A Simple Algorithm to Predict Incident Kidney Disease

Despite the growing burden of chronic kidney disease (CKD), there are no algorithms (to our knowledge) to quantify the effect of concurrent risk factors on the development of incident disease

Association of C-Reactive Protein and Microalbuminuria (from the National Health and Nutrition Examination Surveys, 1999 to 2004)

Chronic kidney disease and cardiovascular disease share many risk factors. Injury to the vascular endothelium, measured by elevated levels of serum C-reactive protein (CRP), may play a role in kidney and cardiovascular disease. We therefore examined the association of CRP with microalbuminuria, a marker of early kidney injury. We conducted a cross-sectional analysis of a nationally representative, population-based survey. Weighted multiple logistic regression was used to study the association between CRP and microalbuminuria, adjusting for well-known risk factors. CRP was analyzed by a continuous variable and two categorized variables using quartiles and clinically recommended cutpoints. CRP concentration was positively associated with microalbuminuria. In the multivariate model, a one unit (in milligrams per liter) increase in CRP concentration was associated with a 2% increased odds of microalbuminuria (odds ratio 1.02, 95% confidence interval [CI] 1.01 to 1.02, p = 0.0003). When CRP concentrations were stratified by clinically recommended cutpoints, compared with persons with CRP concentrations 3 mg/L were 1.15 times (95% CI 0.94 to 1.42) and 1.33 times (95% CI 1.08 to 1.65) more likely to have microalbuminuria, respectively. In subgroup analyses, the strength of association was comparable or stronger. In conclusion, elevated CRP levels were associated with microalbuminuria in a large, nationally representative data set. Vascular inflammation, as measured by CRP, may be a common contributor to early heart and kidney disease

Research Needs and Challenges in the FEW System: Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models for Sustainable Food, Energy, and Water Systems

On October 12–13, a workshop funded by the National Science Foundation was held at Iowa State University in Ames, Iowa with a goal of identifying research needs related to coupled economic and biophysical models within the FEW system. Approximately 80 people attended the workshop with about half representing the social sciences (primarily economics) and the rest from the physical and natural sciences. The focus and attendees were chosen so that findings would be particularly relevant to SBE research needs while taking into account the critical connectivity needed between social sciences and other disciplines. We have identified several major gaps in existing scientific knowledge that present substantial impediments to understanding the FEW system. We especially recommend research in these areas as a priority for future funding: 1. Economic models of decision-making in coupled systems Deliberate human activity has been the dominant factor driving environmental and land-use changes for hundreds of years. While economists have made great strides in modeling and understanding these choices, the coupled systems modeling literature, with some important exceptions, has not reflected these contributions. Several paths forward seem fruitful. First, baseline economic models that assume rationality can be used much more widely than they are currently. Moreover, the current generation of IAMs that include rational agents have emphasized partial equilibrium studies appropriate for smaller systems. To allow this approach to be used to study larger systems, the potential for (and consequences of) general equilibrium effects should be studied as well. Second, it is important to address shortcomings in these models of economic decision-making. Valuable improvements could be gained from developing coupled models that draw insights from behavioral economics. Many decision-makers deviate systematically from actions that would be predicted by strict rationality, but very few IAMs incorporate this behavior, potentially leading to inaccurate predictions about the effects of policies and regulations. Improved models of human adaptation and induced technological change can also be incorporated into coupled models. Particularly for medium to long-run models, decisions about adaptation and technological change will have substantial effects on the conclusions and policy implications, but more compelling methods for incorporating these changes into modeling are sorely needed. In addition, some economic decisions are intrinsically dynamic yet few coupled models explicitly incorporate dynamic models. Economic models that address uncertainty in decision making are also underutilized in coupled models of the FEW system. 2. Coupling models across disciplines Despite much recent progress, established models for one component of the FEW system often cannot currently produce outcomes that can be used as inputs for models of other components. This misalignment makes integrated modeling difficult and is especially apparent in linking models of natural phenomena with models of economic decision-making. Economic agents typically act to maximize a form of utility or welfare that is not directly linked to physical processes, and they typically require probabilistic forecasts as an input to their decision-making that many models in the natural sciences cannot directly produce. We believe that an especially promising approach is the development of “bridge” models that convert outputs from one model into inputs for another. Such models can be viewed as application-specific, reduced-form distillations of a richer and more realistic underlying model. Ideally, these bridge models would be developed in collaborative research projects involving economists, statisticians, and disciplinary specialists, and would contribute to improved understanding in the scientific discipline as well. 3. Model validation and comparison There is little clarity on how models should be evaluated and compared to each other, both within individual disciplines and as components of larger IAMs. This challenge makes larger integrated modeling exercises extremely difficult. Some potential ways to advance are by developing statistical criteria that measure model performance along the dimensions suitable for inclusion in an IAM as well as infrastructure and procedures to facilitate model comparisons. Focusing on the models’ out-of-sample distributional forecasting performance, as well as that of the IAM overall, is especially promising and of particular importance. Moreover, applications of IAMs tend to estimate the effect of hypothetical future policy actions, but there have been very few studies that have used these models to estimate the effect of past policy actions. These exercises should be encouraged. They offer a well-understood test bed for the IAMs, and also contribute to fundamental scientific knowledge through better understanding of the episode in question. The retrospective nature of this form of analysis also presents the opportunity to combine reduced-form estimation strategies with the IAMs as an additional method of validation

Global diversity and antimicrobial resistance of typhoid fever pathogens: insights from a meta-analysis of 13,000 Salmonella Typhi genomes

Background: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). Methods: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. Results: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal ‘sentinel’ surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. Conclusions: The consortium’s aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies

An Empirical Comparison of Consumer Innovation Adoption Models: Implications for Subsistence Marketplaces

So called “pro-poor” innovations may improve consumer wellbeing in subsistence marketplaces. However, there is little research that integrates the area with the vast literature on innovation adoption. Using a questionnaire where respondents were asked to provide their evaluations about a mobile banking innovation, this research fills this gap by providing empirical evidence of the applicability of existing innovation adoption models in subsistence marketplaces. The study was conducted in Bangladesh among a geographically dispersed sample. The data collected allowed an empirical comparison of models in a subsistence context. The research reveals the most useful models in this context to be the Value Based Adoption Model and the Consumer Acceptance of Technology model. In light of these findings and further examination of the model comparison results the research also shows that consumers in subsistence marketplaces are not just motivated by functionality and economic needs. If organizations cannot enhance the hedonic attributes of a pro-poor innovation, and reduce the internal/external constraints related to adoption of that pro-poor innovation, then adoption intention by consumers will be lower

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV

Measurements of the Electroweak Diboson Production Cross Sections in Proton-Proton Collisions at root s=5.02 TeV Using Leptonic Decays

The first measurements of diboson production cross sections in proton-proton interactions at a center-of-mass energy of 5.02 TeV are reported. They are based on data collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 302 pb(-1). Events with two, three, or four charged light leptons (electrons or muons) in the final state are analyzed. The WW, WZ, and ZZ total cross sections are measured as sigma(WW) = 37:0(-5.2)(+5.5) (stat)(-2.6)(+2.7) (syst) pb, sigma(WZ) = 6.4(-2.1)(+2.5) (stat)(-0.3)(+0.5)(syst) pb, and sigma(ZZ) = 5.3(-2.1)(+2.5)(stat)(-0.4)(+0.5) (syst) pb. All measurements are in good agreement with theoretical calculations at combined next-to-next-to-leading order quantum chromodynamics and next-to-leading order electroweak accuracy

Search for lepton-flavor violating decays of the Higgs boson in the mu tau and e tau final states in proton-proton collisions at root s=13 TeV

A search is presented for lepton-flavor violating decays of the Higgs boson to mu t and et. The dataset corresponds to an integrated luminosity of 137 fb(-1) collected at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV. No significant excess has been found, and the results are interpreted in terms of upper limits on lepton-flavor violating branching fractions of the Higgs boson. The observed (expected) upper limits on the branching fractions are, respectively, B(H -> mu t) e tau) < 0.22(0.16)% at 95% confidence level.Peer reviewe

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe