The Benefit of Probabilistic Flood Forecasting on European Scale Results of the European Flood Alert System for 2005/2006

Results of the European Flood Alert System for 2005/2006JRC.H.7-Land management and natural hazard

Summary Report of the 1st Workshop on the use of Ensemble Prediction System in Flood Forecasting (Ispra, 21-22 November 2005)

The first workshop on the use of EPS in flood forecasting was organised by the Joint Research Centre together with researchers from King's College in London (UK) and the Lancaster University (UK). The workshop was organized to address two main concerns of EFAS regarding flood forecasting based on EPS: 1. How to extract meaningful information from the meteorological EPS for medium-range flood forecasting? 2. How to communicate the uncertainty in flood forecasting to end-users? The specific objectives of the workshop were to explore together with flood forecasting experts from the Member States: 3. The usefulness of EPS information implemented in EFAS for operational flood forecasting and decision making, and the perception of uncertainty in flood forecasting. The workshop's concept was to have a small group of flood forecasters from different river basins working through a number of case-studies, each one representing a potential flood situation as forecasted by EFAS. On the first day, the participants worked in groups on each case-study. The second day was targeted mostly to plenary discussions on the use of EPS in flood forecasting.JRC.H.7-Land management and natural hazard

A selective p53 activator and anticancer agent to improve colorectal cancer therapy

Impairment of the p53 pathway is a critical event in cancer. Therefore, reestablishing p53 activity has become one of the most appealing anticancer therapeutic strategies. Here, we disclose the p53-activating anticancer drug (3S)-6,7-bis(hydroxymethyl)-5-methyl-3-phenyl-1H,3H-pyrrolo[1,2-c]thiazole (MANIO). MANIO demonstrates a notable selectivity to the p53 pathway, activating wild-type (WT)p53 and restoring WT-like function to mutant (mut)p53 in human cancer cells. MANIO directly binds to the WT/mutp53 DNA-binding domain, enhancing the protein thermal stability, DNA-binding ability, and transcriptional activity. The high efficacy of MANIO as an anticancer agent toward cancers harboring WT/mutp53 is further demonstrated in patient-derived cells and xenograft mouse models of colorectal cancer (CRC), with no signs of undesirable side effects. MANIO synergizes with conventional chemotherapeutic drugs, and in vitro and in vivo studies predict its adequate drug-likeness and pharmacokinetic properties for a clinical candidate. As a single agent or in combination, MANIO will advance anticancer-targeted therapy, particularly benefiting CRC patients harboring distinct p53 status.We thank PT national funds (FCT/MCTES, Fundação para a Ciência e a Tecnologia, and Ministério da Ciência, Tecnologia e Ensino Superior) through grants UIDB/50006/2020, UID/BIO/04469/2019, UIDB/04539/2020, and UIDP/04539/2020 (CIBB); BioTecNorte operation (NORTE-01-0145-FEDER000004) and Porto Neurosciences and Neurologic Disease Research Initiative at I3S (Norte-01-0145-FEDER-000008) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte; Masaryk University (Project MUNI/A/1127/2019) and Ministry of Education, Youth and Sports of the Czech Republic (project nos. LQ1605 and LM2018125); FCT financial support through the fellowships SFRH/BD/119144/2016 (H.R.) and SFRH/BD/117949/2016 (L.R.); Fondazione AIRC (IG#18985, A.I.); and the Programa Operacional Potencial Humano (POCH), specifically the BiotechHealth Programme (Doctoral Programme on Cellular and Molecular Biotechnology Applied to Health Sciences, PD/00016/2012). We thank Dario Rizzotto for assistance in preparing the libraries for RNA sequencing. Funding: This work was supported by PT National Funds (FCT/MCTES, Fundação para a Ciência e Tecnologia, and Ministério da Ciência, Tecnologia e Ensino Superior) via the projects UIDB/50006/2020 (LAQV/REQUIMTE), UIDB/00313/2020, and UIDP/00313/2020, co-funded by COMPETE2020-UE.info:eu-repo/semantics/publishedVersio

SLMP53-2 Restores Wild-Type-Like Function to Mutant p53 through Hsp70: Promising Activity in Hepatocellular Carcinoma.

Half of human cancers harbor TP53 mutations that render p53 inactive as a tumor suppressor. In these cancers, reactivation of mutant p53 (mutp53) through restoration of wild-type-like function constitutes a valuable anticancer therapeutic strategy. In order to search for mutp53 reactivators, a small library of tryptophanol-derived oxazoloisoindolinones was synthesized and the potential of these compounds as mutp53 reactivators and anticancer agents was investigated in human tumor cells and xenograft mouse models. By analysis of their anti-proliferative effect on a panel of p53-null NCI-H1299 tumor cells ectopically expressing highly prevalent mutp53, the compound SLMP53-2 was selected based on its potential reactivation of multiple structural mutp53. In mutp53-Y220C-expressing hepatocellular carcinoma (HCC) cells, SLMP53-2-induced growth inhibition was mediated by cell cycle arrest, apoptosis, and endoplasmic reticulum stress response. In these cells, SLMP53-2 restored wild-type-like conformation and DNA-binding ability of mutp53-Y220C by enhancing its interaction with the heat shock protein 70 (Hsp70), leading to the reestablishment of p53 transcriptional activity. Additionally, SLMP53-2 displayed synergistic effect with sorafenib, the only approved therapy for advanced HCC. Notably, it exhibited potent antitumor activity in human HCC xenograft mouse models with a favorable toxicological profile. Collectively, SLMP53-2 is a new mutp53-targeting agent with promising antitumor activity, particularly against HCC

Description of vaccination coverage and hesitancy obtained by epidemiological survey of children born in 2017-2018, in Belo Horizonte and Sete Lagoas, Minas Gerais, Brazil

ABSTRACT Objective To describe vaccination coverage and hesitation for the basic children’s schedule in Belo Horizonte and Sete Lagoas, Minas Gerais state, Brazil. Methods Population-based epidemiological surveys performed from 2020 to 2022, which estimated vaccine coverage by type of immunobiological product and full schedule (valid and ministered doses), according to socioeconomic strata; and reasons for vaccination hesitancy. Results Overall coverage with valid doses and vaccination hesitancy for at least one vaccine were, respectively, 50.2% (95%CI 44.1;56.2) and 1.6% (95%CI 0.9;2.7), in Belo Horizonte (n = 1,866), and 64.9% (95%CI 56.9;72.1) and 1.0% (95%CI 0.3;2.8), in Sete Lagoas (n = 451), with differences between socioeconomic strata. Fear of severe reactions was the main reason for vaccination hesitancy. Conclusion Coverage was identified as being below recommended levels for most vaccines. Disinformation should be combated in order to avoid vaccination hesitancy. There is a pressing need to recover coverages, considering public health service access and socioeconomic disparities

Racial inequalities in child vaccination and barriers to vaccination in Brazil among live births in 2017 and 2018: an analysis of a retrospective cohort of the first two years of life

ABSTRACT Objective To describe timely vaccination completion and obstacles in the first 24 months of life in Brazil, examining associations with maternal race/skin color. Methods Study participants were 37,801 children born in 2017 and 2018 included in the National Immunization Coverage Survey. We calculated prevalence and 95% confidence intervals for timely vaccine completeness and obstacles at 5, 12 and 24 months of life, according to maternal race/skin color. Associations were analyzed using logistic regression. Results 7.2% (95%CI 6.3;8.2) of mothers faced difficulties in taking their children to be vaccinated, and 23.4% (95%CI 21.7;25.1) were not vaccinated when taken. These proportions were 75% (95%CI 1.25;2.45) and 97% (95%CI 1.57;2.48) higher, respectively, among Black mothers. At least one vaccination was delayed among 49.9% (95%CI 47.8;51.9) and 61.1% (95%CI 59.2;63.0) of children by 5 and 12 months, respectively. These rates were higher among Black/mixed race mothers. Conclusion There are racial inequalities in both the obstacles faced and in vaccination rates in Brazil

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost