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This article explores the connection between the Heng Xian and the Changes of Zhou tradition, especially the “Tuan” and “Attached Verbalizations” commentaries. Two important Heng Xian terms— heng 恆 and fu 復—are also Changes of Zhou hexagrams and possible connections are explored. Second, the Heng Xian account of the creation of names is compared with the “Attached Verbalizations” account of the creation of the Changes of Zhou system. Third, the roles played by knowing and desire in both Heng Xian and the Changes of Zhou tradition are explored, with particular focus on potential points of similarity. Finally, insights gained through these comparisons are used to interpret the Heng Xian advice on initiating action.

The following translation represents a single, synthetic interpretation that considered the proposals, suggestions, and discussions not only of the three translators mentioned, but of everyone present at the Heng Xian workshop held at the Pennsylvania State University in late 2010. Committed to the goal of presenting a single, coherent perspective, one that made philosophical sense of the various cosmological concepts presented, the three translators made their final selections according to a majority rules approach.

The development and implementation of measures aimed at climate change adaptation face many obstacles. This Perspective takes stock of current research on barriers to adaptation, and argues that more comparative research is now required to increase our in-depth understanding of barriers and to develop strategies to overcome them. The concept of barriers is increasingly used to describe the obstacles that hinder the planning and implementation of climate change adaptation. The growing literature on barriers to adaptation reveals not only commonly reported barriers, but also conflicting evidence, and few explanations of why barriers exist and change. There is thus a need for research that focuses on the interdependencies between barriers and considers the dynamic ways in which barriers develop and persist. Such research, which would be actor-centred and comparative, would help to explain barriers to adaptation and provide insights into how to overcome them.

The hydrothermal alteration of mantle rocks (referred to as serpentinization) occurs in submarine environments extending from mid-ocean ridges to subduction zones. Serpentinization affects the physical and chemical properties of oceanic lithosphere, represents one of the major mechanisms driving mass exchange between the mantle and the Earth’s surface, and is central to current origin of life hypotheses as well as the search for microbial life on the icy moons of Jupiter and Saturn. In spite of increasing interest in the serpentinization process by researchers in diverse fields, the rates of serpentinization and the controlling factors are poorly understood. Here we use a novel in situ experimental method involving olivine micro-reactors and show that the rate of serpentinization is strongly controlled by the salinity (water activity) of the reacting fluid and demonstrate that the rate of serpentinization of olivine slows down as salinity increases and H 2 O activity decreases. Serpentinization of mantle rocks occurs in a variety of tectonic settings, but the controls on the rates of serpentinization are poorly constrained. Here, the authors developed an in situ experimental method to show that the rate of serpentinization is strongly controlled by the salinity of the reacting fluid.

Many tumors evolve sophisticated strategies to evade the immune system, and these represent major obstacles for efficient antitumor immune responses. Here we explored a molecular mechanism of metabolic communication deployed by highly glycolytic tumors for immunoevasion. In contrast to colon adenocarcinomas, melanomas showed comparatively high glycolytic activity, which resulted in high acidification of the tumor microenvironment. This tumor acidosis induced Gprotein–coupled receptor–dependent expression of the transcriptional repressor ICER in tumor-associated macrophages that led to their functional polarization toward a non-inflammatory phenotype and promoted tumor growth. Collectively, our findings identify a molecular mechanism of metabolic communication between non-lymphoid tissue and the immune system that was exploited by high-glycolytic-rate tumors for evasion of the immune system. Tumors can vary in both their control by immunosurveillance and their glycolytic activity. Bopp and colleagues demonstrate that highly glycolytic tumors acidify their microenvironment and use this to initiate a mechanism of localized immunosuppression.

Global DNA hypomethylation is a major event for the development and progression of cancer, although the significance in thyroid cancer remains unclear. Therefore, we aimed to investigate its role in thyroid cancer progression and its potential as a prognostic marker. Global hypomethylation of Alu repeats was used as a surrogate marker for DNA global hypomethylation, and was assessed using the Quantification of Unmethylated Alu technique. Mutations in BRAF and RAS were determined by Sanger sequencing. Ninety primary thyroid tumors were included [28 low-risk differentiated thyroid cancer (DTC), 13 pediatric DTC, 33 distant metastatic DTC, 7 poorly differentiated thyroid cancer (PDTC), and 9 anaplastic thyroid cancer (ATC)], as well as 24 distant metastases and 20 normal thyroid tissues. An increasing hypomethylation was found for distant metastatic DTC [median, 4.0; interquartile range (IQR), 3.1 to 6.2] and PDTC/ATC (median, 9.3; IQR, 7.0 to 12.1) as compared with normal thyroid tissue (median, 2.75; IQR, 2.30 to 3.15), whereas low-risk and pediatric DTC were not affected by hypomethylation. Alu hypomethylation was similar between distant metastases and matched primary tumors. Within distant metastatic DTC, Alu hypomethylation was increased in BRAF vs RAS mutated tumors. Kaplan-Meier and Cox regression analyses showed that thyroid cancer-related and all-cause mortality were associated with tumor hypomethylation, but this association was lost after adjustment for thyroid cancer risk category. Distant metastatic DTC, PDTC, and ATC were increasingly affected by global Alu hypomethylation, suggesting that this epigenetic entity may be involved in thyroid cancer progression and dedifferentiation.

Ischaemic heart disease evokes a complex immune response. However, tools to track the systemic behaviour and dynamics of leukocytes non-invasively in vivo are lacking. Here, we present a multimodal hot-spot imaging approach using an innovative high-density lipoprotein-derived nanotracer with a perfluoro-crown ether payload (19F-HDL) to allow myeloid cell tracking by 19F magnetic resonance imaging. The 19F-HDL nanotracer can additionally be labelled with zirconium-89 and fluorophores to detect myeloid cells by in vivo positron emission tomography imaging and optical modalities, respectively. Using our nanotracer in atherosclerotic mice with myocardial infarction, we observed rapid myeloid cell egress from the spleen and bone marrow by in vivo 19F-HDL magnetic resonance imaging. Concurrently, using ex vivo techniques, we showed that circulating pro-inflammatory myeloid cells accumulated in atherosclerotic plaques and at the myocardial infarct site. Our multimodality imaging approach is a valuable addition to the immunology toolbox, enabling the study of complex myeloid cell behaviour dynamically.A multimodal imaging approach using a high-density lipoprotein-derived nanotracer with a perfluoro-crown ether payload enables myeloid cell dynamics to be studied in vivo in mouse models of atherosclerosis and myocardial infarction.

•We evaluated grand challenges on machine learning and neuroimaging in dementia.•The seven challenges were complementary regarding clinical questions and tasks.•Statistical analysis of factors improving performance could improve future challenges.•Impact would increase by clinical questions and data beyond Alzheimer’s disease.•Grand challenges provide an opportunity for cross-cohort performance evaluation. Machine learning methods exploiting multi-parametric biomarkers, especially based on neuroimaging, have huge potential to improve early diagnosis of dementia and to predict which individuals are at-risk of developing dementia. To benchmark algorithms in the field of machine learning and neuroimaging in dementia and assess their potential for use in clinical practice and clinical trials, seven grand challenges have been organized in the last decade: MIRIAD (2012), Alzheimer’s Disease Big Data DREAM (2014), CADDementia (2014), Machine Learning Challenge (2014), MCI Neuroimaging (2017), TADPOLE (2017), and the Predictive Analytics Competition (2019). Based on two challenge evaluation frameworks, we analyzed how these grand challenges are complementing each other regarding research questions, datasets, validation approaches, results and impact. The seven grand challenges addressed questions related to screening, clinical status estimation, prediction and monitoring in (pre-clinical) dementia. There was little overlap in clinical questions, tasks and performance metrics. Whereas this aids providing insight on a broad range of questions, it also limits the validation of results across challenges. The validation process itself was mostly comparable between challenges, using similar methods for ensuring objective comparison, uncertainty estimation and statistical testing. In general, winning algorithms performed rigorous data pre-processing and combined a wide range of input features. Despite high state-of-the-art performances, most of the methods evaluated by the challenges are not clinically used. To increase impact, future challenges could pay more attention to statistical analysis of which factors (i.e., features, models) relate to higher performance, to clinical questions beyond Alzheimer’s disease, and to using testing data beyond the Alzheimer’s Disease Neuroimaging Initiative. Grand challenges would be an ideal venue for assessing the generalizability of algorithm performance to unseen data of other cohorts. Key for increasing impact in this way are larger testing data sizes, which could be reached by sharing algorithms rather than data to exploit data that cannot be shared. Given the potential and lessons learned in the past ten years, we are excited by the prospects of grand challenges in machine learning and neuroimaging for the next ten years and beyond.

Introduction Patients with diffuse glioma often experience neurocognitive impairment already prior to surgery. Pertinent information on whether damage to a specific brain region due to tumor activity results in neurocognitive impairment or not, is relevant in clinical decision-making, and at the same time renders unique information on brain lesion location and functioning relationships. To examine the impact of tumor location on preoperative neurocognitive functioning (NCF), we performed MRI based lesion-symptom mapping. Methods Seventy-two patients (mean age 40 years) with a radiologically suspected glioma were recruited preoperatively. For each of the six cognitive domains tested, we used tumor localization maps and voxel-based lesion-symptom mapping analyses to identify cortical and subcortical regions associated with NCF impairment. Results Compared to healthy controls, preoperative NCF was significantly impaired in all cognitive domains. Most frequently affected were attention (30% of patients) and working memory (20% of patients). Deficits in attention were significantly associated with regions in the left frontal and parietal cortex, including the precentral and parietal-opercular cortex, and in left-sided subcortical fiber tracts, including the arcuate fasciculus and corticospinal tract. Surprisingly, no regions could be related to working memory capacity. For the other neurocognitive domains, impairments were mainly associated with regions in the left hemisphere. Conclusions Prior to treatment, patients with diffuse glioma in the left hemisphere run the highest risk to have NCF deficits. Identification of a left frontoparietal network involved in NCF not only may optimize surgical procedures but may also be integrated in counseling and cognitive rehabilitation for these patients.

Subseafloor mixing of reduced hydrothermal fluids with seawater is believed to provide the energy and substrates needed to support deep chemolithoautotrophic life in the hydrated oceanic mantle (i.e., serpentinite). However, geosphere-biosphere interactions in serpentinite-hosted subseafloor mixing zones remain poorly constrained. Here we examine fossil microbial communities and fluid mixing processes in the subseafloor of a Cretaceous Lost City-type hydrothermal system at the magma-poor passive Iberia Margin (Ocean Drilling Program Leg 149, Hole 897D). Brucite–calcite mineral assemblages precipitated from mixed fluids ca. 65 m below the Cretaceous paleo-seafloor at temperatures of 31.7 ± 4.3 °C within steep chemical gradients between weathered, carbonate-rich serpentinite breccia and serpentinite. Mixing of oxidized seawater and strongly reducing hydrothermal fluid at moderate temperatures created conditions capable of supporting microbial activity. Dense microbial colonies are fossilized in brucite–calcite veins that are strongly enriched in organic carbon (up to 0.5 wt.% of the total carbon) but depleted in 13C (δ13CTOC= −19.4‰). We detected a combination of bacterial diether lipid biomarkers, archaeol, and archaeal tetraethers analogous to those found in carbonate chimneys at the active Lost City hydrothermal field. The exposure of mantle rocks to seawater during the breakup of Pangaea fueled chemolithoautotrophic microbial communities at the Iberia Margin, possibly before the onset of seafloor spreading. Lost City-type serpentinization systems have been discovered at midocean ridges, in forearc settings of subduction zones, and at continental margins. It appears that, wherever they occur, they can support microbial life, even in deep subseafloor environments.