Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region

White Matter Network Architecture Guides Direct Electrical Stimulation Through Optimal State Transitions

Electrical brain stimulation is currently being investigated as a therapy for neurological disease. However, opportunities to optimize such therapies are challenged by the fact that the beneficial impact of focal stimulation on both neighboring and distant regions is not well understood. Here, we use network control theory to build a model of brain network function that makes predictions about how stimulation spreads through the brain's white matter network and influences large-scale dynamics. We test these predictions using combined electrocorticography (ECoG) and diffusion weighted imaging (DWI) data who volunteered to participate in an extensive stimulation regimen. We posit a specific model-based manner in which white matter tracts constrain stimulation, defining its capacity to drive the brain to new states, including states associated with successful memory encoding. In a first validation of our model, we find that the true pattern of white matter tracts can be used to more accurately predict the state transitions induced by direct electrical stimulation than the artificial patterns of null models. We then use a targeted optimal control framework to solve for the optimal energy required to drive the brain to a given state. We show that, intuitively, our model predicts larger energy requirements when starting from states that are farther away from a target memory state. We then suggest testable hypotheses about which structural properties will lead to efficient stimulation for improving memory based on energy requirements. Our work demonstrates that individual white matter architecture plays a vital role in guiding the dynamics of direct electrical stimulation, more generally offering empirical support for the utility of network control theoretic models of brain response to stimulation

Mycoplasma genitalium Detected by Transcription-Mediated Amplification Is Associated With Chlamydia trachomatis in Adolescent Women

The clinical significance of Mycoplasma genitalium (MG) infection in adolescent women is poorly understood. We compared the prevalence of MG with that of other sexually transmitted organisms such as Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Trichomonas vaginalis (TV) and assessed the associations of MG with sexual behaviors, genitourinary symptoms, physical and laboratory findings

ARF GTPases and their GEFs and GAPs: concepts and challenges

Detailed structural, biochemical, cell biological, and genetic studies of any gene/protein are required to develop models of its actions in cells. Studying a protein family in the aggregate yields additional information, as one can include analyses of their coevolution, acquisition or loss of functionalities, structural pliability, and the emergence of shared or variations in molecular mechanisms. An even richer understanding of cell biology can be achieved through evaluating functionally linked protein families. In this review, we summarize current knowledge of three protein families: the ARF GTPases, the guanine nucleotide exchange factors (ARF GEFs) that activate them, and the GTPase-activating proteins (ARF GAPs) that have the ability to both propagate and terminate signaling. However, despite decades of scrutiny, our understanding of how these essential proteins function in cells remains fragmentary. We believe that the inherent complexity of ARF signaling and its regulation by GEFs and GAPs will require the concerted effort of many laboratories working together, ideally within a consortium to optimally pool information and resources. The collaborative study of these three functionally connected families ( \u3e /=70 mammalian genes) will yield transformative insights into regulation of cell signaling

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Cytoplasmic Polyadenylation Element Binding Protein Deficiency Stimulates PTEN and Stat3 mRNA Translation and Induces Hepatic Insulin Resistance

The cytoplasmic polyadenylation element binding protein CPEB1 (CPEB) regulates germ cell development, synaptic plasticity, and cellular senescence. A microarray analysis of mRNAs regulated by CPEB unexpectedly showed that several encoded proteins are involved in insulin signaling. An investigation of Cpeb1 knockout mice revealed that the expression of two particular negative regulators of insulin action, PTEN and Stat3, were aberrantly increased. Insulin signaling to Akt was attenuated in livers of CPEB–deficient mice, suggesting that they might be defective in regulating glucose homeostasis. Indeed, when the Cpeb1 knockout mice were fed a high-fat diet, their livers became insulin-resistant. Analysis of HepG2 cells, a human liver cell line, depleted of CPEB demonstrated that this protein directly regulates the translation of PTEN and Stat3 mRNAs. Our results show that CPEB regulated translation is a key process involved in insulin signaling

Reduced Gluteal Expression of Adipogenic and Lipogenic Genes in Black South African Women Is Associated with Obesity-Related Insulin Resistance

CONTEXT: Black South African women are less insulin sensitive than their White counterparts, despite less central and greater peripheral fat deposition. We hypothesized that this paradox may be explained, in part, by differences in the adipogenic capacity of sc adipose tissue (SAT). OBJECTIVE: Our objective was to measure adipogenic and lipogenic gene expression in abdominal and gluteal SAT depots and determine their relationships with insulin sensitivity (S(I)) in South African women. PARTICIPANTS AND DESIGN: Fourteen normal-weight [body mass index (BMI) <25 kg/m(2)] Black, 13 normal-weight White, 14 obese (BMI >30 kg/m(2)) Black, and 13 obese White premenopausal South African women participated in this cross-sectional study. MAIN OUTCOMES: S(I) (frequently sampled iv glucose tolerance test) in relation to expression of adipogenic and lipogenic genes in abdominal and gluteal SAT depots. RESULTS: With increasing BMI, Black women had less visceral fat (P = 0.03) and more abdominal (P = 0.017) and gynoid (P = 0.041) SAT but had lower S(I) (P < 0.01) than White women. The expression of adipogenic and lipogenic genes was proportionately lower with obesity in Black but not White women in the gluteal and deep SAT depots (P < 0.05 for ethnicity × BMI effect). In Black women only, the expression of these genes correlated positively with S(I) (all P < 0.05), independently of age and fat mass. CONCLUSIONS: Obese Black women have reduced SAT expression of adipogenic and lipogenic genes compared with White women, which associates with reduced S(I). These findings suggest that obesity in Black women impairs SAT adipogenesis and storage, potentially leading to insulin resistance and increased risk of type 2 diabetes

Practical considerations for measuring the effective reproductive number, Rt.

Estimation of the effective reproductive number Rt is important for detecting changes in disease transmission over time. During the Coronavirus Disease 2019 (COVID-19) pandemic, policy makers and public health officials are using Rt to assess the effectiveness of interventions and to inform policy. However, estimation of Rt from available data presents several challenges, with critical implications for the interpretation of the course of the pandemic. The purpose of this document is to summarize these challenges, illustrate them with examples from synthetic data, and, where possible, make recommendations. For near real-time estimation of Rt, we recommend the approach of Cori and colleagues, which uses data from before time t and empirical estimates of the distribution of time between infections. Methods that require data from after time t, such as Wallinga and Teunis, are conceptually and methodologically less suited for near real-time estimation, but may be appropriate for retrospective analyses of how individuals infected at different time points contributed to the spread. We advise caution when using methods derived from the approach of Bettencourt and Ribeiro, as the resulting Rt estimates may be biased if the underlying structural assumptions are not met. Two key challenges common to all approaches are accurate specification of the generation interval and reconstruction of the time series of new infections from observations occurring long after the moment of transmission. Naive approaches for dealing with observation delays, such as subtracting delays sampled from a distribution, can introduce bias. We provide suggestions for how to mitigate this and other technical challenges and highlight open problems in Rt estimation

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination