Illegal immigration and a heterogeneous labour force. When can quotas generate an internal conflict?

In this paper we analyze the effects on the welfare of heterogeneous native workers in the context of the presence of legal and illegal immigrants, and where the main instrument of economic policy takes the form of entry quotas. In the framework of a model of overlapping generations, we find that these effects are not monotonous. More particularly, we note that in certain circumstances the effects on the native workers of a change in the quota are opposite in nature, depending on whether or not these workers are qualified. The key aspect of this result is, on the one hand, the effect of illegal immigration on wages and, on the other, the part of income generated by the illegal immigrants that is appropriated by the natives for managing this “informal” labour market. Keywords: Illegal immigration; entry quotas; qualification. JEL: F22, J61,J68.

Illegal immigration and a heterogeneous labour force. When can quotas generate an internal conflict?

In this paper we analyze the effects on the welfare of heterogeneous native workers in the context of the presence of legal and illegal immigrants, and where the main instrument of economic policy takes the form of entry quotas. In the framework of a model of overlapping generations, we find that these effects are not monotonous. More particularly, we note that in certain circumstances the effects on the native workers of a change in the quota are opposite in nature, depending on whether or not these workers are qualified. The key aspect of this result is, on the one hand, the effect of illegal immigration on wages and, on the other, the part of income generated by the illegal immigrants that is appropriated by the natives for managing this “informal” labour market. Keywords: Illegal immigration; entry quotas; qualification. JEL: F22, J61,J68

Clinical and structural brain correlates of hypomimia in early-stage Parkinson's disease

Altres ajuts: acord transformatiu CRUE-CSICBackground and purpose: Reduced facial expression of emotions is a very frequent symptom of Parkinson's disease (PD) and has been considered part of the motor features of the disease. However, the neural correlates of hypomimia and the relationship between hypomimia and other non-motor symptoms of PD are poorly understood. Methods: The clinical and structural brain correlates of hypomimia were studied. For this purpose, cross-sectional data from the COPPADIS study database were used. Age, disease duration, levodopa equivalent daily dose, Unified Parkinson's Disease Rating Scale part III (UPDRS-III), severity of apathy and depression and global cognitive status were collected. At the imaging level, analyses based on gray matter volume and cortical thickness were used. Results: After controlling for multiple confounding variables such as age or disease duration, the severity of hypomimia was shown to be indissociable from the UPDRS-III speech and bradykinesia items and was significantly related to the severity of apathy (β = 0.595; p < 0.0001). At the level of neural correlates, hypomimia was related to motor regions brodmann area 8 (BA 8) and to multiple fronto-temporo-parietal regions involved in the decoding, recognition and production of facial expression of emotions. Conclusion: Reduced facial expressivity in PD is related to the severity of symptoms of apathy and is mediated by the dysfunction of brain systems involved in motor control and in the recognition, integration and expression of emotions. Therefore, hypomimia in PD may be conceptualized not exclusively as a motor symptom but as a consequence of a multidimensional deficit leading to a symptom where motor and non-motor aspects converge

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Joint Observation of the Galactic Center with MAGIC and CTA-LST-1

MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes (IACTs), designed to detect very-high-energy gamma rays, and is operating in stereoscopic mode since 2009 at the Observatorio del Roque de Los Muchachos in La Palma, Spain. In 2018, the prototype IACT of the Large-Sized Telescope (LST-1) for the Cherenkov Telescope Array, a next-generation ground-based gamma-ray observatory, was inaugurated at the same site, at a distance of approximately 100 meters from the MAGIC telescopes. Using joint observations between MAGIC and LST-1, we developed a dedicated analysis pipeline and established the threefold telescope system via software, achieving the highest sensitivity in the northern hemisphere. Based on this enhanced performance, MAGIC and LST-1 have been jointly and regularly observing the Galactic Center, a region of paramount importance and complexity for IACTs. In particular, the gamma-ray emission from the dynamical center of the Milky Way is under debate. Although previous measurements suggested that a supermassive black hole Sagittarius A* plays a primary role, its radiation mechanism remains unclear, mainly due to limited angular resolution and sensitivity. The enhanced sensitivity in our novel approach is thus expected to provide new insights into the question. We here present the current status of the data analysis for the Galactic Center joint MAGIC and LST-1 observations

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Human Capital and Optimal Policy in a Lucas-type Model

We present a design of fiscal policy capable of providing the required incentives in order to make a decentralized economy with externalities move along the optimal transitional path in a Lucas-type human capital model. (Copyright: Elsevier)