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This dataset is composed of CT pulmonary angiograms and annotations related to pulmonary embolism. It is available at https://www.rsna.org/education/ai-resources-and-training/ai-image-challenge/rsn...

Nos últimos anos, o desenvolvimento do pensamento algébrico ganha terreno em vários currículos dos anos iniciais, como é o caso da Austrália (MULLIGAN; CAVANAGH; KEANAN-BROWN, 2012) e dos Estados-Unidos. Essa ênfase se deve a uma corrente chamada Early Algebra que se interessa pelo desenvolvimento do pensamento algébrico desde a infância (BLANTON; KAPUT, 2011; CAI; KNUTH, 2011a; CARRAHER; SCHLIEMANN, 2007). No Brasil, o novo programa – BNCC (BRASIL, 2017) integra, de maneira explícita, o desenvolvimento de pensamento algébrico desde o 1º ano do ensino fundamental. Assim, para entender como esse desenvolvimento é contemplado na BNCC, esse artigo propõe analisar as tarefas prescritas na seção Álgebra da BNCC para o desenvolvimento do pensamento algébrico do 1° ao 5° ano do ensino fundamental, do ponto de vista da dupla abordagem didática e ergonómica (ROBERT; ROGALSKI, 2002). Para tal, fizemos uma pesquisa documental que teve como fonte a BNCC publicada em 2017. Uma análise qualitativa foi estruturada sobre os tipos de tarefas solicitadas e as variáveis associadas a cada uma das tarefas na unidade temática álgebra do 1° ao 5° ano. Os resultados mostram que a BNCC propõe uma trajetória rica e diversificada de tarefas, mobilizando diferentes variáveis que promoverão o desenvolvimento do pensamento algébrico..

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

Background: Bubonic plague is amongst the diseases with the highest potential for being used in biological warfare attacks today. This disease, caused by the bacterium Yersina pestis, is highly infectious and can achieve 100% of fatal victims when in its most dangerous form. Besides, there is no effective vaccine, and the chemotherapy available today against plague is ineffective if not administered at the beginning of the infection. Objective: Willing to contribute for changing this reality we propose here new phenylureas as candidates for the drug design against plague meant to target the enzyme dihydrofolate reductase from Y. pestis (YpDHFR). Methods: Seven phenylureas, four of them new, were synthesized, following synthetic routes adapted from procedures available in the literature, and using microwave irradiation. After, they were submitted to docking studies inside YpDHFR and human DHFR (HssDHFR) in order to check their potential as selective inhibitors. Results: Our results revealed four new phenylureas and a new synthetic route for this kind of molecule using microwave irradiation. Also, our docking studies showed that these compounds are capable of binding to both HssDHFR and YpDHFR, with U1 - U4 and U23 showing more selectivity for HssDHFR and U7, U8 being more selective towards YpDHFR. Conclusion: We reported the synthesis with good yields of seven phenylureas, following a simple and clean alternative synthetic route using microwave irradiation. Further molecular docking studies of our compounds suggested that two are capable of binding more selectivity to YpDHFR, qualifying as potential candidates for the drug design of new drugs against plague.

Insufficient epigenetic reprogramming is incompatible with normal development of embryos produced by somatic cell nuclear transfer (SCNT), but treatment with histone deacetylases inhibitors (HDACi) enhances development of SCNT embryos. However, the mechanisms underpinning HDACi benefits in SCNT embryos remain largely uncharacterized. We hypothesized that, in addition to enhancing reprogramming, HDACi treatment may promote expression of genes not required for early development of SCNT embryos. To test this hypothesis, RNA synthesis was inhibited by treating bovine SCNT embryos with 5,6-dichlorobenzimidazole 1-β-D-ribofuranoside (DBR), which were concomitantly treated or not with Scriptaid (Scrip; an HDACi). Development to the blastocyst stage was significantly increased by treatment with Scrip alone (26.6%) or associated with DRB (28.6%) compared to Control (17.9%). The total number of nuclei was significantly improved only in embryos that were treated with both Scrip + DRB. Nuclear decondensation after SCNT was significantly increased by DRB treatment either alone or associated with Scrip. The relative mRNA expression, evaluated during the embryo genome activation (EGA) transition, revealed that some KDMs (KDM1A, KDM3A, KDM4C and KDM6A) and DNMT1 where prematurely expressed in Scrip-treated embryos. However, treatment with Scrip + DRB inhibited early mRNA expression of those genes, as well as several other KDMs (KDM4A, KDM4B, KDM5A, KDM5B, KDM5C and KDM7A) compared to embryos treated with Scrip alone. These findings revealed that HDACi improved development in SCNT embryos compared to Control, but altered the expression of genes involved in epigenetic regulation and did not improve embryo quality. Inhibition of RNA synthesis during HDACi treatment enhanced nuclear chromatin decondensation, modulated gene expression and improved SCNT embryo quality.

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.

International audience; We investigated gene expression patterns in whole blood and fecal microbiota profile as potential predictors of immune response to vaccination, using healthy M. hyopneumoniae infection free piglets (n = 120). Eighty piglets received a dose of prophylactic antibiotics during the first two days of life, whereas the remaining 40 did not. Blood samples for RNA-Seq analysis were collected on experimental Day 0 (D0; 28 days of age) just prior to vaccination, D2, and D6 post-vaccination. A booster vaccine was given at D24. Fecal samples for microbial 16SrRNA sequencing were collected at 7 days of age, and at D0 and D35 post-vaccination. Pigs were ranked based on the levels of M. hyopneumoniae-specific antibodies in serum samples collected at D35, and groups of 'high' (HR) and 'low' (LR) responder pigs (n = 15 each) were selected. Prophylactic antibiotics did not influence antibody titer levels and differential expression analysis did not reveal differences between HR and LR at any time-point (FDR > 0.05); however, based on functional annotation with Ingenuity Pathway Analysis, D2 post-vaccination, HR pigs were enriched for biological terms relating to increased activation of immune cells. In contrast, the immune activation decreased in HR, 6 days post-vaccination. No significant differences were observed prior to vaccination (D0). Two days post-vaccination, multivariate analysis revealed that ADAM8, PROSER3, B4GALNT1, MAP7D1, SPP1, HTRA4, and ENO3 genes were the most promising potential biomarkers. At D0, OTUs annotated to Prevotella, CF21, Bacteroidales and S24-7 were more abundant in HR, whereas Fibrobacter, Paraprevotella, Anaerovibrio, [Prevotella], YRC22, and Helicobacter positively correlated with the antibody titer as well as MYL1, SPP1, and ENO3 genes. Our study integrates gene differential expression and gut microbiota to predict vaccine response in pigs. The results indicate that post-vaccination gene-expression and early-life gut microbiota profile could potentially predict vaccine response in pigs, and inform a direction for future research.

Understanding how populations of microbial pathogens and arthropod pests develop over time is critical for timely and effective intervention to control disease epidemics and pest infestations in agricultural production systems. Various elements including the pathogen or pest, host plant, natural enemies or competitors, environment, and human activity interact in complex ways, and some of these elements can be factored into mathematical models for pest population increase and disease progress. Greenhouse production affords a level of control over climate and growth environment, as well as the opportunity to release biological control agents, and thus the potential to influence pathogen and arthropod pest populations and their development to a much greater degree than in field production. To this end, thresholds for intervention must be derived based on the relationship between losses and yields weighed against the cost of intervention. In the context of integrated pest management, monitoring of pathogen and pest populations, as well as of the environment and the development of resistance to chemical pesticides such as fungicides and insecticides, is necessary to estimate the risk to the crop posed by these diseases and pests and to select the optimal method for their control.

© 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.