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In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development.
In the aftermath of the global financial crisis, the state of macroeconomicmodeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development
This chapter aims to provide a hands-on approach to New Keynesian models and their uses for macroeconomic policy analysis. It starts by reviewing the origins of the New Keynesian approach, the key model ingredients and representative models. Building blocks of current-generation dynamic stochastic general equilibrium (DSGE) models are discussed in detail. These models address the famous Lucas critique by deriving behavioral equations systematically from the optimizing and forward-looking decision-making of households and firms subject to well-defined constraints. State-of-the-art methods for solving and estimating such models are reviewed and presented in examples. The chapter goes beyond the mere presentation of the most popular benchmark model by providing a framework for model comparison along with a database that includes a wide variety of macroeconomic models. Thus, it offers a convenient approach for comparing new models to available benchmarks and for investigating whether particular policy recommendations are robust to model uncertainty. Such robustness analysis is illustrated by evaluating the performance of simple monetary policy rules across a range of recently-estimated models including some with financial market imperfections and by reviewing recent comparative findings regarding the magnitude of government spending multipliers. The chapter concludes with a discussion of important objectives for on-going and future research using the New Keynesian framework.
Der Botanische Arbeitskreis Nordharz e.V. 1) führte vom 10.-11.8.1996 eine Kartierungsexkursion in das Gebiet um Sangerhausen durch2). Zum Zeitpunkt der Exkursionsvorbereitung war kein Kartierer im Rahmen der laufenden Sachsen-Anhalt-Kartierung in diesem Meßtischblatt tätig. Ziel war daher die Erfassung des Grundbestandes in den vier Quadranten. Die erste Augusthälfte wurde gewählt, um mit den Sommer- und Spätsommeraspekten ein möglichst breites Artenspektrum erschließen zu können. Allein der Frühjahrsaspekt blieb damit unberücksichtigt. Im nachfolgenden wird über bemerkenswerte Pflanzenfunde berichtet, sowohl Neufunde gegenüber dem Kenntnisstand, der die Grundlage für den Florenatlas der neuen Bundesländer bildete3), als auch Bestätigungen seltener und überregional bedeutsamer Artenvorkommen. Alle Funde beziehen sich, wenn nicht anders angegeben, auf das Meßtischblatt 4533, so daß den Fundorten nur die Quadrantennummer vorangestellt wird.
Simple Summary: The incidence of brain metastases from breast cancer is increasing and the treatment is still a major challenge. Several scores have been developed in order to estimate the prognosis of patients with brain metastases by objective criteria. Here, we validated all three published graded-prognostic-assessment (GPA)-scores in a subcohort of 882 breast cancer patients with brain metastases in the Brain Metastases in the German Breast Cancer (BMBC) registry. Although all three available GPA-scores were associated with OS, they all show limitations mainly in predicting short-term (below 3 months) survival but also in long-term (above 12 months) survival. We discuss the test performances of all scores in our work and provide evidence how physicians should use them as a tool to select patients for different treatment options.
Abstract: Several scores have been developed in order to estimate the prognosis of patients with brain metastases (BM) by objective criteria. The aim of this analysis was to validate all three published graded-prognostic-assessment (GPA)-scores in a subcohort of 882 breast cancer (BC) patients with BM in the Brain Metastases in the German Breast Cancer (BMBC) registry. The median age at diagnosis of BM was 57 years. All in all, 22.3% of patients (n = 197) had triple-negative, 33.4% (n = 295) luminal A like, 25.1% (n = 221) luminal B/HER2-enriched like and 19.2% (n = 169) HER2 positive like BC. Age ≥60 years, evidence of extracranial metastases (ECM), higher number of BM, triple-negative subtype and low Karnofsky-Performance-Status (KPS) were all associated with worse overall survival (OS) in univariate analysis (p < 0.001 each). All three GPA-scores were associated with OS. The breast-GPA showed the highest probability of classifying patients with survival above 12 months in the best prognostic group (specificity 68.7% compared with 48.1% for the updated breast-GPA and 21.8% for the original GPA). Sensitivities for predicting 3 months survival were very low for all scores. In this analysis, all GPA-scores showed only moderate diagnostic accuracy in predicting the OS of BC patients with BM.
Characteristics and clinical outcome of breast cancer patients with asymptomatic brain metastases
(2020)
Simple Summary: The prognosis for patients with breast cancer that has spread to the brain is poor, and survival for these women hasn’t improved over the last few decades. We do not currently test for asymptomatic brain metastases in breast cancer patients, although this does happen in some other types of cancer. In this study we wanted to find out more about breast cancer that has spread to the brain and in particular to see whether there might be any advantage to spotting brain metastases before the development of neurological symptoms. Overall, our results suggest that women could be better off if their brain metastases are diagnosed before they begin to cause symptoms. We now need to carry out a clinical trial to see what happens if we screen high-risk breast cancer patients for brain metastases. This will verify whether doing so could increase survival, symptom control or quality of life.
Abstract: Background: Brain metastases (BM) have become a major challenge in patients with metastatic breast cancer. Methods: The aim of this analysis was to characterize patients with asymptomatic BM (n = 580) in the overall cohort of 2589 patients with BM from our Brain Metastases in Breast Cancer Network Germany (BMBC) registry. Results: Compared to symptomatic patients, asymptomatic patients were slightly younger at diagnosis (median age: 55.5 vs. 57.0 years, p = 0.01), had a better performance status at diagnosis (Karnofsky index 80–100%: 68.4% vs. 57%, p < 0.001), a lower number of BM (>1 BM: 56% vs. 70%, p = 0.027), and a slightly smaller diameter of BM (median: 1.5 vs. 2.2 cm, p < 0.001). Asymptomatic patients were more likely to have extracranial metastases (86.7% vs. 81.5%, p = 0.003) but were less likely to have leptomeningeal metastasis (6.3% vs. 10.9%, p < 0.001). Asymptomatic patients underwent less intensive BM therapy but had a longer median overall survival (statistically significant for a cohort of HER2-positive patients) compared to symptomatic patients (10.4 vs. 6.9 months, p < 0.001). Conclusions: These analyses show a trend that asymptomatic patients have less severe metastatic brain disease and despite less intensive local BM therapy still have a better outcome (statistically significant for a cohort of HER2-positive patients) than patients who present with symptomatic BM, although a lead time bias of the earlier diagnosis cannot be ruled out. Our analysis is of clinical relevance in the context of potential trials examining the benefit of early detection and treatment of BM.
Synthesis of acetate from carbon dioxide and molecular hydrogen is considered to be the first carbon assimilation pathway on earth. It combines carbon dioxide fixation into acetyl-CoA with the production of ATP via an energized cell membrane. How the pathway is coupled with the net synthesis of ATP has been an enigma. The anaerobic, acetogenic bacterium Acetobacterium woodii uses an ancient version of this pathway without cytochromes and quinones. It generates a sodium ion potential across the cell membrane by the sodium-motive ferredoxin:NAD oxidoreductase (Rnf). The genome sequence of A. woodii solves the enigma: it uncovers Rnf as the only ion-motive enzyme coupled to the pathway and unravels a metabolism designed to produce reduced ferredoxin and overcome energetic barriers by virtue of electron-bifurcating, soluble enzymes.
Epigenetic signatures such as methylation of the monoamine oxidase A (MAOA) gene have been found to be altered in panic disorder (PD). Hypothesizing temporal plasticity of epigenetic processes as a mechanism of successful fear extinction, the present psychotherapy-epigenetic study for we believe the first time investigated MAOA methylation changes during the course of exposure-based cognitive behavioral therapy (CBT) in PD. MAOA methylation was compared between N=28 female Caucasian PD patients (discovery sample) and N=28 age- and sex-matched healthy controls via direct sequencing of sodium bisulfite-treated DNA extracted from blood cells. MAOA methylation was furthermore analyzed at baseline (T0) and after a 6-week CBT (T1) in the discovery sample parallelized by a waiting time in healthy controls, as well as in an independent sample of female PD patients (N=20). Patients exhibited lower MAOA methylation than healthy controls (P<0.001), and baseline PD severity correlated negatively with MAOA methylation (P=0.01). In the discovery sample, MAOA methylation increased up to the level of healthy controls along with CBT response (number of panic attacks; T0–T1: +3.37±2.17%), while non-responders further decreased in methylation (−2.00±1.28%; P=0.001). In the replication sample, increases in MAOA methylation correlated with agoraphobic symptom reduction after CBT (P=0.02–0.03). The present results support previous evidence for MAOA hypomethylation as a PD risk marker and suggest reversibility of MAOA hypomethylation as a potential epigenetic correlate of response to CBT. The emerging notion of epigenetic signatures as a mechanism of action of psychotherapeutic interventions may promote epigenetic patterns as biomarkers of lasting extinction effects.
n this paper we report on the investigation of baryonic resonance production in proton-proton collisions at the kinetic energies of 1.25 GeV and 3.5 GeV, based on data measured with HADES. Exclusive channels npπ+ and ppπ0 as well as ppe+e− were studied simultaneously in the framework of a one-boson exchange model. The resonance cross sections were determined from the one-pion channels for Δ(1232) and N(1440) (1.25 GeV) as well as further Δ and N* resonances up to 2 GeV/c2 for the 3.5 GeV data. The data at 1.25 GeV energy were also analysed within the framework of the partial wave analysis together with the set of several other measurements at lower energies. The obtained solutions provided the evolution of resonance production with the beam energy, showing a sizeable non-resonant contribution but with still dominating contribution of Δ(1232)P33. In the case of 3.5 GeV data, the study of the ppe+e− channel gave the insight on the Dalitz decays of the baryon resonances and, in particular, on the electromagnetic transition form-factors in the time-like region. We show that the assumption of a constant electromagnetic transition form-factors leads to underestimation of the yield in the dielectron invariant mass spectrum below the vector mesons pole. On the other hand, a comparison with various transport models shows the important role of intermediate ρ production, though with a large model dependency. The exclusive channels analysis done by the HADES collaboration provides new stringent restrictions on the parameterizations used in the models.