The Effects of Decompression and Exogenous NGF on Compressed Cerebral Cortex

Voici le texte intégral du communiqué de la DFG, dans la traduction de Christophe Duhamelle (que nous remercions de nous autoriser à la diffuser ici). Des solutions alternatives au European Reference Index for the Humanities (ERIH) : la DFG à la recherche de méthodes bibliométriques adaptées aux sciences humaines et sociales Communiqué d'information n°16, 10 mars 2009 Le système scientifique ne peut exister sans que se pose la question de la qualité - autrement dit, de l'évaluation - des perf..

Identification of a New Peptide for Fibrosarcoma Tumor Targeting and Imaging In Vivo

A 12-mer amino acid peptide SATTHYRLQAAN, denominated TK4, was isolated from a phage-display library with fibrosarcoma tumor-binding activity. In vivo biodistribution analysis of TK4-displaying phage showed a significant increased phage titer in implanted tumor up to 10-fold in comparison with normal tissues after systemic administration in mouse. Competition assay confirmed that the binding of TK4-phage to tumor cells depends on the TK4 peptide. Intravenous injection of 131I-labeled synthetic TK4 peptide in mice showed a tumor retention of 3.3% and 2.7% ID/g at 1- and 4-hour postinjection, respectively. Tumor-to-muscle ratio was 1.1, 5.7, and 3.2 at 1-, 4-, and 24-hour, respectively, and tumors were imaged on a digital γ-camera at 4-hour postinjection. The present data suggest that TK4 holds promise as a lead structure for tumor targeting, and it could be further applied in the development of diagnostic or therapeutic agent

Nuclear Export Signal Mutation of Epidermal Growth Factor Receptor Enhances Malignant Phenotypes of Cancer Cells

Nuclear epidermal growth factor receptor (EGFR) has been shown to be correlated with drug resistance and a poor prognosis in patients with cancer. Previously, we have identified a tripartite nuclear localization signal (NLS) within EGFR. To comprehensively determine the functions and underlying mechanism of nuclear EGFR and its clinical implications, we aimed to explore the nuclear export signal (NES) sequence of EGFR that is responsible for interacting with the exportins. We combined in silico prediction with site-directed mutagenesis approaches and identified a putative NES motif of EGFR, which is located in amino acid residues 736-749. Mutation at leucine 747 (L747) in the EGFR NES led to increased nuclear accumulation of the protein via a less efficient release of the exportin CRM1. Interestingly, L747 with serine (L747S) and with proline (L747P) mutations were found in both tyrosine kinase inhibitor (TKI)-treated and -naïve patients with lung cancer who had acquired or de novo TKI resistance and a poor outcome. Reconstituted expression of the single NES mutant EGF

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe