EarthN: A new Earth System Nitrogen Model

The amount of nitrogen in the atmosphere, oceans, crust, and mantle have important ramifications for Earth's biologic and geologic history. Despite this importance, the history and cycling of nitrogen in the Earth system is poorly constrained over time. For example, various models and proxies contrastingly support atmospheric mass stasis, net outgassing, or net ingassing over time. In addition, the amount available to and processing of nitrogen by organisms is intricately linked with and provides feedbacks on oxygen and nutrient cycles. To investigate the Earth system nitrogen cycle over geologic history, we have constructed a new nitrogen cycle model: EarthN. This model is driven by mantle cooling, links biologic nitrogen cycling to phosphate and oxygen, and incorporates geologic and biologic fluxes. Model output is consistent with large (2-4x) changes in atmospheric mass over time, typically indicating atmospheric drawdown and nitrogen sequestration into the mantle and continental crust. Critical controls on nitrogen distribution include mantle cooling history, weathering, and the total Bulk Silicate Earth+atmosphere nitrogen budget. Linking the nitrogen cycle to phosphorous and oxygen levels, instead of carbon as has been previously done, provides new and more dynamic insight into the history of nitrogen on the planet.Comment: 36 pages, 12 figure

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

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 Verhütung 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

Large-scale database mining reveals hidden trends and future directions for cancer immunotherapy

LLC Cancer immunotherapy has fundamentally changed the landscape of oncology in recent years and significant resources are invested into immunotherapy research. It is in the interests of researchers and clinicians to identify promising and less promising trends in this field in order to rationally allocate resources. This requires a quantitative large-scale analysis of cancer immunotherapy related databases. We developed a novel tool for text mining, statistical analysis and data visualization of scientific literature data. We used this tool to analyze 72002 cancer immunotherapy publications and 1469 clinical trials from public databases. All source codes are available under an open access license. The contribution of specific topics within the cancer immunotherapy field has markedly shifted over the years. We show that the focus is moving from cell-based therapy and vaccination towards checkpoint inhibitors, with these trends reaching statistical significance. Rapidly growing subfields include the combination of chemotherapy with checkpoint blockade. Translational studies have shifted from hematological and skin neoplasms to gastrointestinal and lung cancer and from tumor antigens and angiogenesis to tumor stroma and apoptosis. This work highlights the importance of unbiased large-scale database mining to assess trends in cancer research and cancer immunotherapy in particular. Researchers, clinicians and funding agencies should be aware of quantitative trends in the immunotherapy field, allocate resources to the most promising areas and find new approaches for currently immature topics

The Assessment of Elastic Follow-Up Effects on Cyclic Accumulation of Inelastic Strain Under Displacement-Control Loading

Assessment of strain accumulation due to nonlinear events like creep, plasticity or ratcheting phenomenon has gained importance, as it causes an increase in creep and fatigue damage in structures. Some factors such as the magnitude of loading, constitutive equations or the elastic regions around the nonlinear events have an effect on the rate of strain accumulation. The elastic follow-up can explain the mechanism of plastic strain accumulation. This phenomenon may occur when a mechanical structure with elastic manner is connected to nonlinear events. In cyclic loading with nonzero mean stress, the plastic strain may be accumulated. This behavior is known as ratcheting and usually takes place under cyclic load-control conditions. A new simplified method is proposed in this paper in order to assess the effects of elastic follow-up on the strain accumulation (ratcheting) behavior of two-plate model made up of AISI 1045 steel under displacement-control loading, and a set of experimental tests is conducted to verify this method. The tests were carried out by a servo-hydraulic Zwick–Roell machine. The test results confirm the accuracy of the proposed method and also reveal that in the presence of EFU in the system, the cyclic accumulation of plastic strain in addition to the load-control conditions may occur locally in the displacement-control conditions.<br/

Hf–Zr anomalies in clinopyroxene from mantle xenoliths from France and Poland: implications for Lu–Hf dating of spinel peridotite lithospheric mantle

Clinopyroxenes in some fresh anhydrous spinel peridotite mantle xenoliths from the northern Massif Central (France) and Lower Silesia (Poland), analysed for a range of incompatible trace elements by laser ablation inductively coupled plasma mass spectrometry, show unusually strong negative anomalies in Hf and Zr relative to adjacent elements Sm and Nd, on primitive mantle-normalised diagrams. Similar Zr–Hf anomalies have only rarely been reported from clinopyroxene in spinel peridotite mantle xenoliths worldwide, and most are not as strong as the examples reported here. Low Hf contents give rise to a wide range of Lu/Hf ratios, which over geological time would result in highly radiogenic εHf values, decoupling them from εNd ratios. The high 176Lu/177Hf could in theory produce an isochronous relationship with 176Hf/177Hf over time; an errorchron is shown by clinopyroxene from mantle xenoliths from the northern Massif Central. However, in a review of the literature, we show that most mantle spinel peridotites do not show such high Lu/Hf ratios in their constituent clinopyroxenes, because they lack the distinctive Zr–Hf anomaly, and this limits the usefulness of the application of the Lu–Hf system of dating to garnet-free mantle rocks. Nevertheless, some mantle xenoliths from Poland or the Czech Republic may be amenable to Hf-isotope dating in the future

Th Inducing POZ-Kruppel Factor (ThPOK) Is a Key Regulator of the Immune Response since the Early Steps of Colorectal Carcinogenesis

We purposed to evaluate the role of Th inducing POZ-Kruppel Factor (ThPOK), a transcriptional regulator of T cell fate, in tumour-induced immune system plasticity in colorectal carcinogenesis. The amounts of CD4+, CD8+ and CD56+ and ThPOK+ cells infiltrate in normal colorectal mucosa (NM), in dysplastic aberrant crypt foci (microadenomas, MA), the earliest detectable lesions in colorectal carcinogenesis, and in colorectal carcinomas (CRC), were measured, and the colocalization of ThPOK with the above-mentioned markers of immune cells was evaluated using confocal microscopy. Interestingly, ThPOK showed a prominent increase since MA. A strong colocalization of ThPOK with CD4 both in NM and in MA was observed, weaker in carcinomas. Surprisingly, there was a peak in the colocalization levels of ThPOK with CD8 in MA, which was evident, although to a lesser extent, in carcinomas, too. In conclusion, according to the data of the present study, ThPOK may be considered a central regulator of the earliest events in the immune system during colorectal cancer development, decreasing the immune response against cancer cells

Perceiving societal pressure to be happy is linked to poor well-being, especially in happy nations

Happiness is a valuable experience, and societies want their citizens to be happy. Although this societal commitment seems laudable, overly emphasizing positivity (versus negativity) may create an unattainable emotion norm that ironically compromises individual well-being. In this multi-national study (40 countries; 7443 participants), we investigate how societal pressure to be happy and not sad predicts emotional, cognitive and clinical indicators of well-being around the world, and examine how these relations differ as a function of countries’ national happiness levels (collected from the World Happiness Report). Although detrimental well-being associations manifest for an average country, the strength of these relations varies across countries. People’s felt societal pressure to be happy and not sad is particularly linked to poor well-being in countries with a higher World Happiness Index. Although the cross-sectional nature of our work prohibits causal conclusions, our findings highlight the correlational link between social emotion valuation and individual well-being, and suggest that high national happiness levels may have downsides for some.info:eu-repo/semantics/publishedVersio

High economic inequality is linked to greater moralization

Throughout the 21st century, economic inequality is predicted to increase as we face new challenges, from changes in the technological landscape to the growing climate crisis. It is crucial we understand how these changes in inequality may affect how people think and behave. We propose that economic inequality threatens the social fabric of society, in turn increasing moralization—that is, the greater tendency to employ or emphasize morality in everyday life—as an attempt to restore order and control. Using longitudinal data from X, formerly known as Twitter, our first study demonstrates that high economic inequality is associated with greater use of moral language online (e.g. the use of words such as “disgust”, “hurt”, and “respect’). Study 2 then examined data from 41 regions around the world, generally showing that higher inequality has a small association with harsher moral judgments of people's everyday actions. Together these findings demonstrate that economic inequality is linked to the tendency to see the world through a moral lens.info:eu-repo/semantics/publishedVersio

Automatic Tumor-Stroma Separation in Fluorescence TMAs Enables the Quantitative High-Throughput Analysis of Multiple Cancer Biomarkers

The upcoming quantification and automation in biomarker based histological tumor evaluation will require computational methods capable of automatically identifying tumor areas and differentiating them from the stroma. As no single generally applicable tumor biomarker is available, pathology routinely uses morphological criteria as a spatial reference system. We here present and evaluate a method capable of performing the classification in immunofluorescence histological slides solely using a DAPI background stain. Due to the restriction to a single color channel this is inherently challenging. We formed cell graphs based on the topological distribution of the tissue cell nuclei and extracted the corresponding graph features. By using topological, morphological and intensity based features we could systematically quantify and compare the discrimination capability individual features contribute to the overall algorithm. We here show that when classifying fluorescence tissue slides in the DAPI channel, morphological and intensity based features clearly outpace topological ones which have been used exclusively in related previous approaches. We assembled the 15 best features to train a support vector machine based on Keratin stained tumor areas. On a test set of TMAs with 210 cores of triple negative breast cancers our classifier was able to distinguish between tumor and stroma tissue with a total overall accuracy of 88%. Our method yields first results on the discrimination capability of features groups which is essential for an automated tumor diagnostics. Also, it provides an objective spatial reference system for the multiplex analysis of biomarkers in fluorescence immunohistochemistry