Showing papers by "Northwestern University published in 2016"

Observation of Gravitational Waves from a Binary Black Hole Merger

Abstract: On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of $1.0 \times 10^{-21}$. It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equivalent to a significance greater than 5.1 {\sigma}. The source lies at a luminosity distance of $410^{+160}_{-180}$ Mpc corresponding to a redshift $z = 0.09^{+0.03}_{-0.04}$. In the source frame, the initial black hole masses are $36^{+5}_{-4} M_\odot$ and $29^{+4}_{-4} M_\odot$, and the final black hole mass is $62^{+4}_{-4} M_\odot$, with $3.0^{+0.5}_{-0.5} M_\odot c^2$ radiated in gravitational waves. All uncertainties define 90% credible intervals.These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

GW151226: observation of gravitational waves from a 22-solar-mass binary black hole coalescence

Abstract: We report the observation of a gravitational-wave signal produced by the coalescence of two stellar-mass black holes. The signal, GW151226, was observed by the twin detectors of the Laser Interferometer Gravitational-Wave Observatory (LIGO) on December 26, 2015 at 03:38:53 UTC. The signal was initially identified within 70 s by an online matched-filter search targeting binary coalescences. Subsequent off-line analyses recovered GW151226 with a network signal-to-noise ratio of 13 and a significance greater than 5 σ. The signal persisted in the LIGO frequency band for approximately 1 s, increasing in frequency and amplitude over about 55 cycles from 35 to 450 Hz, and reached a peak gravitational strain of 3.4+0.7−0.9×10−22. The inferred source-frame initial black hole masses are 14.2+8.3−3.7M⊙ and 7.5+2.3−2.3M⊙ and the final black hole mass is 20.8+6.1−1.7M⊙. We find that at least one of the component black holes has spin greater than 0.2. This source is located at a luminosity distance of 440+180−190 Mpc corresponding to a redshift 0.09+0.03−0.04. All uncertainties define a 90 % credible interval. This second gravitational-wave observation provides improved constraints on stellar populations and on deviations from general relativity.

High-efficiency two-dimensional Ruddlesden–Popper perovskite solar cells

Abstract: Three-dimensional organic-inorganic perovskites have emerged as one of the most promising thin-film solar cell materials owing to their remarkable photophysical properties, which have led to power conversion efficiencies exceeding 20 per cent, with the prospect of further improvements towards the Shockley-Queisser limit for a single‐junction solar cell (33.5 per cent). Besides efficiency, another critical factor for photovoltaics and other optoelectronic applications is environmental stability and photostability under operating conditions. In contrast to their three-dimensional counterparts, Ruddlesden-Popper phases--layered two-dimensional perovskite films--have shown promising stability, but poor efficiency at only 4.73 per cent. This relatively poor efficiency is attributed to the inhibition of out-of-plane charge transport by the organic cations, which act like insulating spacing layers between the conducting inorganic slabs. Here we overcome this issue in layered perovskites by producing thin films of near-single-crystalline quality, in which the crystallographic planes of the inorganic perovskite component have a strongly preferential out-of-plane alignment with respect to the contacts in planar solar cells to facilitate efficient charge transport. We report a photovoltaic efficiency of 12.52 per cent with no hysteresis, and the devices exhibit greatly improved stability in comparison to their three-dimensional counterparts when subjected to light, humidity and heat stress tests. Unencapsulated two-dimensional perovskite devices retain over 60 per cent of their efficiency for over 2,250 hours under constant, standard (AM1.5G) illumination, and exhibit greater tolerance to 65 per cent relative humidity than do three-dimensional equivalents. When the devices are encapsulated, the layered devices do not show any degradation under constant AM1.5G illumination or humidity. We anticipate that these results will lead to the growth of single-crystalline, solution-processed, layered, hybrid, perovskite thin films, which are essential for high-performance opto-electronic devices with technologically relevant long-term stability.

Fundamentals of cancer metabolism

Abstract: Tumors reprogram pathways of nutrient acquisition and metabolism to meet the bioenergetic, biosynthetic, and redox demands of malignant cells. These reprogrammed activities are now recognized as hallmarks of cancer, and recent work has uncovered remarkable flexibility in the specific pathways activated by tumor cells to support these key functions. In this perspective, we provide a conceptual framework to understand how and why metabolic reprogramming occurs in tumor cells, and the mechanisms linking altered metabolism to tumorigenesis and metastasis. Understanding these concepts will progressively support the development of new strategies to treat human cancer.

Major depressive disorder

Abstract: Major depressive disorder (MDD) is a debilitating disease that is characterized by depressed mood, diminished interests, impaired cognitive function and vegetative symptoms, such as disturbed sleep or appetite. MDD occurs about twice as often in women than it does in men and affects one in six adults in their lifetime. The aetiology of MDD is multifactorial and its heritability is estimated to be approximately 35%. In addition, environmental factors, such as sexual, physical or emotional abuse during childhood, are strongly associated with the risk of developing MDD. No established mechanism can explain all aspects of the disease. However, MDD is associated with alterations in regional brain volumes, particularly the hippocampus, and with functional changes in brain circuits, such as the cognitive control network and the affective-salience network. Furthermore, disturbances in the main neurobiological stress-responsive systems, including the hypothalamic-pituitary-adrenal axis and the immune system, occur in MDD. Management primarily comprises psychotherapy and pharmacological treatment. For treatment-resistant patients who have not responded to several augmentation or combination treatment attempts, electroconvulsive therapy is the treatment with the best empirical evidence. In this Primer, we provide an overview of the current evidence of MDD, including its epidemiology, aetiology, pathophysiology, diagnosis and treatment.

Ultrahigh power factor and thermoelectric performance in hole-doped single-crystal SnSe

Abstract: Thermoelectric technology, harvesting electric power directly from heat, is a promising environmentally friendly means of energy savings and power generation. The thermoelectric efficiency is determined by the device dimensionless figure of merit ZT(dev), and optimizing this efficiency requires maximizing ZT values over a broad temperature range. Here, we report a record high ZT(dev) ∼1.34, with ZT ranging from 0.7 to 2.0 at 300 to 773 kelvin, realized in hole-doped tin selenide (SnSe) crystals. The exceptional performance arises from the ultrahigh power factor, which comes from a high electrical conductivity and a strongly enhanced Seebeck coefficient enabled by the contribution of multiple electronic valence bands present in SnSe. SnSe is a robust thermoelectric candidate for energy conversion applications in the low and moderate temperature range.

Rationally Designing High-Performance Bulk Thermoelectric Materials

Abstract: There has been a renaissance of interest in exploring highly efficient thermoelectric materials as a possible route to address the worldwide energy generation, utilization, and management. This review describes the recent advances in designing high-performance bulk thermoelectric materials. We begin with the fundamental stratagem of achieving the greatest thermoelectric figure of merit ZT of a given material by carrier concentration engineering, including Fermi level regulation and optimum carrier density stabilization. We proceed to discuss ways of maximizing ZT at a constant doping level, such as increase of band degeneracy (crystal structure symmetry, band convergence), enhancement of band effective mass (resonant levels, band flattening), improvement of carrier mobility (modulation doping, texturing), and decrease of lattice thermal conductivity (synergistic alloying, second-phase nanostructuring, mesostructuring, and all-length-scale hierarchical architectures). We then highlight the decoupling of th...

Ruddlesden-Popper Hybrid Lead Iodide Perovskite 2D Homologous Semiconductors

Abstract: The hybrid two-dimensional (2D) halide perovskites have recently drawn significant interest because they can serve as excellent photoabsorbers in perovskite solar cells. Here we present the large scale synthesis, crystal structure, and optical characterization of the 2D (CH3(CH2)3NH3)2(CH3NH3)n−1PbnI3n+1 (n = 1, 2, 3, 4, ∞) perovskites, a family of layered compounds with tunable semiconductor characteristics. These materials consist of well-defined inorganic perovskite layers intercalated with bulky butylammonium cations that act as spacers between these fragments, adopting the crystal structure of the Ruddlesden–Popper type. We find that the perovskite thickness (n) can be synthetically controlled by adjusting the ratio between the spacer cation and the small organic cation, thus allowing the isolation of compounds in pure form and large scale. The orthorhombic crystal structures of (CH3(CH2)3NH3)2(CH3NH3)Pb2I7 (n = 2, Cc2m; a = 8.9470(4), b = 39.347(2) A, c = 8.8589(6)), (CH3(CH2)3NH3)2(CH3NH3)2Pb3I10 (...

Tests of general relativity with GW150914

Abstract: The LIGO detection of GW150914 provides an unprecedented opportunity to study the two-body motion of a compact-object binary in the large-velocity, highly nonlinear regime, and to witness the final merger of the binary and the excitation of uniquely relativistic modes of the gravitational field. We carry out several investigations to determine whether GW150914 is consistent with a binary black-hole merger in general relativity. We find that the final remnant’s mass and spin, as determined from the low-frequency (inspiral) and high-frequency (postinspiral) phases of the signal, are mutually consistent with the binary black-hole solution in general relativity. Furthermore, the data following the peak of GW150914 are consistent with the least-damped quasinormal mode inferred from the mass and spin of the remnant black hole. By using waveform models that allow for parametrized general-relativity violations during the inspiral and merger phases, we perform quantitative tests on the gravitational-wave phase in the dynamical regime and we determine the first empirical bounds on several high-order post-Newtonian coefficients. We constrain the graviton Compton wavelength, assuming that gravitons are dispersed in vacuum in the same way as particles with mass, obtaining a 90%-confidence lower bound of 1013 km. In conclusion, within our statistical uncertainties, we find no evidence for violations of general relativity in the genuinely strong-field regime of gravity.

Chemical, thermal and mechanical stabilities of metal–organic frameworks

Abstract: The construction of thousands of well-defined, porous, metal–organic framework (MOF) structures, spanning a broad range of topologies and an even broader range of pore sizes and chemical functionalities, has fuelled the exploration of many applications. Accompanying this applied focus has been a recognition of the need to engender MOFs with mechanical, thermal and/or chemical stability. Chemical stability in acidic, basic and neutral aqueous solutions is important. Advances over recent years have made it possible to design MOFs that possess different combinations of mechanical, thermal and chemical stability. Here, we review these advances and the associated design principles and synthesis strategies. We focus on how these advances may render MOFs effective as heterogeneous catalysts, both in chemically harsh condensed phases and in thermally challenging conditions relevant to gas-phase reactions. Finally, we briefly discuss future directions of study for the production of highly stable MOFs. Metal–organic frameworks (MOFs) have shown promise in a broad range of applications, including catalysis. In this Review, the chemical, thermal and mechanical stabilities of MOFs, in particular with catalytic uses in mind, are discussed.

Two Phase 3 Trials of Dupilumab versus Placebo in Atopic Dermatitis

Abstract: BackgroundDupilumab, a human monoclonal antibody against interleukin-4 receptor alpha, inhibits signaling of interleukin-4 and interleukin-13, type 2 cytokines that may be important drivers of atopic or allergic diseases such as atopic dermatitis. MethodsIn two randomized, placebo-controlled, phase 3 trials of identical design (SOLO 1 and SOLO 2), we enrolled adults with moderate-to-severe atopic dermatitis whose disease was inadequately controlled by topical treatment. Patients were randomly assigned in a 1:1:1 ratio to receive, for 16 weeks, subcutaneous dupilumab (300 mg) or placebo weekly or the same dose of dupilumab every other week alternating with placebo. The primary outcome was the proportion of patients who had both a score of 0 or 1 (clear or almost clear) on the Investigator’s Global Assessment and a reduction of 2 points or more in that score from baseline at week 16. ResultsWe enrolled 671 patients in SOLO 1 and 708 in SOLO 2. In SOLO 1, the primary outcome occurred in 85 patients (38%) who...

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Abstract: The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p −12 ) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies

Fulvestrant plus palbociclib versus fulvestrant plus placebo for treatment of hormone-receptor-positive, HER2-negative metastatic breast cancer that progressed on previous endocrine therapy (PALOMA-3): final analysis of the multicentre, double-blind, phase 3 randomised controlled trial

Abstract: Summary Background In the PALOMA-3 study, the combination of the CDK4 and CDK6 inhibitor palbociclib and fulvestrant was associated with significant improvements in progression-free survival compared with fulvestrant plus placebo in patients with metastatic breast cancer. Identification of patients most suitable for the addition of palbociclib to endocrine therapy after tumour recurrence is crucial for treatment optimisation in metastatic breast cancer. We aimed to confirm our earlier findings with this extended follow-up and show our results for subgroup and biomarker analyses. Methods In this multicentre, double-blind, randomised phase 3 study, women aged 18 years or older with hormone-receptor-positive, HER2-negative metastatic breast cancer that had progressed on previous endocrine therapy were stratified by sensitivity to previous hormonal therapy, menopausal status, and presence of visceral metastasis at 144 centres in 17 countries. Eligible patients—ie, any menopausal status, Eastern Cooperative Oncology Group performance status 0–1, measurable disease or bone disease only, and disease relapse or progression after previous endocrine therapy for advanced disease during treatment or within 12 months of completion of adjuvant therapy—were randomly assigned (2:1) via a centralised interactive web-based and voice-based randomisation system to receive oral palbociclib (125 mg daily for 3 weeks followed by a week off over 28-day cycles) plus 500 mg fulvestrant (intramuscular injection on days 1 and 15 of cycle 1; then on day 1 of subsequent 28-day cycles) or placebo plus fulvestrant. The primary endpoint was investigator-assessed progression-free survival. Analysis was by intention to treat. We also assessed endocrine therapy resistance by clinical parameters, quantitative hormone-receptor expression, and tumour PIK3CA mutational status in circulating DNA at baseline. This study is registered with ClinicalTrials.gov, NCT01942135. Findings Between Oct 7, 2013, and Aug 26, 2014, 521 patients were randomly assigned, 347 to fulvestrant plus palbociclib and 174 to fulvestrant plus placebo. Study enrolment is closed and overall survival follow-up is in progress. By March 16, 2015, 259 progression-free-survival events had occurred (145 in the fulvestrant plus palbociclib group and 114 in the fulvestrant plus placebo group); median follow-up was 8·9 months (IQR 8·7–9·2). Median progression-free survival was 9·5 months (95% CI 9·2–11·0) in the fulvestrant plus palbociclib group and 4·6 months (3·5–5·6) in the fulvestrant plus placebo group (hazard ratio 0·46, 95% CI 0·36–0·59, p PIK3CA mutation was detected in the plasma DNA of 129 (33%) of 395 patients for whom these data were available. Neither PIK3CA status nor hormone-receptor expression level significantly affected treatment response. Interpretation Fulvestrant plus palbociclib was associated with significant and consistent improvement in progression-free survival compared with fulvestrant plus placebo, irrespective of the degree of endocrine resistance, hormone-receptor expression level, and PIK3CA mutational status. The combination could be considered as a therapeutic option for patients with recurrent hormone-receptor-positive, HER2-negative metastatic breast cancer that has progressed on previous endocrine therapy. Funding Pfizer.

Binary Black Hole Mergers in the First Advanced LIGO Observing Run

Abstract: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to 100M⊙ and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than 5σ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, which has a 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range 9−240Gpc−3yr−1. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections.

RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials

Abstract: A new software package, RASPA, for simulating adsorption and diffusion of molecules in flexible nanoporous materials is presented. The code implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License.

Metal oxides for optoelectronic applications

Abstract: Optical transparency, tunable conducting properties and easy processability make metal oxides key materials for advanced optoelectronic devices. This Review discusses recent advances in the synthesis of these materials and their use in applications. Metal oxides (MOs) are the most abundant materials in the Earth's crust and are ingredients in traditional ceramics. MO semiconductors are strikingly different from conventional inorganic semiconductors such as silicon and III–V compounds with respect to materials design concepts, electronic structure, charge transport mechanisms, defect states, thin-film processing and optoelectronic properties, thereby enabling both conventional and completely new functions. Recently, remarkable advances in MO semiconductors for electronics have been achieved, including the discovery and characterization of new transparent conducting oxides, realization of p-type along with traditional n-type MO semiconductors for transistors, p–n junctions and complementary circuits, formulations for printing MO electronics and, most importantly, commercialization of amorphous oxide semiconductors for flat panel displays. This Review surveys the uniqueness and universality of MOs versus other unconventional electronic materials in terms of materials chemistry and physics, electronic characteristics, thin-film fabrication strategies and selected applications in thin-film transistors, solar cells, diodes and memories.

Polycystic ovary syndrome.

Abstract: Polycystic ovary syndrome (PCOS) is characterized by a constellation of clinical symptoms that include irregular menses due to chronic oligo-ovulation, phenotypic features of hyperandrogenism, and obesity The term “polycystic ovary” refers to ovarian morphology with increased ovarian stroma and a ring of cortical follicles Core biochemical features include hyperandrogenism and insulin resistance The pathogenesis of PCOS remains a topic of debate Treatment of PCOS typically focuses on mitigating the impact of hyperandrogenism, insulin resistance, and chronic oligo-ovulation and restoring fertility when desired

Guidelines of care for the management of acne vulgaris

Abstract: Acne is one of the most common disorders treated by dermatologists and other health care providers. While it most often affects adolescents, it is not uncommon in adults and can also be seen in children. This evidence-based guideline addresses important clinical questions that arise in its management. Issues from grading of acne to the topical and systemic management of the disease are reviewed. Suggestions on use are provided based on available evidence.

On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

Abstract: The stochastic gradient descent (SGD) method and its variants are algorithms of choice for many Deep Learning tasks. These methods operate in a small-batch regime wherein a fraction of the training data, say $32$-$512$ data points, is sampled to compute an approximation to the gradient. It has been observed in practice that when using a larger batch there is a degradation in the quality of the model, as measured by its ability to generalize. We investigate the cause for this generalization drop in the large-batch regime and present numerical evidence that supports the view that large-batch methods tend to converge to sharp minimizers of the training and testing functions - and as is well known, sharp minima lead to poorer generalization. In contrast, small-batch methods consistently converge to flat minimizers, and our experiments support a commonly held view that this is due to the inherent noise in the gradient estimation. We discuss several strategies to attempt to help large-batch methods eliminate this generalization gap.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

Abstract: The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Soft Tissue Sarcoma, Version 2.2016, NCCN Clinical Practice Guidelines in Oncology

Abstract: Soft tissue sarcomas (STS) are rare solid tumors of mesenchymal cell origin that display a heterogenous mix of clinical and pathologic characteristics. STS can develop from fat, muscle, nerves, blood vessels, and other connective tissues. The evaluation and treatment of patients with STS requires a multidisciplinary team with demonstrated expertise in the management of these tumors. The complete NCCN Guidelines for STS provide recommendations for the diagnosis, evaluation, and treatment of extremity/superficial trunk/head and neck STS, as well as intra-abdominal/retroperitoneal STS, gastrointestinal stromal tumors, desmoid tumors, and rhabdomyosarcoma. This portion of the NCCN Guidelines discusses general principles for the diagnosis, staging, and treatment of STS of the extremities, superficial trunk, or head and neck; outlines treatment recommendations by disease stage; and reviews the evidence to support the guidelines recommendations.

Influence of connected and autonomous vehicles on traffic flow stability and throughput

Abstract: The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.

Properties of the Binary Black Hole Merger GW150914

Abstract: On September 14, 2015, the Laser Interferometer Gravitational-wave Observatory (LIGO) detected a gravitational-wave transient (GW150914); we characterise the properties of the source and its parameters. The data around the time of the event were analysed coherently across the LIGO network using a suite of accurate waveform models that describe gravitational waves from a compact binary system in general relativity. GW150914 was produced by a nearly equal mass binary black hole of $36^{+5}_{-4} M_\odot$ and $29^{+4}_{-4} M_\odot$ (for each parameter we report the median value and the range of the 90% credible interval). The dimensionless spin magnitude of the more massive black hole is bound to be $0.7$ (at 90% probability). The luminosity distance to the source is $410^{+160}_{-180}$ Mpc, corresponding to a redshift $0.09^{+0.03}_{-0.04}$ assuming standard cosmology. The source location is constrained to an annulus section of $590$ deg$^2$, primarily in the southern hemisphere. The binary merges into a black hole of $62^{+4}_{-4} M_\odot$ and spin $0.67^{+0.05}_{-0.07}$. This black hole is significantly more massive than any other known in the stellar-mass regime.

Defining Computational Thinking for Mathematics and Science Classrooms

Abstract: Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include “computational thinking” as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new urgency has come to the challenge of defining computational thinking and providing a theoretical grounding for what form it should take in school science and mathematics classrooms. This paper presents a response to this challenge by proposing a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices. In formulating this taxonomy, we draw on the existing computational thinking literature, interviews with mathematicians and scientists, and exemplary computational thinking instructional materials. This work was undertaken as part of a larger effort to infuse computational thinking into high school science and mathematics curricular materials. In this paper, we argue for the approach of embedding computational thinking in mathematics and science contexts, present the taxonomy, and discuss how we envision the taxonomy being used to bring current educational efforts in line with the increasingly computational nature of modern science and mathematics.

A general-purpose machine learning framework for predicting properties of inorganic materials

Abstract: A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method for partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability. Researchers in the United States have developed a versatile machine learning framework to aid the search for novel materials. Led by Christopher Wolverton and Logan Ward from Northwestern University, the researchers used machine learning techniques trained against known material data to generate models that predict the specific properties of new materials. The utility of the technique was demonstrated through searches for novel crystalline compounds for photovoltaic applications, and for metallic glass alloys based on the probability of glass formation for ternary alloys. New models can be created by optimizing the machine learning algorithm and partitioning input data to maximize the prediction accuracy for specific parameters. The technique has the potential to automate and accelerate the search for new functional materials using the large libraries of material data now available to researchers.

A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat

Abstract: Capabilities in health monitoring enabled by capture and quantitative chemical analysis of sweat could complement, or potentially obviate the need for, approaches based on sporadic assessment of blood samples. Established sweat monitoring technologies use simple fabric swatches and are limited to basic analysis in controlled laboratory or hospital settings. We present a collection of materials and device designs for soft, flexible, and stretchable microfluidic systems, including embodiments that integrate wireless communication electronics, which can intimately and robustly bond to the surface of the skin without chemical and mechanical irritation. This integration defines access points for a small set of sweat glands such that perspiration spontaneously initiates routing of sweat through a microfluidic network and set of reservoirs. Embedded chemical analyses respond in colorimetric fashion to markers such as chloride and hydronium ions, glucose, and lactate. Wireless interfaces to digital image capture hardware serve as a means for quantitation. Human studies demonstrated the functionality of this microfluidic device during fitness cycling in a controlled environment and during long-distance bicycle racing in arid, outdoor conditions. The results include quantitative values for sweat rate, total sweat loss, pH, and concentration of chloride and lactate.