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Neue Osteotomiemethoden wie die Laser- oder piezoelektrische Osteotomie haben Vorteile gegenüber klassischen Methoden, wie z.B. oszillierende Säge oder rotierende Instrumente. Verschiedene Indikationen zur Knochenpräparation stellen unterschiedliche Anforderungen an Methoden der Osteotomie. Demzufolge ist der Knochenverlust und die hinterlassene Oberfläche nach Präparation wichtig, um verschiedene Methoden aufgrund ihrer Effizienz und Invasivität zu beurteilen. Im Zuge dieser Studie wurden sechs Methoden untersucht. Unter diesen waren rotierende Instrumente wie diamantierte Trennscheiben oder eine Lindemannfräse, eine oszillierende Säge, ein Er:YAG-Laser, ein Er,Cr:YSGG-Laser und die piezoelektrische Osteotomie. Sechs Schnitte mit einer Tiefe von 3-5 mm wurden pro Methode in Schweinerippen präpariert. Die Breite der Schnitte wurde mit Hilfe der Auflichtmikroskopie ermittelt und nach Trocknung der Knochenproben die Oberfläche rasterelektronenmikroskopisch beurteilt. Bei allen Instrumenten waren Unterschiede bezüglich der Breite am Boden und im obersten Bereich eines Schnittes zu notieren. Je tiefer ein Schnitt war, desto schmaler wurde er. Gründe dafür waren Probleme bei der Handhabung und Probleme, einen präzisen Schnitt durchzuführen. Die Ränder des Knochens nach der piezoelektrischen Osteotomie zeigten eine zerrüttelte Oberfläche, die von Rissen dominiert wurde. Sowohl bei der Laser-, als auch bei der piezoelektrischen Osteotomie kam es im Bereich der Spongiosa zu Einschmelzungen, da die Kühlung zur Vermeidung von Hitzeentwicklungen in der Tiefe des Schnittes nicht ausreichend war.
For a virtual screening study, we introduce a combination of machine learning techniques, employing a graph kernel, Gaussian process regression and clustered cross-validation. The aim was to find ligands of peroxisome-proliferator activated receptor gamma (PPAR-y). The receptors in the PPAR family belong to the steroid-thyroid-retinoid superfamily of nuclear receptors and act as transcription factors. They play a role in the regulation of lipid and glucose metabolism in vertebrates and are linked to various human processes and diseases. For this study, we used a dataset of 176 PPAR-y agonists published by Ruecker et al. ...
Introduction: Reliable predictive and prognostic markers for routine diagnostic purposes are needed for breast cancer patients treated with neoadjuvant chemotherapy. We evaluated protein biomarkers in a cohort of 116 participants of the GeparDuo study on anthracycline/taxane-based neoadjuvant chemotherapy for operable breast cancer to test for associations with pathological complete response (pCR) and disease-free survival (DFS). Particularly, we evaluated if interactions between hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression might lead to a different clinical behavior of HR+/HER2+ coexpressing and HR+/HER2- tumors and whether subgroups of triple negative tumors might be identified by the help of Ki67 labeling index, cytokeratin 5/6 (CK5/6), as well as cyclooxygenase-2 (COX-2), and Y-box binding protein 1 (YB-1) expression. Methods: Expression analysis was performed using immunohistochemistry and silver-enhanced in situ hybridization on tissue microarrays (TMAs) of pretherapeutic core biopsies. Results: pCR rates were significantly different between the biology-based tumor types (P = 0.044) with HR+/HER2+ and HR-/HER2- tumors having higher pCR rates than HR+/HER2-tumors. Ki67 labeling index, confirmed as significant predictor of pCR in the whole cohort (P = 0.001), identified HR-/HER- (triple negative) carcinomas with a higher chance for a pCR (P = 0.006). Biology-based tumor type (P = 0.046 for HR+/HER2+vs. HR+/HER2-), Ki67 labeling index (P = 0.028), and treatment arm (P = 0.036) were independent predictors of pCR in a multivariate model. DFS was different in the biology-based tumor types (P < 0.0001) with HR+/HER2- and HR+/HER2+ tumors having the best prognosis and HR-/HER2+ tumors showing the worst outcome. Biology-based tumor type was an independent prognostic factor for DFS in multivariate analysis (P < 0.001). Conclusions: Our data demonstrate that a biology-based breast cancer classification using estrogen receptor (ER), progesterone receptor (PgR), and HER2 bears independent predictive and prognostic potential. The HR+/HER2+ coexpressing carcinomas emerged as a group of tumors with a good response rate to neoadjuvant chemotherapy and a favorable prognosis. HR+/HER2- tumors had a good prognosis irrespective of a pCR, whereas patients with HR-/HER- and HR-/HER+ tumors, especially if they had not achieved a pCR, had an unfavorable prognosis and are in need of additional treatment options. Trial registration ClinicalTrials.gov identifier: NCT00793377
The first measurement of two-pion Bose–Einstein correlations in central Pb–Pb collisions at √sNN=2.76 TeV at the Large Hadron Collider is presented. We observe a growing trend with energy now not only for the longitudinal and the outward but also for the sideward pion source radius. The pion homogeneity volume and the decoupling time are significantly larger than those measured at RHIC.
Inclusive transverse momentum spectra of primary charged particles in Pb–Pb collisions at √sNN=2.76 TeV have been measured by the ALICE Collaboration at the LHC. The data are presented for central and peripheral collisions, corresponding to 0–5% and 70–80% of the hadronic Pb–Pb cross section. The measured charged particle spectra in |η|<0.8 and 0.3<pT<20 GeV/c are compared to the expectation in pp collisions at the same sNN, scaled by the number of underlying nucleon–nucleon collisions. The comparison is expressed in terms of the nuclear modification factor RAA. The result indicates only weak medium effects (RAA≈0.7) in peripheral collisions. In central collisions, RAA reaches a minimum of about 0.14 at pT=6–7 GeV/c and increases significantly at larger pT. The measured suppression of high-pT particles is stronger than that observed at lower collision energies, indicating that a very dense medium is formed in central Pb–Pb collisions at the LHC.
The inclusive charged particle transverse momentum distribution is measured in proton–proton collisions at s=900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region (|η|<0.8) over the transverse momentum range 0.15<pT<10 GeV/c. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for |η|<0.8 is 〈pT〉INEL=0.483±0.001 (stat.)±0.007 (syst.) GeV/c and 〈pT〉NSD=0.489±0.001 (stat.)±0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger 〈pT〉 than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.
Poster presentation at 5th German Conference on Cheminformatics: 23. CIC-Workshop Goslar, Germany. 8-10 November 2009 We demonstrate the theoretical and practical application of modern kernel-based machine learning methods to ligand-based virtual screening by successful prospective screening for novel agonists of the peroxisome proliferator-activated receptor gamma (PPARgamma) [1]. PPARgamma is a nuclear receptor involved in lipid and glucose metabolism, and related to type-2 diabetes and dyslipidemia. Applied methods included a graph kernel designed for molecular similarity analysis [2], kernel principle component analysis [3], multiple kernel learning [4], and, Gaussian process regression [5]. In the machine learning approach to ligand-based virtual screening, one uses the similarity principle [6] to identify potentially active compounds based on their similarity to known reference ligands. Kernel-based machine learning [7] uses the "kernel trick", a systematic approach to the derivation of non-linear versions of linear algorithms like separating hyperplanes and regression. Prerequisites for kernel learning are similarity measures with the mathematical property of positive semidefiniteness (kernels). The iterative similarity optimal assignment graph kernel (ISOAK) [2] is defined directly on the annotated structure graph, and was designed specifically for the comparison of small molecules. In our virtual screening study, its use improved results, e.g., in principle component analysis-based visualization and Gaussian process regression. Following a thorough retrospective validation using a data set of 176 published PPARgamma agonists [8], we screened a vendor library for novel agonists. Subsequent testing of 15 compounds in a cell-based transactivation assay [9] yielded four active compounds. The most interesting hit, a natural product derivative with cyclobutane scaffold, is a full selective PPARgamma agonist (EC50 = 10 ± 0.2 microM, inactive on PPARalpha and PPARbeta/delta at 10 microM). We demonstrate how the interplay of several modern kernel-based machine learning approaches can successfully improve ligand-based virtual screening results.
This novel kind of neutron beam facility will provide 1 ns short neutron pulses with an approximately thermal energy distribution around 30 keV. The pulse repetition rate will be up to 250 kHz, the total proton number per pulse will be up to 6×1010 in the final stage, starting with a p – source current of 200 mA. A second target station will allow n – activation experiments by cw beam operation. An intense 2 MeV proton beam will drive a neutron source by the 7 Li (p,n) 7 Be reaction. The facility is under construction at the physics experimental hall of the J.W. Goethe – University. The 1m thick concrete tunnel was installed in 2009. In 2011 all rf amplifiers will be delivered and installed. Successful 200 mA proton source experiments in 2010 at a test stand will be followed by experiments on the 120 kV FRANZ terminal in 2011. The 250 kHz, 100 ns chopper in front of the rf linac is under construction, while the 2 MeV bunch compressor design was finished and the technical design of all components has started. The main accelerator cavity is under construction. First 2 MeV beam tests are expected for end of 2012.
Rapidity and transverse momentum dependence of inclusive J/ψ production in pp collisions at √s=7 TeV
(2011)
The ALICE experiment at the LHC has studied inclusive J/ψ production at central and forward rapidities in pp collisions at √s=7 TeV. In this Letter, we report on the first results obtained detecting the J/ψ through the dilepton decay into e+e− and μ+μ− pairs in the rapidity ranges |y|<0.9 and 2.5<y<4, respectively, and with acceptance down to zero pT. In the dielectron channel the analysis was carried out on a data sample corresponding to an integrated luminosity Lint=5.6 nb−1 and the number of signal events is NJ/ψ=352±32(stat.)±28(syst.); the corresponding figures in the dimuon channel are Lint=15.6 nb−1 and NJ/ψ=1924±77(stat.)±144(syst.). The measured production cross sections are σJ/ψ(|y|<0.9)=10.7±1.0(stat.)±1.6(syst.)−2.3+1.6(syst.pol.)μb and σJ/ψ(2.5<y<4)=6.31±0.25(stat.)±0.76(syst.)−1.96+0.95(syst.pol.)μb. The differential cross sections, in transverse momentum and rapidity, of the J/ψ were also measured.