cssi/SciSciGPT-SciSciNet huggingface dataset:
Signatures of human impact on self-organized vegetation in the Horn of Africa

In many dryland environments, vegetation self-organizes into bands that can be clearly identified in remotely-sensed imagery. The status of individual bands can be tracked over time, allowing for a detailed remote analysis of how human populations affect the vital balance of dryland ecosystems. In this study, we characterize vegetation change in areas of the Horn of Africa where imagery taken in the early 1950s is available. We find that substantial change is associated with steep increases in human activity, which we infer primarily through the extent of road and dirt track development. A seemingly paradoxical signature of human impact appears as an increase in the widths of the vegetation bands, which effectively increases the extent of vegetation cover in many areas. We show that this widening occurs due to altered rates of vegetation colonization and mortality at the edges of the bands, and conjecture that such changes are driven by human-induced shifts in plant species composition. Our findings suggest signatures of human impact that may aid in identifying and monitoring vulnerable drylands in the Horn of Africa.
The data systems tests - The final phase

The U.S.A. has conducted a series of data systems tests (DSTs) as a precursor to its participation in FGGE, the Global Weather Experiment. The paper briefly describes the impact those tests have had on the FGGE observing system and on the data management plans. In particular, the final phase of the DST programs is described, wherein a number of investigators have been selected to work with the DST data sets in research studies directed toward the GARP objectives. Thus, an important first step has been taken in providing feedback to the potential FGGE research community.
Biogeography and environmental conditions shape bacteriophage-bacteria networks across the human microbiome

Viruses and bacteria are critical components of the human microbiome and play important roles in health and disease. Most previous work has relied on studying bacteria and viruses independently, thereby reducing them to two separate communities. Such approaches are unable to capture how these microbial communities interact, such as through processes that maintain community robustness or allow phage-host populations to co-evolve. We implemented a network-based analytical approach to describe phage-bacteria network diversity throughout the human body. We built these community networks using a machine learning algorithm to predict which phages could infect which bacteria in a given microbiome. Our algorithm was applied to paired viral and bacterial metagenomic sequence sets from three previously published human cohorts. We organized the predicted interactions into networks that allowed us to evaluate phage-bacteria connectedness across the human body. We observed evidence that gut and skin network structures were person-specific and not conserved among cohabitating family members. High-fat diets appeared to be associated with less connected networks. Network structure differed between skin sites, with those exposed to the external environment being less connected and likely more susceptible to network degradation by microbial extinction events. This study quantified and contrasted the diversity of virome-microbiome networks across the human body and illustrated how environmental factors may influence phage-bacteria interactive dynamics. This work provides a baseline for future studies to better understand system perturbations, such as disease states, through ecological networks.
Adversarial Learning of Task-Oriented Neural Dialog Models

In this work, we propose an adversarial learning method for reward estimation in reinforcement learning (RL) based task-oriented dialog models. Most of the current RL based task-oriented dialog systems require the access to a reward signal from either user feedback or user ratings. Such user ratings, however, may not always be consistent or available in practice. Furthermore, online dialog policy learning with RL typically requires a large number of queries to users, suffering from sample efficiency problem. To address these challenges, we propose an adversarial learning method to learn dialog rewards directly from dialog samples. Such rewards are further used to optimize the dialog policy with policy gradient based RL. In the evaluation in a restaurant search domain, we show that the proposed adversarial dialog learning method achieves advanced dialog success rate comparing to strong baseline methods. We further discuss the covariate shift problem in online adversarial dialog learning and show how we can address that with partial access to user feedback.
Angiotensin-related genetic determinants of cardiovascular disease in patients undergoing hemodialysis.

BACKGROUND Cardiovascular mortality in patients receiving dialysis remains unacceptably high, with unexplained ancestry differences suggesting a genetic component. METHODS We analyzed DNA samples from 37% of subjects enrolled in the EValuation Of Cinacalcet Hydrochloride (HCl) Therapy to Lower CardioVascular Events (EVOLVE) trial, a randomized trial conducted in patients receiving hemodialysis with secondary hyperparathyroidism, comparing cinacalcet to placebo on a background of usual care. DNA was analyzed for single-nucleotide polymorphisms (SNPs) in the genes encoding the angiotensin-converting enzyme receptor type I (AGTR1) and angiotensin-converting enzyme (ACE). Survival analyses were conducted separately in European Ancestry (EA) and African Ancestry (AfAn) due to known differences in cardiovascular events, minor alleles for the same variant and the frequency of minor alleles. Our primary determination was a meta-analysis across both races. RESULTS Meta-analysis showed significant associations between rs5186 in AGTR1 and increased rates by 25-34% for the primary endpoint (composite of death or nonfatal myocardial infarction, hospitalization for unstable angina, heart failure or peripheral vascular event), all-cause mortality, cardiovascular mortality and heart failure; all P < 0.001. Three correlated SNPs in ACE were associated with lower rates of sudden cardiac death (SCD) in EA samples. One ACE SNP, rs4318, only found in the AfAn samples, was associated with a lower rate of SCD in the AfAn samples. CONCLUSIONS The C allele in rs5186 in AGTR1 was associated with higher rates of death and major cardiovascular events in a meta-analysis of EA and AfAn patients with end-stage kidney disease. SNPs in ACE were associated with SCD.
Automatic analysis of treadmill running to estimate times to fatigue and exhaustion in rodents

Introduction The determination of fatigue and exhaustion in experimental animals is complicated by the subjective nature of the measurement. Typically, it requires an observer to watch exercising animals, e.g. rats running on the treadmill, and to identify the time of the event. In this study, we hypothesized that automatic analysis of the time-averaged position of a rat on a treadmill could be an objective way for estimating times to fatigue and exhaustion. To test this hypothesis, we compared these times measured by a human observer to the results of an automated video tracking system. Methods Rats, previously familiarized to running on the treadmill, ran at a fixed speed with zero incline, until exhaustion. The experiments were performed at either room temperature (24 °C) or in a hot environment (32 °C). Each experiment was video recorded. A trained observer estimated the times to fatigue and exhaustion. Then, video tracking software was used to determine the position of the animals on the treadmill belt. The times to fatigue and exhaustion were determined, based on the position on the treadmill using predefined criteria. Results Manual scores and the average position on the treadmill had significant correlation. Both the observer and the automated video tracking determined that exercise in a hot environment, compared with the exercise at room temperature, results in shorter times to exhaustion and fatigue. Also, estimates of times made by the observer and the automated video tracking were not statistically different from each other. Discussion A similarity between the estimates of times to fatigue and exhaustion made by the observer and the automated technique suggests that video tracking of rodents running on a treadmill can be used to determine both parameters in experimental studies. Video tracking technique allows for a more objective measure and would allow for an increased performance in experimentation. The Supplemental information to this manuscript contains an Excel file, which includes the code in Virtual Basic with freeware license, to process and visualize running data and automatically estimate the times to fatigue and exhaustion. Instructions for the software are also included.
Age and entrepreneurship: nuances from entrepreneur types and generation effects

The literature on the relationship between age and entrepreneurship has been inconclusive. This study for the first time examines this relationship by extending the occupational choice literature to eight entrepreneur types and four generational modification effects in the USA. Multilevel mixed-effect logistic regression models are estimated to examine the age effects in entrepreneur type propensities. Generational modification effects are compared for the same ages across neighboring generations by hierarchical age-period-cohort (HAPC) models. We find that entrepreneurial propensity rises with age until around 80. The propensity of novice (versus non-novice) and unincorporated (versus incorporated) entrepreneurs has a U-shaped age trend dipping around age 60, while the propensity of full-time (versus part-time) declines since age 30s. The propensity of incorporated (versus unincorporated) entrepreneurs declines from ages 44 to 51 for Gen-Xers, but not for Boomers; this propensity also declines faster for Boomers than for Traditionalists from ages 63 to 70.
Local food prices, SNAP purchasing power, and child health

The Supplemental Nutrition Assistance Program (SNAP, formerly food stamps) is one of the most important elements of the social safety net. Unlike most other safety net programs, SNAP varies little across states and over time, which creates challenges for quasi-experimental evaluation. Notably, SNAP benefits are fixed across 48 states; but local food prices vary, leading to geographic variation in the real value - or purchasing power - of SNAP benefits. In this study, we provide the first estimates that leverage variation in SNAP purchasing power across markets to examine effects of SNAP on child health. We link panel data on regional food prices to National Health Interview Survey data and use a fixed effects framework to estimate the relationship between local purchasing power of SNAP and children's health and health care utilization. We find that lower SNAP purchasing power leads to lower utilization of preventive health care and more days of school missed due to illness. We estimate no effect on parent-reported health status.
Epidemiology of helicopter accidents: Trends, rates, and covariates

Abstract The objective of this work is to provide a better understanding of helicopter accidents and to identify important areas for different stakeholders to focus their attention and resources for accident prevention. To this end, we undertook Record Linkage of two federal data sources: the FAA civil helicopter registration data and the NTSB accident data. First, the analysis of accident rates and trends shows little progress in accident prevention over the last decade. Second, we find that helicopter accident rates vary significantly by number of main rotor blades, with the four- and six-bladed helicopters having the safest track record. Third, we show that accident rates vary by engine types when controlling for the number of blades. For example, the combination of reciprocating engine and three-bladed (3B) helicopters is associated with one of the highest accident rates. We further examine differences in accident rates between single and twin-engine helicopters, controlling for engine type and number of blades. The worst-in-class in terms of rates are the 5B and 6B single-engine turboshaft helicopters, whereas the worst-offenders in terms of contributing to the total count of accidents are the single-engine 2B reciprocating and turboshaft helicopters. The 4B single-engine turboshaft occupy a safety sweet spot and have the lowest accident rates of all single-engine helicopters. We provide risk ratios for pairwise comparisons and 95% confidence intervals for all accident rates, and discuss possible confounders for these results. The issues here examined lend themselves to a rich set of technical and operational implications, and they deserve careful attention from helicopter operators, regulators, and manufacturers. Any serious effort to improve helicopter safety will entail action on multiple safety levers, including design, operational, and policy-related ones. These actions should be evidence-based and they require better helicopter accident investigations and better data.
Reverse weathering as a long-term stabilizer of marine pH and planetary climate

For the first four billion years of Earth’s history, climate was marked by apparent stability and warmth despite the Sun having lower luminosity1. Proposed mechanisms for maintaining an elevated partial pressure of carbon dioxide in the atmosphere ( $${p}_{{{\rm{CO}}}_{{\rm{2}}}}$$ ) centre on a reduction in the weatherability of Earth’s crust and therefore in the efficiency of carbon dioxide removal from the atmosphere2. However, the effectiveness of these mechanisms remains debated2,3. Here we use a global carbon cycle model to explore the evolution of processes that govern marine pH, a factor that regulates the partitioning of carbon between the ocean and the atmosphere. We find that elevated rates of ‘reverse weathering’—that is, the consumption of alkalinity and generation of acidity during marine authigenic clay formation4–7—enhanced the retention of carbon within the ocean–atmosphere system, leading to an elevated $${p}_{{{\rm{CO}}}_{{\rm{2}}}}$$ baseline. Although this process is dampened by sluggish kinetics today, we propose that more prolific rates of reverse weathering would have persisted under the pervasively silica-rich conditions8,9 that dominated Earth’s early oceans. This distinct ocean and coupled carbon–silicon cycle state would have successfully maintained the equable and ice-free environment that characterized most of the Precambrian period. Further, we propose that during this time, the establishment of a strong negative feedback between marine pH and authigenic clay formation would have also enhanced climate stability by mitigating large swings in $${p}_{{{\rm{CO}}}_{{\rm{2}}}}$$ —a critical component of Earth’s natural thermostat that would have been dominant for most of Earth’s history. We speculate that the late ecological rise of siliceous organisms8 and a resulting decline in silica-rich conditions dampened the reverse weathering buffer, destabilizing Earth’s climate system and lowering baseline $${p}_{{{\rm{CO}}}_{{\rm{2}}}}$$ . Elevated rates of reverse weathering within silica-rich oceans led to enhanced carbon retention within the ocean–atmosphere system, promoting a stable, equable ice-free climate throughout Earth’s early to middle ages.
Human pluripotent stem cell-derived brain pericyte-like cells induce blood-brain barrier properties.

Brain pericytes play important roles in the formation and maintenance of the neurovascular unit (NVU), and their dysfunction has been implicated in central nervous system disorders. While human pluripotent stem cells (hPSCs) have been used to model other NVU cell types, including brain microvascular endothelial cells (BMECs), astrocytes, and neurons, hPSC-derived brain pericyte–like cells have not been integrated into these models. In this study, we generated neural crest stem cells (NCSCs), the embryonic precursor to forebrain pericytes, from hPSCs and subsequently differentiated NCSCs to brain pericyte–like cells. These cells closely resembled primary human brain pericytes and self-assembled with endothelial cells. The brain pericyte–like cells induced blood-brain barrier properties in BMECs, including barrier enhancement and reduced transcytosis. Last, brain pericyte–like cells were incorporated with iPSC-derived BMECs, astrocytes, and neurons to form an isogenic human model that should prove useful for the study of the NVU.
The Fluid Mechanics of Liquid Democracy

Liquid democracy is the principle of making collective decisions by letting agents transitively delegate their votes. Despite its significant appeal, it has become apparent that a weakness of liquid democracy is that a small subset of agents may gain massive influence. To address this, we propose to change the current practice by allowing agents to specify multiple delegation options instead of just one. Much like in nature, where—fluid mechanics teaches us—liquid maintains an equal level in connected vessels, we seek to control the flow of votes in a way that balances influence as much as possible. Specifically, we analyze the problem of choosing delegations to approximately minimize the maximum number of votes entrusted to any agent by drawing connections to the literature on confluent flow. We also introduce a random graph model for liquid democracy and use it to demonstrate the benefits of our approach both theoretically and empirically.
Quantitative sovereign default models and the European debt crisis

Abstract A large literature has developed quantitative versions of the Eaton and Gersovitz (1981) model to analyze default episodes on external debt. In this paper, we study whether the same framework can be applied to the analysis of debt crises in which domestic public debt plays a prominent role. We consider a model where a government can issue debt to both domestic and foreign investors, and we derive conditions under which their sum is the relevant state variable for default incentives. We then apply our framework to the European debt crisis. We show that matching the cyclicality of public debt—rather than that of external debt—allows the model to better capture the empirical distribution of interest rate spreads and gives rise to more realistic crises dynamics.
CRN ++: Molecular programming language

Synthetic biology is a rapidly emerging research area, with expected wide-ranging impact in biology, nanofabrication, and medicine. A key technical challenge lies in embedding computation in molecular contexts where electronic micro-controllers cannot be inserted. This necessitates effective representation of computation using molecular components. While previous work established the Turing-completeness of chemical reactions, defining representations that are faithful, efficient, and practical remains challenging. This paper introduces Open image in new window , a new language for programming deterministic (mass-action) chemical kinetics to perform computation. We present its syntax and semantics, and build a compiler translating Open image in new window programs into chemical reactions, thereby laying the foundation of a comprehensive framework for molecular programming. Our language addresses the key challenge of embedding familiar imperative constructs into a set of chemical reactions happening simultaneously and manipulating real-valued concentrations. Although some deviation from ideal output value cannot be avoided, we develop methods to minimize the error, and implement error analysis tools. We demonstrate the feasibility of using Open image in new window on a suite of well-known algorithms for discrete and real-valued computation. Open image in new window can be easily extended to support new commands or chemical reaction implementations, and thus provides a foundation for developing more robust and practical molecular programs.
Supervised Domain Enablement Attention for Personalized Domain Classification

In large-scale domain classification for natural language understanding, leveraging each user’s domain enablement information, which refers to the preferred or authenticated domains by the user, with attention mechanism has been shown to improve the overall domain classification performance. In this paper, we propose a supervised enablement attention mechanism, which utilizes sigmoid activation for the attention weighting so that the attention can be computed with more expressive power without the weight sum constraint of softmax attention. The attention weights are explicitly encouraged to be similar to the corresponding elements of the output one-hot vector, and self-distillation is used to leverage the attention information of the other enabled domains. By evaluating on the actual utterances from a large-scale IPDA, we show that our approach significantly improves domain classification performance
Thrombopoietin level predicts response to treatment with eltrombopag and romiplostim in immune thrombocytopenia

Thrombopoietin receptor agonists (TPO-RAs) are used to treat immune thrombocytopenia (ITP), but predicting clinical response to TPO-RAs before initiation is not possible. To determine whether endogenous TPO levels predict treatment response to TPO-RAs we performed a retrospective analysis of ITP patients with known baseline TPO levels who received TPO-RAs. Data was collected for ITP patients with a baseline TPO level treated with eltrombopag or romiplostim. Multiple logistic regression was used to model the probability of 3 classes of treatment response (overall, moderate, and superior) based on TPO level; receiver operating characteristic (ROC) analysis was performed to identify optimal TPO thresholds for response; correlations between TPO level and various response characteristics were analyzed. A total of 67 patients (37 receiving eltrombopag and 46 receiving romiplostim) were included. Logistic regression models demonstrated a significant predictive relation between TPO level and probability of all classes of response; per 10 pg/mL TPO increase, odds ratio for overall response to eltrombopag was 0.524 (95% CI 0.327, 0.837) and romiplostim was 0.905 (95% CI, 0.844, 0.970). TPO level was inversely correlated with all classes of response; for overall response, r = -0.719 (P < .001) for eltrombopag and r = -0.584 (P < .001) for romiplostim. ROC analysis identified TPO thresholds of ≤136 pg/mL (eltrombopag) and ≤209 pg/mL (romiplostim) as optimally discriminating between responders and nonresponders. Most non-responders had high TPO levels but did respond after addition of low-dose prednisone. In conclusion, TPO levels predict response to eltrombopag and romiplostim in ITP patients, with lower levels predicting improved probability and magnitude of response.
Determinants of a foreclosure discount

This study adds to previous research analyzing the impact of foreclosure status on real estate sales price by using a Swedish dataset were an appraiser has estimated the market value of apartments before they were sold at foreclosure auction. Appraisal data can address the issue of selection bias and a potential overestimation of foreclosure related discount. A mean discount of 7.9% with a corresponding median value of 9.5% is shown when comparing appraisal estimates with prices achieved at foreclosure auction. A hedonic model is also applied, and the resulting discount is estimated at 23.9%. Measures of local market conditions are related to the foreclosure discount, with hedonic price models and models using appraisal data producing consistent results. It is found that the discount is higher in lower priced neighborhoods, in neighborhoods that are heterogeneous in terms of price and in less liquid neighborhoods (significant in the hedonic model). It is also found that apartments with a higher value relative to the neighborhood price level sell at larger discounts. The results are consistent with studies on search and matching theory and contrast from earlier studies that attribute a foreclosure discount to seller motivational factors.
Dynamic Investment Models in Accounting Research

This monograph presents three variants of the neoclassical investment model and characterizes the firm's optimal investment policy, equity value, and the desirable properties of accrual accounting rules in each setting. Two main questions are considered: (1) What accounting rules result in the most informative financial statements from the perspective of investors seeking to value the firm's equity? and (2) What accounting rules can be efficiently used by shareholders in evaluating the performance of better informed managers? One accounting treatment, referred to as replacement cost accounting, achieves efficiency along both dimensions. The notion of replacement cost studied in this monograph corresponds closely to that of fair value, as defined in IFRS 13, in that it is defined as either (i) the current price of the capital goods in a perfectly competitive market, if such a market is available, or (ii) the hypothetical amount that would have to be incurred today to replace the current and future capacity of the capital goods in question. While the replacement cost rule is, in many settings, unique in providing the firm's shareholders with sufficient information for precise equity valuation, the problem of efficient performance measurement is generally less informationally demanding. For example, under certain plausible conditions, the owners can incentivize a better informed manager to make efficient investment decisions using the straight-line depreciation method.
Use of F2 Bulks in Training Sets for Genomic Prediction of Combining Ability and Hybrid Performance

Developing training sets for genomic prediction in hybrid crops requires producing hybrid seed for a large number of entries. In autogamous crop species (e.g., wheat, rice, rapeseed, cotton) this requires elaborate hybridization systems to prevent self-pollination and presents a significant impediment to the implementation of hybrid breeding in general and genomic selection in particular. An alternative to F1 hybrids are bulks of F2 seed from selfed F1 plants (F1:2). Seed production for F1:2 bulks requires no hybridization system because the number of F1 plants needed for producing enough F1:2 seed for multi-environment testing can be generated by hand-pollination. This study evaluated the suitability of F1:2 bulks for use in training sets for genomic prediction of F1 level general combining ability and hybrid performance, under different degrees of divergence between heterotic groups and modes of gene action, using quantitative genetic theory and simulation of a genomic prediction experiment. The simulation, backed by theory, showed that F1:2 training sets are expected to have a lower prediction accuracy relative to F1 training sets, particularly when heterotic groups have strongly diverged. The accuracy penalty, however, was only modest and mostly because of a lower heritability, rather than because of a difference in F1 and F1:2 genetic values. It is concluded that resorting to F1:2 bulks is, in theory at least, a promising approach to remove the significant complication of a hybridization system from the breeding process.
Three Things Clinicians Should Know About Disability.

The historical relationship between health care professionals and people with disabilities is fraught
Quantum Malware

When quantum communication networks proliferate they will likely be subject to a new type of attack by hackers, virus makers, and other malicious intruders. Here we introduce the concept of "quantum malware" to describe such human-made intrusions. We offer a simple solution for storage of quantum information in a manner, which protects quantum networks from quantum malware. This solution involves swapping the quantum information at random times between the network and isolated, distributed ancillas. It applies to arbitrary attack types, provided the protective operations are themselves not compromised.
Proceedings of the 2005 ACM workshop on Rapid malcode

It is my pleasure to welcome you to the 3rd ACM Workshop on Rapid Malcode (WORM). This year's workshop builds on the success of the previous two workshops, establishing WORM as the premier forum for exchanging ideas on the problem of self-propagating programs. The continuing threat of worms and the numerous related incidents in the past year have maintained the topic area as one of paramount importance to users and organizations. The increasing exploitation of worm-compromised hosts for criminal purposes has introduced a new urgency in our search for ways to solve, or at least manage, the problem.This year we received 36 submissions from Asia, Canada, Europe, Africa, and the United States, making WORM a truly international workshop. The program committee accepted 9 papers that cover a variety of topics, based on quality, novelty and clarity. In addition, the program committee invited three distinguished speakers: Brian Hernacki of Symantec ("Emerging Threats"), Vern Paxson of ICSI ("An Analysis of the Witty Outbreak: Exploiting Underlying Structure for Detailed Reconstructions of an Internet-scale Event"), and Stefan Savage ("Scalable Internet Threat Monitoring"). In putting together the program, our goal was to stimulate discussion and encourage further work, both in directly enhancing our defense capabilities and in anticipating future directions of worm evolution.
The Hunchback temporal transcription factor determines motor neuron axon and dendrite targeting in Drosophila

ABSTRACT The generation of neuronal diversity is essential for circuit formation and behavior. Morphological differences in sequentially born neurons could be due to intrinsic molecular identity specified by temporal transcription factors (henceforth called intrinsic temporal identity) or due to changing extrinsic cues. Here, we have used the Drosophila NB7-1 lineage to address this issue. NB7-1 generates the U1-U5 motor neurons sequentially; each has a distinct intrinsic temporal identity due to inheritance of different temporal transcription factors at its time of birth. We show that the U1-U5 neurons project axons sequentially, followed by sequential dendrite extension. We misexpressed the earliest temporal transcription factor, Hunchback, to create ‘ectopic’ U1 neurons with an early intrinsic temporal identity but later birth-order. These ectopic U1 neurons have axon muscle targeting and dendrite neuropil targeting that are consistent with U1 intrinsic temporal identity, rather than with their time of birth or differentiation. We conclude that intrinsic temporal identity plays a major role in establishing both motor axon muscle targeting and dendritic arbor targeting, which are required for proper motor circuit development.
Parallel-Line Assay†

Parallel-line assays are the most common form of indirect analytical assays. The aim is to estimate the potency of substance under test relative to the potency of a standard. The test and standard preparations are administered at several dose levels. The key assumption is that the expected response for a given dose of the test preparation is the same as that which would be obtained from the standard preparation administered at a dose that is ρ times the given dose: ρ is known as the relative potency. It is further assumed that the expected response is linearly related to the logarithm of the dose. If this obtains, the graphs of expected response against log dose for the test and standard preparations will give parallel lines. The response can be continuous, in which case estimation is through a linear model, or quantal, in which case analysis usually assumes a logistic model. The estimator of ρ is defined in terms of ratios of regression coefficients and interval estimates are often obtained by use of Fieller's theorem. Keywords: dose metameter; Fieller's theorem; linear model; logistic model; quantal response; relative potency; slope-ratio assay
The Ethylene Signaling Pathway Negatively Impacts CBF/DREB-Regulated Cold Response in Soybean (Glycine max).

During cold stress, soybean CBF/DREB1 transcript levels increase rapidly; however, expected downstream targets appear unresponsive. Here, we asked whether the ethylene signaling pathway, which is enhanced in the cold can negatively regulate the soybean CBF/DREB1 cold responsive pathway; thus contributing to the relatively poor cold tolerance of soybean. Inhibition of the ethylene signaling pathway resulted in a significant increase in GmDREB1A;1 and GmDREB1A;2 transcripts, while stimulation led to decreased GmDREB1A;1 and GmDREB1B;1 transcripts. A cold responsive reporter construct (AtRD29Aprom::GFP/GUS), as well as predicted downstream targets of soybean CBF/DREB1 [Glyma.12g015100 (ADH), Glyma.14g212200 (ubiquitin ligase), Glyma.05g186700 (AP2), and Glyma.19g014600 (CYP)] were impacted by the modulation of the ethylene signaling pathway. Photosynthetic parameters were affected by ethylene pathway stimulation, but only at control temperatures. Freezing tolerance (as measured by electrolyte leakage), free proline, and MDA; in both acclimated and non-acclimated plants were increased by silver nitrate but not by other ethylene pathway inhibitors. This work provides evidence that the ethylene signaling pathway, possibly through the action of EIN3, transcriptionally inhibits the CBF/DREB1 pathway in soybean.
Improved filtering of DNA methylation microarray data by detection p values and its impact on downstream analyses.

DNA methylation microarrays are popular for epigenome-wide association studies (EWAS), but spurious values complicate downstream analysis and threaten replication. Conventional cut-offs for detection p values for filtering out undetected probes were demonstrated in a single previous study as insufficient leading to many apparent methylation calls in samples from females in probes targeting the Y-chromosome. We present an alternative approach to calculate more accurate detection p values utilizing non-specific background fluorescence. We evaluate and compare our proposed approach of filtering observations with conventional ones by assessing the detection of Y-chromosome probes among males and females in 2755 samples from 17 studies on the 450K microarray and masking of large outliers between technical replicates and their impact downstream via an EWAS reanalysis. In contrast to conventional approaches, ours marks most Y-chromosome probes in females as undetected while removing a median of only 0.14% of the data per sample, catches more (30% vs. 6%) of large outliers (more than 20 percentage point difference between technical replicates), and helps to identify strong associations previously obfuscated by outliers between whole blood DNA methylation and chronological age in a well-powered EWAS (n = 729). We provide guidance for filtering both 450K and EPIC microarrays as an essential preprocessing step to reduce spurious values. An implementation (including a function compatible with objects from the popular minfi package) was added to ewastools, an R package for comprehensive quality control of DNA methylation microarrays. Scripts to reproduce all analyses are available at doi.org/10.5281/zenodo.1443561 .
Fractional coalescent

An approach to the coalescent, the fractional coalescent (f-coalescent), is introduced. The derivation is based on the discrete-time Cannings population model in which the variance of the number of offspring depends on the parameter α. This additional parameter α affects the variability of the patterns of the waiting times; values of α 1 lead to an increase of short time intervals, but occasionally allow for very long time intervals. When α = 1 , the f-coalescent and the Kingman’s n-coalescent are equivalent. The distribution of the time to the most recent common ancestor and the probability that n genes descend from m ancestral genes in a time interval of length T for the f-coalescent are derived. The f-coalescent has been implemented in the population genetic model inference software Migrate. Simulation studies suggest that it is possible to accurately estimate α values from data that were generated with known α values and that the f-coalescent can detect potential environmental heterogeneity within a population. Bayes factor comparisons of simulated data with α 1 and real data (H1N1 influenza and malaria parasites) showed an improved model fit of the f-coalescent over the n-coalescent. The development of the f-coalescent and its inclusion into the inference program Migrate facilitates testing for deviations from the n-coalescent.
KDOQI US Commentary on the 2017 ACC/AHA Hypertension Guideline.

Hypertension is a modifiable risk factor for cardiovascular morbidity and mortality and reduction of elevated blood pressure (BP) remains an important intervention for slowing kidney disease progression. Over the past decade, the most appropriate BP target for initiation and titration of BP-lowering medications has been an area of intense research and debate within the clinical community. In 2017, the American College of Cardiology and the American Heart Association (ACC/AHA) in conjunction with several other professional societies released new hypertension guidelines based on data from a systematic review of clinical trials and observational data. While many of the recommendations in the ACC/AHA hypertension guideline are relevant to nephrology practice, BP targets and management strategies for patients receiving dialysis are not discussed. This Kidney Disease Outcomes Quality Initiative (KDOQI) commentary focuses largely on recommendations from the ACC/AHA hypertension guidelines that are pertinent to individuals at risk of chronic kidney disease or with non–dialysis-dependent chronic kidney disease. This KDOQI commentary also includes a brief discussion of the consensus statement regarding hypertension diagnosis and management for adults receiving maintenance dialysis published by the European Renal and Cardiovascular Medicine Working Group of the European Renal Association–European Dialysis and Transplant Association (ERA-EDTA) and the Hypertension and the Kidney working group of the European Society of Hypertension. Overall, we support the vast majority of the ACC/AHA recommendations and highlight select areas in which best diagnosis and treatment options remain controversial.
CCL5 promotes breast cancer recurrence through macrophage recruitment in residual tumors

Over half of breast-cancer-related deaths are due to recurrence 5 or more years after initial diagnosis and treatment. This latency suggests that a population of residual tumor cells can survive treatment and persist in a dormant state for many years. The role of the microenvironment in regulating the survival and proliferation of residual cells following therapy remains unexplored. Using a conditional mouse model for Her2-driven breast cancer, we identify interactions between residual tumor cells and their microenvironment as critical for promoting tumor recurrence. Her2 downregulation leads to an inflammatory program driven by TNFα/NFκB signaling, which promotes immune cell infiltration in regressing and residual tumors. The cytokine CCL5 is elevated following Her2 downregulation and remains high in residual tumors. CCL5 promotes tumor recurrence by recruiting CCR5-expressing macrophages, which may contribute to collagen deposition in residual tumors. Blocking this TNFα-CCL5-macrophage axis may be efficacious in preventing breast cancer recurrence.
Theories of the Causes of Poverty

There has been a lack of debate between and frameworks for theories of the causes of poverty. This article proposes that most theories of poverty can be productively categorized into three broader ...
Injectable osteogenic microtissues containing mesenchymal stromal cells conformally fill and repair critical-size defects

Repair of complex fractures with bone loss requires a potent, space-filling intervention to promote regeneration of bone. We present a biomaterials-based strategy combining mesenchymal stromal cells (MSC) with a chitosan-collagen matrix to form modular microtissues designed for delivery through a needle to conformally fill cavital defects. Implantation of microtissues into a calvarial defect in the mouse showed that osteogenically pre-differentiated MSC resulted in complete bridging of the cavity, while undifferentiated MSC produced mineralized tissue only in apposition to native bone. Decreasing the implant volume reduced bone regeneration, while increasing the MSC concentration also attenuated bone formation, suggesting that the cell-matrix ratio is important in achieving a robust response. Conformal filling of the defect with microtissues in a carrier gel resulted in complete healing. Taken together, these results show that modular microtissues can be used to augment the differentiated function of MSC and provide an extracellular environment that potentiates bone repair.
A Ca2+-ATPase Regulates E-cadherin Biogenesis and Epithelial-Mesenchymal Transition in Breast Cancer Cells

Progression of benign tumors to invasive, metastatic cancer is accompanied by the epithelial-to-mesenchymal transition (EMT), characterized by loss of the cell-adhesion protein E-cadherin. Although silencing mutations and transcriptional repression of the E-cadherin gene have been widely studied, not much is known about posttranslational regulation of E-cadherin in tumors. We show that E-cadherin is tightly coexpressed with the secretory pathway Ca2+-ATPase isoform 2, SPCA2 (ATP2C2), in breast tumors. Loss of SPCA2 impairs surface expression of E-cadherin and elicits mesenchymal gene expression through disruption of cell adhesion in tumorspheres and downstream Hippo-YAP signaling. Conversely, ectopic expression of SPCA2 in triple-negative breast cancer elevates baseline Ca2+ and YAP phosphorylation, enhances posttranslational expression of E-cadherin, and suppresses mesenchymal gene expression. Thus, loss of SPCA2 phenocopies loss of E-cadherin in the Hippo signaling pathway and EMT-MET transitions, consistent with a functional role for SPCA2 in E-cadherin biogenesis. Furthermore, we show that SPCA2 suppresses invasive phenotypes, including cell migration in vitro and tumor metastasis in vivo. Based on these findings, we propose that SPCA2 functions as a key regulator of EMT and may be a potential therapeutic target for treatment of metastatic cancer. IMPLICATIONS: Posttranslational control of E-cadherin and the Hippo pathway by calcium signaling regulates EMT in breast cancer cells.
Institutional allocations in the primary market for corporate bonds

Abstract Using 2002–2014 insurer transactions, we provide the first empirical evidence on underwriters’ allocation practices in the primary market for corporate bonds. Since bonds are often underpriced, allocations generate for investors an estimated $41 billion of first-day profits. These profits increase with proxies for investors’ information production during the bookbuilding process and, more strongly, with investors’ prior trading with underwriters. Information production has a larger impact when asymmetric information is higher, while prior trading has a larger impact when the issuer-underwriter agency problem is more severe. When there is more competition for allocations, prior trading further increases an insurer’s first-day profits.
Wormhole: A Fast Ordered Index for In-memory Data Management

In-memory data management systems, such as key-value stores, have become an essential infrastructure in today's big-data processing and cloud computing. They rely on efficient index structures to access data. While unordered indexes, such as hash tables, can perform point search with O(1) time, they cannot be used in many scenarios where range queries must be supported. Many ordered indexes, such as B+ tree and skip list, have a O(log N) lookup cost, where N is number of keys in an index. For an ordered index hosting billions of keys, it may take more than 30 key-comparisons in a lookup, which is an order of magnitude more expensive than that on a hash table. With availability of large memory and fast network in today's data centers, this O(log N) time is taking a heavy toll on applications that rely on ordered indexes. In this paper we introduce a new ordered index structure, named Wormhole, that takes O(log L) worst-case time for looking up a key with a length of L. The low cost is achieved by simultaneously leveraging strengths of three indexing structures, namely hash table, prefix tree, and B+ tree, to orchestrate a single fast ordered index. Wormhole's range operations can be performed by a linear scan of a list after an initial lookup. This improvement of access efficiency does not come at a price of compromised space efficiency. Instead, Wormhole's index space is comparable to those of B+ tree and skip list. Experiment results show that Wormhole outperforms skip list, B+ tree, ART, and Masstree by up to 8.4x, 4.9x, 4.3x, and 6.6x in terms of key lookup throughput, respectively.
A three-tier redundant architecture for safe and reliable cloud-based CNC over public internet networks

Abstract Cloud-based CNC (C-CNC) is an emerging concept within Industry 4.0 where computer numerical control (CNC) functionalities are moved to the cloud and provided to manufacturing machines as a service. Among many benefits, C-CNC allows manufacturing machines to leverage advanced control algorithms running on cloud computers to boost their performance at low cost, without need for major hardware upgrades. However, a fundamental challenge of C-CNC is how to guarantee safety and reliability of machine control given variable Internet quality of service (e.g. delays), especially on public Internet networks. We propose a three-tier redundant architecture to address this challenge. We then prototype tier one of the architecture on a 3D printer successfully controlled via C-CNC over public Internet connections, and discuss follow-on research opportunities.
GenomeScope: fast reference-free genome profiling from short reads

Summary: GenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates. Availability and Implementation: http://genomescope.org , https://github.com/schatzlab/genomescope.git. Contact: mschatz@jhu.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics.

SUMMARY Large biobanks linking phenotype to genotype have led to an explosion of genetic association studies across a wide range of phenotypes. Sharing the knowledge generated by these resources with the scientific community remains a challenge due to patient privacy and the vast amount of data. Here, we present Global Biobank Engine (GBE), a web-based tool that enables exploration of the relationship between genotype and phenotype in biobank cohorts, such as the UK Biobank. GBE supports browsing for results from genome-wide association studies, phenome-wide association studies, gene-based tests and genetic correlation between phenotypes. We envision GBE as a platform that facilitates the dissemination of summary statistics from biobanks to the scientific and clinical communities. AVAILABILITY AND IMPLEMENTATION GBE currently hosts data from the UK Biobank and can be found freely available at biobankengine.stanford.edu.
Synthesis and crystal structure of NdFe0.45Ge2 and HoFe0.33Ge2

Abstract The compounds NdFe 0.45 Ge 2 and HoFe 0.33 Ge 2 have been synthesized and studied by single-crystal X-ray diffraction. They crystallize in the space group D 2 h 17 − C m c m of the orthorhombic system with Z =4 in the unit cell: a =4.091 (2) A, b =15.679(7) A, c =3.985(2) A, V =255.6(4) A 3 ( T =296 K) for HoFe 0.33 Ge 2 ; and a =4.214(2) A, b =16.455(9) A, c =4.070(2) A, V =282.2(4) A 3 (T=296 K) for NdFe 0.45 Ge 2 . The compounds exhibit the defect CeNiSi 2 structure-type.