Widespread phytoplankton blooms triggered by 2019–2020 Australian wildfires

Droughts and climate-change-driven warming are leading to more frequent and intense wildfires1,2,3, arguably contributing to the severe 2019–2020 Australian wildfires4. The environmental and ecological impacts of the fires include loss of habitats and the emission of substantial amounts of atmospheric aerosols5,6,7. Aerosol emissions from wildfires can lead to the atmospheric transport of macronutrients and bio-essential trace metals such as nitrogen and iron, respectively8,9,10. It has been suggested that the oceanic deposition of wildfire aerosols can relieve nutrient limitations and, consequently, enhance marine productivity11,12, but direct observations are lacking. Here we use satellite and autonomous biogeochemical Argo float data to evaluate the effect of 2019–2020 Australian wildfire aerosol deposition on phytoplankton productivity. We find anomalously widespread phytoplankton blooms from December 2019 to March 2020 in the Southern Ocean downwind of Australia. Aerosol samples originating from the Australian wildfires contained a high iron content and atmospheric trajectories show that these aerosols were likely to be transported to the bloom regions, suggesting that the blooms resulted from the fertilization of the iron-limited waters of the Southern Ocean. Climate models project more frequent and severe wildfires in many regions1,2,3. A greater appreciation of the links between wildfires, pyrogenic aerosols13, nutrient cycling and marine photosynthesis could improve our understanding of the contemporary and glacial–interglacial cycling of atmospheric CO2 and the global climate system.Analyses of satellite aerosol observations used in this study were produced with the Giovanni online data system, developed and maintained by the NASA GES DISC. We thank SeaWiFS and MODIS mission scientists and associated NASA personnel for the production of the data used in this research effort. The BGC-Argo data were collected and made freely available by the International Argo Program and the national programs that contribute to it (http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo Program is part of the Global Ocean Observing System (https://doi.org/10.17882/42182). W.T. is supported by the Harry H. Hess Postdoctoral Fellowship from Princeton University. N.C. is supported by the “Laboratoire d’Excellence” LabexMER (ANR‐10‐LABX‐19) and co-funded by a grant from the French government under the program “Investissements d’Avenir”. S.B. acknowledges the AXA Research Fund for the support of the long-term research line on Sand and Dust Storms at the Barcelona Supercomputing Center (BSC) and CAMS Global Validation (CAMS-84). P.G.S., J.L., M.M.G.P. and A.R.B. are supported by the Australian Research Council Discovery Projects scheme (DP190103504). P.G.S. and J.W. are supported by the Australian Research Council Centre of Excellence for Climate Extremes (CLEX: CE170100023). J.L. is supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 754433. A.R.B. is supported by the Australian Research Council Future Fellowship scheme (FT130100037). R.M. is supported by the CSIRO Decadal Climate Forecasting Project. We thank M. Strzelec, M. East, T. Holmes, M. Corkill, S. Meyerink and the Wellington Park Management Trust for help with installation and sampling the Tasmanian aerosol time-series station; A. Townsend for iron aerosol analyses by ICPMS at the University of Tasmania; and A. Benedetti and S. Remy for providing insights on the validation of aerosol reanalysis.Peer Reviewed"Article signat per 15 autors/es: Weiyi Tang, Joan Llort, Jakob Weis, Morgane M. G. Perron, Sara Basart, Zuchuan Li, Shubha Sathyendranath, Thomas Jackson, Estrella Sanz Rodriguez, Bernadette C. Proemse, Andrew R. Bowie, Christina Schallenberg, Peter G. Strutton, Richard Matear & Nicolas Cassar"Postprint (author's final draft

ANLN and TLE2 in Muscle Invasive Bladder Cancer: A Functional and Clinical Evaluation Based on In Silico and In Vitro Data

Anilin actin binding protein (ANLN) and transducing-like enhancer protein 2 (TLE2) are associated with cancer patient survival and progression. The impact of their gene expression on progression-free survival (PFS) of patients with muscle invasive bladder cancer (MIBC) treated with radical cystectomy (RC) and subtype association has not yet been investigated. qRT-PCR was used to measure the transcript levels of ANLN and TLE2 in the Mannheim cohort, and validated in silico by The Cancer Genome Atlas (TCGA) cohort. Uni- and multivariate Cox regression analyses identified predictors for disease-specific survival (DSS) and overall survival (OS). In the Mannheim cohort, tumors with high ANLN expression were associated with lower OS and DSS, while high TLE2 expression was associated with a favorable OS. The TCGA cohort confirmed that high ANLN and low TLE2 expression was associated with shorter OS and disease-free survival (DFS). In both cohorts, multivariate analyses showed ANLN and TLE2 expression as independent outcome predictors. Furthermore, ANLN was more highly expressed in cell lines and patients with the basal subtype, while TLE2 expression was higher in cell lines and patients with the luminal subtype. ANLN and TLE2 are promising biomarkers for individualized bladder cancer therapy including cancer subclassification and informed MIBC prognosis

Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome

Background: Tumor budding, meaning a detachment of tumor cells at the invasion front of colorectal carcinoma (CRC) into single cells or clusters (<=5 tumor cells), has been shown to correlate to an inferior clinical outcome by several independent studies. Therefore, it has been discussed as a complementary prognostic factor to the TNM staging system, and it is already included in national guidelines as an additional prognostic parameter. However, its application by manual evaluation in routine pathology is hampered due to the use of several slightly different assessment systems, a time-consuming manual counting process and a high inter-observer variability. Hence, we established and validated an automatic image processing approach to reliably quantify tumor budding in immunohistochemically (IHC) stained sections of CRC samples. Methods: This approach combines classical segmentation methods (like morphological operations) and machine learning techniques (k-means and hierarchical clustering, convolutional neural networks) to reliably detect tumor buds in colorectal carcinoma samples immunohistochemically stained for pan-cytokeratin. As a possible application, we tested it on whole-slide images as well as on tissue microarrays (TMA) from a clinically well-annotated CRC cohort. Results: Our automatic tumor budding evaluation tool detected the absolute number of tumor buds per image with a very good correlation to the manually segmented ground truth (R2 value of 0.86). Furthermore the automatic evaluation of whole-slide images from 20 CRC-patients, we found that neither the detected number of tumor buds at the invasion front nor the number in hotspots was associated with the nodal status. However, the number of spatial clusters of tumor buds (budding hotspots) significantly correlated to the nodal status (p-value = 0.003 for N0 vs. N1/N2). TMAs were not feasible for tumor budding evaluation, as the spatial relationship of tumor buds (especially hotspots) was not preserved. Conclusions: Automatic image processing is a feasible and valid assessment tool for tumor budding in CRC on whole-slide images. Interestingly, only the spatial clustering of the tumor buds in hotspots (and especially the number of hotspots) and not the absolute number of tumor buds showed a clinically relevant correlation with patient outcome in our data

Differential effects of nitrogen and sulfur deprivation on growth and biodiesel feedstock production of chlamydomonas reinhardtii

Cataloged from PDF version of article.Biodiesel production from microalgae is a promising approach for energy production; however, high cost of its process limits the use of microalgal biodiesel. Increasing the levels of triacylglycerol (TAG) levels, which is used as a biodiesel feedstock, in microalgae has been achieved mainly by nitrogen starvation. In this study, we compared effects of sulfur (S) and nitrogen (N) starvation on TAG accumulation and related parameters in wild-type Chlamydomonas reinhardtii CC-124 mt(-) and CC-125 mt(+) strains. Cell division was interrupted, protein and chlorophyll levels rapidly declined while cell volume, total neutral lipid, carotenoid, and carbohydrate content increased in response to nutrient starvation. Cytosolic lipid droplets in microalgae under nutrient starvation were monitored by three-dimensional confocal laser imaging of live cells. Infrared spectroscopy results showed that relative TAG, oligosaccharide and polysaccharide levels increased rapidly in response to nutrient starvation, especially S starvation. Both strains exhibited similar levels of regulation responses under mineral deficiency, however, the degree of their responses were significantly different, which emphasizes the importance of mating type on the physiological response of algae. Neutral lipid, TAG, and carbohydrate levels reached their peak values following 4 days of N or S starvation. Therefore, 4 days of N or S starvation provides an excellent way of increasing TAG content. Although increase in these parameters was followed by a subsequent decline in N-starved strains after 4 days, this decline was not observed in S-starved ones, which shows that S starvation is a better way of increasing TAG production of C. reinhardtii than N starvation. Biotechnol. Bioeng. 2012; 109:19471957. (c) 2012 Wiley Periodicals, In

The BrainScaleS-2 Neuromorphic Platform — A Report on the Integration and Operation of an Open Science Hardware Platform within EBRAINS

This report presents the challenges encountered and the solutions created for the operation of the BrainScaleS neuromorphic platform, and the overall progress leading to this state at the end of the Human Brain Project (HBP)

A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware.

Neuromorphic systems open up opportunities to enlarge the explorative space for computational research. However, it is often challenging to unite efficiency and usability. This work presents the software aspects of this endeavor for the BrainScaleS-2 system, a hybrid accelerated neuromorphic hardware architecture based on physical modeling. We introduce key aspects of the BrainScaleS-2 Operating System: experiment workflow, API layering, software design, and platform operation. We present use cases to discuss and derive requirements for the software and showcase the implementation. The focus lies on novel system and software features such as multi-compartmental neurons, fast re-configuration for hardware-in-the-loop training, applications for the embedded processors, the non-spiking operation mode, interactive platform access, and sustainable hardware/software co-development. Finally, we discuss further developments in terms of hardware scale-up, system usability, and efficiency

Detection of interstellar oxidaniumyl: abundant H2O+ towards the star-forming regions DR21, Sgr B2, and NGC6334

We identify a prominent absorption feature at 1115 GHz, detected in first HIFI spectra towards high-mass star-forming regions, and interpret its astrophysical origin. The characteristic hyperfine pattern of the H2O+ ground-state rotational transition, and the lack of other known low-energy transitions in this frequency range, identifies the feature as H2O+ absorption against the dust continuum background and allows us to derive the velocity profile of the absorbing gas. By comparing this velocity profile with velocity profiles of other tracers in the DR21 star-forming region, we constrain the frequency of the transition and the conditions for its formation. In DR21, the velocity distribution of H2O+ matches that of the [CII] line at 158\mu\m and of OH cm-wave absorption, both stemming from the hot and dense clump surfaces facing the HII-region and dynamically affected by the blister outflow. Diffuse foreground gas dominates the absorption towards Sgr B2. The integrated intensity of the absorption line allows us to derive lower limits to the H2O+ column density of 7.2e12 cm^-2 in NGC 6334, 2.3e13 cm^-2 in DR21, and 1.1e15 cm^-2 in Sgr B2.Comment: Accepted for publication in A&

In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer.

Despite the fact that the local immunological microenvironment shapes the prognosis of colorectal cancer, immunotherapy has shown no benefit for the vast majority of colorectal cancer patients. A better understanding of the complex immunological interplay within the microenvironment is required. In this study, we utilized wet lab migration experiments and quantitative histological data of human colorectal cancer tissue samples (n = 20) including tumor cells, lymphocytes, stroma, and necrosis to generate a multiagent spatial model. The resulting data accurately reflected a wide range of situations of successful and failed immune surveillance. Validation of simulated tissue outcomes on an independent set of human colorectal cancer specimens (n = 37) revealed the model recapitulated the spatial layout typically found in human tumors. Stroma slowed down tumor growth in a lymphocyte-deprived environment but promoted immune escape in a lymphocyte-enriched environment. A subgroup of tumors with less stroma and high numbers of immune cells showed high rates of tumor control. These findings were validated using data from colorectal cancer patients (n = 261). Low-density stroma and high lymphocyte levels showed increased overall survival (hazard ratio 0.322, P = 0.0219) as compared with high stroma and high lymphocyte levels. To guide immunotherapy in colorectal cancer, simulation of immunotherapy in preestablished tumors showed that a complex landscape with optimal stroma permeabilization and immune cell activation is able to markedly increase therapy response in silico These results can help guide the rational design of complex therapeutic interventions, which target the colorectal cancer microenvironment. Cancer Res; 77(22); 6442-52. (c)2017 AACR