Showing papers by "University of Tübingen published in 2018"

Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Abstract: Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

Abstract: Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis can be highly time consuming. In motor control studies, humans or other animals are often marked with reflective markers to assist with computer-based tracking, but markers are intrusive, and the number and location of the markers must be determined a priori. Here we present an efficient method for markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results with minimal training data. We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. Remarkably, even when only a small number of frames are labeled (~200), the algorithm achieves excellent tracking performance on test frames that is comparable to human accuracy.

Analysis of shared heritability in common disorders of the brain

Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Abstract: Convolutional Neural Networks (CNNs) are commonly thought to recognise objects by learning increasingly complex representations of object shapes. Some recent studies suggest a more important role of image textures. We here put these conflicting hypotheses to a quantitative test by evaluating CNNs and human observers on images with a texture-shape cue conflict. We show that ImageNet-trained CNNs are strongly biased towards recognising textures rather than shapes, which is in stark contrast to human behavioural evidence and reveals fundamentally different classification strategies. We then demonstrate that the same standard architecture (ResNet-50) that learns a texture-based representation on ImageNet is able to learn a shape-based representation instead when trained on "Stylized-ImageNet", a stylized version of ImageNet. This provides a much better fit for human behavioural performance in our well-controlled psychophysical lab setting (nine experiments totalling 48,560 psychophysical trials across 97 observers) and comes with a number of unexpected emergent benefits such as improved object detection performance and previously unseen robustness towards a wide range of image distortions, highlighting advantages of a shape-based representation.

Occupancy Networks: Learning 3D Reconstruction in Function Space

Abstract: With the advent of deep neural networks, learning-based approaches for 3D reconstruction have gained popularity. However, unlike for images, in 3D there is no canonical representation which is both computationally and memory efficient yet allows for representing high-resolution geometry of arbitrary topology. Many of the state-of-the-art learning-based 3D reconstruction approaches can hence only represent very coarse 3D geometry or are limited to a restricted domain. In this paper, we propose Occupancy Networks, a new representation for learning-based 3D reconstruction methods. Occupancy networks implicitly represent the 3D surface as the continuous decision boundary of a deep neural network classifier. In contrast to existing approaches, our representation encodes a description of the 3D output at infinite resolution without excessive memory footprint. We validate that our representation can efficiently encode 3D structure and can be inferred from various kinds of input. Our experiments demonstrate competitive results, both qualitatively and quantitatively, for the challenging tasks of 3D reconstruction from single images, noisy point clouds and coarse discrete voxel grids. We believe that occupancy networks will become a useful tool in a wide variety of learning-based 3D tasks.

Microplastics as an emerging threat to terrestrial ecosystems

Abstract: Microplastics (plastics < 5 mm, including nanoplastics which are < 0.1 μm) originate from the fragmentation of large plastic litter or from direct environmental emission. Their potential impacts in terrestrial ecosystems remain largely unexplored despite numerous reported effects on marine organisms. Most plastics arriving in the oceans were produced, used, and often disposed on land. Hence, it is within terrestrial systems that microplastics might first interact with biota eliciting ecologically relevant impacts. This article introduces the pervasive microplastic contamination as a potential agent of global change in terrestrial systems, highlights the physical and chemical nature of the respective observed effects, and discusses the broad toxicity of nanoplastics derived from plastic breakdown. Making relevant links to the fate of microplastics in aquatic continental systems, we here present new insights into the mechanisms of impacts on terrestrial geochemistry, the biophysical environment, and ecotoxicology. Broad changes in continental environments are possible even in particle-rich habitats such as soils. Furthermore, there is a growing body of evidence indicating that microplastics interact with terrestrial organisms that mediate essential ecosystem services and functions, such as soil dwelling invertebrates, terrestrial fungi, and plant-pollinators. Therefore, research is needed to clarify the terrestrial fate and effects of microplastics. We suggest that due to the widespread presence, environmental persistence, and various interactions with continental biota, microplastic pollution might represent an emerging global change threat to terrestrial ecosystems.

Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes

Abstract: Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Abstract: Convolutional Neural Networks (CNNs) are commonly thought to recognise objects by learning increasingly complex representations of object shapes. Some recent studies suggest a more important role of image textures. We here put these conflicting hypotheses to a quantitative test by evaluating CNNs and human observers on images with a texture-shape cue conflict. We show that ImageNet-trained CNNs are strongly biased towards recognising textures rather than shapes, which is in stark contrast to human behavioural evidence and reveals fundamentally different classification strategies. We then demonstrate that the same standard architecture (ResNet-50) that learns a texture-based representation on ImageNet is able to learn a shape-based representation instead when trained on "Stylized-ImageNet", a stylized version of ImageNet. This provides a much better fit for human behavioural performance in our well-controlled psychophysical lab setting (nine experiments totalling 48,560 psychophysical trials across 97 observers) and comes with a number of unexpected emergent benefits such as improved object detection performance and previously unseen robustness towards a wide range of image distortions, highlighting advantages of a shape-based representation.

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Abstract: Many machine learning algorithms are vulnerable to almost imperceptible perturbations of their inputs. So far it was unclear how much risk adversarial perturbations carry for the safety of real-world machine learning applications because most methods used to generate such perturbations rely either on detailed model information (gradient-based attacks) or on confidence scores such as class probabilities (score-based attacks), neither of which are available in most real-world scenarios. In many such cases one currently needs to retreat to transfer-based attacks which rely on cumbersome substitute models, need access to the training data and can be defended against. Here we emphasise the importance of attacks which solely rely on the final model decision. Such decision-based attacks are (1) applicable to real-world black-box models such as autonomous cars, (2) need less knowledge and are easier to apply than transfer-based attacks and (3) are more robust to simple defences than gradient- or score-based attacks. Previous attacks in this category were limited to simple models or simple datasets. Here we introduce the Boundary Attack, a decision-based attack that starts from a large adversarial perturbation and then seeks to reduce the perturbation while staying adversarial. The attack is conceptually simple, requires close to no hyperparameter tuning, does not rely on substitute models and is competitive with the best gradient-based attacks in standard computer vision tasks like ImageNet. We apply the attack on two black-box algorithms from this http URL. The Boundary Attack in particular and the class of decision-based attacks in general open new avenues to study the robustness of machine learning models and raise new questions regarding the safety of deployed machine learning systems. An implementation of the attack is available as part of Foolbox at this https URL .

Encorafenib plus binimetinib versus vemurafenib or encorafenib in patients with BRAF-mutant melanoma (COLUMBUS): a multicentre, open-label, randomised phase 3 trial

Abstract: Summary Background Combined BRAF-MEK inhibitor therapy is the standard of care for BRAF V600 -mutant advanced melanoma. We investigated encorafenib, a BRAF inhibitor with unique target-binding properties, alone or in combination with the MEK inhibitor binimetinib, versus vemurafenib in patients with advanced BRAF V600 -mutant melanoma. Methods COLUMBUS was conducted as a two-part, randomised, open-label phase 3 study at 162 hospitals in 28 countries. Eligible patients were aged 18 years or older and had histologically confirmed locally advanced (American Joint Committee on Cancer [AJCC] stage IIIB, IIIC, or IV), unresectable or metastatic cutaneous melanoma, or unknown primary melanoma; a BRAF V600E or BRAF V600K mutation; an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1; and were treatment naive or had progressed on or after previous first-line immunotherapy. In part 1 of the study, patients were randomly assigned (1:1:1) via interactive response technology to receive either oral encorafenib 450 mg once daily plus oral binimetinib 45 mg twice daily (encorafenib plus binimetinib group), oral encorafenib 300 mg once daily (encorafenib group), or oral vemurafenib 960 mg twice daily (vemurafenib group). The primary endpoint was progression-free survival by blinded independent central review for encorafenib plus binimetinib versus vemurafenib. Efficacy analyses were by intention-to-treat. Safety was analysed in patients who received at least one dose of study drug and one postbaseline safety assessment. The results of part 2 will be published separately. This study is registered with ClinicalTrials.gov, number NCT01909453, and EudraCT, number 2013-001176-38. Findings Between Dec 30, 2013, and April 10, 2015, 577 of 1345 screened patients were randomly assigned to either the encorafenib plus binimetinib group (n=192), the encorafenib group (n=194), or the vemurafenib group (n=191). With a median follow-up of 16·6 months (95% CI 14·8–16·9), median progression-free survival was 14·9 months (95% CI 11·0–18·5) in the encorafenib plus binimetinib group and 7·3 months (5·6–8·2) in the vemurafenib group (hazard ratio [HR] 0·54, 95% CI 0·41–0·71; two-sided p Interpretation Encorafenib plus binimetinib and encorafenib monotherapy showed favourable efficacy compared with vemurafenib. Overall, encorafenib plus binimetinib appears to have an improved tolerability profile compared with encorafenib or vemurafenib. Encorafenib plus binimetinib could represent a new treatment option for patients with BRAF -mutant melanoma. Funding Array BioPharma, Novartis.

Methicillin-resistant Staphylococcus aureus.

Abstract: Since the 1960s, methicillin-resistant Staphylococcus aureus (MRSA) has emerged, disseminated globally and become a leading cause of bacterial infections in both health-care and community settings. However, there is marked geographical variation in MRSA burden owing to several factors, including differences in local infection control practices and pathogen-specific characteristics of the circulating clones. Different MRSA clones have resulted from the independent acquisition of staphylococcal cassette chromosome mec (SCCmec), which contains genes encoding proteins that render the bacterium resistant to most β-lactam antibiotics (such as methicillin), by several S. aureus clones. The success of MRSA is a consequence of the extensive arsenal of virulence factors produced by S. aureus combined with β-lactam resistance and, for most clones, resistance to other antibiotic classes. Clinical manifestations of MRSA range from asymptomatic colonization of the nasal mucosa to mild skin and soft tissue infections to fulminant invasive disease with high mortality. Although treatment options for MRSA are limited, several new antimicrobials are under development. An understanding of colonization dynamics, routes of transmission, risk factors for progression to infection and conditions that promote the emergence of resistance will enable optimization of strategies to effectively control MRSA. Vaccine candidates are also under development and could become an effective prevention measure.

Innate immune memory in the brain shapes neurological disease hallmarks

Abstract: Innate immune memory is a vital mechanism of myeloid cell plasticity that occurs in response to environmental stimuli and alters subsequent immune responses. Two types of immunological imprinting can be distinguished—training and tolerance. These are epigenetically mediated and enhance or suppress subsequent inflammation, respectively. Whether immune memory occurs in tissue-resident macrophages in vivo and how it may affect pathology remains largely unknown. Here we demonstrate that peripherally applied inflammatory stimuli induce acute immune training and tolerance in the brain and lead to differential epigenetic reprogramming of brain-resident macrophages (microglia) that persists for at least six months. Strikingly, in a mouse model of Alzheimer’s pathology, immune training exacerbates cerebral β-amyloidosis and immune tolerance alleviates it; similarly, peripheral immune stimulation modifies pathological features after stroke. Our results identify immune memory in the brain as an important modifier of neuropathology.

Discovery of a planetary-mass companion within the gap of the transition disk around PDS 70

Abstract: Context. Young circumstellar disks are the birthplaces of planets. Their study is of prime interest to understand the physical and chemical conditions under which planet formation takes place. Only very few detections of planet candidates within these disks exist, and most of them are currently suspected to be disk features.Aims. In this context, the transition disk around the young star PDS 70 is of particular interest, due to its large gap identified in previous observations, indicative of ongoing planet formation. We aim to search for the presence of an embedded young planet and search for disk structures that may be the result of disk–planet interactions and other evolutionary processes.Methods. We analyse new and archival near-infrared images of the transition disk PDS 70 obtained with the VLT/SPHERE, VLT/NaCo, and Gemini/NICI instruments in polarimetric differential imaging and angular differential imaging modes.Results. We detect a point source within the gap of the disk at about 195 mas (~22 au) projected separation. The detection is confirmed at five different epochs, in three filter bands and using different instruments. The astrometry results in an object of bound nature, with high significance. The comparison of the measured magnitudes and colours to evolutionary tracks suggests that the detection is a companion of planetary mass. The luminosity of the detected object is consistent with that of an L-type dwarf, but its IR colours are redder, possibly indicating the presence of warm surrounding material. Further, we confirm the detection of a large gap of ~54 au in size within the disk in our scattered light images, and detect a signal from an inner disk component. We find that its spatial extent is very likely smaller than ~17 au in radius, and its position angle is consistent with that of the outer disk. The images of the outer disk show evidence of a complex azimuthal brightness distribution which is different at different wavelengths and may in part be explained by Rayleigh scattering from very small grains.Conclusions. The detection of a young protoplanet within the gap of the transition disk around PDS 70 opens the door to a so far observationally unexplored parameter space of planetary formation and evolution. Future observations of this system at different wavelengths and continuing astrometry will allow us to test theoretical predictions regarding planet–disk interactions, planetary atmospheres, and evolutionary models.

The Beaker phenomenon and the genomic transformation of northwest Europe

Abstract: From around 2750 to 2500 bc, Bell Beaker pottery became widespread across western and central Europe, before it disappeared between 2200 and 1800 bc. The forces that propelled its expansion are a matter of long-standing debate, and there is support for both cultural diffusion and migration having a role in this process. Here we present genome-wide data from 400 Neolithic, Copper Age and Bronze Age Europeans, including 226 individuals associated with Beaker-complex artefacts. We detected limited genetic affinity between Beaker-complex-associated individuals from Iberia and central Europe, and thus exclude migration as an important mechanism of spread between these two regions. However, migration had a key role in the further dissemination of the Beaker complex. We document this phenomenon most clearly in Britain, where the spread of the Beaker complex introduced high levels of steppe-related ancestry and was associated with the replacement of approximately 90% of Britain's gene pool within a few hundred years, continuing the east-to-west expansion that had brought steppe-related ancestry into central and northern Europe over the previous centuries.

Bax, Bak and beyond - mitochondrial performance in apoptosis.

Abstract: Bax and Bak are members of the Bcl-2 family and core regulators of the intrinsic pathway of apoptosis. Upon apoptotic stimuli, they are activated and oligomerize at the mitochondrial outer membrane (MOM) to mediate its permeabilization, which is considered a key step in apoptosis. However, the molecular mechanism underlying Bax and Bak function has remained a key question in the field. Here, we review recent structural and biophysical evidence that has changed our understanding of how Bax and Bak promote MOM permeabilization. We also discuss how the spatial regulation of Bcl-2 family preference for binding partners contributes to regulate Bax and Bak activation. Finally, we consider the contribution of mitochondrial composition, dynamics and interaction with other organelles to apoptosis commitment. A new perspective is emerging, in which the control of apoptosis by Bax and Bak goes beyond them and is highly influenced by additional mitochondrial components.

New Gauss-Bonnet Black Holes with Curvature-Induced Scalarization in Extended Scalar-Tensor Theories

Abstract: In the present Letter, we consider a class of extended scalar-tensor-Gauss-Bonnet (ESTGB) theories for which the scalar degree of freedom is excited only in the extreme curvature regime. We show that in the mentioned class of ESTGB theories there exist new black-hole solutions that are formed by spontaneous scalarization of the Schwarzschild black holes in the extreme curvature regime. In this regime, below certain mass, the Schwarzschild solution becomes unstable and a new branch of solutions with a nontrivial scalar field bifurcates from the Schwarzschild one. As a matter of fact, more than one branch with a nontrivial scalar field can bifurcate at different masses, but only the first one is supposed to be stable. This effect is quite similar to the spontaneous scalarization of neutron stars. In contrast to the standard spontaneous scalarization of neutron stars, which is induced by the presence of matter, in our case, the scalarization is induced by the curvature of the spacetime.

Recon3D enables a three-dimensional view of gene variation in human metabolism.

Abstract: Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.

The genomic history of southeastern Europe

Abstract: Farming was first introduced to Europe in the mid-seventh millennium bc, and was associated with migrants from Anatolia who settled in the southeast before spreading throughout Europe. Here, to und ...

Overall survival in patients with BRAF-mutant melanoma receiving encorafenib plus binimetinib versus vemurafenib or encorafenib (COLUMBUS): a multicentre, open-label, randomised, phase 3 trial

Abstract: Summary Background Encorafenib plus binimetinib and encorafenib alone improved progression-free survival compared with vemurafenib in patients with BRAF V600 -mutant melanoma in the COLUMBUS trial. Here, we report the results of the secondary endpoint of overall survival. Methods COLUMBUS was a two-part, randomised, open-label, phase 3 study done at 162 hospitals in 28 countries. Eligible patients were aged at least 18 years with histologically confirmed, locally advanced, unresectable, or metastatic cutaneous melanoma, or unknown primary melanoma, BRAF V600E or BRAF V600K mutation, an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1, and were treatment naive or had progressed on or after first-line immunotherapy. In part 1 of the study, patients were randomly assigned (1:1:1) by use of interactive response technology to receive oral encorafenib 450 mg once daily plus oral binimetinib 45 mg twice daily (encorafenib plus binimetinib group), oral encorafenib 300 mg once daily (encorafenib group), or oral vemurafenib 960 mg twice daily (vemurafenib group). Randomisation was stratified by the American Joint Committee on Cancer stage, ECOG performance status, and BRAF mutation status. The primary outcome of the trial, progression-free survival with encorafenib plus binimetinib versus vemurafenib, was reported previously. Here we present the prespecified interim overall survival analysis. Efficacy analyses were by intent to treat. Safety was analysed in patients who received at least one dose of study drug. Part 2 of the study was initiated at the request of the US Food and Drug Administration to better understand the contribution of binimetinib to the combination therapy by comparing encorafenib 300 mg once daily plus binimetinib 45 mg twice daily with encorafenib 300 mg once daily alone. Results of part 2 will be published separately. This trial is ongoing and is registered with ClinicalTrials.gov, number NCT01909453, and EudraCT, number 2013-001176-38. Findings Between Dec 30, 2013, and April 10, 2015, 577 of 1345 screened patients were randomly assigned to receive encorafenib plus binimetinib (n=192), encorafenib (n=194), or vemurafenib (n=191). Median follow-up for overall survival was 36·8 months (95% CI 35·9–37·5). Median overall survival was 33·6 months (95% CI 24·4–39·2) with encorafenib plus binimetinib and 16·9 months (14·0–24·5) with vemurafenib (hazard ratio 0·61 [95% CI 0·47–0·79]; two-sided p Interpretation The combination of encorafenib plus binimetinib provided clinically meaningful efficacy with good tolerability as shown by improvements in both progression-free survival and overall survival compared with vemurafenib. These data suggest that the combination of encorafenib plus binimetinib is likely to become an important therapeutic option in patients with BRAF V600 -mutant melanoma. Funding Array BioPharma, Novartis.

Quantum-enhanced measurements without entanglement

Abstract: Quantum-enhanced measurements exploit quantum mechanical effects for increasing the sensitivity of measurements of certain physical parameters and have great potential for both fundamental science and concrete applications. Most of the research has so far focused on using highly entangled states, which are, however, difficult to produce and to stabilize for a large number of constituents. In the following we review alternative mechanisms, notably the use of more general quantum correlations such as quantum discord, identical particles, or non-trivial hamiltonians; the estimation of thermodynamical parameters or parameters characterizing non-equilibrium states; and the use of quantum phase transitions. We describe both theoretically achievable enhancements and enhanced sensitivities, not primarily based on entanglement, that have already been demonstrated experimentally, and indicate some possible future research directions.

Combination therapy with anti-HIV-1 antibodies maintains viral suppression

Abstract: Individuals infected with HIV-1 require lifelong antiretroviral therapy, because interruption of treatment leads to rapid rebound viraemia Here we report on a phase 1b clinical trial in which a combination of 3BNC117 and 10-1074, two potent monoclonal anti-HIV-1 broadly neutralizing antibodies that target independent sites on the HIV-1 envelope spike, was administered during analytical treatment interruption Participants received three infusions of 30 mg kg−1 of each antibody at 0, 3 and 6 weeks Infusions of the two antibodies were generally well-tolerated The nine enrolled individuals with antibody-sensitive latent viral reservoirs maintained suppression for between 15 and more than 30 weeks (median of 21 weeks), and none developed viruses that were resistant to both antibodies We conclude that the combination of the anti-HIV-1 monoclonal antibodies 3BNC117 and 10-1074 can maintain long-term suppression in the absence of antiretroviral therapy in individuals with antibody-sensitive viral reservoirs

Impacts of species richness on productivity in a large-scale subtropical forest experiment.

Abstract: Biodiversity experiments have shown that species loss reduces ecosystem functioning in grassland. To test whether this result can be extrapolated to forests, the main contributors to terrestrial primary productivity, requires large-scale experiments. We manipulated tree species richness by planting more than 150,000 trees in plots with 1 to 16 species. Simulating multiple extinction scenarios, we found that richness strongly increased stand-level productivity. After 8 years, 16-species mixtures had accumulated over twice the amount of carbon found in average monocultures and similar amounts as those of two commercial monocultures. Species richness effects were strongly associated with functional and phylogenetic diversity. A shrub addition treatment reduced tree productivity, but this reduction was smaller at high shrub species richness. Our results encourage multispecies afforestation strategies to restore biodiversity and mitigate climate change.

Generalisation in humans and deep neural networks

Abstract: We compare the robustness of humans and current convolutional deep neural networks (DNNs) on object recognition under twelve different types of image degradations. First, using three well known DNNs (ResNet-152, VGG-19, GoogLeNet) we find the human visual system to be more robust to nearly all of the tested image manipulations, and we observe progressively diverging classification error-patterns between humans and DNNs when the signal gets weaker. Secondly, we show that DNNs trained directly on distorted images consistently surpass human performance on the exact distortion types they were trained on, yet they display extremely poor generalisation abilities when tested on other distortion types. For example, training on salt-and-pepper noise does not imply robustness on uniform white noise and vice versa. Thus, changes in the noise distribution between training and testing constitutes a crucial challenge to deep learning vision systems that can be systematically addressed in a lifelong machine learning approach. Our new dataset consisting of 83K carefully measured human psychophysical trials provide a useful reference for lifelong robustness against image degradations set by the human visual system.

Improved Limit on Neutrinoless Double-$\beta$ Decay of $^{76}$Ge from GERDA Phase II

Abstract: The GERDA experiment searches for the lepton-number-violating neutrinoless double-β decay of ^{76}Ge (^{76}Ge→^{76}Se+2e^{-}) operating bare Ge diodes with an enriched ^{76}Ge fraction in liquid argon. The exposure for broad-energy germanium type (BEGe) detectors is increased threefold with respect to our previous data release. The BEGe detectors feature an excellent background suppression from the analysis of the time profile of the detector signals. In the analysis window a background level of 1.0_{-0.4}^{+0.6}×10^{-3} counts/(keV kg yr) has been achieved; if normalized to the energy resolution this is the lowest ever achieved in any 0νββ experiment. No signal is observed and a new 90% C.L. lower limit for the half-life of 8.0×10^{25} yr is placed when combining with our previous data. The expected median sensitivity assuming no signal is 5.8×10^{25} yr.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study.

Abstract: Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = -0.24 to -0.73; P < 1.49 × 10-4), and lower thickness in the precentral gyri bilaterally (d = -0.34 to -0.52; P < 4.31 × 10-6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = -1.73 to -1.91, P < 1.4 × 10-19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = -0.36 to -0.52; P < 1.49 × 10-4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = -0.29 to -0.54; P < 1.49 × 10-4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = -0.27 to -0.51; P < 1.49 × 10-4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < -0.0018; P < 1.49 × 10-4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Justify your alpha

Abstract: In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.