Explore the vast range of titles available.

After the domestication of animals and crops in the Near East some 11,000 years ago, farming had reached much of central Europe by 7500 years before the present. The extent to which these early European farmers were immigrants or descendants of resident hunter-gatherers who had adopted farming has been widely debated. We compared new mitochondrial DNA (mtDNA) sequences from late European hunter-gatherer skeletons with those from early farmers and from modern Europeans. We find large genetic differences between all three groups that cannot be explained by population continuity alone. Most (82%) of the ancient hunter-gatherers share mtDNA types that are relatively rare in central Europeans today. Together, these analyses provide persuasive evidence that the first farmers were not the descendants of local hunter-gatherers but immigrated into central Europe at the onset of the Neolithic.

Differential glacio-isostatic movement and climatically controlled eustatic change has caused transgression and regression in the Baltic Sea during its Holocene development. In the southern Baltic, glacio-isostatic subsidence superimposed with eustatic rise has provoked a continuously retreating coastline since the beginning of the Littorina transgression, 8000 BP. On the contrary, at the same time, uplift of the Fennoscandian Shield has caused permanent regression along the Scandinavian coast. An especially developed numerical space/time model displays the transgression and regression processes. Along the southern sinking coast, the entire ecosystem, including the conditions for human settlements, is influenced by the sea transgression. The complex processes require interdisciplinary research teams consisting of geoscientists (geologists, geomorphologists, geodesists), biologists (paleobotanists, paleozoologists), climate researchers, and archaeologists to study the complex processes affected by retreating coastlines and their socioeconomic implications. Such a team has investigated, since September 2002 along the southern Baltic Sea coast, the cause and effect relation between driving forces (climatic and geological processes) and the response of the natural and social environment in the coastal areas of a transgressive sea. Since 1999, underwater archaeological studies have discovered Mesolithic and Neolithic settlements along drowned coastlines of the Mecklenburgian Bight. Dated artifacts helped to describe the relative sea level change in the western Baltic Sea. On the basis of these data, methods of backstripping have been developed to describe, at a high resolution, the process of coastal development along a sinking coast of a tideless sea. Greenhouse gas emission scenarios provided by the Intergovernmental Panel on Climate Change and their effects on sea level change have been coupled with predictions of isostatic vertical crustal movement, resulting in scenarios of future coastline development. Those scenarios help to elaborate protection strategies in the frame of long-term planning in coastal zone management.

Objectives To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity. Materials and methods Paired inspiratory/expiratory CT and clinical data from COPDGene and COSYCONET cohort studies were included. COPDGene data served as training/validation/test data sets ( N = 3144/786/1310) and COSYCONET as external test set ( N = 446). To differentiate low-risk (healthy/minimal disease, [GOLD 0]) from COPD patients (GOLD 1–4), the self-supervised DL model learned semantic information from 50 × 50 × 50 voxel samples from segmented intact lungs. An anomaly detection approach was trained to quantify lung abnormalities related to COPD, as regional deviations. Four supervised DL models were run for comparison. The clinical and radiological predictive power of the proposed anomaly score was assessed using linear mixed effects models (LMM). Results The proposed approach achieved an area under the curve of 84.3 ± 0.3 ( p < 0.001) for COPDGene and 76.3 ± 0.6 ( p < 0.001) for COSYCONET, outperforming supervised models even when including only inspiratory CT. Anomaly scores significantly improved fitting of LMM for predicting lung function, health status, and quantitative CT features (emphysema/air trapping; p < 0.001). Higher anomaly scores were significantly associated with exacerbations for both cohorts ( p < 0.001) and greater dyspnea scores for COPDGene ( p < 0.001). Conclusion Quantifying heterogeneous COPD manifestations as anomaly offers advantages over supervised methods and was found to be predictive for lung function impairment and morphology deterioration. Clinical relevance statement Using deep learning, lung manifestations of COPD can be identified as deviations from normal-appearing chest CT and attributed an anomaly score which is consistent with decreased pulmonary function, emphysema, and air trapping. Key Points • A self-supervised DL anomaly detection method discriminated low-risk individuals and COPD subjects, outperforming classic DL methods on two datasets (COPDGene AUC = 84.3%, COSYCONET AUC = 76.3%). • Our contrastive task exhibits robust performance even without the inclusion of expiratory images, while voxel-based methods demonstrate significant performance enhancement when incorporating expiratory images, in the COPDGene dataset. • Anomaly scores improved the fitting of linear mixed effects models in predicting clinical parameters and imaging alterations (p < 0.001) and were directly associated with clinical outcomes (p < 0.001).

Hepatitis D is the most severe form of chronic viral hepatitis. Treatment guidelines recommend 1 year of peginterferon alfa, which is effective in 25–30% of patients only. Whether prolonged therapy with peginterferon alfa-2a for 96 weeks and combination therapy with tenofovir disoproxil fumarate (TDF) would increase hepatitis D virus (HDV) RNA suppression is unknown. We aimed to explore whether prolonged treatment of HDV with 96 weeks of peginterferon would increase HDV RNA response rates and reduces post-treatment relapses. We did two parallel, investigator-initiated, multicentre, double-blind randomised, controlled trials at 14 study sites in Germany, Greece, Romania, and Turkey. Patients with chronic HDV infection and compensated liver disease who were aged 18 years or older were eligible for inclusion. All patients were HBsAg positive for at least 7 months, anti-HDV positive for at least 3 months, and HDV-RNA positive at the local laboratory at the screening visit. Patients were ineligible if alanine aminotransferase levels were higher than ten times above the upper limit of normal and if platelet counts were lower than 90 000 per μL, or if they had received interferon therapy or treatment with a nucleoside and nucleotide analogue within the preceding 6 months. Patients were randomly assigned by blinded stratified block randomisation (1:1) to receive 180 μg of peginterferon alfa-2a weekly plus either TDF (300 mg once daily) or placebo for 96 weeks. The primary endpoint was the percentage of patients with undetectable HDV RNA at the end of treatment assessed by intention to treat. The trials are registered as NCT00932971 and NCT01088659. Between June 24, 2009, and Feb 28, 2011, we randomly assigned 59 HDV RNA-positive patients to receive peginterferon alfa-2a plus TDF and 61 to receive peginterferon alfa-2a plus placebo, including 48 (40%) patients with cirrhosis to the two treatment groups (23 in the peginterferon alfa-2a plus TDF group and 25 in the peginterferon alfa-2a plus placebo group). The primary endpoint was achieved in 28 (48%) of 59 patients in the peginterferon alfa-2a plus TDF group and in 20 (33%) of 61 patients in the peginterferon alfa-2a plus placebo group (odds ratio 1·84, 95% CI 0·86–3·91, p=0·12). We recorded 944 adverse events (459 in the peginterferon alfa-2a plus TDF group and 485 in the peginterferon alfa-2a plus placebo group). The most common adverse events were haematological, behavioural (eg, fatigue), musculoskeletal, influenza-like syndromes, and psychiatric complaints. Addition of TDF resulted in no significant improvement in HDV RNA response rates at the end of treatment. These findings highlight that alternative treatment options are needed for hepatitis D. The HepNet Study-House (a project of the German Liver Foundation founded by the German Liver Foundation, the German Ministry for Education and Research, and the German Center for Infectious Disease Research), Hoffmann-La Roche, and Gilead Sciences.

Depression is a debilitating condition for which new treatments are sorely needed. Now, Erich Gulbins and his colleagues report that reducing ceramide levels in the brain has antidepressant effects in mouse models of the disease. Major depression is a highly prevalent severe mood disorder that is treated with antidepressants. The molecular targets of antidepressants require definition. We investigated the role of the acid sphingomyelinase (Asm)-ceramide system as a target for antidepressants. Therapeutic concentrations of the antidepressants amitriptyline and fluoxetine reduced Asm activity and ceramide concentrations in the hippocampus, increased neuronal proliferation, maturation and survival and improved behavior in mouse models of stress-induced depression. Genetic Asm deficiency abrogated these effects. Mice overexpressing Asm, heterozygous for acid ceramidase, treated with blockers of ceramide metabolism or directly injected with C16 ceramide in the hippocampus had higher ceramide concentrations and lower rates of neuronal proliferation, maturation and survival compared with controls and showed depression-like behavior even in the absence of stress. The decrease of ceramide abundance achieved by antidepressant-mediated inhibition of Asm normalized these effects. Lowering ceramide abundance may thus be a central goal for the future development of antidepressants.

Two of the elements of the Cabibbo–Kobayashi–Maskawa quark mixing matrix, | V ub | and | V cb | , are extracted from semileptonic B decays. The results of the B factories, analysed in the light of the most recent theoretical calculations, remain puzzling, because for both | V ub | and | V cb | the exclusive and inclusive determinations are in clear tension. Further, measurements in the τ channels at Belle, Babar, and LHCb show discrepancies with the Standard Model predictions, pointing to a possible violation of lepton flavor universality. LHCb and Belle II have the potential to resolve these issues in the next few years. This article summarizes the discussions and results obtained at the MITP workshop held on April 9–13, 2018, in Mainz, Germany, with the goal to develop a medium-term strategy of analyses and calculations aimed at solving the puzzles. Lattice and continuum theorists working together with experimentalists have discussed how to reshape the semileptonic analyses in view of the much higher luminosity expected at Belle II, searching for ways to systematically validate the theoretical predictions in both exclusive and inclusive B decays, and to exploit the rich possibilities at LHCb.

The mechanism of action of 2-hydroxyoleic acid (2OHOA), a potent antitumor compound, has not yet been fully elucidated. Here, we show that human cancer cells have markedly lower levels of sphingomyelin (SM) than nontumor (MRC-5) cells. In this context, 2OHOA treatment strongly augments SM mass (4.6-fold), restoring the levels found in MRC-5 cells, while a loss of phosphatidylethanolamine and phosphatidylcholine is observed (57 and 30%, respectively). The increased SM mass was due to a rapid and highly specific activation of SM synthases (SMS). This effect appeared to be specific against cancer cells as it did not affect nontumor MRC-5 cells. Therefore, low SM levels are associated with the tumorigenic transformation that produces cancer cells. SM accumulation occurred at the plasma membrane and caused an increase in membrane global order and lipid raft packing in model membranes. These modifications would account for the observed alteration by 2OHOA in the localization of proteins involved in cell apoptosis (Fas receptor) or differentiation (Ras). Importantly, SMS inhibition by D609 diminished 2OHOA effect on cell cycle. Therefore, we propose that the regulation of SMS activity in tumor cells is a critical upstream event in 2OHOA antitumor mechanism, which also explains its specificity for cancer cells, its potency, and the lack of undesired side effects. Finally, the specific activation of SMS explains the ability of this compound to trigger cell cycle arrest, cell differentiation, and autophagy or apoptosis in cancer cells.

ObjectivesTo evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations.Materials and methodsInspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56–69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised learning (SL) vs. three self-supervised learning (SSL) methods. Distribution shifts across ethnicity were further assessed for the top-performing methods.ResultsThe learning strategy significantly influenced model performance, with SSL methods achieving higher performances compared to SL methods (p < 0.001), across all training configurations. Training on balanced datasets containing NHW and AA individuals resulted in improved model performance compared to population-specific datasets. Distribution shifts were found between ethnicities for the same health status, particularly when models were trained on nearest-neighbor contrastive SSL. Training on a balanced dataset resulted in fewer distribution shifts across ethnicity and health status, highlighting its efficacy in reducing biases.ConclusionOur findings demonstrate that utilizing SSL methods and training on large and balanced datasets can enhance COPD detection model performance and reduce biases across diverse ethnic populations. These findings emphasize the importance of equitable AI-driven healthcare solutions for COPD diagnosis.Critical relevance statementSelf-supervised learning coupled with balanced datasets significantly improves COPD detection model performance, addressing biases across diverse ethnic populations and emphasizing the crucial role of equitable AI-driven healthcare solutions.Key PointsSelf-supervised learning methods outperform supervised learning methods, showing higher AUC values (p < 0.001).Balanced datasets with non-Hispanic White and African American individuals improve model performance.Training on diverse datasets enhances COPD detection accuracy.Ethnically diverse datasets reduce bias in COPD detection models.SimCLR models mitigate biases in COPD detection across ethnicities.

The understanding of coupled thermo-hydro-mechanical behaviour of fault zones or in naturally fractured reservoirs is essential both for fundamental and applied sciences and in particular for the safety assessment of radioactive waste disposal facilities. The overall objective of the CHENILLE project is to better understand the physical processes resulting from thermal and hydraulic loading in a small fault zone in a highly consolidated shale formation. Consequently, a thermally controlled in-situ fluid injection experiment is intended to be performed on a strike-slip fault zone outcropping at the Tournemire/France Underground Research Laboratory (URL). A heating system has been installed around the injection area to enable a precise and controlled incremental increase of the thermal load. Different monitoring systems are designed to measure the seismic and aseismic deformation induced either by thermal and/or by hydraulic loading. The seismic monitoring system is composed of Acoustic Emission (AE) and broadband seismic sensors enabling monitoring of seismic fracturing processes down to sub-decimetre scale as well as slow deformation processes. Furthermore, we are about to install an injection chamber allowing to perform a controlled gaz injection test. The injection borehole will also be partly equipped with fiber optics in order to measure temperature in a distributed manner in the borehole. Time-lapse active seismic surveys are scheduled for before and after the experiment to image the structural network but also to detect the appearance of new structures triggered from the hydro-thermal pressurization of the fault as well as eventual changes in the velocity field.