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The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at $0.35 < z < 0.65$. It was selected from ROSAT data in the 10,000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX program on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ $lensfit$ shape measurement and perform a conservative colour-space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope $��$, normalization $��$, and scatter $��_{\ln ��| ��}$ of our richness-mass scaling relation model in log-space: $\left = ����+ ��$, with $��= \ln (M_{200c}/M_{\mathrm{piv}})$, and $M_{\mathrm{piv}} = 10^{14.81} M_{\odot}$. We find a slope $��= 0.49^{+0.20}_{-0.15}$, normalization $ \exp(��) = 84.0^{+9.2}_{-14.8}$ and $��_{\ln ��| ��} = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness-mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range ($0.0 37 pages, 12 figures

This study presents a multiparameter analysis of aerosol trends over the last 2 decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical-composition and mass aerosol properties by using the observations from several ground-based networks. From these regional time series the aerosol trends have been derived for the different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases in aerosol optical depth (AOD) are found in Europe, North America, South America, North Africa and Asia, ranging from −1.2 % yr−1 to −3.1 % yr−1. An error and representativity analysis of the spatially and temporally limited observational data has been performed using model data subsets in order to investigate how much the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of 10 models (6 AeroCom phase III models and 4 CMIP6 models) and the CAMS reanalysis dataset and of their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, the column Ångström exponent, sulfate and particulate matter well (except in North Africa), but they show larger discrepancies for coarse-mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from that depicted by solely relying on ground-based observations. Using a model with complete diagnostics (NorESM2), we find a global increase in AOD of about 0.2 % yr−1 between 2000 and 2014, primarily caused by an increase in the loads of organic aerosols, sulfate and black carbon.

© 2019 International Society for Heart and Lung Transplantation BACKGROUND: We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype (3AA)or 4-archetype (4AA)unsupervised algorithms to estimate rejection. In the present study we examined the stability of machine-learning algorithms in new biopsies, compared 3AA vs 4AA algorithms, assessed supervised binary classifiers trained on histologic or molecular diagnoses, created a report combining many scores into an ensemble of estimates, and examined possible automated sign-outs. METHODS: We studied 889 EMBs from 454 transplant recipients at 8 centers: the initial cohort (N = 331)and a new cohort (N = 558). Published 3AA algorithms derived in Cohort 331 were tested in Cohort 558, the 3AA and 4AA models were compared, and supervised binary classifiers were created. RESULTS: A‘lgorithms derived in Cohort 331 performed similarly in new biopsies despite differences in case mix. In the combined cohort, the 4AA model, including a parenchymal injury score, retained correlations with histologic rejection and DSA similar to the 3AA model. Supervised molecular classifiers predicted molecular rejection (areas under the curve [AUCs]>0.87)better than histologic rejection (AUCs <0.78), even when trained on histology diagnoses. A report incorporating many AA and binary classifier scores interpreted by 1 expert showed highly significant agreement with histology (p < 0.001), but with many discrepancies, as expected from the known noise in histology. An automated random forest score closely predicted expert diagnoses, confirming potential for automated signouts. CONCLUSIONS: Molecular algorithms are stable in new populations and can be assembled into an ensemble that combines many supervised and unsupervised estimates of the molecular disease states.

Cancer is a complex disease and the role played by innate lymphoid cells (ILCs) in cancer development has begun to be uncovered over recent years. We aim to provide an exhaustive summary of the knowledge acquired on the role of ILCs in cancer. ILCs are classified into 3 different categories, ILC1s, ILC2s, and ILC3s, each encompassing specific and unique functions. ILC1s exhibit NK cells characteristics and can exert anti-tumor functions, but surprisingly their IFNγ production is not associated with a better immune response. In response to TGF-β or IL-12, ILC1s were shown to exert pro-tumor functions and to favor tumor growth. ILC2s role in cancer immune response is dependent on cytokine context. The production of IL-13 by ILC2s is associated with a negative outcome in cancer. ILC2s can also produce IL-5, leading to eosinophil activation and an increased anti-tumor immune response in lung cancer. ILC3s produce IL-22, which could promote tumor growth. In contrast, ILC3s recognize tumor cells and facilitate leukocyte tumor entry, increasing anti-tumor immunity. In some contexts, ILC3s were found at the edge of tertiary lymphoid structures, associated with a good prognostic. We are at the dawn of our understanding of ILCs role in cancer. This review aims to thoroughly analyze existing data and to provide a comprehensive overview of our present knowledge on the impact of ILCs in cancer.

Abstract Marinesco-Sjögren syndrome is a rare human disorder caused by biallelic mutations in SIL1 characterized by cataracts in infancy, myopathy and ataxia, symptoms which are also associated with a novel disorder caused by mutations in INPP5K. While these phenotypic similarities may suggest commonalties at a molecular level, an overlapping pathomechanism has not been established yet. In this study, we present six new INPP5K patients and expand the current mutational and phenotypical spectrum of the disease showing the clinical overlap between Marinesco-Sjögren syndrome and the INPP5K phenotype. We applied unbiased proteomic profiling on cells derived from Marinesco-Sjögren syndrome and INPP5K patients and identified alterations in d-3-PHGDH as a common molecular feature. d-3-PHGDH modulates the production of l-serine and mutations in this enzyme were previously associated with a neurological phenotype, which clinically overlaps with Marinesco-Sjögren syndrome and INPP5K disease. As l-serine administration represents a promising therapeutic strategy for d-3-PHGDH patients, we tested the effect of l-serine in generated sil1, phgdh and inpp5k a+b zebrafish models, which showed an improvement in their neuronal phenotype. Thus, our study defines a core phenotypical feature underpinning a key common molecular mechanism in three rare diseases and reveals a common and novel therapeutic target for these patients.

International audience; We show how the use of graded alphabets allows one to provide simpler proofs of some results on free monoids and free Lie algebras. We first generalize to graded alphabets the characterization of the length distributions of circular codes. We also show that the existence of a circular code with a given distribution of degrees is equivalent to the existence of an embedding of Lie algebras. We finally give a generalization to graded alphabets of the famous result of Eastman on comma free codes of odd degree.

We report the results of a neutrino search in Super-Kamiokande for coincident signals with the first detected gravitational wave produced by a binary neutron star merger, GW170817, which was followed by a short gamma-ray burst, GRB170817A, and a kilonova/macronova. We searched for coincident neutrino events in the range from 3.5 MeV to $\sim$100 PeV, in a time window $\pm$500 seconds around the gravitational wave detection time, as well as during a 14-day period after the detection. No significant neutrino signal was observed for either time window. We calculated 90% confidence level upper limits on the neutrino fluence for GW170817. From the upward-going-muon events in the energy region above 1.6 GeV, the neutrino fluence limit is $16.0^{+0.7}_{-0.6}$ ($21.3^{+1.1}_{-0.8}$) cm$^{-2}$ for muon neutrinos (muon antineutrinos), with an error range of $\pm5^{\circ}$ around the zenith angle of NGC4993, and the energy spectrum is under the assumption of an index of $-2$. The fluence limit for neutrino energies less than 100 MeV, for which the emission mechanism would be different than for higher-energy neutrinos, is also calculated. It is $6.6 \times 10^7$ cm$^{-2}$ for anti-electron neutrinos under the assumption of a Fermi-Dirac spectrum with average energy of 20 MeV. 8 pages, 4 figures