Real-time forecasting of inflation and output growth with autoregressive models in the presence of data revisions

We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

Probability distributions or point predictions? Survey forecasts of US output growth and inflation

We consider whether survey respondents’ probability distributions, reported as histograms, provide reliable and coherent point predictions, when viewed through the lens of a Bayesian learning model. We argue that a role remains for eliciting directly-reported point predictions in surveys of professional forecasters.

US inflation expectations and heterogeneous loss functions, 1968-2010

Recent literature has suggested that macroeconomic forecasters may have asymmetric loss functions, and that there may be heterogeneity across forecasters in the degree to which they weigh under- and over-predictions. Using an individual-level analysis that exploits the Survey of Professional Forecasters respondents’ histogram forecasts, we find little evidence of asymmetric loss for the inflation forecasters

Targeting stem cell niches and trafficking for cardiovascular therapy.

Regenerative cardiovascular medicine is the frontline of 21st-century health care. Cell therapy trials using bone marrow progenitor cells documented that the approach is feasible, safe and potentially beneficial in patients with ischemic disease. However, cardiovascular prevention and rehabilitation strategies should aim to conserve the pristine healing capacity of a healthy organism as well as reactivate it under disease conditions. This requires an increased understanding of stem cell microenvironment and trafficking mechanisms. Engagement and disengagement of stem cells of the osteoblastic niche is a dynamic process, finely tuned to allow low amounts of cells move out of the bone marrow and into the circulation on a regular basis. The balance is altered under stress situations, like tissue injury or ischemia, leading to remarkably increased cell egression. Individual populations of circulating progenitor cells could give rise to mature tissue cells (e.g. endothelial cells or cardiomyocytes), while the majority may differentiate to leukocytes, affecting the environment of homing sites in a paracrine way, e.g. promoting endothelial survival, proliferation and function, as well as attenuating or enhancing inflammation. This review focuses on the dynamics of the stem cell niche in healthy and disease conditions and on therapeutic means to direct stem cell/progenitor cell mobilization and recruitment into improved tissue repair.

Targeting Staphylococcus aureus quorum sensing with non-peptidic small molecule inhibitors

A series of 3-oxo-C12-HSL, tetramic acid and tetronic acid analogues was synthesized to gain insights into the structural requirements for quorum sensing inhibition in Staphylococcus aureus. Compounds active against agr were non-competitive inhibitors of the auto-inducing peptide (AIP)-activated AgrC receptor, by altering the activation efficacy of the cognate AIP-1. They appeared to act as negative allosteric modulators and are exemplified by 3-tetradecanoyltetronic acid 17 which reduced nasal cell colonization and arthritis in a murine infection model.

Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t-test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type-1 error rates, when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type-1 error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.

Forecast uncertainty—ex Ante and ex Post: U.S. inflation and output growth

Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to the ex post measure as the forecast horizon shortens. There is little evidence of a link between individuals’ ex post forecast accuracy and their ex ante subjective assessments.

Military targeting in the context of self-defence actions

In order to bring conceptual clarity to a particular dimension of the relationship between the jus ad bellum and the jus in bello regimes, this article explores the independent sources of a military targeting rule in both branches of international law. The aim is not to displace the jus in bello as the ‘lead’ regime on how targeting decisions must be made, or to undermine the traditional separation between these regimes. Rather, conceptual light is shed on a sometimes assumed but generally neglected dimension of the jus ad bellum’s necessity and proportionality criteria that may, in limited circumstances, have significance for our understanding of human protection during war, by covering possible gaps in the jus in bello targeting rules.

A SNP-based consensus genetic map for synteny-based trait targeting in faba bean (Vicia faba L.)

Faba bean (Vicia faba L.) is a globally important nitrogen-fixing legume, which is widely grown in a diverse range of environments. In this work, we mine and validate a set of 845 SNPs from the aligned transcriptomes of two contrasting inbred lines. Each V. faba SNP is assigned by BLAST analysis to a single Medicago orthologue. This set of syntenically anchored polymorphisms were then validated as individual KASP assays, classified according to their informativeness and performance on a panel of 37 inbred lines, and the best performing 757 markers used to genotype six mapping populations. The six resulting linkage maps were merged into a single consensus map on which 687 SNPs were placed on six linkage groups, each presumed to correspond to one of the six V. faba chromosomes. This sequence-based consensus map was used to explore synteny with the most closely-related crop species, lentil, and the most closely related fully sequenced genome, Medicago. Large tracts of uninterrupted colinearity were found between faba bean and Medicago, making it relatively straightforward to predict gene content and order in mapped genetic interval. As a demonstration of this, we mapped a flower colour gene to a 2 cM interval of Vf chromosome 2 which was highly collinear with Mt3. The obvious candidate gene from 77 gene models in the collinear Medicago chromosome segment was the previously characterized MtWD40-1 gene (Mt3g092830, Mt3g092840) controlling anthocyanin production in Medicago and re-sequencing of the Vf orthologue showed a putative causative deletion of the entire 5’ end of the gene.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

Targeting myocardial remodelling to develop novel therapies for heart failure: a position paper from the Working Group on Myocardial Function of the European Society of Cardiology

The failing heart is characterized by complex tissue remodelling involving increased cardiomyocyte death, and impairment of sarcomere function, metabolic activity, endothelial and vascular function, together with increased inflammation and interstitial fibrosis. For years, therapeutic approaches for heart failure (HF) relied on vasodilators and diuretics which relieve cardiac workload and HF symptoms. The introduction in the clinic of drugs interfering with beta-adrenergic and angiotensin signalling have ameliorated survival by interfering with the intimate mechanism of cardiac compensation. Current therapy, though, still has a limited capacity to restore muscle function fully, and the development of novel therapeutic targets is still an important medical need. Recent progress in understanding the molecular basis of myocardial dysfunction in HF is paving the way for development of new treatments capable of restoring muscle function and targeting specific pathological subsets of LV dysfunction. These include potentiating cardiomyocyte contractility, increasing cardiomyocyte survival and adaptive hypertrophy, increasing oxygen and nutrition supply by sustaining vessel formation, and reducing ventricular stiffness by favourable extracellular matrix remodelling. Here, we consider drugs such as omecamtiv mecarbil, nitroxyl donors, cyclosporin A, SERCA2a (sarcoplasmic/endoplasmic Ca(2 +) ATPase 2a), neuregulin, and bromocriptine, all of which are currently in clinical trials as potential HF therapies, and discuss novel molecular targets with potential therapeutic impact that are in the pre-clinical phases of investigation. Finally, we consider conceptual changes in basic science approaches to improve their translation into successful clinical applications.

Meta-analysis to integrate effect sizes within a paper: Possible misuse and Type-1 error inflation

In recent years an increasing number of papers have employed meta-analysis to integrate effect sizes of researchers’ own series of studies within a single paper (“internal meta-analysis”). Although this approach has the obvious advantage of obtaining narrower confidence intervals, we show that it could inadvertently inflate false-positive rates if researchers are motivated to use internal meta-analysis in order to obtain a significant overall effect. Specifically, if one decides whether to stop or continue a further replication experiment depending on the significance of the results in an internal meta-analysis, false-positive rates would increase beyond the nominal level. We conducted a set of Monte-Carlo simulations to demonstrate our argument, and provided a literature review to gauge awareness and prevalence of this issue. Furthermore, we made several recommendations when using internal meta-analysis to make a judgment on statistical significance.

The impact of the elderly on inflation rates in developed countries

What explains the cross-national variation in inflation rates in developed countries? Previous literature has emphasised the role of ideas and institutions, and to a lesser extent interest groups, while leaving the role of electoral politics comparatively unexplored. This paper seeks to redress this neglect by focusing on one case where electoral politics matters for inflation: the share of the population above 65 years old in a country. I argue that countries with a larger share of elderly have lower inflation because older people are both more inflation averse and politically powerful, forcing governments to pursue lower inflation. I test my argument in three steps. First, logistic regression analysis of survey data confirms older people are more inflation averse. Second, panel data regression analysis of party manifesto data reveals that European countries with more old people have more economically orthodox political parties. Third, time series cross-section regression analyses demonstrate that the share of the elderly is negatively correlated with inflation in both a sample of 21 advanced OECD economies and a larger sample of 175 countries. Ageing may therefore push governments to adopt a low inflation regime.

The effect of targeting tolerance of children's negative emotions among anxious parents of children with anxiety disorders: a pilot randomised controlled trial

Following cognitive behavioural therapy for child anxiety a significant minority of children fail to lose their diagnosis status. One potential barrier is high parental anxiety. We designed a pilot RCT to test claims that parental intolerance of the child’s negative emotions may impact treatment outcomes. Parents of 60 children with an anxiety disorder, who were themselves highly anxious, received either brief parent-delivered treatment for child anxiety or the same treatment with strategies specifically targeting parental tolerance of their child’s negative emotions. Consistent with predictions, parental tolerance of the child’s negative emotions significantly improved from pre- to post-treatment. However, there was no evidence to inform the direction of this association as improvements were substantial in both groups. Moreover, while there were significant improvements in child anxiety in both conditions, there was little evidence that this was associated with the improvement in parental tolerance. Nevertheless, findings provide important clinical insight, including that parent-led treatments are appropriate even when the parent is highly anxious and that it may not be necessary to adjust interventions for many families.