Sozialstaatliche Kürzungspolitik in Deutschland: Nur eine Mär? Eine quantitative Gesetzgebungsanalyse 1974–2014

Quantitative analyses on welfare state dynamics have to cope with the “dependent variable problem”, as studies on social spending reach different conclusions than analyses of replacement rate data. This article suggests a way around this problem by presenting results from a fine-grained analysis of welfare state legislation in Germany between 1974 and 2014. We show that the German welfare state has seen both cuts and expansions occur in all decades. Moreover, we show by means of a regression analysis that partisan politics play a role. Supporting the “Nixon-in-China”-thesis, social democratic governments are associated with a higher probability of cutbacks – especially in times of budgetary pressure – whereas expansions are more likely under Christian democratic governments

A Stochastic Model of Latently Infected Cell Reactivation and Viral Blip Generation in Treated HIV Patients

Motivated by viral persistence in HIV+ patients on long-term anti-retroviral treatment (ART), we present a stochastic model of HIV viral dynamics in the blood stream. We consider the hypothesis that the residual viremia in patients on ART can be explained principally by the activation of cells latently infected by HIV before the initiation of ART and that viral blips (clinically-observed short periods of detectable viral load) represent large deviations from the mean. We model the system as a continuous-time, multi-type branching process. Deriving equations for the probability generating function we use a novel numerical approach to extract the probability distributions for latent reservoir sizes and viral loads. We find that latent reservoir extinction-time distributions underscore the importance of considering reservoir dynamics beyond simply the half-life. We calculate blip amplitudes and frequencies by computing complete viral load probability distributions, and study the duration of viral blips via direct numerical simulation. We find that our model qualitatively reproduces short small-amplitude blips detected in clinical studies of treated HIV infection. Stochastic models of this type provide insight into treatment-outcome variability that cannot be found from deterministic models

Rapid Turnover of 2-LTR HIV-1 DNA during Early Stage of Highly Active Antiretroviral Therapy

BACKGROUND: Despite prolonged treatment with highly active antiretroviral therapy (HAART), the infectious HIV-1 continues to replicate and resides latently in the resting memory CD4+ T lymphocytes, which blocks the eradication of HIV-1. The viral persistence of HIV-1 is mainly caused by its proviral DNA being either linear nonintegrated, circular nonintegrated, or integrated. Previous reports have largely focused on the dynamics of HIV-1 DNA from the samples collected with relatively long time intervals during the process of disease and HAART treatment, which may have missed the intricate changes during the intervals in early treatment. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we investigated the dynamics of HIV-1 DNA in patients during the early phase of HARRT treatment. Using optimized real time PCR, we observed significant changes in 2-LTR during the first 12-week of treatment, while total and integrated HIV-1 DNA remained stable. The doubling time and half-life of 2-LTR were not correlated with the baseline and the rate of changes in plasma viral load and various CD4+ T-cell populations. Longitudinal analyses on 2-LTR sequences and plasma lipopolysaccharide (LPS) levels did not reveal any significant changes in the same treatment period. CONCLUSIONS/SIGNIFICANCE: Our study revealed the rapid changes in 2-LTR concentration in a relatively large number of patients during the early HAART treatment. The rapid changes indicate the rapid infusion and clearance of cells bearing 2-LTR in the peripheral blood. Those changes are not expected to be caused by the blocking of viral integration, as our study did not include the integrase inhibitor raltegravir. Our study helps better understand the dynamics of HIV-DNA and its potential role as a biomarker for the diseases and for the treatment efficacy of HAART