What You Do in High School Matters: The Effects of High School GPA on Educational Attainment and Labor Market Earnings in Adulthood

Using abstracted grades and other data from Add Health, we investigate the effects of cumulative high school GPA on educational attainment and labor market earnings among a sample of young adults (ages 24-34). We estimate several models with an extensive list of control variables and high school fixed effects. Results consistently show that high school GPA is a positive and statistically significant predictor of educational attainment and earnings in adulthood. Moreover, the effects are large and economically important for each gender. Interesting and somewhat unexpected findings emerge for race. Various sensitivity tests support the stability of the core findings.High school grades; Educational attainment; Earnings; Panel data

Type three secretion system-mediated escape of Burkholderia pseudomallei into the host cytosol is critical for the activation of NFκB.

BackgroundBurkholderia pseudomallei is the causative agent of melioidosis, a potentially fatal disease endemic in Southeast Asia and Northern Australia. This Gram-negative pathogen possesses numerous virulence factors including three "injection type" type three secretion systems (T3SSs). B. pseudomallei has been shown to activate NFκB in HEK293T cells in a Toll-like receptor and MyD88 independent manner that requires T3SS gene cluster 3 (T3SS3 or T3SSBsa). However, the mechanism of how T3SS3 contributes to NFκB activation is unknown.ResultsKnown T3SS3 effectors are not responsible for NFκB activation. Furthermore, T3SS3-null mutants are able to activate NFκB almost to the same extent as wildtype bacteria at late time points of infection, corresponding to delayed escape into the cytosol. NFκB activation also occurs when bacteria are delivered directly into the cytosol by photothermal nanoblade injection.ConclusionsT3SS3 does not directly activate NFκB but facilitates bacterial escape into the cytosol where the host is able to sense the presence of the pathogen through cytosolic sensors leading to NFκB activation

Can Vertical Profiles of Tropospheric Methane on Titan Be Derived from Radio-Occultation Soundings?

The intensity of the received signal at Earth in the radio occultations of Titan is attenuated both by refractive defocusing and pressure-induced absorption from N2-N2 and CH4-N2 pairs. Because the absorption strength is different for the two sets of pairs, matching the retrieved absorptivity profile can in principle yield the vertical variation in gaseous methane in the troposphere. There are two factors that make this difficult. The first is the propagation of noise in the phase and amplitude of the received signal in the absorption retrieval. The phase data is first inverted to retrieve vertical profiles of refractivity, from which the refractive defocusing is calculated. This is then subtracted from the observed. intensity attenuation of the received signal to generate a profile of atmospheric absorption. The second problem is the uncertainty in the pressure-induced absorption coefficients. Laboratory data at radio wavelengths is only available near room temperature (see, e.g., [1] for N2-N2), and the extrapolation to the low temperatures in Titan's troposphere is not well established. Ab initio calculations by Borysow et al. [2, 3] provide absorption coefficients at low temperatures and long wavelengths, but their accuracy has come into question. We present examples from Cassini radio occultations of Titan to illustrate the difficulties. For methane mole fractions in the lower troposphere comparable to that inferred from the Huygens probe (approximately 0.05), it will be difficult to separate the contributions of N2-N2 collisions from those of N2-CH4, collisions to the retrieved absorption. However, higher concentrations of CH4 and/or a higher signal-to-noise ratio from a future uplink experiment could result in a successful separation of the two components. However, key to this are highly accurate estimates of the absorption from a combination of laboratory measurements at love temperatures and long wavelengths, and possibly improved theoretical calculations

Mapping modeled exposure of wildland fire smoke for human health studies in California

Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM2.5. The 24-h average concentration of PM2.5 from all sources in 12-km gridded output from all sources in California (2007–2013) was 4.91 μg/m3. The average concentration of fire-PM2.5 in California by year was 1.22 μg/m3 (~25% of total PM2.5). The fire-PM2.5 daily mean was estimated at 4.40 μg/m3 in a high fire year (2008). Based on the model-derived fire-PM2.5 data, 97.4% of California’s population lived in a county that experienced at least one episode of high smoke exposure (“smokewave”) from 2007–2013. Photochemical model predictions of wildfire impacts on daily average PM2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m3 bias) and 2013 (1.6 µg/m3 bias) while underestimating for 2009 (−2.1 µg/m3 bias). The modeling system isolated wildfire and PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and general additive modeling

Background A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Methods Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. Results The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. Conclusions The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data

The Tetrodotoxin Receptor of Voltage-Gated Sodium Channels—Perspectives from Interactions with μ-Conotoxins

Neurotoxin receptor site 1, in the outer vestibule of the conducting pore of voltage-gated sodium channels (VGSCs), was first functionally defined by its ability to bind the guanidinium-containing agents, tetrodotoxin (TTX) and saxitoxin (STX). Subsequent studies showed that peptide μ-conotoxins competed for binding at site 1. All of these natural inhibitors block single sodium channels in an all-or-none manner on binding. With the discovery of an increasing variety of μ-conotoxins, and the synthesis of numerous derivatives, observed interactions between the channel and these different ligands have become more complex. Certain μ-conotoxin derivatives block single-channel currents partially, rather than completely, thus enabling the demonstration of interactions between the bound toxin and the channel’s voltage sensor. Most recently, the relatively small μ-conotoxin KIIIA (16 amino acids) and its variants have been shown to bind simultaneously with TTX and exhibit both synergistic and antagonistic interactions with TTX. These interactions raise new pharmacological possibilities and place new constraints on the possible structures of the bound complexes of VGSCs with these toxins

Rare Genetic Variation in 135 Families With Family History Suggestive of X-Linked Intellectual Disability.

Families with multiple male children with intellectual disability (ID) are usually suspected of having disease due to a X-linked mode of inheritance and genetic studies focus on analysis of segregating variants in X-linked genes. However, the genetic cause of ID remains elusive in approximately 50% of affected individuals. Here, we report the analysis of next-generation sequencing data in 274 affected individuals from 135 families with a family history suggestive of X-linked ID. Genetic diagnoses were obtained for 19% (25/135) of the families, and 24% (33/135) had a variant of uncertain significance. In 12% of cases (16/135), the variants were not shared within the family, suggesting genetic heterogeneity and phenocopies are frequent. Of all the families with reportable variants (43%, 58/135), we observed that 55% (32/58) were in X-linked genes, but 38% (22/58) were in autosomal genes, while the remaining 7% (4/58) had multiple variants in genes with different modes on inheritance. This study highlights that in families with multiple affected males, X linkage should not be assumed, and both individuals should be considered, as different genetic etiologies are common in apparent familial cases

Climate-Induced Boreal Forest Change: Predictions versus Current Observations

For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change

Modeling regional-scale wildland fire emissions with the wildland fire emissions information system

As carbon modeling tools become more comprehensive, spatial data are needed to improve quantitative maps of carbon emissions from fire. The Wildland Fire Emissions Information System (WFEIS) provides mapped estimates of carbon emissions from historical forest fires in the United States through a web browser. WFEIS improves access to data and provides a consistent approach to estimating emissions at landscape, regional, and continental scales. The system taps into data and tools developed by the U.S. Forest Service to describe fuels, fuel loadings, and fuel consumption and merges information from the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration on fire location and timing. Currently, WFEIS provides web access to Moderate Resolution Imaging Spectroradiometer (MODIS) burned area for North America and U.S. fire-perimeter maps from the Monitoring Trends in Burn Severity products from the USGS, overlays them on 1-km fuel maps for the United States, and calculates fuel consumption and emissions with an open-source version of the Consume model. Mapped fuel moisture is derived from daily meteorological data from remote automated weather stations. In addition to tabular output results, WFEIS produces multiple vector and raster formats. This paper provides an overview of the WFEIS system, including the web-based system functionality and datasets used for emissions estimates. WFEIS operates on the web and is built using open-source software components that work with open international standards such as keyhole markup language (KML). Examples of emissions outputs from WFEIS are presented showing that the system provides results that vary widely across the many ecosystems of North America and are consistent with previous emissions modeling estimates and products