative microRNA - target mRNA interactions we identified and validated 77 novel candidates with known or potential involvement in leukemogenesis, such as IRF2-miR-20a, KIT-miR-20a and MN1-miR-15a. Furthermore, our data showed that deregulated expression of tumor suppressor microRNAs, such as miR-29a and miR-30c, might contribute to sensitivity to cytarabine, which is observed in NPM1 mutated acute myeloid leukemia., Conclusions: Overall, our observations highlight that integrative data analysis approaches can improve insights into leukemia biology, and lead to the identification of novel microRNA - target gene interactions of potential relevance for acute myeloid leukemia treatment.

Objective: The cardiac inwardly rectifying potassium current IK1 and its molecular correlates Kir2.1 and Kir2.2 play an important role in cardiac repolarisation and in the pathogenesis of hereditary long-QT syndrome (LQTS-7). Protein kinases A (PKA) and C (PKC) are key enzymes in adrenergic signal transduction, inducing arrhythmias in heart disease. This study investigated the regulation of Kir2.2 (KCNJ12) by PKA., Methods: Cloned Kir2.2 channels were expressed heterologously in Xenopus oocytes and currents were measured with the double-electrode voltage-clamp technique., Results: After activation of PKA by forskolin (100 micromol/l) or Ro-20-1724 (100 micromol/l), wild type currents at -120 mV were increased by 93.7% and 79.0%, respectively. Coapplication of the PKA inhibitor KT-5720 (2.5 micromol/l) attenuated this effect. No significant changes were apparent after mutation of the single PKA consensus site S430. In addition, removal of all four PKC consensus sites in Kir2.2 induced a phorbolester-mediated current increase which could be suppressed by PKA inhibitors H-89 (50 micromol/l) and KT-5720 (2.5 micromol/l)., Conclusions: This study demonstrates antagonistic effects of PKA and PKC in the regulation of Kir2.2. Phosphorylation by PKC has been shown to cause an inhibition of Kir2.2 currents, whereas activation of PKA leads to current upregulation., (Copryright 2004 European Society of Cardiology)