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Institution

University of Gothenburg

EducationGothenburg, Sweden
About: University of Gothenburg is a education organization based out in Gothenburg, Sweden. It is known for research contribution in the topics: Population & Health care. The organization has 23855 authors who have published 65241 publications receiving 2606327 citations. The organization is also known as: Göteborg University & Gothenburg University.


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Journal ArticleDOI
TL;DR: It is concluded that failing implants show a continuous decrease of stability until failure, and low RFA levels after 1 and 2 months seem to indicate an increased risk for future failure.
Abstract: OBJECTIVES: The objective of this study was to analyze the development of implant stability by repeated resonance frequency analysis (RFA) measurements during 1 year in 23 patients treated according to an immediate/early-loading protocol. The objective was also to evaluate the possible differences between failing and successful implants. MATERIAL AND METHODS: Eighty-one Branemark System implants were placed in 23 patients for immediate/early-occlusal loading in all jaw regions. Thirty of the implants were placed in extraction sockets and 62 were subjected to GBR procedures. Apart from clinical and radiographic examinations, the patients were followed with RFA at placement, prosthesis connection and after 1-3, 6 and 12 months. Statistical analyses were carried out to study the possible differences between implants that failed during the study period and implants that remained successful. RESULTS: Nine implants failed (11.2%) during the 1 year of loading. RFA showed a distinct different pattern between the implants that remained stable and the implants that were lost. The implants that failed during the course of the study showed a significantly lower stability already after 1 month. CONCLUSION: Within the limitations of this study, it is concluded that failing implants show a continuous decrease of stability until failure. Low RFA levels after 1 and 2 months seem to indicate an increased risk for future failure. This information may be used to avoid implant failure in the future by unloading implants with decreasing degree of stability with time as diagnosed with the RFA technique.

354 citations

Journal ArticleDOI
Richard Anney1, Lambertus Klei2, Dalila Pinto3, Dalila Pinto4, Joana Almeida, Elena Bacchelli5, Gillian Baird6, Nadia Bolshakova1, Sven Bölte7, Patrick Bolton8, Thomas Bourgeron9, Thomas Bourgeron10, Sean Brennan1, Jessica Brian4, Jillian P. Casey11, Judith Conroy11, Catarina Correia12, Catarina Correia13, Christina Corsello14, Emily L. Crawford15, Maretha de Jonge16, Richard Delorme, Eftichia Duketis7, Frederico Duque, Annette Estes17, Penny Farrar18, Bridget A. Fernandez19, Susan E. Folstein20, Eric Fombonne21, John R. Gilbert20, Christopher Gillberg22, Joseph T. Glessner23, Andrew Green11, Jonathan Green24, Stephen J. Guter25, Elizabeth A. Heron1, Richard Holt18, Jennifer L. Howe4, Gillian Hughes1, Vanessa Hus14, Roberta Igliozzi, Suma Jacob25, Graham Kenny1, Cecilia Kim23, Alexander Kolevzon3, Vlad Kustanovich, Clara Lajonchere, Janine A. Lamb24, Miriam Law-Smith1, Marion Leboyer10, Ann Le Couteur26, Bennett L. Leventhal27, Bennett L. Leventhal28, Xiao-Qing Liu29, Frances Lombard1, Catherine Lord30, Linda Lotspeich31, Sabata C. Lund15, Tiago R. Magalhaes13, Tiago R. Magalhaes12, Carine Mantoulan32, Christopher J. McDougle33, Christopher J. McDougle34, Nadine M. Melhem2, Alison K. Merikangas1, Nancy J. Minshew2, Ghazala Mirza18, Jeff Munson17, Carolyn Noakes4, Gudrun Nygren22, Katerina Papanikolaou35, Alistair T. Pagnamenta18, Barbara Parrini, Tara Paton4, Andrew Pickles24, David J. Posey34, Fritz Poustka7, Jiannis Ragoussis18, Regina Regan11, Wendy Roberts4, Kathryn Roeder36, Bernadette Rogé32, Michael Rutter37, Sabine Schlitt7, Naisha Shah11, Val C. Sheffield38, Latha Soorya3, Inês Sousa18, Vera Stoppioni, Nuala Sykes18, Raffaella Tancredi, Ann P. Thompson39, Susanne Thomson15, Ana Tryfon3, John Tsiantis35, Herman van Engeland16, John B. Vincent4, Fred R. Volkmar40, Jacob A. S. Vorstman16, Simon Wallace18, Kirsty Wing18, Kerstin Wittemeyer18, Shawn Wood2, Danielle Zurawiecki3, Lonnie Zwaigenbaum41, Anthony J. Bailey42, Agatino Battaglia, Rita M. Cantor43, Hilary Coon44, Michael L. Cuccaro20, Geraldine Dawson45, Geraldine Dawson46, Sean Ennis11, Christine M. Freitag7, Daniel H. Geschwind43, Jonathan L. Haines47, Sabine M. Klauck48, William M. McMahon44, Elena Maestrini5, Judith Miller44, Judith Miller23, Anthony P. Monaco18, Anthony P. Monaco49, Stanley F. Nelson43, John I. Nurnberger34, Guiomar Oliveira, Jeremy R. Parr26, Margaret A. Pericak-Vance20, Joseph Piven46, Gerard D. Schellenberg23, Stephen W. Scherer4, Astrid M. Vicente12, Astrid M. Vicente13, Thomas H. Wassink38, Ellen M. Wijsman17, Catalina Betancur50, Catalina Betancur51, Catalina Betancur52, Joseph D. Buxbaum3, Edwin H. Cook25, Louise Gallagher1, Michael Gill1, Joachim Hallmayer31, Andrew D. Paterson4, James S. Sutcliffe15, Peter Szatmari39, Veronica J. Vieland53, Hakon Hakonarson23, Bernie Devlin2 
Trinity College, Dublin1, University of Pittsburgh2, Icahn School of Medicine at Mount Sinai3, University of Toronto4, University of Bologna5, Guy's and St Thomas' NHS Foundation Trust6, Goethe University Frankfurt7, King's College London8, Pasteur Institute9, University of Paris10, University College Dublin11, University of Lisbon12, Instituto Gulbenkian de Ciência13, University of Michigan14, Vanderbilt University15, Utrecht University16, University of Washington17, University of Oxford18, Memorial University of Newfoundland19, University of Miami20, McGill University21, University of Gothenburg22, University of Pennsylvania23, University of Manchester24, University of Illinois at Chicago25, Newcastle University26, Nathan Kline Institute for Psychiatric Research27, New York University28, University of Manitoba29, Cornell University30, Stanford University31, University of Toulouse32, Harvard University33, Indiana University34, National and Kapodistrian University of Athens35, Carnegie Mellon University36, Medical Research Council37, University of Iowa38, McMaster University39, Yale University40, University of Alberta41, University of British Columbia42, University of California, Los Angeles43, University of Utah44, Autism Speaks45, University of North Carolina at Chapel Hill46, Veterans Health Administration47, German Cancer Research Center48, Tufts University49, Pierre-and-Marie-Curie University50, French Institute of Health and Medical Research51, Centre national de la recherche scientifique52, Ohio State University53
TL;DR: Stage 2 of the Autism Genome Project genome-wide association study is reported, adding 1301 ASD families and bringing the total to 2705 families analysed, and it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
Abstract: While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.

353 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated what specific types of economic freedom measures are important for growth and the robustness of the results is carefully analyzed since the potential problem with multicollinearity is one of the negative effects of decomposing an index.
Abstract: Most studies of the relation between economic freedom andgrowth of GDP have found a positive relation One problem inthis area is the choice of economic freedom measure A singlemeasure does not reflect the complex economic environment anda highly aggregated index makes it difficult to draw policyconclusions In this paper we investigate what specific typesof economic freedom measures that are important for growthThe robustness of the results is carefully analysed since thepotential problem with multicollinearity is one of thenegative effects of decomposing an index The results showthat economic freedom does matter for growth This does notmean that increasing economic freedom, defined in generalterms, is good for economic growth since some of thecategories in the index are insignificant and some of thesignificant variables have negative effects

353 citations

Journal ArticleDOI
TL;DR: Cerebrospinal fluid NFL concentration is increased by the early clinical stage of AD and is associated with cognitive deterioration and structural brain changes over time, which corroborates the contention that degeneration of large-caliber axons is an important feature of AD neurodegeneration.
Abstract: Importance The extent to which large-caliber axonal degeneration contributes to Alzheimer disease (AD) progression is unknown. Cerebrospinal fluid (CSF) neurofilament light (NFL) concentration is a general marker of damage to large-caliber myelinated axons. Objective To test whether CSF NFL concentration is associated with cognitive decline and imaging evidence of neurodegeneration and white matter change in AD. Design, Setting, and Participants A commercially available immunoassay was used to analyze CSF NFL concentration in a cohort of patients with AD (n = 95) or mild cognitive impairment (MCI) (n = 192) and in cognitively normal individuals (n = 110) from the Alzheimer’s Disease Neuroimaging Initiative. The study dates were January 2005 to December 2007. The NFL analysis was performed in November 2014. Main Outcomes and Measures Correlation was investigated among baseline CSF NFL concentration and longitudinal cognitive impairment, white matter change, and regional brain atrophy within each diagnostic group. Results Cerebrospinal fluid NFL concentration (median [interquartile range]) was higher in the AD dementia group (1479 [1134-1842] pg/mL), stable MCI group (no progression to AD during follow-up; 1182 [923-1687] pg/mL), and progressive MCI group (MCI with progression to AD dementia during follow-up; 1336 [1061-1693] pg/mL) compared with control participants (1047 [809-1265] pg/mL) ( P P = .01). In the MCI group, a higher CSF NFL concentration was associated with faster brain atrophy over time as measured by changes in whole-brain volume (β = −4177, P = .003), ventricular volume (β = 1835, P P P P P Conclusions and Relevance Cerebrospinal fluid NFL concentration is increased by the early clinical stage of AD and is associated with cognitive deterioration and structural brain changes over time. This finding corroborates the contention that degeneration of large-caliber axons is an important feature of AD neurodegeneration.

353 citations

Journal ArticleDOI
TL;DR: IGF-I functions as a putative regenerative agent in the adult CNS and is found to increase progenitor cell proliferation and new neurons, oligodendrocytes, and blood vessels in the dentate gyrus of the hippocampus.
Abstract: Apart from regulating somatic growth and metabolic processes, accumulating evidence suggests that the growth hormone (GH)/insulin-like growth factor-I (IGF-I) axis is involved in the regulation of brain growth, development, and myelination. In addition, both GH and IGF-I affect cognition and biochemistry in the adult brain. Some of the effects of GH are attributable to circulating IGF-I, while others may be due to IGF-I produced locally within the brain. Some of the shared effects in common to GH and IGF-I may also be explained by cross-talk between the GH and IGF-I transduction pathways, as indicated by recent data from other cell systems. Otherwise, it also seems that GH may act directly without involving IGF-I (either circulating or locally). Plasticity in the central nervous system (CNS) may be viewed as changes in the functional interplay between the major cell types, neurons, astrocytes, and oligodendrocytes. GH and IGF-I affect all three of these cell types in several ways. Apart from the neuroprotective effects of GH and IGF-I posited in different experimental models of CNS injury, IGF-I has been found to increase progenitor cell proliferation and new neurons, oligodendrocytes, and blood vessels in the dentate gyrus of the hippocampus. It appears that the MAPK signaling pathway is required for IGF-I-stimulated proliferation in vitro, whereas the PI3K/Akt or MAPK/Erk signaling pathway appears to mediate antiapoptotic effects. The increase of IGF-I on endothelial cell phenotype may explain the increase in cerebral arteriole density observed after GH treatment. The functional role of GH and IGF-I in the adult brain will be reviewed with reference to neurotransmitters, glucose metabolism, cerebral blood flow, gap junctional communication, dendritic arborization, exercise, enriched environment, depression, learning, memory, and aging. Briefly, these findings suggest that IGF-I functions as a putative regenerative agent in the adult CNS. Hitherto less studied regarding in these aspects, GH may have similar effects, especially as it is the main regulator of IGF-I in vivo. Some of the positive cognitive features of GH treatment are likely attributable to the mechanisms reviewed here.

353 citations


Authors

Showing all 24120 results

NameH-indexPapersCitations
Peter J. Barnes1941530166618
Luigi Ferrucci1931601181199
Richard H. Friend1691182140032
Napoleone Ferrara167494140647
Timothy A. Springer167669122421
Anders Björklund16576984268
Hua Zhang1631503116769
Kaj Blennow1601845116237
Leif Groop158919136056
Tomas Hökfelt158103395979
Johan G. Eriksson1561257123325
Naveed Sattar1551326116368
Paul Elliott153773103839
Claude Bouchard1531076115307
Hakon Hakonarson152968101604
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023145
2022539
20215,065
20204,657
20194,254
20183,850