A low-cost and do-it-yourself device for pumping monitoring in deep aquifers

Water crises due to climate change, high population growth and increasing demands from industry and agriculture claim for increasing efficiency and universalizing water resources management strategies and techniques. Water monitoring helps providing necessary evidences for making sound decisions about managing water resources both now and in the future. In this work, a low cost and “do it yourself” communication device is proposed to record water production and energy consumption of electric pumpings from deep boreholes/wells, and to predict the impact of the ongoing and previous pumpings in the evolution of the water level in the aquifer. The proposal incorporates an edge-computing approach for the simulation of the aquifer response in real-time. Computation of results of interest is performed at the sensor, minimizing communication requirements and ensuring almost immediate results. An approximated solution to physically based modeling of aquifer response is computed thanks to the a priori expression of the water level time evolution in a reduced basis. The accuracy is enough to detect deviations from expected behaviour. The energy consumption of the device is very much reduced with respect to that of a full modelling, which can be computed off-line for calibrating reduced model parameters and perform detailed analyses. The device is tested in a real scenario, in a mountain subbasin of the Ebro river in Spain, obtaining a good trade-off between performance, price, and energy consumption.This research has been partly supported by EU under grant agreement N. 825184 and funded by the Government of Spain under contracts PID2019-106774RB-C21, PID2019-106774RB-C22, and PID2020-113172RB-I00 and by the Government of Catalonia as Consolidated Research Groups 2017-SGR-688 and 2017-SGR-990, and Pre-consolidated Research Group 2017-SGR-1496. The APC was funded by the Open program from Universitat Rovira i Virgili.Peer ReviewedPostprint (published version

A Phase I-II multicenter trial with Avelumab plus autologous dendritic cell vaccine in pre-treated mismatch repair-proficient (MSS) metastatic colorectal cancer patients; GEMCAD 1602 study

Metabolism; Resistance; VaccinesMetabolisme; Resistència; VacunesMetabolismo; Resistencia; VacunasBackground Immune check-point blockade (ICB) has shown clinical benefit in mismatch repair-deficient/microsatellite instability high metastatic colorectal cancer (mCRC) but not in mismatch repair-proficient/microsatellite stable patients. Cancer vaccines with autologous dendritic cells (ADC) could be a complementary therapeutic approach to ICB as this combination has the potential to achieve synergistic effects. Methods This was a Phase I/II multicentric study with translational sub-studies, to evaluate the safety, pharmacodynamics and anti-tumor effects of Avelumab plus ADC vaccine in heavily pre-treated MSS mCRC patients. Primary objective was to determine the maximum tolerated dose and the efficacy of the combination. The primary end-point was 40% progression-free survival at 6 months with a 2 Simon Stage. Results A total of 28 patients were screened and 19 pts were included. Combined therapy was safe and well tolerated. An interim analysis (Simon design first-stage) recommended early termination because only 2/19 (11%) patients were disease free at 6 months. Median PFS was 3.1 months [2.1–5.3 months] and overall survival was 12.2 months [3.2–23.2 months]. Stimulation of immune system was observed in vitro but not clinically. The evaluation of basal RNA-seq noted significant changes between pre and post-therapy liver biopsies related to lipid metabolism and transport, inflammation and oxidative stress pathways. Conclusions The combination of Avelumab plus ADC vaccine is safe and well tolerated but exhibited modest clinical activity. Our study describes, for the first-time, a de novo post-therapy metabolic rewiring, that could represent novel immunotherapy-induced tumor vulnerabilities.The study was funded by grants from the FIS PI17/00732 from Instituto de Salud Carlos III, Premi Fi de Residència Emili Letang from Hospital Clínic Barcelona, Plan Nacional de I + D (PID-107139RB-C21 to DB-R and PID2020-115051RB-I00 to MC) and Grupo Español Multidisciplinar en Cáncer Digestivo (GEMCAD). The study was funded with Grants from Catalan Agency for Management of University and Research Grants (AGAUR) (2014-SGR-474, 2017-SGR-1174 and 2017-SGR-1033), Fundació la Marató de TV3 (201330.10), Instituto de Salud Carlos III (PI13/01728 and PI19/00740) and Fundacion Olga Torres (Modalitat A. 2019/2020) to JM. IMMETCOLS signature is under patent protection (EP21382772.8.) This research was financially supported by GEMCAD and (OR Avelumab was provided) by Merck, S.L.U., Madrid, Spain, an affiliate of Merck KGaA, Darmstadt, Germany, as part of an alliance between the healthcare business of Merck KGaA, Darmstadt, Germany (CrossRef Funder ID: https://doi.org/10.13039/100009945) and Pfizer

The landscape of tiered regulation of breast cancer cell metabolism

Altered metabolism is a hallmark of cancer, but little is still known about its regulation. In this study, we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line (MCF7) across three different growth conditions. Integrating these multiomics data within a genome scale human metabolic model in combination with machine learning, we systematically chart the different layers of metabolic regulation in breast cancer cells, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly and indirectly regulated. Directly-regulated reactions include those whose flux is regulated by transcriptomic alterations (~890) or via proteomic or phospho-proteomics alterations (~140) in the enzymes catalyzing them. We term the reactions that currently lack evidence for direct regulation as (putative) indirectly regulated (~930). Many metabolic pathways are predicted to be regulated at different levels, and those may change at different media conditions. Remarkably, we find that the flux of predicted indirectly regulated reactions is strongly coupled to the flux of the predicted directly regulated ones, uncovering a tiered hierarchical organization of breast cancer cell metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly reversible. Taken together, this architecture may facilitate rapid and efficient metabolic reprogramming in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for mapping metabolic regulation in additional cancers

Integrating systemic and molecular levels to infer key drivers sustaining metabolic adaptations

Metabolic adaptations to complex perturbations, like the response to pharmacological treatments in multifactorial diseases such as cancer, can be described through measurements of part of the fluxes and concentrations at the systemic level and individual transporter and enzyme activities at the molecular level. In the framework of Metabolic Control Analysis (MCA), ensembles of linear constraints can be built integrating these measurements at both systemic and molecular levels, which are expressed as relative differences or changes produced in the metabolic adaptation. Here, combining MCA with Linear Programming, an efficient computational strategy is developed to infer additional non-measured changes at the molecular level that are required to satisfy these constraints. An application of this strategy is illustrated by using a set of fluxes, concentrations, and differentially expressed genes that characterize the response to cyclin-dependent kinases 4 and 6 inhibition in colon cancer cells. Decreases and increases in transporter and enzyme individual activities required to reprogram the measured changes in fluxes and concentrations are compared with down-regulated and up-regulated metabolic genes to unveil those that are key molecular drivers of the metabolic response

Metabolomics in systems medicine: an overview of methods and applications

Patient-derived metabolomics offers valuable insights into the metabolic phenotype underlying diseases with a strong metabolic component. Thus, these data sets will be pivotal to the implementation of personalized medicine strategies in health and disease. However, to take full advantage of such data sets, they must be integrated with other omics within a coherent pathophysiological framework to enable improved diagnostics, to identify therapeutic interventions, and to accurately stratify patients. Herein, we provide an overview of the state-of-the-art data analysis and modeling approaches applicable to metabolomics data and of their potential for systems medicine

HepatoDyn: a dynamic model of hepatocyte metabolism that integrates 13C isotopomer data

The liver performs many essential metabolic functions, which can be studied using computational models of hepatocytes. Here we present HepatoDyn, a highly detailed dynamic model of hepatocyte metabolism. HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is capable of dynamically simulating the redox and energy metabolism of hepatocytes. Furthermore, the model was coupled to the module for isotopic label propagation of the software package IsoDyn, allowing HepatoDyn to integrate data derived from 13C based experiments. As an example of dynamical simulations applied to hepatocytes, we studied the effects of high fructose concentrations on hepatocyte metabolism by integrating data from experiments in which rat hepatocytes were incubated with 20 mM glucose supplemented with either 3 mM or 20 mM fructose. These experiments showed that glycogen accumulation was significantly lower in hepatocytes incubated with medium supplemented with 20 mM fructose than in hepatocytes incubated with medium supplemented with 3 mM fructose. Through the integration of extracellular fluxes and 13C enrichment measurements, HepatoDyn predicted that this phenomenon can be attributed to a depletion of cytosolic ATP and phosphate induced by high fructose concentrations in the medium

Genome-scale integration of transcriptome and metabolome unveils squalene synthase and dihydrofolate reductase as targets against AML cells resistant to chemotherapy

The development of resistance to chemotherapeutic agents, such as Doxorubicin (DOX) and cytarabine (AraC), is one of the greatest challenges to the successful treatment of Acute Myeloid Leukemia (AML). Such acquisition is often underlined by a metabolic reprogramming that can provide a therapeutic opportunity, as it can lead to the emergence of vulnerabilities and dependencies to be exploited as targets against the resistant cells. In this regard, genome-scale metabolic models (GSMMs) have emerged as powerful tools to integrate multiple layers of data to build cancer-specific models and identify putative metabolic vulnerabilities. Here, we use genome-scale metabolic modelling to reconstruct a GSMM of the THP1 AML cell line and two derivative cell lines, one with acquired resistance to AraC and the second with acquired resistance to DOX. We also explore how, adding to the transcriptomic layer, the metabolomic layer enhances the selectivity of the resulting condition specific reconstructions. The resulting models enabled us to identify and experimentally validate that drug-resistant THP1 cells are sensitive to the FDA-approved antifolate methotrexate. Moreover, we discovered and validated that the resistant cell lines could be selectively targeted by inhibiting squalene synthase, providing a new and promising strategy to directly inhibit cholesterol synthesis in AML drug resistant cells

El desig teatral d'Europa

La coŀecció «Escenes Europees», coordinada per Francesc Foguet i Núria Santamaria, és una iniciativa del Grup de Recerca en Arts Escèniques de la Universitat Autònoma de Barcelona.Inclou els resums dels capítols a la pàgina 209.Aquests textos són reflexions que pretenen establir un diàleg al voltant de l'especificitat de les històries polítiques i culturals d'Europa, al voltant de les seves zones i les seves regions, entorn de les seves tradicions i les seves projeccions, sempre a partir del teatre

Cysteine and Folate metabolism are targetable vulnerabilities of metastatic colorectal cancer

With most cancer-related deaths resulting from metastasis, the development of new therapeutic approaches against metastatic colorectal cancer (mCRC) is essential to increasing patient survival. The metabolic adaptations that support mCRC remain undefined and their elucidation is crucial to identify potential therapeutic targets. Here, we employed a strategy for the rational identification of targetable metabolic vulnerabilities. This strategy involved first a thorough metabolic characterisation of same-patient-derived cell lines from primary colon adenocarcinoma (SW480), its lymph node metastasis (SW620) and a liver metastatic derivative (SW620-LiM2), and second, using a novel multi-omics integration workflow, identification of metabolic vulnerabilities specific to the metastatic cell lines. We discovered that the metastatic cell lines are selectively vulnerable to the inhibition of cystine import and folate metabolism, two key pathways in redox homeostasis. Specifically, we identified the system xCT and MTHFD1 genes as potential therapeutic targets, both individually and combined, for combating mCRC