Showing papers by "Ludwig Maximilian University of Munich published in 2019"

Colloquium: Many-body localization, thermalization, and entanglement

Abstract: Thermalizing quantum systems are conventionallydescribed by statistical mechanics at equilib-rium. However, not all systems fall into this category, with many-body localization providinga generic mechanism for thermalization to fail in strongly disordered systems. Many-bodylocalized (MBL) systems remain perfect insulators at nonzero temperature, which do notthermalize and therefore cannot be describedusing statistical mechanics. This Colloquiumreviews recent theoretical and experimental advances in studies of MBL systems, focusing onthe new perspective provided by entanglement and nonequilibrium experimental probes suchas quantum quenches. Theoretically, MBL systems exhibit a new kind of robust integrability: anextensive set of quasilocal integrals of motion emerges, which provides an intuitive explanationof the breakdown of thermalization. A description based on quasilocal integrals of motion isused to predict dynamical properties of MBL systems, such as the spreading of quantumentanglement, the behavior of local observables, and the response to external dissipativeprocesses. Furthermore, MBL systems can exhibit eigenstate transitions and quantum ordersforbidden in thermodynamic equilibrium. An outline isgiven of the current theoretical under-standing of the quantum-to-classical transitionbetween many-body localized and ergodic phasesand anomalous transport in the vicinity of that transition. Experimentally, synthetic quantumsystems, which are well isolated from an external thermal reservoir, provide natural platforms forrealizing the MBL phase. Recent experiments with ultracold atoms, trapped ions, superconductingqubits, and quantum materials, in which different signatures of many-body localization have beenobserved, are reviewed. This Colloquium concludes by listing outstanding challenges andpromising future research directions.

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.

The KOF Globalisation Index – revisited

Abstract: We introduce the revised version of the KOF Globalisation Index, a composite index measuring globalization for every country in the world along the economic, social and political dimension. The original index was introduced by Dreher (Applied Economics, 38(10):1091–1110, 2006) and updated in Dreher et al. (2008). This second revision of the index distinguishes between de facto and de jure measures along the different dimensions of globalization. We also disentangle trade and financial globalization within the economic dimension of globalization and use time-varying weighting of the variables. The new index is based on 43 instead of 23 variables in the previous version. Following Dreher (Applied Economics, 38(10):1091–1110, 2006), we use the new index to examine the effect of globalization on economic growth. The results suggest that de facto and de jure globalization influence economic growth differently. Future research should use the new KOF Globalisation Index to re-examine other important consequences of globalization and why globalization was proceeding rapidly in some countries, such as South Korea, but less so in others. The KOF Globalisation Index can be downloaded from http://www.kof.ethz.ch/globalisation/ .

Global Carbon Budget 2019

Abstract: . Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( EFF ) are based on energy statistics and cement production data, while emissions from land use change ( ELUC ), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate ( GATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( SOCEAN ) and terrestrial CO2 sink ( SLAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( BIM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2009–2018), EFF was 9.5±0.5 GtC yr −1 , ELUC 1.5±0.7 GtC yr −1 , GATM 4.9±0.02 GtC yr −1 ( 2.3±0.01 ppm yr −1 ), SOCEAN 2.5±0.6 GtC yr −1 , and SLAND 3.2±0.6 GtC yr −1 , with a budget imbalance BIM of 0.4 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr −1 , reaching 10 GtC yr −1 for the first time in history, ELUC was 1.5±0.7 GtC yr −1 , for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr −1 ( 42.5±3.3 GtCO2 ). Also for 2018, GATM was 5.1±0.2 GtC yr −1 ( 2.4±0.1 ppm yr −1 ), SOCEAN was 2.6±0.6 GtC yr −1 , and SLAND was 3.5±0.7 GtC yr −1 , with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis

Abstract: Summary Background Deep learning offers considerable promise for medical diagnostics. We aimed to evaluate the diagnostic accuracy of deep learning algorithms versus health-care professionals in classifying diseases using medical imaging. Methods In this systematic review and meta-analysis, we searched Ovid-MEDLINE, Embase, Science Citation Index, and Conference Proceedings Citation Index for studies published from Jan 1, 2012, to June 6, 2019. Studies comparing the diagnostic performance of deep learning models and health-care professionals based on medical imaging, for any disease, were included. We excluded studies that used medical waveform data graphics material or investigated the accuracy of image segmentation rather than disease classification. We extracted binary diagnostic accuracy data and constructed contingency tables to derive the outcomes of interest: sensitivity and specificity. Studies undertaking an out-of-sample external validation were included in a meta-analysis, using a unified hierarchical model. This study is registered with PROSPERO, CRD42018091176. Findings Our search identified 31 587 studies, of which 82 (describing 147 patient cohorts) were included. 69 studies provided enough data to construct contingency tables, enabling calculation of test accuracy, with sensitivity ranging from 9·7% to 100·0% (mean 79·1%, SD 0·2) and specificity ranging from 38·9% to 100·0% (mean 88·3%, SD 0·1). An out-of-sample external validation was done in 25 studies, of which 14 made the comparison between deep learning models and health-care professionals in the same sample. Comparison of the performance between health-care professionals in these 14 studies, when restricting the analysis to the contingency table for each study reporting the highest accuracy, found a pooled sensitivity of 87·0% (95% CI 83·0–90·2) for deep learning models and 86·4% (79·9–91·0) for health-care professionals, and a pooled specificity of 92·5% (95% CI 85·1–96·4) for deep learning models and 90·5% (80·6–95·7) for health-care professionals. Interpretation Our review found the diagnostic performance of deep learning models to be equivalent to that of health-care professionals. However, a major finding of the review is that few studies presented externally validated results or compared the performance of deep learning models and health-care professionals using the same sample. Additionally, poor reporting is prevalent in deep learning studies, which limits reliable interpretation of the reported diagnostic accuracy. New reporting standards that address specific challenges of deep learning could improve future studies, enabling greater confidence in the results of future evaluations of this promising technology. Funding None.

Metal Halide Perovskite Nanocrystals: Synthesis, Post-Synthesis Modifications, and Their Optical Properties.

Abstract: Metal halide perovskites represent a flourishing area of research, which is driven by both their potential application in photovoltaics and optoelectronics and by the fundamental science behind their unique optoelectronic properties. The emergence of new colloidal methods for the synthesis of halide perovskite nanocrystals, as well as the interesting characteristics of this new type of material, has attracted the attention of many researchers. This review aims to provide an up-to-date survey of this fast-moving field and will mainly focus on the different colloidal synthesis approaches that have been developed. We will examine the chemistry and the capability of different colloidal synthetic routes with regard to controlling the shape, size, and optical properties of the resulting nanocrystals. We will also provide an up-to-date overview of their postsynthesis transformations, and summarize the various solution processes that are aimed at fabricating halide perovskite-based nanocomposites. Furthermore, we...

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.

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.

Overall Survival with Ribociclib plus Endocrine Therapy in Breast Cancer

Abstract: Background An earlier analysis of this phase 3 trial showed that the addition of a cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor to endocrine therapy provided a greater benefit with r...

Frequency comb spectroscopy

Abstract: A laser frequency comb is a broad spectrum composed of equidistant narrow lines. Initially invented for frequency metrology, such combs enable new approaches to spectroscopy over broad spectral bandwidths, of particular relevance to molecules. The performance of existing spectrometers — such as crossed dispersers employing, for example, virtual imaging phase array etalons, or Michelson-based Fourier transform interferometers — can be dramatically enhanced with optical frequency combs. A new class of instruments, such as dual-comb spectrometers without moving parts, enables fast and accurate measurements over broad spectral ranges. The direct self-calibration of the frequency scale of the spectra within the accuracy of an atomic clock and the negligible contribution of the instrumental line-shape will enable determinations of all spectral parameters with high accuracy for stringent comparisons with theories in atomic and molecular physics. Chip-scale frequency comb spectrometers promise integrated devices for real-time sensing in analytical chemistry and biomedicine. This Review gives a summary of the developments in the emerging and rapidly advancing field of atomic and molecular broadband spectroscopy with frequency combs. Frequency comb spectroscopy is a recent field of research that has blossomed in the past five years. This Review discusses developments in the emerging and rapidly advancing field of atomic and molecular broadband spectroscopy with frequency combs.

Hyperparameters and tuning strategies for random forest

Abstract: The random forest algorithm (RF) has several hyperparameters that have to be set by the user, e.g., the number of observations drawn randomly for each tree and whether they are drawn with or without replacement, the number of variables drawn randomly for each split, the splitting rule, the minimum number of samples that a node must contain and the number of trees. In this paper, we first provide a literature review on the parameters' influence on the prediction performance and on variable importance measures. It is well known that in most cases RF works reasonably well with the default values of the hyperparameters specified in software packages. Nevertheless, tuning the hyperparameters can improve the performance of RF. In the second part of this paper, after a brief overview of tuning strategies we demonstrate the application of one of the most established tuning strategies, model-based optimization (MBO). To make it easier to use, we provide the tuneRanger R package that tunes RF with MBO automatically. In a benchmark study on several datasets, we compare the prediction performance and runtime of tuneRanger with other tuning implementations in R and RF with default hyperparameters.

Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2.

Abstract: A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two‐layer model.

Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation

Abstract: The innate immune cell compartment is highly diverse in the healthy central nervous system (CNS), including parenchymal and non-parenchymal macrophages. However, this complexity is increased in inflammatory settings by the recruitment of circulating myeloid cells. It is unclear which disease-specific myeloid subsets exist and what their transcriptional profiles and dynamics during CNS pathology are. Combining deep single-cell transcriptome analysis, fate mapping, in vivo imaging, clonal analysis, and transgenic mouse lines, we comprehensively characterized unappreciated myeloid subsets in several CNS compartments during neuroinflammation. During inflammation, CNS macrophage subsets undergo self-renewal, and random proliferation shifts toward clonal expansion. Last, functional studies demonstrated that endogenous CNS tissue macrophages are redundant for antigen presentation. Our results highlight myeloid cell diversity and provide insights into the brain's innate immune system.

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.

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease

Abstract: Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer’s disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini–Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer’s disease, which supports its potential utility as a clinically useful biomarker.

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa

Abstract: Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.

Liquid-Liquid Phase Separation in Disease.

Abstract: We have made rapid progress in recent years in identifying the genetic causes of many human diseases. However, despite this recent progress, our mechanistic understanding of these diseases is often incomplete. This is a problem because it limits our ability to develop effective disease treatments. To overcome this limitation, we need new concepts to describe and comprehend the complex mechanisms underlying human diseases. Condensate formation by phase separation emerges as a new principle to explain the organization of living cells. In this review, we present emerging evidence that aberrant forms of condensates are associated with many human diseases, including cancer, neurodegeneration, and infectious diseases. We examine disease mechanisms driven by aberrant condensates, and we point out opportunities for therapeutic interventions. We conclude that phase separation provides a useful new framework to understand and fight some of the most severe human diseases.

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Abstract: Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they ar ...

Assessment of 68Ga-PSMA-11 PET Accuracy in Localizing Recurrent Prostate Cancer: A Prospective Single-Arm Clinical Trial

Abstract: Importance: In retrospective studies, 68Ga-PSMA-11 positron emission tomographic (PET) imaging improves detection of biochemically recurrent prostate cancer compared with conventional imaging. Objective: To assess 68Ga-PSMA-11 PET accuracy in a prospective multicenter trial. Design, Setting, and Participants: In this single-arm prospective trial conducted at University of California, San Francisco and University of California, Los Angeles, 635 patients with biochemically recurrent prostate cancer after prostatectomy (n = 262, 41%), radiation therapy (n = 169, 27%), or both (n = 204, 32%) underwent 68Ga-PSMA-11 PET. Presence of prostate cancer was recorded by 3 blinded readers on a per-patient and per-region base. Lesions were validated by histopathologic analysis and a composite reference standard. Main Outcomes and Measures: Endpoints were positive predictive value (PPV), detection rate, interreader reproducibility, and safety. Results: A total of 635 men were enrolled with a median age of 69 years (range, 44-95 years). On a per-patient basis, PPV was 0.84 (95% CI, 0.75-0.90) by histopathologic validation (primary endpoint, n = 87) and 0.92 (95% CI, 0.88-0.95) by the composite reference standard (n = 217). 68Ga-PSMA-11 PET localized recurrent prostate cancer in 475 of 635 (75%) patients; detection rates significantly increased with prostate-specific antigen (PSA): 38% for <0.5 ng/mL (n = 136), 57% for 0.5 to <1.0 ng/mL (n = 79), 84% for 1.0 to <2.0 ng/mL (n = 89), 86% for 2.0 to <5.0 ng/mL (n = 158), and 97% for ≥5.0 ng/mL (n = 173, P < .001). Interreader reproducibility was substantial (Fleiss κ, 0.65-0.78). There were no serious adverse events associated with 68Ga-PSMA-11 administration. PET-directed focal therapy alone led to a PSA drop of 50% or more in 31 of 39 (80%) patients. Conclusions and Relevance: Using blinded reads and independent lesion validation, we establish high PPV for 68Ga-PSMA-11 PET, detection rate and interreader agreement for localization of recurrent prostate cancer. Trial Registration: ClinicalTrials.gov Identifiers: NCT02940262 and NCT03353740.

FCC-hh: The Hadron Collider

Abstract: Particle physics has arrived at an important moment of its history. The discovery of the Higgs boson, with a mass of 125 GeV, completes the matrix of particles and interactions that has constituted the “Standard Model” for several decades. This model is a consistent and predictive theory, which has so far proven successful at describing all phenomena accessible to collider experiments. However, several experimental facts do require the extension of the Standard Model and explanations are needed for observations such as the abundance of matter over antimatter, the striking evidence for dark matter and the non-zero neutrino masses. Theoretical issues such as the hierarchy problem, and, more in general, the dynamical origin of the Higgs mechanism, do likewise point to the existence of physics beyond the Standard Model. This report contains the description of a novel research infrastructure based on a highest-energy hadron collider with a centre-of-mass collision energy of 100 TeV and an integrated luminosity of at least a factor of 5 larger than the HL-LHC. It will extend the current energy frontier by almost an order of magnitude. The mass reach for direct discovery will reach several tens of TeV, and allow, for example, to produce new particles whose existence could be indirectly exposed by precision measurements during the earlier preceding e+e– collider phase. This collider will also precisely measure the Higgs self-coupling and thoroughly explore the dynamics of electroweak symmetry breaking at the TeV scale, to elucidate the nature of the electroweak phase transition. WIMPs as thermal dark matter candidates will be discovered, or ruled out. As a single project, this particle collider infrastructure will serve the world-wide physics community for about 25 years and, in combination with a lepton collider (see FCC conceptual design report volume 2), will provide a research tool until the end of the 21st century. Collision energies beyond 100 TeV can be considered when using high-temperature superconductors. The European Strategy for Particle Physics (ESPP) update 2013 stated “To stay at the forefront of particle physics, Europe needs to be in a position to propose an ambitious post-LHC accelerator project at CERN by the time of the next Strategy update”. The FCC study has implemented the ESPP recommendation by developing a long-term vision for an “accelerator project in a global context”. This document describes the detailed design and preparation of a construction project for a post-LHC circular energy frontier collider “in collaboration with national institutes, laboratories and universities worldwide”, and enhanced by a strong participation of industrial partners. Now, a coordinated preparation effort can be based on a core of an ever-growing consortium of already more than 135 institutes worldwide. The technology for constructing a high-energy circular hadron collider can be brought to the technology readiness level required for constructing within the coming ten years through a focused R&D programme. The FCC-hh concept comprises in the baseline scenario a power-saving, low-temperature superconducting magnet system based on an evolution of the Nb3Sn technology pioneered at the HL-LHC, an energy-efficient cryogenic refrigeration infrastructure based on a neon-helium (Nelium) light gas mixture, a high-reliability and low loss cryogen distribution infrastructure based on Invar, high-power distributed beam transfer using superconducting elements and local magnet energy recovery and re-use technologies that are already gradually introduced at other CERN accelerators. On a longer timescale, high-temperature superconductors can be developed together with industrial partners to achieve an even more energy efficient particle collider or to reach even higher collision energies.The re-use of the LHC and its injector chain, which also serve for a concurrently running physics programme, is an essential lever to come to an overall sustainable research infrastructure at the energy frontier. Strategic R&D for FCC-hh aims at minimising construction cost and energy consumption, while maximising the socio-economic impact. It will mitigate technology-related risks and ensure that industry can benefit from an acceptable utility. Concerning the implementation, a preparatory phase of about eight years is both necessary and adequate to establish the project governance and organisation structures, to build the international machine and experiment consortia, to develop a territorial implantation plan in agreement with the host-states’ requirements, to optimise the disposal of land and underground volumes, and to prepare the civil engineering project. Such a large-scale, international fundamental research infrastructure, tightly involving industrial partners and providing training at all education levels, will be a strong motor of economic and societal development in all participating nations. The FCC study has implemented a set of actions towards a coherent vision for the world-wide high-energy and particle physics community, providing a collaborative framework for topically complementary and geographically well-balanced contributions. This conceptual design report lays the foundation for a subsequent infrastructure preparatory and technical design phase.

Vascular dysfunction-The disregarded partner of Alzheimer's disease

Abstract: Increasing evidence recognizes Alzheimer's disease (AD) as a multifactorial and heterogeneous disease with multiple contributors to its pathophysiology, including vascular dysfunction. The recently updated AD Research Framework put forth by the National Institute on Aging-Alzheimer's Association describes a biomarker-based pathologic definition of AD focused on amyloid, tau, and neuronal injury. In response to this article, here we first discussed evidence that vascular dysfunction is an important early event in AD pathophysiology. Next, we examined various imaging sequences that could be easily implemented to evaluate different types of vascular dysfunction associated with, and/or contributing to, AD pathophysiology, including changes in blood-brain barrier integrity and cerebral blood flow. Vascular imaging biomarkers of small vessel disease of the brain, which is responsible for >50% of dementia worldwide, including AD, are already established, well characterized, and easy to recognize. We suggest that these vascular biomarkers should be incorporated into the AD Research Framework to gain a better understanding of AD pathophysiology and aid in treatment efforts.

FCC Physics Opportunities: Future Circular Collider Conceptual Design Report Volume 1

Abstract: We review the physics opportunities of the Future Circular Collider, covering its e+e-, pp, ep and heavy ion programmes. We describe the measurement capabilities of each FCC component, addressing the study of electroweak, Higgs and strong interactions, the top quark and flavour, as well as phenomena beyond the Standard Model. We highlight the synergy and complementarity of the different colliders, which will contribute to a uniquely coherent and ambitious research programme, providing an unmatchable combination of precision and sensitivity to new physics.

Heterochromatin drives compartmentalization of inverted and conventional nuclei

Abstract: The nucleus of mammalian cells displays a distinct spatial segregation of active euchromatic and inactive heterochromatic regions of the genome1,2. In conventional nuclei, microscopy shows that euchromatin is localized in the nuclear interior and heterochromatin at the nuclear periphery1,2. Genome-wide chromosome conformation capture (Hi-C) analyses show this segregation as a plaid pattern of contact enrichment within euchromatin and heterochromatin compartments3, and depletion between them. Many mechanisms for the formation of compartments have been proposed, such as attraction of heterochromatin to the nuclear lamina2,4, preferential attraction of similar chromatin to each other1,4–12, higher levels of chromatin mobility in active chromatin13–15 and transcription-related clustering of euchromatin16,17. However, these hypotheses have remained inconclusive, owing to the difficulty of disentangling intra-chromatin and chromatin–lamina interactions in conventional nuclei18. The marked reorganization of interphase chromosomes in the inverted nuclei of rods in nocturnal mammals19,20 provides an opportunity to elucidate the mechanisms that underlie spatial compartmentalization. Here we combine Hi-C analysis of inverted rod nuclei with microscopy and polymer simulations. We find that attractions between heterochromatic regions are crucial for establishing both compartmentalization and the concentric shells of pericentromeric heterochromatin, facultative heterochromatin and euchromatin in the inverted nucleus. When interactions between heterochromatin and the lamina are added, the same model recreates the conventional nuclear organization. In addition, our models allow us to rule out mechanisms of compartmentalization that involve strong euchromatin interactions. Together, our experiments and modelling suggest that attractions between heterochromatic regions are essential for the phase separation of the active and inactive genome in inverted and conventional nuclei, whereas interactions of the chromatin with the lamina are necessary to build the conventional architecture from these segregated phases. Attractions between heterochromatic regions are essential for phase separation of the active and inactive genome in inverted and conventional nuclei, whereas chromatin–lamina interactions are necessary to build the conventional genomic architecture from these segregated phases.

Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences

Abstract: Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

Atomic force microscopy-based mechanobiology

Abstract: Mechanobiology emerges at the crossroads of medicine, biology, biophysics and engineering and describes how the responses of proteins, cells, tissues and organs to mechanical cues contribute to development, differentiation, physiology and disease. The grand challenge in mechanobiology is to quantify how biological systems sense, transduce, respond and apply mechanical signals. Over the past three decades, atomic force microscopy (AFM) has emerged as a key platform enabling the simultaneous morphological and mechanical characterization of living biological systems. In this Review, we survey the basic principles, advantages and limitations of the most common AFM modalities used to map the dynamic mechanical properties of complex biological samples to their morphology. We discuss how mechanical properties can be directly linked to function, which has remained a poorly addressed issue. We outline the potential of combining AFM with complementary techniques, including optical microscopy and spectroscopy of mechanosensitive fluorescent constructs, super-resolution microscopy, the patch clamp technique and the use of microstructured and fluidic devices to characterize the 3D distribution of mechanical responses within biological systems and to track their morphology and functional state. Mechanobiology describes how biological systems respond to mechanical stimuli. This Review surveys basic principles, advantages and limitations of applying and combining atomic force microscopy-based modalities with complementary techniques to characterize the morphology, mechanical properties and functional response of complex biological systems to mechanical cues.

Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family

Abstract: Bacteria within family S24-7 (phylum Bacteroidetes) are dominant in the mouse gut microbiota and detected in the intestine of other animals. Because they had not been cultured until recently and the family classification is still ambiguous, interaction with their host was difficult to study and confusion still exists regarding sequence data annotation. We investigated family S24-7 by combining data from large-scale 16S rRNA gene analysis and from functional and taxonomic studies of metagenomic and cultured species. A total of 685 species was inferred by full-length 16S rRNA gene sequence clustering. While many species could not be assigned ecological habitats (93,045 samples analyzed), the mouse was the most commonly identified host (average of 20% relative abundance and nine co-occurring species). Shotgun metagenomics allowed reconstruction of 59 molecular species, of which 34 were representative of the 16S rRNA gene-derived species clusters. In addition, cultivation efforts allowed isolating five strains representing three species, including two novel taxa. Genome analysis revealed that S24-7 spp. are functionally distinct from neighboring families and versatile with respect to complex carbohydrate degradation. We provide novel data on the diversity, ecology, and description of bacterial family S24-7, for which the name Muribaculaceae is proposed.