Harmonized-Multinational qEEG Norms (HarMNqEEG)

This paper extends the frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. ii) We also show that the multinational harmonized Riemannian norms produce z-scores with increased diagnostic accuracy to predict brain dysfunction at school-age produced by malnutrition only in the first year of life. iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings

Host Galaxies of Luminous Type 2 Quasars at z ~ 0.5

We present deep Gemini GMOS optical spectroscopy of nine luminous quasars at redshifts z ~ 0.5, drawn from the SDSS type 2 quasar sample. Our targets were selected to have high intrinsic luminosities (M_V < -26 mag) as indicated by the [O III] 5007 A emission-line luminosity (L_[O III]). Our sample has a median black hole mass of ~ 10^8.8 M_sun inferred assuming the local M_BH-sigma_* relation and a median Eddington ratio of ~ 0.7, using stellar velocity dispersions sigma_* measured from the G band. We estimate the contamination of the stellar continuum from scattered quasar light based on the strength of broad H-beta, and provide an empirical calibration of the contamination as a function of L_[O III]; the scattered light fraction is ~ 30% of L_5100 for objects with L_[O III] = 10^9.5 L_sun. Population synthesis indicates that young post-starburst populations (< 0.1 Gyr) are prevalent in luminous type 2 quasars, in addition to a relatively old population (> 1 Gyr) which dominates the stellar mass. Broad emission complexes around He II 4686 A with luminosities up to 10^8.3 L_sun are unambiguously detected in three out of the nine targets, indicative of Wolf-Rayet populations. Population synthesis shows that ~ 5-Myr post-starburst populations contribute substantially to the luminosities (> 50% of L_5100) of all three objects with Wolf-Rayet detections. We find two objects with double cores and four with close companions. Our results may suggest that luminous type 2 quasars trace an early stage of galaxy interaction, perhaps responsible for both the quasar and the starburst activity.Comment: 20 pages, 13 figures, 7 tables; accepted to Ap

First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data

Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a fully coherent search, based on matched filtering, which uses the position and rotational parameters obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto- noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have been developed, allowing a fully coherent search for gravitational waves from known pulsars over a fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of 11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial outliers, further studies show no significant evidence for the presence of a gravitational wave signal. Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for the first time. For an additional 3 targets, the median upper limit across the search bands is below the spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried out so far

ICAM-2 Expression Mediates a Membrane-Actin Link, Confers a Nonmetastatic Phenotype and Reflects Favorable Tumor Stage or Histology in Neuroblastoma

The actin cytoskeleton is a primary determinant of tumor cell motility and metastatic potential. Motility and metastasis are thought to be regulated, in large part, by the interaction of membrane proteins with cytoplasmic linker proteins and of these linker proteins, in turn, with actin. However, complete membrane-to-actin linkages have been difficult to identify. We used co-immunoprecipitation and competitive peptide assays to show that intercellular adhesion molecule-2 (ICAM-2)/α-actinin/actin may comprise such a linkage in neuroblastoma cells. ICAM-2 expression limited the motility of these cells and redistributed actin fibers in vitro, and suppressed development of disseminated tumors in an in vivo model of metastatic neuroblastoma. Consistent with these observations, immunohistochemical analysis demonstrated ICAM-2 expression in primary neuroblastoma tumors exhibiting features that are associated with limited metastatic disease and more favorable clinical outcome. In neuroblastoma cell lines, ICAM-2 expression did not affect AKT activation, tumorigenic potential or chemosensitivity, as has been reported for some types of transfected cells. The observed ICAM-2-mediated suppression of metastatic phenotype is a novel function for this protein, and the interaction of ICAM-2/α-actinin/actin represents the first complete membrane-linker protein-actin linkage to impact tumor cell motility in vitro and metastatic potential in an in vivo model. Current work focuses on identifying specific protein domains critical to the regulation of neuroblastoma cell motility and metastasis and on determining if these domains represent exploitable therapeutic targets

Real-Time Visualization and Quantitation of Vascular Permeability In Vivo: Implications for Drug Delivery

The leaky, heterogeneous vasculature of human tumors prevents the even distribution of systemic drugs within cancer tissues. However, techniques for studying vascular delivery systems in vivo often require complex mammalian models and time-consuming, surgical protocols. The developing chicken embryo is a well-established model for human cancer that is easily accessible for tumor imaging. To assess this model for the in vivo analysis of tumor permeability, human tumors were grown on the chorioallantoic membrane (CAM), a thin vascular membrane which overlays the growing chick embryo. The real-time movement of small fluorescent dextrans through the tumor vasculature and surrounding tissues were used to measure vascular leak within tumor xenografts. Dextran extravasation within tumor sites was selectively enhanced an interleukin-2 (IL-2) peptide fragment or vascular endothelial growth factor (VEGF). VEGF treatment increased vascular leak in the tumor core relative to surrounding normal tissue and increased doxorubicin uptake in human tumor xenografts. This new system easily visualizes vascular permeability changes in vivo and suggests that vascular permeability may be manipulated to improve chemotherapeutic targeting to tumors

Genome-Wide Gene Expression Analysis Suggests an Important Role of Hypoxia in the Pathogenesis of Endemic Osteochondropathy Kashin-Beck Disease

Kashin-Beck Disease (KBD) is an endemic osteochondropathy, the pathogenesis of which remains unclear now. In this study, we compared gene expression profiles of articular cartilage derived respectively from KBD patients and normal controls. Total RNA were isolated, amplified, labeled and hybridized to Agilent human 1A 22 k whole genome microarray chip. qRT-PCR was conducted to validate our microarray data. We detected 57 up-regulated genes (ratios ≥2.0) and 24 down-regulated genes (ratios ≤0.5) in KBD cartilage. To further identify the key genes involved in the pathogenesis of KBD, Bayesian analysis of variance for microarrays(BAM) software was applied and identified 12 potential key genes with an average ratio 6.64, involved in apoptosis, metabolism, cytokine & growth factor and cytoskeleton & cell movement. Gene Set Enrichment Analysis (GSEA) software was used to identify differently expressed gene ontology categories and pathways. GSEA found that a set of apoptosis, hypoxia and mitochondrial function related gene ontology categories and pathways were significantly up-regulated in KBD compared to normal controls. Based on the results of this study, we suggest that chronic hypoxia-induced mitochondrial damage and apoptosis might play an important role in the pathogenesis of KBD. Our efforts may help to understand the pathogenesis of KBD as well as other osteoarthrosis with similar articular cartilage lesions

Spectral Classification and Redshift Measurement for the SDSS-III Baryon Oscillation Spectroscopic Survey

(abridged) We describe the automated spectral classification, redshift determination, and parameter measurement pipeline in use for the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III (SDSS-III) as of Data Release 9, encompassing 831,000 moderate-resolution optical spectra. We give a review of the algorithms employed, and describe the changes to the pipeline that have been implemented for BOSS relative to previous SDSS-I/II versions, including new sets of stellar, galaxy, and quasar redshift templates. For the color-selected CMASS sample of massive galaxies at redshift 0.4 <~ z <~ 0.8 targeted by BOSS for the purposes of large-scale cosmological measurements, the pipeline achieves an automated classification success rate of 98.7% and confirms 95.4% of unique CMASS targets as galaxies (with the balance being mostly M stars). Based on visual inspections of a subset of BOSS galaxies, we find that ~0.2% of confidently reported CMASS sample classifications and redshifts are incorrect, and ~0.4% of all CMASS spectra are objects unclassified by the current algorithm which are potentially recoverable. The BOSS pipeline confirms that ~51.5% of the quasar targets have quasar spectra, with the balance mainly consisting of stars. Statistical (as opposed to systematic) redshift errors propagated from photon noise are typically a few tens of km/s for both galaxies and quasars, with a significant tail to a few hundreds of km/s for quasars. We test the accuracy of these statistical redshift error estimates using repeat observations, finding them underestimated by a factor of 1.19 to 1.34 for galaxies, and by a factor of 2 for quasars. We assess the impact of sky-subtraction quality, S/N, and other factors on galaxy redshift success. Finally, we document known issues, and describe directions of ongoing development.Comment: 20 pages, multiple figures. Minor changes relative to version 1. Accepted for publication in The Astronomical Journa

Brain clocks capture diversity and disparities in aging and dementia

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.</p

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

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