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Institution

University of Bergen

EducationBergen, Hordaland, Norway
About: University of Bergen is a education organization based out in Bergen, Hordaland, Norway. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 17106 authors who have published 52492 publications receiving 2009844 citations. The organization is also known as: Universitetet i Bergen & Universitas Bergensis.


Papers
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Journal ArticleDOI
TL;DR: Total homocysteine in serum/plasma is increased markedly in patients with cobalamin or folate deficiency, and decreases only when they are treated with the deficient vitamin, and justify introduction of the total homocy steine assay in the routine clinical chemistry laboratory.
Abstract: Total homocysteine is defined as the sum of all homocysteine species in plasma/serum, including free and protein-bound forms. In the present review, we compare and evaluate several techniques for the determination of total homocysteine. Because these assays include the conversion of all forms into a single species by reduction, the redistribution between free and protein-bound homocysteine through disulfide interchange does not affect the results, and total homocysteine can be measured in stored samples. Total homocysteine in whole blood increases at room temperature because of a continuous production and release of homocysteine from blood cells, but artificial increase is low if the blood sample is centrifuged within 1 h of collection or placed on ice. Different methods correlate well, and values between 5 and 15 mumol/L in fasting subjects are considered normal. Total homocysteine in serum/plasma is increased markedly in patients with cobalamin or folate deficiency, and decreases only when they are treated with the deficient vitamin. Total homocysteine is therefore of value for the diagnosis and follow-up of these deficiency states and may compensate for weaknesses of the traditional laboratory tests. In addition, total homocysteine is an independent risk factor for premature cardiovascular diseases. These disorders justify introduction of the total homocysteine assay in the routine clinical chemistry laboratory.

1,018 citations

Journal ArticleDOI
24 Nov 2001-BMJ
TL;DR: Genetic factors that increase the risk of cardiovascular disease may also be linked to pre-eclampsia, which occurs in 3-5% of pregnancies and is compatible with maternal genes for thrombophilia having an effect on therisk of pre- eClampsia and of death from cardiovascular disease.
Abstract: Objective: To assess whether mothers and fathers have a higher long term risk of death, particularly from cardiovascular disease and cancer, after the mother has had pre-eclampsia. Design: Population based cohort study of registry data. Subjects: Mothers and fathers of all 626 272 births that were the mothers9 first deliveries, recorded in the Norwegian medical birth registry from 1967 to 1992. Parents were divided into two cohorts based on whether the mother had pre-eclampsia during the pregnancy. Subjects were also stratified by whether the birth was term or preterm, given that pre-eclampsia might be more severe in preterm pregnancies. Main outcome measures: Total mortality and mortality from cardiovascular causes, cancer, and stroke from 1967 to 1992, from data from the Norwegian registry of causes of death. Results: Women who had pre-eclampsia had a 1.2-fold higher long term risk of death (95% confidence interval 1.02 to 1.37) than women who did not have pre-eclampsia. The risk in women with pre-eclampsia and a preterm delivery was 2.71-fold higher (1.99 to 3.68) than in women who did not have pre-eclampsia and whose pregnancies went to term. In particular, the risk of death from cardiovascular causes among women with pre-eclampsia and a preterm delivery was 8.12-fold higher (4.31 to 15.33). However, these women had a 0.36-fold (not significant) decreased risk of cancer. The long term risk of death was no higher among the fathers of the pre-eclamptic pregnancies than the fathers of pregnancies in which pre-eclampsia did not occur. Conclusions: Genetic factors that increase the risk of cardiovascular disease may also be linked to pre-eclampsia. A possible genetic contribution from fathers to the risk of pre-eclampsia was not reflected in increased risks of death from cardiovascular causes or cancer among fathers. What is already known on this topic Maternal and fetal genes (including those inherited from the father) may contribute to pre-eclampsia, which occurs in 3-5% of pregnancies One set of candidate genes for pre-eclampsia is the maternal genes for thrombophilia, which may increase the mother9s risk of death from cardiovascular disease What this study adds Women who have pre-eclampsia during a pregnancy that ends in a preterm delivery have an eightfold higher risk of death from cardiovascular disease compared with women who do not have pre-eclampsia and whose pregnancy goes to term Fathers of pregnancies in which pre-eclampsia occurred have no increased risk of death from cardiovascular disease These results are compatible with maternal genes for thrombophilia having an effect on the risk of pre-eclampsia and of death from cardiovascular disease

1,015 citations

Journal ArticleDOI
TL;DR: The purpose of this review is to provide an international expert opinion on the practical aspects of total homocysteine determinations in clinical practice and in the research setting and on the relevance of total Homocystinuria measurements as diagnostic or screening tests in several target populations.
Abstract: Background: Measurement of plasma total homocysteine has become common as new methods have been introduced. A wide range of disorders are associated with increased concentrations of total homocysteine. The purpose of this review is to provide an international expert opinion on the practical aspects of total homocysteine determinations in clinical practice and in the research setting and on the relevance of total homocysteine measurements as diagnostic or screening tests in several target populations. Methods: Published data available on Medline were used as the basis for the recommendations. Drafts of the recommendations were critically discussed at meetings over a period of 3 years. Outcome: This review is divided into two sections: (a) determination of homocysteine (methods and their performance, sample collection and handling, biological determinants, reference intervals, within-person variability, and methionine loading test); and (b) risk assessment and disease diagnosis (homocystinuria, folate and cobalamin deficiencies, cardiovascular disease, renal failure, psychiatric disorders and cognitive impairment, pregnancy complications and birth defects, and screening of elderly and newborns). Each of these subsections concludes with a separate series of recommendations to assist the clinician and the research scientist in making informed decisions. The review concludes with a list of unresolved questions.

1,001 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide a short overview of recent advances and some associated challenges in machine learning applied to medical image processing and image analysis, and provide a starting point for people interested in experimenting and perhaps contributing to the field of machine learning for medical imaging.
Abstract: What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when so-called deep artificial neural networks began outperforming other established models on a number of important benchmarks. Deep neural networks are now the state-of-the-art machine learning models across a variety of areas, from image analysis to natural language processing, and widely deployed in academia and industry. These developments have a huge potential for medical imaging technology, medical data analysis, medical diagnostics and healthcare in general, slowly being realized. We provide a short overview of recent advances and some associated challenges in machine learning applied to medical image processing and image analysis. As this has become a very broad and fast expanding field we will not survey the entire landscape of applications, but put particular focus on deep learning in MRI. Our aim is threefold: (i) give a brief introduction to deep learning with pointers to core references; (ii) indicate how deep learning has been applied to the entire MRI processing chain, from acquisition to image retrieval, from segmentation to disease prediction; (iii) provide a starting point for people interested in experimenting and perhaps contributing to the field of machine learning for medical imaging by pointing out good educational resources, state-of-the-art open-source code, and interesting sources of data and problems related medical imaging.

991 citations

Journal ArticleDOI
TL;DR: Gingipains from Porphyromonas gingivalis drive Alzheimer’s pathology and can be blocked with small-molecule inhibitors, suggesting that gingipain inhibitors could be valuable for treating P. gedivalis brain colonization and neurodegeneration in Alzheimer's disease.
Abstract: Porphyromonas gingivalis, the keystone pathogen in chronic periodontitis, was identified in the brain of Alzheimer's disease patients. Toxic proteases from the bacterium called gingipains were also identified in the brain of Alzheimer's patients, and levels correlated with tau and ubiquitin pathology. Oral P. gingivalis infection in mice resulted in brain colonization and increased production of Aβ1-42, a component of amyloid plaques. Further, gingipains were neurotoxic in vivo and in vitro, exerting detrimental effects on tau, a protein needed for normal neuronal function. To block this neurotoxicity, we designed and synthesized small-molecule inhibitors targeting gingipains. Gingipain inhibition reduced the bacterial load of an established P. gingivalis brain infection, blocked Aβ1-42 production, reduced neuroinflammation, and rescued neurons in the hippocampus. These data suggest that gingipain inhibitors could be valuable for treating P. gingivalis brain colonization and neurodegeneration in Alzheimer's disease.

988 citations


Authors

Showing all 17370 results

NameH-indexPapersCitations
Stephen V. Faraone1881427140298
Patrick O. Brown183755200985
Anil K. Jain1831016192151
Marc Weber1672716153502
Johan Auwerx15865395779
Leif Groop158919136056
Charles M. Perou156573202951
Bart Staels15282486638
Zhenwei Yang150956109344
G. Eigen1482188117450
Thomas Lohse1481237101631
Marco Costa1461458105096
Timothy P. Hughes14583191357
Hermann Kolanoski145127996152
Kjell Fuxe142147989846
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023149
2022448
20213,229
20203,149
20192,800
20182,648