Non-Isothermal Mercury Pipe Flow Turbulent Characteristics

The turbulence structure of fully-developed mercury pipe flow, with and without heat transfer, was studied using hot-film anemometry at Reynolds number of approximately 50,000. Single sensors and slanted multiple sensors were used to obtain the radial distribution of axial fluctuating velocity and temperature quantities. Isothermal data were generally in good agreement with comparable air data indicating similar velocity structure. Temperature intensity data agreed with other data in liquid metals. Axial and radial turbulent heat flux results were somewhat inconclusive. Spectra and turbulence scales were developed providing a picture of the structure

Long-range potentials and (n−1)d+ns(n-1)d+ns molecular resonances in an ultracold rydberg gas

We have calculated long-range molecular potentials of the $0_g^{+}$, $0_u^{-}$ and $1_u$ symmetries between highly-excited rubidium atoms. Strong $np+np$ potentials characterized by these symmetries are important in describing interaction-induced phenomena in the excitation spectra of high $np$ Rydberg states. Long-range molecular resonances are such phenomena and they were first reported in S.M. Farooqi {\it et al.}, Phys. Rev. Lett. {\bf 91} 183002. One class of these resonances occurs at energies corresponding to excited atom pairs $(n-1)d+ns$. Such resonances are attributed to $\ell$-mixing due to Rydberg-Rydberg interactions so that otherwise forbidden molecular transitions become allowed. We calculate molecular potentials in Hund's case (c), use them to find the resonance lineshape and compare to experimental results.Comment: 11 pages, 7 figure

Kinetic modelling and molecular dynamics simulation of ultracold neutral plasmas including ionic correlations

A kinetic approach for the evolution of ultracold neutral plasmas including interionic correlations and the treatment of ionization/excitation and recombination/deexcitation by rate equations is described in detail. To assess the reliability of the approximations inherent in the kinetic model, we have developed a hybrid molecular dynamics method. Comparison of the results reveals that the kinetic model describes the atomic and ionic observables of the ultracold plasma surprisingly well, confirming our earlier findings concerning the role of ion-ion correlations [Phys. Rev. A {\bf 68}, 010703]. In addition, the molecular dynamics approach allows one to study the relaxation of the ionic plasma component towards thermodynamical equilibrium

Photoassociative Production and Trapping of Ultracold KRb Molecules

We have produced ultracold heteronuclear KRb molecules by the process of photoassociation in a two-species magneto-optical trap. Following decay of the photoassociated KRb*, the molecules are detected using two-photon ionization and time-of-flight mass spectroscopy of KRb$^+$. A portion of the metastable triplet molecules thus formed are magnetically trapped. Photoassociative spectra down to 91 cm$^{-1}$ below the K(4$s$) + Rb (5$p_{1/2}$) asymptote have been obtained. We have made assignments to all eight of the attractive Hund's case (c) KRb* potential curves in this spectral region.Comment: 4 pages, 4 figure

Clinical Implication of Targeting of Cancer Stem Cells

The existence of cancer stem cells (CSCs) is receiving increasing interest particularly due to its potential ability to enter clinical routine. Rapid advances in the CSC field have provided evidence for the development of more reliable anticancer therapies in the future. CSCs typically only constitute a small fraction of the total tumor burden; however, they harbor self-renewal capacity and appear to be relatively resistant to conventional therapies. Recent therapeutic approaches aim to eliminate or differentiate CSCs or to disrupt the niches in which they reside. Better understanding of the biological characteristics of CSCs as well as improved preclinical and clinical trials targeting CSCs may revolutionize the treatment of many cancers. Copyright (c) 2012 S. Karger AG, Base

Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD

Genetic Influences on Cortical Regionalization in the Human Brain

SummaryAnimal data demonstrate that the development of distinct cortical areas is influenced by genes that exhibit highly regionalized expression patterns. In this paper, we show genetic patterning of cortical surface area derived from MRI data from 406 adult human twins. We mapped genetic correlations of areal expansion between selected seed regions and all other cortical locations, with the selection of seed points based on results from animal studies. “Marching seeds” and a data-driven, hypothesis-free, fuzzy-clustering approach provided convergent validation. The results reveal strong anterior-to-posterior graded, bilaterally symmetric patterns of regionalization, largely consistent with patterns previously reported in nonhuman mammalian models. Broad similarities in genetic patterning between rodents and humans might suggest a conservation of cortical patterning mechanisms, whereas dissimilarities might reflect the functionalities most essential to each species

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors