GLORIA

GEOMAR Library Ocean Research Information Access

X

Ihre E-Mail wurde erfolgreich gesendet. Bitte prüfen Sie Ihren Maileingang.

Leider ist ein Fehler beim E-Mail-Versand aufgetreten. Bitte versuchen Sie es erneut.

Vorgang fortführen?

Exportieren
Filter
  • Proceedings of the National Academy of Sciences  (5)
  • 1
    Online-Ressource
    Online-Ressource
    Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 2 ( 2023-01-10)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 2 ( 2023-01-10)
    Kurzfassung: The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or that lack neuroanatomic interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training on the MRIs of 4,681 cognitively normal (CN) participants and testing on 1,170 CN participants from an independent sample. BA estimation errors are notably lower than those of previous studies. At both individual and cohort levels, the CNN provides detailed anatomic maps of brain aging patterns that reveal sex dimorphisms and neurocognitive trajectories in adults with mild cognitive impairment (MCI, N  = 351) and Alzheimer’s disease (AD, N  = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2214634120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2023
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 2
    Online-Ressource
    Online-Ressource
    Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 22 ( 2018-05-29)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 22 ( 2018-05-29)
    Kurzfassung: Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets ( n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1718418115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2018
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 3
    Online-Ressource
    Online-Ressource
    Statistical tests and identifiability conditions for pooling and analyzing multisite datasets
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 7 ( 2018-02-13), p. 1481-1486
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 7 ( 2018-02-13), p. 1481-1486
    Kurzfassung: When sample sizes are small, the ability to identify weak (but scientifically interesting) associations between a set of predictors and a response may be enhanced by pooling existing datasets. However, variations in acquisition methods and the distribution of participants or observations between datasets, especially due to the distributional shifts in some predictors, may obfuscate real effects when datasets are combined. We present a rigorous statistical treatment of this problem and identify conditions where we can correct the distributional shift. We also provide an algorithm for the situation where the correction is identifiable. We analyze various properties of the framework for testing model fit, constructing confidence intervals, and evaluating consistency characteristics. Our technical development is motivated by Alzheimer’s disease (AD) studies, and we present empirical results showing that our framework enables harmonizing of protein biomarkers, even when the assays across sites differ. Our contribution may, in part, mitigate a bottleneck that researchers face in clinical research when pooling smaller sized datasets and may offer benefits when the subjects of interest are difficult to recruit or when resources prohibit large single-site studies.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1719747115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2018
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 4
    Online-Ressource
    Online-Ressource
    Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 15 ( 2022-04-12)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 15 ( 2022-04-12)
    Kurzfassung: Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub ( https://covid19forecasthub.org/ ) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2113561119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2022
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 5
    Online-Ressource
    Online-Ressource
    Discovery of active off-axis hydrothermal vents at 9° 54′N East Pacific Rise
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 30 ( 2022-07-26)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 30 ( 2022-07-26)
    Kurzfassung: Comprehensive knowledge of the distribution of active hydrothermal vent fields along midocean ridges is essential to understanding global chemical and heat fluxes and endemic faunal distributions. However, current knowledge is biased by a historical preference for on-axis surveys. A scarcity of high-resolution bathymetric surveys in off-axis regions limits vent identification, which implies that the number of vents may be underestimated. Here, we present the discovery of an active, high-temperature, off-axis hydrothermal field on a fast-spreading ridge. The vent field is located 750 m east of the East Pacific Rise axis and ∼7 km north of on-axis vents at 9° 50′N, which are situated in a 50- to 100-m-wide trough. This site is currently the largest vent field known on the East Pacific Rise between 9 and 10° N. Its proximity to a normal fault suggests that hydrothermal fluid pathways are tectonically controlled. Geochemical evidence reveals deep fluid circulation to depths only 160 m above the axial magma lens. Relative to on-axis vents at 9° 50′N, these off-axis fluids attain higher temperatures and pressures. This tectonically controlled vent field may therefore exhibit greater stability in fluid composition, in contrast to more dynamic, dike-controlled, on-axis vents. The location of this site indicates that high-temperature convective circulation cells extend to greater distances off axis than previously realized. Thorough high-resolution mapping is necessary to understand the distribution, frequency, and physical controls on active off-axis vent fields so that their contribution to global heat and chemical fluxes and role in metacommunity dynamics can be determined.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2205602119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2022
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
Schließen ⊗
Diese Webseite nutzt Cookies und das Analyse-Tool Matomo. Weitere Informationen finden Sie hier...