A Leading Indicator for the Dutch Economy – Methodological and Empirical Revision of the CPB System

Since 1990 the Netherlands Bureau for Economic Policy Analysis (CPB) uses a leading indicator in preparing short-term forecasts for the Dutch economy. This paper describes some recent methodological innovations as well as the current structure and empirical results of the revised CPB leading indicator. Special attention is paid to the role and significance of IFO data. The structure of the CPB leading indicator is tailored to its use as a supplement to model-based projections, and thus has a unique character in several respects. The system of the CPB leading indicator is composed of ten separate composite indicators, seven for expenditure categories (‘demand’) and three for the main production sectors (‘supply’). This system approach has important advantages over the usual structure, in which the basis series are directly linked to a single reference series. The revised system, which uses 25 different basic series, performs quite well in describing the economic cycle of GDP, in indicating the upturns and downturns, and in telling the story behind the business cycle.leading indicator, short-term forecasts

Simian Immunodeficiency Virus Infection of Chimpanzees (Pan troglodytes) Shares Features of Both Pathogenic and Non-pathogenic Lentiviral Infections.

The virus-host relationship in simian immunodeficiency virus (SIV) infected chimpanzees is thought to be different from that found in other SIV infected African primates. However, studies of captive SIVcpz infected chimpanzees are limited. Previously, the natural SIVcpz infection of one chimpanzee, and the experimental infection of six chimpanzees was reported, with limited follow-up. Here, we present a long-term study of these seven animals, with a retrospective re-examination of the early stages of infection. The only clinical signs consistent with AIDS or AIDS associated disease was thrombocytopenia in two cases, associated with the development of anti-platelet antibodies. However, compared to uninfected and HIV-1 infected animals, SIVcpz infected animals had significantly lower levels of peripheral blood CD4+ T-cells. Despite this, levels of T-cell activation in chronic infection were not significantly elevated. In addition, while plasma levels of β2 microglobulin, neopterin and soluble TNF-related apoptosis inducing ligand (sTRAIL) were elevated in acute infection, these markers returned to near-normal levels in chronic infection, reminiscent of immune activation patterns in 'natural host' species. Furthermore, plasma soluble CD14 was not elevated in chronic infection. However, examination of the secondary lymphoid environment revealed persistent changes to the lymphoid structure, including follicular hyperplasia in SIVcpz infected animals. In addition, both SIV and HIV-1 infected chimpanzees showed increased levels of deposition of collagen and increased levels of Mx1 expression in the T-cell zones of the lymph node. The outcome of SIVcpz infection of captive chimpanzees therefore shares features of both non-pathogenic and pathogenic lentivirus infections.This work was supported by the Biotechnology and Biological Sciences Research Council and by the Wellcome Trust.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.ppat.100514

One model and various experts: Evaluating Dutch macroeconomic forecasts

The Netherlands Bureau for Economic Policy Analysis (CPB) uses a large macroeconomic model to create forecasts of various important macroeconomic variables. The outcomes of this model are usually filtered by experts, and it is the expert forecasts that are made available to the general public. In this paper we re-create the model forecasts for the period 1997-2008 and compare the expert forecasts with the pure model forecasts. Our key findings from the first time that this unique database has been analyzed are that (i) experts adjust upwards more often; (ii) expert adjustments are not autocorrelated, but their sizes do depend on the value of the model forecast; (iii) the CPB model forecasts are biased for a range of variables, but (iv) at the same time, the associated expert forecasts are more often unbiased; and that (v) expert forecasts are far more accurate than the model forecasts, particularly when the forecast horizon is short. In summary, the final CPB forecasts de-bias the model forecasts and lead to higher accuracies than the initial model forecasts.Macroeconomic forecasting Expert adjustment Forecast accuracy

Witte vlekken ingekleurd : archeologie in het tracé van de HSL-Zuid

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Human adipocyte extracellular vesicles in reciprocal signaling between adipocytes and macrophages

OBJECTIVE: Extracellular vesicles (EVs) released by human adipocytes or adipose tissue (AT)-explants play a role in the paracrine interaction between adipocytes and macrophages, a key mechanism in AT inflammation, leading to metabolic complications like insulin resistance (IR) were determined. METHODS: EVs released from in vitro differentiated adipocytes and AT-explants ex vivo were characterized by electron microscopy, Western blot, multiplex adipokine-profiling, and quantified by flow cytometry. Primary monocytes were stimulated with EVs from adipocytes, subcutaneous (SCAT) or omental-derived AT (OAT), and phenotyped. Macrophage supernatant was subsequently used to assess the effect on insulin signaling in adipocytes. RESULTS: Adipocyte and AT-derived EVs differentiated monocytes into macrophages characteristic of human adipose tissue macrophages (ATM), defined by release of both pro- and anti-inflammatory cytokines. The adiponectin-positive subset of AT-derived EVs, presumably representing adipocyte-derived EVs, induced a more pronounced ATM-phenotype than the adiponectin-negative AT-EVs. This effect was more evident for OAT-EVs versus SCAT-EVs. Furthermore, supernatant of macrophages pre-stimulated with AT-EVs interfered with insulin signaling in human adipocytes. Finally, the number of OAT-derived EVs correlated positively with patients HOMA-IR. CONCLUSIONS: A possible role for human AT-EVs in a reciprocal pro-inflammatory loop between adipocytes and macrophages, with the potential to aggravate local and systemic IR was demonstrated

Predicting Poor Outcome Before Endovascular Treatment in Patients With Acute Ischemic Stroke

Background: Although endovascular treatment (EVT) has greatly improved outcomes in acute ischemic stroke, still one third of patients die or remain severely disabled after stroke. If we could select patients with poor clinical outcome despite EVT, we could prevent futile treatment, avoid treatment complications, and further improve stroke care. We aimed to determine the accuracy of poor functional outcome prediction, defined as 90-day modified Rankin Scale (mRS) score ≥5, despite EVT treatment. Methods: We included 1,526 patients from the MR CLEAN Registry, a prospective, observational, multicenter registry of ischemic stroke patients treated with EVT. We developed machine learning prediction models using all variables available at baseline before treatment. We optimized the models for both maximizing the area under the curve (AUC), reducing the number of false positives. Results: From 1,526 patients included, 480 (31%) of patients showed poor outcome. The highest AUC was 0.81 for random forest. The highest area under the precision recall curve was 0.69 for the support vector machine. The highest achieved specificity was 95% with a sensitivity of 34% for neural networks, indicating that all models contained false positives in their predictions. From 921 mRS 0–4 patients, 27–61 (3–6%) were incorrectly classified as poor outcome. From 480 poor outcome patients in the registry, 99–163 (21–34%) were correctly identified by the models. Conclusions: All prediction models showed a high AUC. The best-performing models correctly identified 34% of the poor outcome patients at a cost of misclassifying 4% of non-poor outcome patients. Further studies are necessary to determine whether these accuracies are reproducible before implementation in clinical practice

Predicting Poor Outcome Before Endovascular Treatment in Patients With Acute Ischemic Stroke

Background: Although endovascular treatment (EVT) has greatly improved outcomes in acute ischemic stroke, still one third of patients die or remain severely disabled after stroke. If we could select patients with poor clinical outcome despite EVT, we could prevent futile treatment, avoid treatment complications, and further improve stroke care. We aimed to determine the accuracy of poor functional outcome prediction, defined as 90-day modified Rankin Scale (mRS) score >= 5, despite EVT treatment. Methods: We included 1,526 patients from the MR CLEAN Registry, a prospective, observational, multicenter registry of ischemic stroke patients treated with EVT. We developed machine learning prediction models using all variables available at baseline before treatment. We optimized the models for both maximizing the area under the curve (AUC), reducing the number of false positives. Results: From 1,526 patients included, 480 (31%) of patients showed poor outcome. The highest AUC was 0.81 for random forest. The highest area under the precision recall curve was 0.69 for the support vector machine. The highest achieved specificity was 95% with a sensitivity of 34% for neural networks, indicating that all models contained false positives in their predictions. From 921 mRS 0-4 patients, 27-61 (3-6%) were incorrectly classified as poor outcome. From 480 poor outcome patients in the registry, 99-163 (21-34%) were correctly identified by the models. Conclusions: All prediction models showed a high AUC. The best-performing models correctly identified 34% of the poor outcome patients at a cost of misclassifying 4% of non-poor outcome patients. Further studies are necessary to determine whether these accuracies are reproducible before implementation in clinical practice

Phase behavior of hard particles

The phase behavior of hard particles and mixtures thereof is reviewed. Special attention is given to a lattice model consisting of hard hexagons and points on a triangular lattice. This model appears to have two disordered phases and an ordered phase