Regional employment forecasts with spatial interdependencies

"The labour-market policy-mix in Germany is increasingly being decided on a regional level. This requires additional knowledge about the regional development which (disaggregated) national forecasts cannot provide. Therefore, we separately forecast employment for the 176 German labour- market districts on a monthly basis. We first compare the prediction accuracy of standard time-series methods: autoregressive integrated moving averages (ARIMA), exponentially weighted moving averages (EWMA) and the structural-components approach (SC) in these small spatial units. Second, we augment the SC model by including autoregressive elements (SCAR) in order to incorporate the influence of former periods of the dependent variable on its current value. Due to the importance of spatial interdependencies in small labour-market units, we further augment the basic SC model by lagged values of neighbouring districts in a spatial dynamic panel (SCSAR). The prediction accuracies of the models are compared using the mean absolute percentage forecast error (MAPFE) for the simulated out-of-sample forecast for 2005. Our results show that the SCSAR is superior to the SCAR and basic SC model. ARIMA and EWMA models perform slightly better than SCSAR in many of the German labour-market districts. This reflects that these two moving-average models can better capture the trend reversal beginning in some regions at the end of 2004. All our models have a high forecast quality with an average MAPFE lower than 2.2 percent." (Author's abstract, IAB-Doku) ((en))regionaler Arbeitsmarkt, Beschäftigungsentwicklung, Prognoseverfahren, Arbeitsmarktprognose - Methode

Regional Unemployment Forecasting Using Structural Component Models With Spatial Autocorrelation

Labour-market policies are increasingly being decided on a regional level. This implies that institutions have an increased need for regional forecasts as a guideline for their decision-making process. Therefore, we forecast regional unemployment in the 176 German labour market districts. We use an augmented structural component (SC) model and compare the results from this model with those from basic SC and autoregressive integrated moving average (ARIMA) models. Basic SC models lack two important dimensions: First, they only use level, trend, seasonal and cyclical components, although former periods of the dependent variable generally have a significant influence on the current value. Second, as spatial units become smaller, the influence of “neighbour-effects†becomes more important. In this paper we augment the SC model for structural breaks, autoregressive components and spatial autocorrelation. Using unemployment data from the Federal Employment Services in Germany for the period December 1997 to August 2005, we first estimate basic SC models with components for structural breaks and ARIMA models for each spatial unit separately. In a second stage, autoregressive components are added into the SC model. Third, spatial autocorrelation is introduced into the SC model. We assume that unemployment in adjacent districts is not independent for two reasons: One source of spatial autocorrelation may be that the effect of certain determinants of unemployment is not limited to the particular district but also spills over to neighbouring districts. Second, factors may exist which influence a whole region but are not fully captured by exogenous variables and are reflected in the residuals. We test the quality of the forecasts from the basic models and the augmented SC model by ex-post-estimation for the period September 2004 to August 2005. First results show that the SC model with autoregressive elements and spatial autocorrelation is superior to basic SC and ARIMA models in most of the German labour market districts.

Estimation of flux control coefficients from inhibitor titrations by non-linear regression

AbstractA mathematical model was developed to estimate flux control coefficients (Co) from titration studies with specific non-competitive inhibitors. In contrast to the normally used graphical determination the model pays regard to the dissociation equilibrium (kD) that exists between inhibitor and its binding sites (Eo) as well as to an objective estimation of the initial slope. The model was used for the analysis of titration experiments where the respiration of rat liver mitochondria was inhibited with carboxyatractyloside and antimycin A. It is shown that the graphical estimation of Eo and Co lead to significant overestimation if the ratio Kd/Eo is larger than 10−4 which can be avoided by using our model

Regional employment forecasts with spatial interdependencies

"The labour-market policy-mix in Germany is increasingly being decided on a regional level. This requires additional knowledge about the regional development which (disaggregated) national forecasts cannot provide. Therefore, we separately forecast employment for the 176 German labour- market districts on a monthly basis. We first compare the prediction accuracy of standard time-series methods: autoregressive integrated moving averages (ARIMA), exponentially weighted moving averages (EWMA) and the structural-components approach (SC) in these small spatial units. Second, we augment the SC model by including autoregressive elements (SCAR) in order to incorporate the influence of former periods of the dependent variable on its current value. Due to the importance of spatial interdependencies in small labour-market units, we further augment the basic SC model by lagged values of neighbouring districts in a spatial dynamic panel (SCSAR). The prediction accuracies of the models are compared using the mean absolute percentage forecast error (MAPFE) for the simulated out-of-sample forecast for 2005. Our results show that the SCSAR is superior to the SCAR and basic SC model. ARIMA and EWMA models perform slightly better than SCSAR in many of the German labour-market districts. This reflects that these two moving-average models can better capture the trend reversal beginning in some regions at the end of 2004. All our models have a high forecast quality with an average MAPFE lower than 2.2 percent." [authors abstract

Fucosylated oligosaccharides in mother’s milk alleviate the effects of caesarean birth on infant gut microbiota

Peer reviewe

3-nitroimidazo[1,2-b]pyridazine as a novel scaffold for antiparasitics with sub-nanomolar anti-Giardia lamblia activity.

As there is a continuous need for novel anti-infectives, the present study aimed to fuse two modes of action into a novel 3-nitroimidazo[1,2-b]pyridazine scaffold to improve antiparasitic efficacy. For this purpose, we combined known structural elements of phosphodiesterase inhibitors, a target recently proposed for Trypanosoma brucei and Giardia lamblia, with a nitroimidazole scaffold to generate nitrosative stress. The compounds were evaluated in vitro against a panel of protozoal parasites, namely Giardia lamblia, Trypanosoma brucei, T. cruzi, Leishmania infantum and Plasmodium falciparum and for cytotoxicity on MRC-5 cells. Interestingly, selective sub-nanomolar activity was obtained against G. lamblia, and by testing several analogues with and without the nitro group, it was shown that the presence of a nitro group, but not PDE inhibition, is responsible for the low IC50 values of these novel compounds. Adding the favourable drug-like properties (low molecular weight, cLogP (1.2-4.1) and low polar surface area), the key compounds from the 3-nitroimidazo[1,2-b]pyridazine series can be considered as valuable hits for further anti-giardiasis drug exploration and development

Comparison of 454 Ultra-Deep Sequencing and Allele-Specific Real-Time PCR with Regard to the Detection of Emerging Drug-Resistant Minor HIV-1 Variants after Antiretroviral Prophylaxis for Vertical Transmission

Background: Pregnant HIV-infected women were screened for the development of HIV-1 drug resistance after implementation of a triple-antiretroviral transmission prophylaxis as recommended by the WHO in 2006. The study offered the opportunity to compare amplicon-based 454 ultra-deep sequencing (UDS) and allele-specific real-time PCR (ASPCR) for the detection of drug-resistant minor variants in the HIV-1 reverse transcriptase (RT). Methods: Plasma samples from 34 Tanzanian women were previously analysed by ASPCR for key resistance mutations in the viral RT selected by AZT, 3TC, and NVP (K70R, K103N, Y181C, M184V, T215Y/F). In this study, the RT region of the same samples was investigated by amplicon-based UDS for resistance mutations using the 454 GS FLX System. Results: Drug-resistant HIV-variants were identified in 69% (20/29) of women by UDS and in 45% (13/29) by ASPCR. The absolute number of resistance mutations identified by UDS was twice that identified by ASPCR (45 vs 24). By UDS 14 of 24 ASPCR-detected resistance mutations were identified at the same position. The overall concordance between UDS and ASPCR was 61.0% (25/41). The proportions of variants quantified by UDS were approximately 2–3 times lower than by ASPCR. Amplicon generation from samples with viral loads below 20,000 copies/ml failed more frequently by UDS compared to ASPCR (limit of detection = 650 copies/ml), resulting in missing or insufficient sequence coverage. Conclusions: Both methods can provide useful information about drug-resistant minor HIV-1 variants. ASPCR has a higher sensitivity than UDS, but is restricted to single resistance mutations. In contrast, UDS is limited by its requirement for high viral loads to achieve sufficient sequence coverage, but the sequence information reveals the complete resistance patterns within the genomic region analysed. Improvements to the UDS limit of detection are in progress, and UDS could then facilitate monitoring of drug-resistant minor variants in the HIV-1 quasispecies

Compartmentalized Production of CCL17 In Vivo: Strong Inducibility in Peripheral Dendritic Cells Contrasts Selective Absence from the Spleen

Dendritic cells (DCs)* fulfill an important regulatory function at the interface of the innate and adaptive immune system. The thymus and activation-regulated chemokine (TARC/CCL17) is produced by DCs and facilitates the attraction of activated T cells. Using a fluorescence-based in vivo reporter system, we show that CCL17 expression in mice is found in activated Langerhans cells and mature DCs located in various lymphoid and nonlymphoid organs, and is up-regulated after stimulation with Toll-like receptor ligands. DCs expressing CCL17 belong to the CD11b+CD8−Dec205+ DC subset, including the myeloid-related DCs located in the subepithelial dome of Peyer's patches. CCL17-deficient mice mount diminished T cell–dependent contact hypersensitivity responses and display a deficiency in rejection of allogeneic organ transplants. In contrast to lymphoid organs located at external barriers of the skin and mucosa, CCL17 is not expressed in the spleen, even after systemic microbial challenge or after in vitro stimulation. These findings indicate that CCL17 production is a hallmark of local DC stimulation in peripheral organs but is absent from the spleen as a filter of blood-borne antigens