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  • 1
    Online Resource
    Online Resource
    Elsevier BV ; 1973
    In:  Journal of Experimental Child Psychology Vol. 15, No. 2 ( 1973-4), p. 237-246
    In: Journal of Experimental Child Psychology, Elsevier BV, Vol. 15, No. 2 ( 1973-4), p. 237-246
    Type of Medium: Online Resource
    ISSN: 0022-0965
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 1973
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  • 2
    Online Resource
    Online Resource
    American Association for the Advancement of Science (AAAS) ; 1999
    In:  Science Vol. 283, No. 5408 ( 1999-03-12), p. 1730-1733
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 283, No. 5408 ( 1999-03-12), p. 1730-1733
    Abstract: A constitutive equation based on stress-strain models of bulk solids was adapted to relate the surface pressure, compression rate, and temperature of an insoluble monolayer of monodendrons during collapse at the air-water interface. A power law relation between compression rate and surface pressure and an Arrhenius temperature dependence of the steady-state creep rate were observed in data from compression rate and creep experiments in the collapse region. These relations were combined into a single constitutive equation to calculate the temperature dependence of the collapse pressure with a maximum error of 5 percent for temperatures ranging from 10° to 25°C.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 1999
    detail.hit.zdb_id: 128410-1
    detail.hit.zdb_id: 2066996-3
    detail.hit.zdb_id: 2060783-0
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  • 3
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2010
    In:  Proceedings of the National Academy of Sciences Vol. 107, No. 48 ( 2010-11-30), p. 20709-20714
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 107, No. 48 ( 2010-11-30), p. 20709-20714
    Abstract: Cell encapsulating poly(ethylene glycol) hydrogels represent a promising approach for constructing 3D cultures designed to more closely approximate in vivo tissue environment. Improved strategies are needed, however, to optimally balance hydrogel permeability to support metabolic activities of encapsulated cells, while maintaining patternability to restore key aspects of tissue architecture. Herein, we have developed one such strategy incorporating hydrophobic nanoparticles to partially induce looser cross-linking density at the particle-hydrogel interface. Strikingly, our network design significantly increased hydrogel permeability, while only minimally affecting the matrix mechanical strength or prepolymer viscosity. This structural advantage improved viability and functions of encapsulated cells and permitted micron-scale structures to control over spatial distribution of incorporated cells. We expect that this design strategy holds promise for the development of more advanced artificial tissues that can promote high levels of cell metabolic activity and recapitulate key architectural features.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2010
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 4
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2002
    In:  Proceedings of the National Academy of Sciences Vol. 99, No. 8 ( 2002-04-16), p. 5024-5027
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 99, No. 8 ( 2002-04-16), p. 5024-5027
    Abstract: The self-organization of multicomponent tetrarosette assemblies into ordered nanostructures on graphite surfaces has been studied by atomic force microscopy (AFM). Real-space information on the level of individual molecules allowed us to analyze the underlying structure in unprecedented detail. In highly ordered nanorod domains, tetrarosettes 1 3 ⋅(DEB) 12 arrange in the form of parallel rows with a spacing of 4.6 ± 0.1 nm. High resolution AFM revealed the internal packing of the tetrarosette assemblies in these rows, which can be described by an oblique lattice with a = 2.5 ± 0.3 nm, b = 5.0 ± 0.1 nm, and γ = 122 ± 3°. The results, together with recent improvements in synthetic approaches, contribute to the development of a general strategy to develop H-bonding-based nanostructures with molecular precision.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2002
    detail.hit.zdb_id: 209104-5
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  • 5
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 39 ( 2016-09-27)
    Abstract: Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
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  • 6
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 107, No. 18 ( 2010-05-04), p. 8404-8409
    Abstract: A recently identified variant within the fat mass and obesity-associated ( FTO ) gene is carried by 46% of Western Europeans and is associated with an ~1.2 kg higher weight, on average, in adults and an ~1 cm greater waist circumference. With 〉 1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ~8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2010
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 7
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 42 ( 2016-10-18)
    Abstract: We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer’s disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid–positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 8
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 107, No. 1 ( 2010-01-05), p. 384-388
    Abstract: Loss-of-function mutations in the genes associated with primary microcephaly (MCPH) reduce human brain size by about two-thirds, without producing gross abnormalities in brain organization or physiology and leaving other organs largely unaffected [Woods CG, et al. (2005) Am J Hum Genet 76:717–728]. There is also evidence suggesting that MCPH genes have evolved rapidly in primates and humans and have been subjected to selection in recent human evolution [Vallender EJ, et al. (2008) Trends Neurosci 31:637–644]. Here, we show that common variants of MCPH genes account for some of the common variation in brain structure in humans, independently of disease status. We investigated the correlations of SNPs from four MCPH genes with brain morphometry phenotypes obtained with MRI. We found significant, sex-specific associations between common, nonexonic, SNPs of the genes CDK5RAP2 , MCPH1 , and ASPM , with brain volume or cortical surface area in an ethnically homogenous Norwegian discovery sample ( n = 287), including patients with mental illness. The most strongly associated SNP findings were replicated in an independent North American sample ( n = 656), which included patients with dementia. These results are consistent with the view that common variation in brain structure is associated with genetic variants located in nonexonic, presumably regulatory, regions.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2010
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 9
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 106, No. 49 ( 2009-12-08), p. 20954-20959
    Abstract: Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2009
    detail.hit.zdb_id: 209104-5
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  • 10
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 107, No. 22 ( 2010-06), p. 10256-10261
    Abstract: The ε4 allele of the apolipoprotein E (APOE) gene is the major genetic risk factor for Alzheimer’s disease (AD), but limited work has suggested that APOE genotype may modulate disease phenotype. Carriers of the ε4 allele have been reported to have greater medial temporal lobe (MTL) pathology and poorer memory than noncarriers. Less attention has focused on whether there are domains of cognition and neuroanatomical regions more affected in noncarriers. Further, a major potential confound of prior in vivo studies is the possibility of different rates of clinical misdiagnosis for carriers vs. noncarriers. We compared phenotypic differences in cognition and topography of regional cortical atrophy of ε4 carriers ( n = 67) vs. noncarriers ( n = 24) with mild AD from the Alzheimer’s Disease Neuroimaging Initiative, restricted to those with a cerebrospinal fluid (CSF) molecular profile consistent with AD. Between-group comparisons were made for psychometric tests and morphometric measures of cortical thickness and hippocampal volume. Carriers displayed significantly greater impairment on measures of memory retention, whereas noncarriers were more impaired on tests of working memory, executive control, and lexical access. Consistent with this cognitive dissociation, carriers exhibited greater MTL atrophy, whereas noncarriers had greater frontoparietal atrophy. Performance deficits in particular cognitive domains were associated with disproportionate regional brain atrophy within nodes of cortical networks thought to subserve these cognitive processes. These convergent cognitive and neuroanatomic findings in individuals with a CSF molecular profile consistent with AD support the hypothesis that APOE genotype modulates the clinical phenotype of AD through influence on specific large-scale brain networks.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2010
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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