KOBV Portal

1

Online Resource

40th EASD Annual Meeting of the European Association for the Study of Diabetes : Munich, Germany, 5–9 September 2004

Veitenhansl, M. ; Group D.E.S.I.R. ; Stegner, K. ; [et al.]

Springer Science and Business Media LLC ; 2004

In: Diabetologia Vol. 47, No. S1 ( 2004-8), p. A1-A464

add to watchlist on the watchlist

Details

In: Diabetologia, Springer Science and Business Media LLC, Vol. 47, No. S1 ( 2004-8), p. A1-A464

Type of Medium: Online Resource

ISSN: 0012-186X , 1432-0428

URL: Article

DOI: 10.1007/BF03375463

RVK:

XA 40615

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2004

detail.hit.zdb_id: 1458993-X

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

2

Online Resource

Identifying healthy individuals with Alzheimer’s disease neuroimaging phenotypes in the UK Biobank

Azevedo, Tiago ; Bethlehem, Richard A. I. ; Whiteside, David J. ; [et al.]

Springer Science and Business Media LLC ; 2023

In: Communications Medicine Vol. 3, No. 1 ( 2023-07-20)

add to watchlist on the watchlist

Details

In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-07-20)

Abstract: Identifying prediagnostic neurodegenerative disease is a critical issue in neurodegenerative disease research, and Alzheimer’s disease (AD) in particular, to identify populations suitable for preventive and early disease-modifying trials. Evidence from genetic and other studies suggests the neurodegeneration of Alzheimer’s disease measured by brain atrophy starts many years before diagnosis, but it is unclear whether these changes can be used to reliably detect prediagnostic sporadic disease. Methods We trained a Bayesian machine learning neural network model to generate a neuroimaging phenotype and AD score representing the probability of AD using structural MRI data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Cohort (cut-off 0.5, AUC 0.92, PPV 0.90, NPV 0.93). We go on to validate the model in an independent real-world dataset of the National Alzheimer’s Coordinating Centre (AUC 0.74, PPV 0.65, NPV 0.80) and demonstrate the correlation of the AD-score with cognitive scores in those with an AD-score above 0.5. We then apply the model to a healthy population in the UK Biobank study to identify a cohort at risk for Alzheimer’s disease. Results We show that the cohort with a neuroimaging Alzheimer’s phenotype has a cognitive profile in keeping with Alzheimer’s disease, with strong evidence for poorer fluid intelligence, and some evidence of poorer numeric memory, reaction time, working memory, and prospective memory. We found some evidence in the AD-score positive cohort for modifiable risk factors of hypertension and smoking. Conclusions This approach demonstrates the feasibility of using AI methods to identify a potentially prediagnostic population at high risk for developing sporadic Alzheimer’s disease.

Type of Medium: Online Resource

ISSN: 2730-664X

URL: Article

DOI: 10.1038/s43856-023-00313-w

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2023

detail.hit.zdb_id: 3096949-9

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

3

Online Resource

Author Correction: Predicting Alzheimer’s disease progression using multi-modal deep learning approach

Lee, Garam ; Nho, Kwangsik ; Kang, Byungkon ; [et al.]

Springer Science and Business Media LLC ; 2023

In: Scientific Reports Vol. 13, No. 1 ( 2023-08-01)

add to watchlist on the watchlist

Details

In: Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2023-08-01)

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/s41598-023-39138-x

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2023

detail.hit.zdb_id: 2615211-3

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

4

Online Resource

Longitudinal measurement and hierarchical classification framework for the prediction of Alzheimer’s disease

Huang, Meiyan ; Yang, Wei ; Feng, Qianjin ; [et al.]

Springer Science and Business Media LLC ; 2017

In: Scientific Reports Vol. 7, No. 1 ( 2017-01-12)

add to watchlist on the watchlist

Details

In: Scientific Reports, Springer Science and Business Media LLC, Vol. 7, No. 1 ( 2017-01-12)

Abstract: Accurate prediction of Alzheimer’s disease (AD) is important for the early diagnosis and treatment of this condition. Mild cognitive impairment (MCI) is an early stage of AD. Therefore, patients with MCI who are at high risk of fully developing AD should be identified to accurately predict AD. However, the relationship between brain images and AD is difficult to construct because of the complex characteristics of neuroimaging data. To address this problem, we present a longitudinal measurement of MCI brain images and a hierarchical classification method for AD prediction. Longitudinal images obtained from individuals with MCI were investigated to acquire important information on the longitudinal changes, which can be used to classify MCI subjects as either MCI conversion (MCIc) or MCI non-conversion (MCInc) individuals. Moreover, a hierarchical framework was introduced to the classifier to manage high feature dimensionality issues and incorporate spatial information for improving the prediction accuracy. The proposed method was evaluated using 131 patients with MCI (70 MCIc and 61 MCInc) based on MRI scans taken at different time points. Results showed that the proposed method achieved 79.4% accuracy for the classification of MCIc versus MCInc, thereby demonstrating very promising performance for AD prediction.

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/srep39880

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2017

detail.hit.zdb_id: 2615211-3

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

5

Online Resource

Genome-wide association analysis of hippocampal volume identifies enrichment of neurogenesis-related pathways

Horgusluoglu-Moloch, Emrin ; Risacher, Shannon L. ; Crane, Paul K. ; [et al.]

Springer Science and Business Media LLC ; 2019

In: Scientific Reports Vol. 9, No. 1 ( 2019-10-10)

add to watchlist on the watchlist

Details

In: Scientific Reports, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2019-10-10)

Abstract: Adult neurogenesis occurs in the dentate gyrus of the hippocampus during adulthood and contributes to sustaining the hippocampal formation. To investigate whether neurogenesis-related pathways are associated with hippocampal volume, we performed gene-set enrichment analysis using summary statistics from a large-scale genome-wide association study (N = 13,163) of hippocampal volume from the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium and two year hippocampal volume changes from baseline in cognitively normal individuals from Alzheimer’s Disease Neuroimaging Initiative Cohort (ADNI). Gene-set enrichment analysis of hippocampal volume identified 44 significantly enriched biological pathways (FDR corrected p -value 〈 0.05), of which 38 pathways were related to neurogenesis-related processes including neurogenesis, generation of new neurons, neuronal development, and neuronal migration and differentiation. For genes highly represented in the significantly enriched neurogenesis-related pathways, gene-based association analysis identified TESC , ACVR1 , MSRB3 , and DPP4 as significantly associated with hippocampal volume. Furthermore, co-expression network-based functional analysis of gene expression data in the hippocampal subfields, CA1 and CA3, from 32 normal controls showed that distinct co-expression modules were mostly enriched in neurogenesis related pathways. Our results suggest that neurogenesis-related pathways may be enriched for hippocampal volume and that hippocampal volume may serve as a potential phenotype for the investigation of human adult neurogenesis.

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/s41598-019-50507-3

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2019

detail.hit.zdb_id: 2615211-3

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

6

Online Resource

Author Correction: Multimodal hippocampal subfield grading for Alzheimer’s disease classification

Hett, Kilian ; Ta, Vinh-Thong ; Catheline, Gwenaëlle ; [et al.]

Springer Science and Business Media LLC ; 2020

In: Scientific Reports Vol. 10, No. 1 ( 2020-06-30)

add to watchlist on the watchlist

Details

In: Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2020-06-30)

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/s41598-020-67581-7

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2020

detail.hit.zdb_id: 2615211-3

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

7

Online Resource

Prognostic relevance of gait-related cognitive functions for dementia conversion in amnestic mild cognitive impairment

Tuena, Cosimo ; Maestri, Sara ; Serino, Silvia ; [et al.]

Springer Science and Business Media LLC ; 2023

In: BMC Geriatrics Vol. 23, No. 1 ( 2023-07-31)

add to watchlist on the watchlist

Details

In: BMC Geriatrics, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2023-07-31)

Abstract: Increasing research suggests that gait abnormalities can be a risk factor for Alzheimer’s Disease (AD). Notably, there is growing evidence highlighting this risk factor in individuals with amnestic Mild Cognitive Impairment (aMCI), however further studies are needed. The aim of this study is to analyze cognitive tests results and brain-related measures over time in aMCI and examine how the presence of gait abnormalities (neurological or orthopedic) or normal gait affects these trends. Additionally, we sought to assess the significance of gait and gait-related measures as prognostic indicators for the progression from aMCI to AD dementia, comparing those who converted to AD with those who remained with a stable aMCI diagnosis during the follow-up. Methods Four hundred two individuals with aMCI from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were included. Robust linear mixed-effects models were used to study the impact of gait abnormalities on a comprehensive neuropsychological battery over 36 months while controlling for relevant medical variables at baseline. The impact of gait on brain measures was also investigated. Lastly, the Cox proportional-hazards model was used to explore the prognostic relevance of abnormal gait and neuropsychological associated tests. Results While controlling for relevant covariates, we found that gait abnormalities led to a greater decline over time in attention (DSST) and global cognition (MMSE). Intriguingly, psychomotor speed (TMT-A) and divided attention (TMT-B) declined uniquely in the abnormal gait group. Conversely, specific AD global cognition tests (ADAS-13) and auditory-verbal memory (RAVLT immediate recall) declined over time independently of gait profile. All the other cognitive tests were not significantly affected by time or by gait profile. In addition, we found that ventricles size increased faster in the abnormal gait group compared to the normal gait group. In terms of prognosis, abnormal gait (HR = 1.7), MMSE (HR = 1.09), and DSST (HR = 1.03) covariates showed a higher impact on AD dementia conversion. Conclusions The importance of the link between gait and related cognitive functions in terms of diagnosis, prognosis, and rehabilitation in aMCI is critical. We showed that in aMCI gait abnormalities lead to executive functions/attention deterioration and conversion to AD dementia.

Type of Medium: Online Resource

ISSN: 1471-2318

URL: Article

DOI: 10.1186/s12877-023-04175-8

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2023

detail.hit.zdb_id: 2059865-8

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

8

Online Resource

Lipid exchanges drove the evolution of mutualism during plant terrestrialization

Rich, Mélanie K. ; Vigneron, Nicolas ; Libourel, Cyril ; [et al.]

American Association for the Advancement of Science (AAAS) ; 2021

In: Science Vol. 372, No. 6544 ( 2021-05-21), p. 864-868

add to watchlist on the watchlist

Details

In: Science, American Association for the Advancement of Science (AAAS), Vol. 372, No. 6544 ( 2021-05-21), p. 864-868

Abstract: Symbiosis with arbuscular mycorrhizal fungi (AMF) improves plant nutrition in most land plants, and its contribution to the colonization of land by plants has been hypothesized. Here, we identify a conserved transcriptomic response to AMF among land plants, including the activation of lipid metabolism. Using gain of function, we show the transfer of lipids from the liverwort Marchantia paleacea to AMF and its direct regulation by the transcription factor WRINKLED (WRI). Arbuscules, the nutrient-exchange structures, were not formed in loss-of-function wri mutants in M. paleacea , leading to aborted mutualism. Our results show the orthology of the symbiotic transfer of lipids across land plants and demonstrate that mutualism with arbuscular mycorrhizal fungi was present in the most recent ancestor of land plants 450 million years ago.

Type of Medium: Online Resource

ISSN: 0036-8075 , 1095-9203

URL: Article

DOI: 10.1126/science.abg0929

RVK:

TA 1000

RVK:

WA 15000

Language: English

Publisher: American Association for the Advancement of Science (AAAS)

Publication Date: 2021

detail.hit.zdb_id: 128410-1

detail.hit.zdb_id: 2066996-3

detail.hit.zdb_id: 2060783-0

SSG: 11

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

9

Online Resource

Retraction Note: Aging-associated distinctive DNA methylation changes of LINE-1 retrotransposons in pure cell-free DNA from human blood

Mahmood, Wardah ; Erichsen, Lars ; Ott, Pauline ; [et al.]

Springer Science and Business Media LLC ; 2022

In: Scientific Reports Vol. 12, No. 1 ( 2022-02-22)

add to watchlist on the watchlist

Details

In: Scientific Reports, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2022-02-22)

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/s41598-022-07275-4

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2022

detail.hit.zdb_id: 2615211-3

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

10

Online Resource

Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty

Du, Lei ; Liu, Kefei ; Yao, Xiaohui ; [et al.]

Springer Science and Business Media LLC ; 2017

In: Scientific Reports Vol. 7, No. 1 ( 2017-10-25)

add to watchlist on the watchlist

Details

In: Scientific Reports, Springer Science and Business Media LLC, Vol. 7, No. 1 ( 2017-10-25)

Abstract: Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose $${\ell }_{{\bf{1}}}$$ ℓ 1 -norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the $${\ell }_{{\bf{1}}}$$ ℓ 1 -norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer’s disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/s41598-017-13930-y

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2017

detail.hit.zdb_id: 2615211-3

Bookmarklink

Library	Location	Call Number	Volume/Issue/Year	Availability

Others were also interested in ...

Online Resource

Open Access Request

Availability (electronic / print)

Link to publisher

Kooperativer Bibliotheksverbund

Berlin Brandenburg