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Abstract Occurrence of resistance to olaparib, a poly(ADP-ribose) polymerase (PARP) inhibitor (PARPi) approved in ovarian carcinoma, has already been shown in clinical settings. Identifying combination treatments to sensitize tumor cells and/or overcome resistance to olaparib is critical. Polo-like kinase 1 (PLK1), a master regulator of mitosis, is also involved in the DNA damage response promoting homologous recombination (HR)-mediated DNA repair and in the recovery from the G2/M checkpoint. We hypothesized that PLK1 inhibition could sensitize tumor cells to PARP inhibition. Onvansertib, a highly selective PLK1 inhibitor, and olaparib were tested in vitro and in vivo in BRCA1 mutated and wild-type (wt) ovarian cancer models, including patient-derived xenografts (PDXs) resistant to olaparib. The combination of onvansertib and olaparib was additive or synergic in different ovarian cancer cell lines, causing a G2/M block of the cell cycle, DNA damage, and apoptosis, much more pronounced in cells treated with the two drugs as compared to controls and single agents treated cells. The combined treatment was well tolerated in vivo and resulted in tumor growth inhibition and a statistically increased survival in olaparib-resistant-BRCA1 mutated models. The combination was also active, although to a lesser extent, in BRCA1 wt PDXs. Pharmacodynamic analyses showed an increase in mitotic, apoptotic, and DNA damage markers in tumor samples derived from mice treated with the combination versus vehicle. We could demonstrate that in vitro onvansertib inhibited both HR and non-homologous end-joining repair pathways and in vivo induced a decrease in the number of RAD51 foci-positive tumor cells, supporting its ability to induce HR deficiency and favoring the activity of olaparib. Considering that the combination was well tolerated, these data support and foster the clinical evaluation of onvansertib with PARPis in ovarian cancer, particularly in the PARPis-resistant setting.

Abstract In ovarian tumors, the omental microenvironment profoundly influences the behavior of cancer cells and sustains the acquisition of stem-like traits, with major impacts on tumor aggressiveness and relapse. Here, we leverage a patient-derived platform of organotypic cultures to study the crosstalk between the tumor microenvironment and ovarian cancer stem cells. We discovered that the pro-tumorigenic transcription factor FOXM1 is specifically induced by the microenvironment in ovarian cancer stem cells, through activation of FAK/YAP signaling. The microenvironment-induced FOXM1 sustains stemness, and its inactivation reduces cancer stem cells survival in the omental niche and enhances their response to the PARP inhibitor Olaparib. By unveiling the novel role of FOXM1 in ovarian cancer stemness, our findings highlight patient-derived organotypic co-cultures as a powerful tool to capture clinically relevant mechanisms of the microenvironment/cancer stem cells crosstalk, contributing to the identification of tumor vulnerabilities.

Preventing the onset of autoimmune type 1 diabetes (T1D) is feasible through pharmacological interventions that target molecular stress-responsive mechanisms. Cellular stresses, such as nutrient deficiency, viral infection, or unfolded proteins, trigger the integrated stress response (ISR), which curtails protein synthesis by phosphorylating eukaryotic translation initiation factor-2[alpha] (eIF2[alpha]). In T1D, maladaptive unfolded protein response (UPR) in insulin-producing [beta] cells renders these cells susceptible to autoimmunity. We found that inhibition of the eIF2a kinase PKR-like ER kinase (PERK), a common component of the UPR and ISR, reversed the mRNA translation block in stressed human islets and delayed the onset of diabetes, reduced islet inflammation, and preserved [beta] cell mass in T1D-susceptible mice. Single-cell RNA-Seq of islets from PERK-inhibited mice showed reductions in the UPR and PERK signaling pathways and alterations in antigen-processing and presentation pathways in p cells. Spatial proteomics of islets from these mice showed an increase in the immune checkpoint protein programmed death-ligand 1 (PD-L1) in [beta] cells. Golgi membrane protein 1, whose levels increased following PERK inhibition in human islets and EndoC-[beta]H1 human [beta] cells, interacted with and stabilized PD-L1. Collectively, our studies show that PERK activity enhances [beta] cell immunogenicity and that inhibition of PERK may offer a strategy for preventing or delaying the development of T1D., Introduction Type 1 diabetes (T1D) is a disorder of glucose homeostasis that results from the autoimmune destruction of insulin-producing islet [beta] cells. The importance of the immune system in initiating [...]

BackgroundChildren’s mental health, including their well-being, is a major public health concern, as the burden of related disorders may last throughout one’s life. Although epidemiological mental health surveillance systems for children and adolescents have been implemented in several countries, they are sorely lacking in France. ObjectiveThis study aims to describe the first step of the implementation of a novel surveillance system in France called Enabee (Etude nationale sur le bien-être des enfants), which focuses on the issue of mental health in children. The system aims to (1) describe the temporal trends in the population-based prevalence of the main mental health disorders and well-being in children aged 3 to 11 years, (2) explore their major determinants, and (3) assess mental health care use by this population. To do this, Enabee will rely on results from a recurrent national cross-sectional homonymous study. This paper presents the protocol for the first edition of this study (called Enabee 2022), as well as initial results regarding participation. MethodsEnabee 2022 is a national cross-sectional study that was implemented in French schools in 2022. It used a probabilistic, multistage, stratified, and balanced sampling plan as follows: first, schools were randomly drawn and stratified according to the type of school. Up to 4 classes per school were then randomly drawn, and finally, all the pupils within each class were selected. The study covered children from preschool and kindergarten (aged 3 to 6 years, US grading system) to fifth grade (aged 6 to 11 years). Children from first to fifth grades provided a self-assessment of their mental health using 2 validated self-administered questionnaires: the Dominic Interactive (DI) and the KINDL. Parents and teachers completed a web-based questionnaire, including the Strengths and Difficulties Questionnaire. Parents also answered additional questions about their parenting attitudes; their own mental health; known social, economic, and environmental determinants of mental health in children; and their child’s life habits. Health, education, and family stakeholders were involved in designing and implementing the study as part of a large consultation group. ResultsData were collected from May 2, 2022, to July 31, 2022, in 399 schools across metropolitan France. Teachers completed questionnaires for 5721 pupils in preschool and kindergarten and for 15,263 pupils from first to fifth grades. Parents completed questionnaires for 3785 children in preschool and kindergarten and for 9227 children from first to fifth grades. Finally, 15,206 children from first to fifth grades completed the self-administered questionnaire. ConclusionsEnabee 2022 constitutes the first milestone in the development of a novel national epidemiological surveillance system, paving the way for improved children’s mental health policies in France.

Background: Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise. Scope of Review: Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D. Major Conclusions: We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.

Abstract Background Lipids are regulators of insulitis and β-cell death in type 1 diabetes development, but the underlying mechanisms are poorly understood. Here, we investigated how the islet lipid composition and downstream signaling regulate β-cell death. Methods We performed lipidomics using three models of insulitis: human islets and EndoC-βH1 β cells treated with the pro-inflammatory cytokines interlukine-1β and interferon-γ, and islets from pre-diabetic non-obese mice. We also performed mass spectrometry and fluorescence imaging to determine the localization of lipids and enzyme in islets. RNAi, apoptotic assay, and qPCR were performed to determine the role of a specific factor in lipid-mediated cytokine signaling. Results Across all three models, lipidomic analyses showed a consistent increase of lysophosphatidylcholine species and phosphatidylcholines with polyunsaturated fatty acids and a reduction of triacylglycerol species. Imaging assays showed that phosphatidylcholines with polyunsaturated fatty acids and their hydrolyzing enzyme phospholipase PLA2G6 are enriched in islets. In downstream signaling, omega-3 fatty acids reduce cytokine-induced β-cell death by improving the expression of ADP-ribosylhydrolase ARH3. The mechanism involves omega-3 fatty acid-mediated reduction of the histone methylation polycomb complex PRC2 component Suz12, upregulating the expression of Arh3, which in turn decreases cell apoptosis. Conclusions Our data provide insights into the change of lipidomics landscape in β cells during insulitis and identify a protective mechanism by omega-3 fatty acids. Video Abstract

The unique geographical and topographical features of Madeira International Airport in Portugal significantly influence flight safety, primarily due to variable wind patterns. In this study, a machine learning approach is developed to predict runway operational statuses at Madeira International Airport, focusing on addressing wind-related challenges. To tackle this issue, a Deep Learning model is utilized. This model undergoes a particle swarm optimization process, resulting in one optimized model for each timestep, to provide minute-resolution predictions within a 20-minute timeframe. The training, validation, and testing phases for the optimized models were conducted using high-frequency wind data from Madeira International Airport. The main objective is to accurately predict the runway operational statuses, specifically whether the airport is open or closed for landing, take-off, or both. The models exhibit high performance, particularly in identifying operational conditions, reaching 99.93% precision, and a top accuracy of 94.35% predicting all runway status, underscoring their potential to enhance decision-making processes and operational efficiency under challenging weather conditions.

Nowadays, emissions from internal combustion engines are a relevant topic of investigation, taking into account the continuous reduction of emission limits imposed by environmental regulatory agencies around the world, obviously as the result of earnest studies that have pointed out the impact on the human health of high levels of contaminants released into the environment. Over recent years, the use of biofuels has contributed to attenuating this environmental issue; however, new problems have been raised, such as NOx emissions tend to increase as the biofuel percentage in the fuel used in engines increases. In this research, the emissions of a compression ignition internal combustion engine modeled as a variable volume reactor with homogeneous combustion were numerically investigated. To analyze the combustion process, a detailed kinetics model tailored specifically for this purpose was used. The kinetics model comprised 30,975 chemical reactions involving 691 chemical species. Mixtures of fuel surrogates were then created to represent the fuel used in the Brazilian fuel marketplace, involving (i) fossil diesel—“diesel A”, (ii) soybean diesel—“biodiesel”, and (iii) hydrotreated vegetable oil— “HVO”. Surrogate species were then selected for each of the aforementioned fuels, and blends of those surrogates were then proposed as mixture M1 (diesel A:biodiesel:HVO—90:10:0), mixture M2 (diesel A:biodiesel:HVO—85:15:0), and mixture M3 (diesel A:biodiesel:HVO—80:15:5). The species allowed in the kinetics model included all the fuel surrogates used in this research as well as the target emission species of this study: total hydrocarbons, non-methane hydrocarbons, carbon monoxide, methane, nitrogen oxides, carbon dioxide, soot, and soot precursors. When compared to experimental trends of emissions available in the literature, it was observed that, for all the proposed fuel surrogates blends, the numerical approach performed in this research was able to capture qualitative trends for engine power and the target emissions in the whole ranges of engine speeds and engine loads, despite the CO and NOx emissions at specific engine speeds and loads.

Texto de apresentação para o dossiê da Extraprensa: Ecologias digitais do Sul