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Institution

Lund University

EducationLund, Sweden
About: Lund University is a education organization based out in Lund, Sweden. It is known for research contribution in the topics: Population & Cancer. The organization has 42345 authors who have published 124676 publications receiving 5016438 citations. The organization is also known as: Lunds Universitet & University of Lund.


Papers
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Journal ArticleDOI
TL;DR: The COST 2100 channel model is a geometry-based stochastic channel model (GSCM) that can reproduce MIMO channels over time, frequency, and space as mentioned in this paper.
Abstract: The COST 2100 channel model is a geometry- based stochastic channel model (GSCM) that can reproduce the stochastic properties of MIMO channels over time, frequency, and space. In contrast to other popular GSCMs, the COST 2100 approach is generic and flexible, making it suitable to model multi-user or distributed MIMO scenarios. In this article a concise overview of the COST 2100 channel model is presented. Main concepts are described, together with useful implementation guidelines. Recent developments, including dense multipath components, polarization, and multi-link aspects, are also discussed.

544 citations

Journal ArticleDOI
TL;DR: In this article, the implicit assumption of many scientific and regulatory frameworks that ecosystems impacted by human pressures may revert to their original condition by suppressing the pressure was tested using coastal eutrophication.
Abstract: The implicit assumption of many scientific and regulatory frameworks that ecosystems impacted by human pressures may be reverted to their original condition by suppressing the pressure was tested using coastal eutrophication. The response to nutrient abatement of four thoroughly studied coastal ecosystems that received increased nutrient inputs between the 1970s and the 1980s showed that the trajectories of these ecosystems were not directly reversible. All four ecosystems displayed convoluted trajectories that failed to return to the reference status upon nutrient reduction. This failure is proposed to result from the broad changes in environmental conditions, all affecting ecosystem dynamics, that occurred over the 30 years spanning from the onset of eutrophication to the reduction of nutrient levels. Understanding ecosystem response to multiple shifting baselines is essential to set reliable targets for restoration efforts.

544 citations

Journal ArticleDOI
TL;DR: This work sequenced bacterial 16S rRNA from fecal samples of Aβ precursor protein (APP) transgenic mouse model and found a remarkable shift in the gut microbiota as compared to non-transgenic wild-type mice, indicating a microbial involvement in the development of Abeta amyloid pathology and suggesting that microbiota may contribute to the developed neurodegenerative diseases.
Abstract: Alzheimer's disease is the most common form of dementia in the western world, however there is no cure available for this devastating neurodegenerative disorder. Despite clinical and experimental evidence implicating the intestinal microbiota in a number of brain disorders, its impact on Alzheimer's disease is not known. To this end we sequenced bacterial 16S rRNA from fecal samples of Aβ precursor protein (APP) transgenic mouse model and found a remarkable shift in the gut microbiota as compared to non-transgenic wild-type mice. Subsequently we generated germ-free APP transgenic mice and found a drastic reduction of cerebral Aβ amyloid pathology when compared to control mice with intestinal microbiota. Importantly, colonization of germ-free APP transgenic mice with microbiota from conventionally-raised APP transgenic mice increased cerebral Aβ pathology, while colonization with microbiota from wild-type mice was less effective in increasing cerebral Aβ levels. Our results indicate a microbial involvement in the development of Abeta amyloid pathology, and suggest that microbiota may contribute to the development of neurodegenerative diseases.

544 citations

Journal ArticleDOI
TL;DR: It is concluded that the catecholamine fluorophores can be identified and distinguished by microspectrofluorometry from those of other fluorogenic monoamines known to occur in the vertebrate brain.
Abstract: This paper gives a detailed description of the glyoxylic acid fluorescence histochemical method as designed for the highly sensitive visualization of catecholamine neurons. In this method, the primary catecholamines, dopamine and noradrenaline, are efficiently converted to intensely fluorescent 2-carboxymethyl-dihydroisoquinoline derivatives in a well defined reaction with glyoxylic acid. The method is carried out on sections from fresh or glyoxylic acid-perfused tissue, which are immersed in a glyoxylic acid solution, dried, and then reacted either by heating at +100°C, or by glyoxylic acid vapour treatment at +100°C. The method has a high reproducibility, is rapid and convenient, and if desired, sections of good quality can be ready for fluorescence microscopy within half an hour after the sacrifice of the animal. The glyoxylic acid method demonstrates central and peripheral dopamine- and noradrenaline-containing neurons with an extraordinary sensitivity and precision. The entire adrenergic neuron, including the non-terminal portions of the axon and sometimes also the dendrites, becomes fluorescent, making the method ideal for neuroanatomical tracing of central catecholamine pathways. The spectral characteristics of the glyoxylic acid-induced fluorophores have been investigated, and it is concluded that the catecholamine fluorophores can be identified and distinguished by microspectrofluorometry from those of other fluorogenic monoamines known to occur in the vertebrate brain.

543 citations


Authors

Showing all 42777 results

NameH-indexPapersCitations
Yi Chen2174342293080
Fred H. Gage216967185732
Kari Stefansson206794174819
Mark I. McCarthy2001028187898
Ruedi Aebersold182879141881
Jie Zhang1784857221720
Feng Zhang1721278181865
Martin G. Larson171620117708
Michael Snyder169840130225
Unnur Thorsteinsdottir167444121009
Anders Björklund16576984268
Carl W. Cotman165809105323
Dennis R. Burton16468390959
Jaakko Kaprio1631532126320
Panos Deloukas162410154018
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023246
2022698
20216,295
20206,032
20195,584
20185,249