Weak states, human rights violations, and the outbreak of civil war.

In recent years, explanations for the occurrence of civil war have mainly emphasized state weakness as providing an opportunity for greed-based rebellions. Yet, this explanation leaves many questions open, as it cannot distinguish between weak states that do and those that do not experience civil war. In this paper, I argue that abuses of personal integrity rights, committed or sponsored by the government, provide this missing link. The theory is illustrated and formalized in a game-theoretic model and then tested empirically, building on earlier work by Fearon and Laitin (2003a) and Sambanis (2004). The results show that repression is highly significant in both statistical and substantive terms. According to one model, the probability of civil war onset increases by a factor of almost 16 in highly repressive countries compared to countries with no repression. Further robustness tests across alternative civil war lists largely confirm the importance of human rights abuses in explaining the occurrence of civil war

Dissecting the Association Between Inflammation, Metabolic Dysregulation, and Specific Depressive Symptoms: A Genetic Correlation and 2-Sample Mendelian Randomization Study.

IMPORTANCE: Observational studies highlight associations of C-reactive protein (CRP), a general marker of inflammation, and interleukin 6 (IL-6), a cytokine-stimulating CRP production, with individual depressive symptoms. However, it is unclear whether inflammatory activity is associated with individual depressive symptoms and to what extent metabolic dysregulation underlies the reported associations. OBJECTIVE: To explore the genetic overlap and associations between inflammatory activity, metabolic dysregulation, and individual depressive symptoms. GWAS DATA SOURCES: Genome-wide association study (GWAS) summary data of European individuals, including the following: CRP levels (204 402 individuals); 9 individual depressive symptoms (3 of which did not differentiate between underlying diametrically opposite symptoms [eg, insomnia and hypersomnia]) as measured with the Patient Health Questionnaire 9 (up to 117 907 individuals); summary statistics for major depression, including and excluding UK Biobank participants, resulting in sample sizes of 500 199 and up to 230 214 individuals, respectively; insomnia (up to 386 533 individuals); body mass index (BMI) (up to 322 154 individuals); and height (up to 253 280 individuals). DESIGN: In this genetic correlation and 2-sample mendelian randomization (MR) study, linkage disequilibrium score (LDSC) regression was applied to infer single-nucleotide variant-based heritability and genetic correlation estimates. Two-sample MR tested potential causal associations of genetic variants associated with CRP levels, IL-6 signaling, and BMI with depressive symptoms. The study dates were November 2019 to April 2020. RESULTS: Based on large GWAS data sources, genetic correlation analyses revealed consistent false discovery rate (FDR)-controlled associations (genetic correlation range, 0.152-0.362; FDR P = .006 to P < .001) between CRP levels and depressive symptoms that were similar in size to genetic correlations of BMI with depressive symptoms. Two-sample MR analyses suggested that genetic upregulation of IL-6 signaling was associated with suicidality (estimate [SE], 0.035 [0.010]; FDR plus Bonferroni correction P = .01), a finding that remained stable across statistical models and sensitivity analyses using alternative instrument selection strategies. Mendelian randomization analyses did not consistently show associations of higher CRP levels or IL-6 signaling with other depressive symptoms, but higher BMI was associated with anhedonia, tiredness, changes in appetite, and feelings of inadequacy. CONCLUSIONS AND RELEVANCE: This study reports coheritability between CRP levels and individual depressive symptoms, which may result from the potentially causal association of metabolic dysregulation with anhedonia, tiredness, changes in appetite, and feelings of inadequacy. The study also found that IL-6 signaling is associated with suicidality. These findings may have clinical implications, highlighting the potential of anti-inflammatory approaches, especially IL-6 blockade, as a putative strategy for suicide prevention.Wellcome Trust (grant code: 201486/Z/16/Z

Seismoacoustic coupling induced by the breakup of the 15 February 2013 Chelyabinsk meteor

International audienceOn 15 February 2013 around 03:20:00 UTC, the largest meteor reported since the 1908 Tunguska event was observed as a fireball traveling through the Earth's atmosphere, exploding in an air burst near the city of Chelyabinsk, Russia. The rarity of such an event provides a unique window on the physics of meteoroid collision. We report the fine seismic detection of Rayleigh waves produced by the coupling of ground motion with the incident shock wave at distances up to 4000 km from the event. Combining information from seismic beam-forming analysis, recon- structed trajectory from casual video records, and remote sensing, we identify the Rayleigh waves as being initiated by the shock wave produced by the main blast that occasioned damages and injuries in Chelyabinsk. From the Rayleigh wave observations, we report a magnitude Ms ~ 3.7 seismic source

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Identifying the underlying mechanisms of change during acceptance and commitment therapy (ACT): A systematic review of contemporary mediation studies

BACKGROUND: Mediation studies test the mechanisms by which interventions produce clinical outcomes. Consistent positive mediation results have previously been evidenced (Hayes et al., 2006) for the putative processes that compromise the psychological flexibility model of acceptance and commitment therapy (ACT). AIMS: The present review aimed to update and extend the ACT mediation evidence base by reviewing mediation studies published since the review of Hayes et al. (2006). METHOD: ACT mediation studies published between 2006 and 2015 were systematically collated, synthesized and quality assessed. RESULTS: Twelve studies met inclusion criteria and findings were synthesized by (a) the putative processes under investigation, and (b) the outcomes on which processes were tested for mediation. Mediation results were found to be generally consistent with the psychological flexibility model of ACT. However, studies were limited in methodological quality and were overly focused on a small number of putative processes. CONCLUSIONS: Further research is required that addresses the identified methodological limitations and also examines currently under-researched putative processes

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries