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Institution

University of Antwerp

EducationAntwerp, Belgium
About: University of Antwerp is a education organization based out in Antwerp, Belgium. It is known for research contribution in the topics: Population & Context (language use). The organization has 16682 authors who have published 48837 publications receiving 1689748 citations. The organization is also known as: Universiteit Antwerpen & UAntwerp.


Papers
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Journal ArticleDOI
TL;DR: It is shown, using single-cell electrophysiology techniques, electron microscopy analysis and theoretical modelling, that nanotubes improve the responsiveness of neurons by forming tight contacts with the cell membranes that might favour electrical shortcuts between the proximal and distal compartments of the neuron.
Abstract: Carbon nanotubes have been applied in several areas of nerve tissue engineering to probe and augment cell behaviour, to label and track subcellular components, and to study the growth and organization of neural networks. Recent reports show that nanotubes can sustain and promote neuronal electrical activity in networks of cultured cells, but the ways in which they affect cellular function are still poorly understood. Here, we show, using single-cell electrophysiology techniques, electron microscopy analysis and theoretical modelling, that nanotubes improve the responsiveness of neurons by forming tight contacts with the cell membranes that might favour electrical shortcuts between the proximal and distal compartments of the neuron. We propose the 'electrotonic hypothesis' to explain the physical interactions between the cell and nanotube, and the mechanisms of how carbon nanotubes might affect the collective electrical activity of cultured neuronal networks. These considerations offer a perspective that would allow us to predict or engineer interactions between neurons and carbon nanotubes.

465 citations

Journal ArticleDOI
TL;DR: In this article, the authors measured the transverse momentum and pseudorapidity distributions in proton-proton collisions at root s = 7 TeV with the inner tracking system of the CMS detector at the LHC.
Abstract: Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at root s = 7 TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity dN(ch)/d eta vertical bar(vertical bar eta vertical bar<0.5) = 5.78 +/- 0.01(stat) +/- 0.23(stat) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from root s = 0.9 to 7 TeV is [66.1 +/- 1.0(stat) +/- 4.2(syst)]%. The mean transverse momentum is measured to be 0.545 +/- 0.005(stat) +/- 0.015(syst) GeV/c. The results are compared with similar measurements at lower energies.

464 citations

Journal ArticleDOI
TL;DR: The NFS and FIB-4 scores have similar accuracy for advanced fibrosis in patients aged >35 years, however, the specificity forAdvanced fibrosis is unacceptably low in patients ages aged ≥65 years, resulting in a high false positive rate.

463 citations

Journal ArticleDOI
TL;DR: It was concluded that the current model is adequate to model photosynthesis in elevated [CO2], and the underlying biochemistry of photosynthesis was affected, as shown by a down-regulation of the parameters Jmax and Vcmax of the order of 10%.
Abstract: The effects of elevated atmospheric CO2 concentration on growth of forest tree species are difficult to predict because practical limitations restrict experiments to much shorter than the average life-span of a tree. Long-term, processbased computer models must be used to extrapolate from shorter-term experiments. A key problem is to ensure a strong flow of information between experiments and models. In this study, meta-analysis techniques were used to summarize a suite of photosynthetic model parameters obtained from 15 field-based elevated [CO2] experiments on European forest tree species. The parameters studied are commonly used in modelling photosynthesis, and include observed light-saturated photosynthetic rates (Amax), the potential electron transport rate (Jmax), the maximum Rubisco activity (Vcmax) and leaf nitrogen concentration on mass (Nm) and area (Na) bases. Across all experiments, light-saturated photosynthesis was strongly stimulated by growth in elevated [CO2]. However, significant down-regulation of photosynthesis was also observed; when measured at the same CO2 concentration, photosynthesis was reduced by 10‐20%. The underlying biochemistry of photosynthesis was affected, as shown by a down-regulation of the parameters Jmax and Vcmax of the order of 10%. This reduction in Jmax and Vcmax was linked to the effects of elevated [CO2] on leaf nitrogen concentration. It was concluded that the current model is adequate to model photosynthesis in elevated [CO2]. Tables of model parameter values for different European forest species are given.

462 citations

Journal ArticleDOI
TL;DR: A dataset from a collaborative non-target screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non- target screening using high-resolution mass spectrometry in water analysis.
Abstract: In this article, a dataset from a collaborative non-target screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non-target screening using high-resolution mass spectrometry in water analysis. A total of 18 institutes from 12 European countries analysed an extract of the same water sample collected from the River Danube with either one or both of liquid and gas chromatography coupled with mass spectrometry detection. This article focuses mainly on the use of high resolution screening techniques with target, suspect, and non-target workflows to identify substances in environmental samples. Specific examples are given to emphasise major challenges including isobaric and co-eluting substances, dependence on target and suspect lists, formula assignment, the use of retention information, and the confidence of identification. Approaches and methods applicable to unit resolution data are also discussed. Although most substances were identified using high resolution data with target and suspect-screening approaches, some participants proposed tentative non-target identifications. This comprehensive dataset revealed that non-target analytical techniques are already substantially harmonised between the participants, but the data processing remains time-consuming. Although the objective of a “fully-automated identification workflow” remains elusive in the short term, important steps in this direction have been taken, exemplified by the growing popularity of suspect screening approaches. Major recommendations to improve non-target screening include better integration and connection of desired features into software packages, the exchange of target and suspect lists, and the contribution of more spectra from standard substances into (openly accessible) databases.

462 citations


Authors

Showing all 16957 results

NameH-indexPapersCitations
Cornelia M. van Duijn1831030146009
John Hardy1771178171694
Mark Gerstein168751149578
Hannes Jung1592069125069
Rui Zhang1512625107917
Dirk Inzé14964774468
Walter Paulus14980986252
Robin Erbacher1381721100252
Rupert Leitner136120190597
Alison Goate13672185846
Andrea Giammanco135136298093
Maria Spiropulu135145596674
Peter Robmann135143897569
Michael Tytgat134144994133
Matthew Herndon133173297466
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023137
2022460
20213,656
20203,332
20192,982
20182,844