35 research outputs found
Lorentz TEM imaging of stripe structures embedded in a soft magnetic matrix
N\'eel walls in soft magnetic NiFe/NiFeGa hybrid stripe structures surrounded
by a NiFe film are investigated by high resolution Lorentz transmission
electron microscopic imaging. An anti-parallel orientation of magnetization in
1000 nm wide neighboring unirradiated-irradiated stripes is observed by forming
high angle domain walls during magnetization reversal. Upon downscaling the
stripe structure size from 1000 nm to 200 nm a transition from a discrete
domain pattern to an effective magnetic medium is observed for external
magnetic field reversal. This transition is associated with vanishing ability
of hosting high angle domain walls between adjacent stripes. The investigation
also demonstrated the potentiality of Lorentz microscopy to image periodic
stripe structures well under micron length-scale.Comment: 7 pages, 6 figure
HiNO: An Approach for Inferring Hierarchical Organization from Regulatory Networks
BACKGROUND: Gene expression as governed by the interplay of the components of regulatory networks is indeed one of the most complex fundamental processes in biological systems. Although several methods have been published to unravel the hierarchical structure of regulatory networks, weaknesses such as the incorrect or inconsistent assignment of elements to their hierarchical levels, the incapability to cope with cyclic dependencies within the networks or the need for a manual curation to retrieve non-overlapping levels remain unsolved. METHODOLOGY/RESULTS: We developed HiNO as a significant improvement of the so-called breadth-first-search (BFS) method. While BFS is capable of determining the overall hierarchical structures from gene regulatory networks, it especially has problems solving feed-forward type of loops leading to conflicts within the level assignments. We resolved these problems by adding a recursive correction approach consisting of two steps. First each vertex is placed on the lowest level that this vertex and its regulating vertices are assigned to (downgrade procedure). Second, vertices are assigned to the next higher level (upgrade procedure) if they have successors with the same level assignment and have themselves no regulators. We evaluated HiNO by comparing it with the BFS method by applying them to the regulatory networks from Saccharomyces cerevisiae and Escherichia coli, respectively. The comparison shows clearly how conflicts in level assignment are resolved in HiNO in order to produce correct hierarchical structures even on the local levels in an automated fashion. CONCLUSIONS: We showed that the resolution of conflicting assignments clearly improves the BFS-method. While we restricted our analysis to gene regulatory networks, our approach is suitable to deal with any directed hierarchical networks structure such as the interaction of microRNAs or the action of non-coding RNAs in general. Furthermore we provide a user-friendly web-interface for HiNO that enables the extraction of the hierarchical structure of any directed regulatory network. AVAILABILITY: HiNO is freely accessible at http://mips.helmholtz-muenchen.de/hino/
Neuropsychosocial profiles of current and future adolescent alcohol misusers
A comprehensive account of the causes of alcohol misuse must accommodate individual differences in biology, psychology and environment, and must disentangle cause and effect. Animal models1 can demonstrate the effects of neurotoxic substances; however, they provide limited insight into the psycho-social and higher cognitive factors involved in the initiation of substance use and progression to misuse. One can search for pre-existing risk factors by testing for endophenotypic biomarkers2 in non-using relatives; however, these relatives may have personality or neural resilience factors that protect them from developing dependence3. A longitudinal study has potential to identify predictors of adolescent substance misuse, particularly if it can incorporate a wide range of potential causal factors, both proximal and distal, and their influence on numerous social, psychological and biological mechanisms4. Here we apply machine learning to a wide range of data from a large sample of adolescents (n = 692) to generate models of current and future adolescent alcohol misuse that incorporate brain structure and function, individual personality and cognitive differences, environmental factors (including gestational cigarette and alcohol exposure), life experiences, and candidate genes. These models were accurate and generalized to novel data, and point to life experiences, neurobiological differences and personality as important antecedents of binge drinking. By identifying the vulnerability factors underlying individual differences in alcohol misuse, these models shed light on the aetiology of alcohol misuse and suggest targets for prevention
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Differential predictors for alcohol use in adolescents as a function of familial risk
Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions
Differential predictors for alcohol use in adolescents as a function of familial risk
Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions
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Introducing artificial length scales to tailor magnetic properties
Magnetism is a collective phenomenon. Hence, a local variation on the nanoscale of material properties, which act on the magnetic properties, affects the overall magnetism in an intriguing way. Of particular importance are the length scales on which a material property changes. These might be related to the exchange length, the domain wall width, a typical roughness correlation length, or a length scale introduced by patterning of the material. Here we report on the influence of two artificially created length scales: (i) ion erosion templates that serve as a source of a predefined surface morphology (ripple structure) and hence allow for the investigation of roughness phenomena. It is demonstrated that the ripple wave length can be easily tuned over a wide range (25–175 nm) by varying the primary ion erosion energy. The effect of this ripple morphology on the induced uniaxial magnetic anisotropy in soft magnetic Permalloy films is studied. Only below a ripple wavelength threshold (≈60 nm) is a significant induced magnetic anisotropy found. Above this threshold the corrugated Permalloy film acts as a flat film. This cross-over is discussed in the frame of dipolar interactions giving rise to the induced anisotropies. (ii) Ion implantation through a lithographically defined mask, which is used for a magnetic property patterning on various length scales. The resulting magnetic properties are neither present in non-implanted nor in homogeneously implanted films. Here new insight is gained by the comparison of different stripe patterning widths ranging from 1 to 10 μm. In addition, the appearance of more complicated magnetic domain structures, i.e. spin-flop domain configurations and head-on domain walls, during hard axis magnetization reversal is demonstrated. In both cases the magnetic properties, the magnetization reversal process as well as the magnetic domain configurations depend sensitively on the artificially introduced length scale