Showing papers by "Heidelberg University published in 2019"

Sarcopenia: Revised European consensus on definition and diagnosis

Abstract: Background in 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) published a sarcopenia definition that aimed to foster advances in identifying and caring for people with sarcopenia. In early 2018, the Working Group met again (EWGSOP2) to update the original definition in order to reflect scientific and clinical evidence that has built over the last decade. This paper presents our updated findings. Objectives to increase consistency of research design, clinical diagnoses and ultimately, care for people with sarcopenia. Recommendations sarcopenia is a muscle disease (muscle failure) rooted in adverse muscle changes that accrue across a lifetime; sarcopenia is common among adults of older age but can also occur earlier in life. In this updated consensus paper on sarcopenia, EWGSOP2: (1) focuses on low muscle strength as a key characteristic of sarcopenia, uses detection of low muscle quantity and quality to confirm the sarcopenia diagnosis, and identifies poor physical performance as indicative of severe sarcopenia; (2) updates the clinical algorithm that can be used for sarcopenia case-finding, diagnosis and confirmation, and severity determination and (3) provides clear cut-off points for measurements of variables that identify and characterise sarcopenia. Conclusions EWGSOP2's updated recommendations aim to increase awareness of sarcopenia and its risk. With these new recommendations, EWGSOP2 calls for healthcare professionals who treat patients at risk for sarcopenia to take actions that will promote early detection and treatment. We also encourage more research in the field of sarcopenia in order to prevent or delay adverse health outcomes that incur a heavy burden for patients and healthcare systems.

ilastik: interactive machine learning for (bio)image analysis.

Abstract: We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise. It contains pre-defined workflows for image segmentation, object classification, counting and tracking. Users adapt the workflows to the problem at hand by interactively providing sparse training annotations for a nonlinear classifier. ilastik can process data in up to five dimensions (3D, time and number of channels). Its computational back end runs operations on-demand wherever possible, allowing for interactive prediction on data larger than RAM. Once the classifiers are trained, ilastik workflows can be applied to new data from the command line without further user interaction. We describe all ilastik workflows in detail, including three case studies and a discussion on the expected performance.

Chronic pain as a symptom or a disease: the IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11).

Abstract: Chronic pain is a major source of suffering. It interferes with daily functioning and often is accompanied by distress. Yet, in the International Classification of Diseases, chronic pain diagnoses are not represented systematically. The lack of appropriate codes renders accurate epidemiological investigations difficult and impedes health policy decisions regarding chronic pain such as adequate financing of access to multimodal pain management. In cooperation with the WHO, an IASP Working Group has developed a classification system that is applicable in a wide range of contexts, including pain medicine, primary care, and low-resource environments. Chronic pain is defined as pain that persists or recurs for more than 3 months. In chronic pain syndromes, pain can be the sole or a leading complaint and requires special treatment and care. In conditions such as fibromyalgia or nonspecific low-back pain, chronic pain may be conceived as a disease in its own right; in our proposal, we call this subgroup "chronic primary pain." In 6 other subgroups, pain is secondary to an underlying disease: chronic cancer-related pain, chronic neuropathic pain, chronic secondary visceral pain, chronic posttraumatic and postsurgical pain, chronic secondary headache and orofacial pain, and chronic secondary musculoskeletal pain. These conditions are summarized as "chronic secondary pain" where pain may at least initially be conceived as a symptom. Implementation of these codes in the upcoming 11th edition of International Classification of Diseases will lead to improved classification and diagnostic coding, thereby advancing the recognition of chronic pain as a health condition in its own right.

Exercise Guidelines for Cancer Survivors: Consensus Statement from International Multidisciplinary Roundtable

Abstract: PurposeThe number of cancer survivors worldwide is growing, with over 15.5 million cancer survivors in the United States alone—a figure expected to double in the coming decades. Cancer survivors face unique health challenges as a result of their cancer diagnosis and the impact of treatments

Genome-wide association study identifies 30 loci associated with bipolar disorder

Abstract: Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.

Panoptic Segmentation

Abstract: We propose and study a task we name panoptic segmentation (PS). Panoptic segmentation unifies the typically distinct tasks of semantic segmentation (assign a class label to each pixel) and instance segmentation (detect and segment each object instance). The proposed task requires generating a coherent scene segmentation that is rich and complete, an important step toward real-world vision systems. While early work in computer vision addressed related image/scene parsing tasks, these are not currently popular, possibly due to lack of appropriate metrics or associated recognition challenges. To address this, we propose a novel panoptic quality (PQ) metric that captures performance for all classes (stuff and things) in an interpretable and unified manner. Using the proposed metric, we perform a rigorous study of both human and machine performance for PS on three existing datasets, revealing interesting insights about the task. The aim of our work is to revive the interest of the community in a more unified view of image segmentation. For more analysis and up-to-date results, please check the arXiv version of the paper: {\small\url{https://arxiv.org/abs/1801.00868}}.

Psoriasis Pathogenesis and Treatment.

Abstract: Research on psoriasis pathogenesis has largely increased knowledge on skin biology in general. In the past 15 years, breakthroughs in the understanding of the pathogenesis of psoriasis have been translated into targeted and highly effective therapies providing fundamental insights into the pathogenesis of chronic inflammatory diseases with a dominant IL-23/Th17 axis. This review discusses the mechanisms involved in the initiation and development of the disease, as well as the therapeutic options that have arisen from the dissection of the inflammatory psoriatic pathways. Our discussion begins by addressing the inflammatory pathways and key cell types initiating and perpetuating psoriatic inflammation. Next, we describe the role of genetics, associated epigenetic mechanisms, and the interaction of the skin flora in the pathophysiology of psoriasis. Finally, we include a comprehensive review of well-established widely available therapies and novel targeted drugs.

Nature and mental health: An ecosystem service perspective.

Abstract: A growing body of empirical evidence is revealing the value of nature experience for mental health. With rapid urbanization and declines in human contact with nature globally, crucial decisions must be made about how to preserve and enhance opportunities for nature experience. Here, we first provide points of consensus across the natural, social, and health sciences on the impacts of nature experience on cognitive functioning, emotional well-being, and other dimensions of mental health. We then show how ecosystem service assessments can be expanded to include mental health, and provide a heuristic, conceptual model for doing so.

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.

Abstract: Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohistochemical tests. Here we show that deep residual learning can predict MSI directly from H&E histology, which is ubiquitously available. This approach has the potential to provide immunotherapy to a much broader subset of patients with gastrointestinal cancer.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

Abstract: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond

Abstract: L-Tryptophan (Trp) metabolism through the kynurenine pathway (KP) is involved in the regulation of immunity, neuronal function and intestinal homeostasis. Imbalances in Trp metabolism in disorders ranging from cancer to neurodegenerative disease have stimulated interest in therapeutically targeting the KP, particularly the main rate-limiting enzymes indoleamine-2,3-dioxygenase 1 (IDO1), IDO2 and tryptophan-2,3-dioxygenase (TDO) as well as kynurenine monooxygenase (KMO). However, although small-molecule IDO1 inhibitors showed promise in early-stage cancer immunotherapy clinical trials, a phase III trial was negative. This Review summarizes the physiological and pathophysiological roles of Trp metabolism, highlighting the vast opportunities and challenges for drug development in multiple diseases.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Capecitabine compared with observation in resected biliary tract cancer (BILCAP): a randomised, controlled, multicentre, phase 3 study.

Abstract: BACKGROUND Despite improvements in multidisciplinary management, patients with biliary tract cancer have a poor outcome. Only 20% of patients are eligible for surgical resection with curative intent, with 5-year overall survival of less than 10% for all patients. To our knowledge, no studies have described a benefit of adjuvant therapy. We aimed to determine whether adjuvant capecitabine improved overall survival compared with observation following surgery for biliary tract cancer. METHODS This randomised, controlled, multicentre, phase 3 study was done across 44 specialist hepatopancreatobiliary centres in the UK. Eligible patients were aged 18 years or older and had histologically confirmed cholangiocarcinoma or muscle-invasive gallbladder cancer who had undergone a macroscopically complete resection (which includes liver resection, pancreatic resection, or, less commonly, both) with curative intent, and an Eastern Cooperative Oncology Group performance status of less than 2. Patients who had not completely recovered from previous surgery or who had previous chemotherapy or radiotherapy for biliary tract cancer were also excluded. Patients were randomly assigned 1:1 to receive oral capecitabine (1250 mg/m twice daily on days 1-14 of a 21-day cycle, for eight cycles) or observation commencing within 16 weeks of surgery. Treatment was not masked, and allocation concealment was achieved with a computerised minimisation algorithm that stratified patients by surgical centre, site of disease, resection status, and performance status. The primary outcome was overall survival. As prespecified, analyses were done by intention to treat and per protocol. This study is registered with EudraCT, number 2005-003318-13. FINDINGS Between March 15, 2006, and Dec 4, 2014, 447 patients were enrolled; 223 patients with biliary tract cancer resected with curative intent were randomly assigned to the capecitabine group and 224 to the observation group. The data cutoff for this analysis was March 6, 2017. The median follow-up for all patients was 60 months (IQR 37-60). In the intention-to-treat analysis, median overall survival was 51·1 months (95% CI 34·6-59·1) in the capecitabine group compared with 36·4 months (29·7-44·5) in the observation group (adjusted hazard ratio [HR] 0·81, 95% CI 0·63-1·04; p=0·097). In a protocol-specified sensitivity analysis, adjusting for minimisation factors and nodal status, grade, and gender, the overall survival HR was 0·71 (95% CI 0·55-0·92; p=0·010). In the prespecified per-protocol analysis (210 patients in the capecitabine group and 220 in the observation group), median overall survival was 53 months (95% CI 40 to not reached) in the capecitabine group and 36 months (30-44) in the observation group (adjusted HR 0·75, 95% CI 0·58-0·97; p=0·028). In the intention-to-treat analysis, median recurrence-free survival was 24·4 months (95% CI 18·6-35·9) in the capecitabine group and 17·5 months (12·0-23·8) in the observation group. In the per-protocol analysis, median recurrence-free survival was 25·9 months (95% CI 19·8-46·3) in the capecitabine group and 17·4 months (12·0-23·7) in the observation group. Adverse events were measured in the capecitabine group only, and of the 213 patients who received at least one cycle, 94 (44%) had at least one grade 3 toxicity, the most frequent of which were hand-foot syndrome in 43 (20%) patients, diarrhoea in 16 (8%) patients, and fatigue in 16 (8%) patients. One (<1%) patient had grade 4 cardiac ischaemia or infarction. Serious adverse events were observed in 47 (21%) of 223 patients in the capecitabine group and 22 (10%) of 224 patients in the observation group. No deaths were deemed to be treatment related. INTERPRETATION Although this study did not meet its primary endpoint of improving overall survival in the intention-to-treat population, the prespecified sensitivity and per-protocol analyses suggest that capecitabine can improve overall survival in patients with resected biliary tract cancer when used as adjuvant chemotherapy following surgery and could be considered as standard of care. Furthermore, the safety profile is manageable, supporting the use of capecitabine in this setting. FUNDING Cancer Research UK and Roche.

Daratumumab plus Lenalidomide and Dexamethasone for Untreated Myeloma.

Abstract: Background Lenalidomide plus dexamethasone is a standard treatment for patients with newly diagnosed multiple myeloma who are ineligible for autologous stem-cell transplantation. We sought...

Single-pot, solid-phase-enhanced sample preparation for proteomics experiments.

Abstract: A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead–based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration. This protocol describes a single-pot, solid-phase-enhanced sample-preparation (SP3) method for rapid, robust, and efficient processing of protein samples for proteomic analysis.

The IllustrisTNG simulations: public data release

Abstract: We present the full public release of all data from the TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG is a suite of large volume, cosmological, gravo-magnetohydrodynamical simulations run with the moving-mesh code Arepo. TNG includes a comprehensive model for galaxy formation physics, and each TNG simulation self-consistently solves for the coupled evolution of dark matter, cosmic gas, luminous stars, and supermassive black holes from early time to the present day, $z=0$ . Each of the flagship runs—TNG50, TNG100, and TNG300—are accompanied by halo/subhalo catalogs, merger trees, lower-resolution and dark-matter only counterparts, all available with 100 snapshots. We discuss scientific and numerical cautions and caveats relevant when using TNG. The data volume now directly accessible online is ∼750 TB, including 1200 full volume snapshots and ∼80,000 high time-resolution subbox snapshots. This will increase to ∼1.1 PB with the future release of TNG50. Data access and analysis examples are available in IDL, Python, and Matlab. We describe improvements and new functionality in the web-based API, including on-demand visualization and analysis of galaxies and halos, exploratory plotting of scaling relations and other relationships between galactic and halo properties, and a new JupyterLab interface. This provides an online, browser-based, near-native data analysis platform enabling user computation with local access to TNG data, alleviating the need to download large datasets.

The Hsp70 chaperone network

Abstract: The 70-kDa heat shock proteins (Hsp70s) are ubiquitous molecular chaperones that act in a large variety of cellular protein folding and remodelling processes. They function virtually at all stages of the life of proteins from synthesis to degradation and are thus crucial for maintaining protein homeostasis, with direct implications for human health. A large set of co-chaperones comprising J-domain proteins and nucleotide exchange factors regulate the ATPase cycle of Hsp70s, which is allosterically coupled to substrate binding and release. Moreover, Hsp70s cooperate with other cellular chaperone systems including Hsp90, Hsp60 chaperonins, small heat shock proteins and Hsp100 AAA+ disaggregases, together constituting a dynamic and functionally versatile network for protein folding, unfolding, regulation, targeting, aggregation and disaggregation, as well as degradation. In this Review we describe recent advances that have increased our understanding of the molecular mechanisms and working principles of the Hsp70 network. This knowledge showcases how the Hsp70 chaperone system controls diverse cellular functions, and offers new opportunities for the development of chemical compounds that modulate disease-related Hsp70 activities. The Hsp70 chaperones regulate protein metabolism, including folding, unfolding, subcellular localization, aggregation/disaggregation and incorporation into protein complexes. Recent studies have revealed the mechanisms of functions of Hsp70s and their co-chaperones, highlighting new opportunities for modulating disease-related Hsp70 roles.

Electrical and synaptic integration of glioma into neural circuits

Abstract: High-grade gliomas are lethal brain cancers whose progression is robustly regulated by neuronal activity. Activity-regulated release of growth factors promotes glioma growth, but this alone is insufficient to explain the effect that neuronal activity exerts on glioma progression. Here we show that neuron and glioma interactions include electrochemical communication through bona fide AMPA receptor-dependent neuron–glioma synapses. Neuronal activity also evokes non-synaptic activity-dependent potassium currents that are amplified by gap junction-mediated tumour interconnections, forming an electrically coupled network. Depolarization of glioma membranes assessed by in vivo optogenetics promotes proliferation, whereas pharmacologically or genetically blocking electrochemical signalling inhibits the growth of glioma xenografts and extends mouse survival. Emphasizing the positive feedback mechanisms by which gliomas increase neuronal excitability and thus activity-regulated glioma growth, human intraoperative electrocorticography demonstrates increased cortical excitability in the glioma-infiltrated brain. Together, these findings indicate that synaptic and electrical integration into neural circuits promotes glioma progression. Neurons form synapses onto glioma cells, and depolarization of glioma membranes promotes glioma growth in vivo, whereas blocking electrochemical signalling blocks tumour growth.

OpenMolcas : From Source Code to Insight

Abstract: In this Article we describe the OpenMolcas environment and invite the computational chemistry community to collaborate. The open-source project already includes a large number of new developments realized during the transition from the commercial MOLCAS product to the open-source platform. The paper initially describes the technical details of the new software development platform. This is followed by brief presentations of many new methods, implementations, and features of the OpenMolcas program suite. These developments include novel wave function methods such as stochastic complete active space self-consistent field, density matrix renormalization group (DMRG) methods, and hybrid multiconfigurational wave function and density functional theory models. Some of these implementations include an array of additional options and functionalities. The paper proceeds and describes developments related to explorations of potential energy surfaces. Here we present methods for the optimization of conical intersections, the simulation of adiabatic and nonadiabatic molecular dynamics, and interfaces to tools for semiclassical and quantum mechanical nuclear dynamics. Furthermore, the Article describes features unique to simulations of spectroscopic and magnetic phenomena such as the exact semiclassical description of the interaction between light and matter, various X-ray processes, magnetic circular dichroism, and properties. Finally, the paper describes a number of built-in and add-on features to support the OpenMolcas platform with postcalculation analysis and visualization, a multiscale simulation option using frozen-density embedding theory, and new electronic and muonic basis sets.

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.

Abstract: BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images. METHODS AND FINDINGS: We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I-IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a "deep stroma score," which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27-3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I-IV CRC patients from the "Darmkrebs: Chancen der Verhutung durch Screening" (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14-2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5-3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34-2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows. CONCLUSIONS: In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images.

The IASP classification of chronic pain for ICD-11: Chronic primary pain

Abstract: This article describes a proposal for the new diagnosis of chronic primary pain (CPP) in ICD-11. Chronic primary pain is chosen when pain has persisted for more than 3 months and is associated with significant emotional distress and/or functional disability, and the pain is not better accounted for by another condition. As with all pain, the article assumes a biopsychosocial framework for understanding CPP, which means all subtypes of the diagnosis are considered to be multifactorial in nature, with biological, psychological, and social factors contributing to each. Unlike the perspectives found in DSM-5 and ICD-10, the diagnosis of CPP is considered to be appropriate independently of identified biological or psychological contributors, unless another diagnosis would better account for the presenting symptoms. Such other diagnoses are called "chronic secondary pain" where pain may at least initially be conceived as a symptom secondary to an underlying disease. The goal here is to create a classification that is useful in both primary care and specialized pain management settings for the development of individualized management plans, and to assist both clinicians and researchers by providing a more accurate description of each diagnostic category.

FCC-ee: The Lepton Collider: Future Circular Collider Conceptual Design Report Volume 2

Abstract: In response to the 2013 Update of the European Strategy for Particle Physics, the Future Circular Collider (FCC) study was launched, as an international collaboration hosted by CERN. This study covers a highest-luminosity high-energy lepton collider (FCC-ee) and an energy-frontier hadron collider (FCC-hh), which could, successively, be installed in the same 100 km tunnel. The scientific capabilities of the integrated FCC programme would serve the worldwide community throughout the 21st century. The FCC study also investigates an LHC energy upgrade, using FCC-hh technology. This document constitutes the second volume of the FCC Conceptual Design Report, devoted to the electron-positron collider FCC-ee. After summarizing the physics discovery opportunities, it presents the accelerator design, performance reach, a staged operation scenario, the underlying technologies, civil engineering, technical infrastructure, and an implementation plan. FCC-ee can be built with today’s technology. Most of the FCC-ee infrastructure could be reused for FCC-hh. Combining concepts from past and present lepton colliders and adding a few novel elements, the FCC-ee design promises outstandingly high luminosity. This will make the FCC-ee a unique precision instrument to study the heaviest known particles (Z, W and H bosons and the top quark), offering great direct and indirect sensitivity to new physics.

Single-cell genomics identifies cell type-specific molecular changes in autism.

Abstract: Despite the clinical and genetic heterogeneity of autism, bulk gene expression studies show that changes in the neocortex of autism patients converge on common genes and pathways. However, direct assessment of specific cell types in the brain affected by autism has not been feasible until recently. We used single-nucleus RNA sequencing of cortical tissue from patients with autism to identify autism-associated transcriptomic changes in specific cell types. We found that synaptic signaling of upper-layer excitatory neurons and the molecular state of microglia are preferentially affected in autism. Moreover, our results show that dysregulation of specific groups of genes in cortico-cortical projection neurons correlates with clinical severity of autism. These findings suggest that molecular changes in upper-layer cortical circuits are linked to behavioral manifestations of autism.

Glutamatergic synaptic input to glioma cells drives brain tumour progression

Abstract: A network of communicating tumour cells that is connected by tumour microtubes mediates the progression of incurable gliomas. Moreover, neuronal activity can foster malignant behaviour of glioma cells by non-synaptic paracrine and autocrine mechanisms. Here we report a direct communication channel between neurons and glioma cells in different disease models and human tumours: functional bona fide chemical synapses between presynaptic neurons and postsynaptic glioma cells. These neurogliomal synapses show a typical synaptic ultrastructure, are located on tumour microtubes, and produce postsynaptic currents that are mediated by glutamate receptors of the AMPA subtype. Neuronal activity including epileptic conditions generates synchronised calcium transients in tumour-microtube-connected glioma networks. Glioma-cell-specific genetic perturbation of AMPA receptors reduces calcium-related invasiveness of tumour-microtube-positive tumour cells and glioma growth. Invasion and growth are also reduced by anaesthesia and the AMPA receptor antagonist perampanel, respectively. These findings reveal a biologically relevant direct synaptic communication between neurons and glioma cells with potential clinical implications.

Global, regional, and national burden of suicide mortality 1990 to 2016: systematic analysis for the Global Burden of Disease Study 2016

Abstract: Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7% (95% uncertainty interval 0.4% to 15.6%) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7% (27.2% to 36.6%) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6%. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0%, 95% uncertainty interval 42.6% to 54.6%) than men (23.8%, 15.6% to 32.7%). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates.

Search for Lepton-Universality Violation in B + →K + ℓ+ ℓ- Decays

Abstract: A measurement of the ratio of branching fractions of the decays B + → K + μ + μ − and B + → K + e + e − is presented. The proton-proton collision data used correspond to an integrated luminosity of 5.0 fb − 1 recorded with the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV. For the dilepton mass-squared range 1.1 < q 2 < 6.0 GeV 2 / c 4 the ratio of branching fractions is measured to be R K = 0.84 6 + 0.060 − 0.054 + 0.016 − 0.014 , where the first uncertainty is statistical and the second systematic. This is the most precise measurement of R K to date and is compatible with the standard model at the level of 2.5 standard deviations.

First results from the TNG50 simulation: galactic outflows driven by supernovae and black hole feedback

Abstract: We present the new TNG50 cosmological, magnetohydrodynamical simulation -- the third and final volume of the IllustrisTNG project. This simulation occupies a unique combination of large volume and high resolution, with a 50 Mpc box sampled by 2160^3 gas cells (baryon mass of 8x10^4 Msun). The median spatial resolution of star-forming ISM gas is ~100-140 parsecs. This resolution approaches or exceeds that of modern 'zoom' simulations of individual massive galaxies, while the volume contains ~20,000 resolved galaxies with M*>10^7 Msun. Herein we show first results from TNG50, focusing on galactic outflows driven by supernovae as well as supermassive black hole feedback. We find that the outflow mass loading is a non-monotonic function of galaxy stellar mass, turning over and rising rapidly above 10^10.5 Msun due to the action of the central black hole. Outflow velocity increases with stellar mass, and at fixed mass is faster at higher redshift. The TNG model can produce high velocity, multi-phase outflows which include cool, dense components. These outflows reach speeds in excess of 3000 km/s out to 20 kpc with an ejective, BH-driven origin. Critically, we show how the relative simplicity of model inputs (and scalings) at the injection scale produces complex behavior at galactic and halo scales. For example, despite isotropic wind launching, outflows exhibit natural collimation and an emergent bipolarity. Furthermore, galaxies above the star-forming main sequence drive faster outflows, although this correlation inverts at high mass with the onset of quenching, whereby low luminosity, slowly accreting, massive black holes drive the strongest outflows.

Iridium-Catalyzed Asymmetric Allylic Substitution Reactions

Abstract: In this review, we summarize the origin and advancements of iridium-catalyzed asymmetric allylic substitution reactions during the past two decades. Since the first report in 1997, Ir-catalyzed asymmetric allylic substitution reactions have attracted intense attention due to their exceptionally high regio- and enantioselectivities. Ir-catalyzed asymmetric allylic substitution reactions have been significantly developed in recent years in many respects, including ligand development, mechanistic understanding, substrate scope, and application in the synthesis of complex functional molecules. In this review, an explicit outline of ligands, mechanism, scope of nucleophiles, and applications is presented.