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Publication Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study.(2022-05-17) Klén, Riku; Purohit, Disha; Gómez-Huelgas, Ricardo; Casas-Rojo, José Manuel; Antón-Santos, Juan Miguel; Núñez-Cortés, Jesús Millán; Lumbreras, Carlos; Ramos-Rincón, José Manuel; García Barrio, Noelia; Pedrera-Jiménez, Miguel; Lalueza Blanco, Antonio; Martin-Escalante, María Dolores; Rivas-Ruiz, Francisco; Onieva-García, Maria Ángeles; Young, Pablo; Ramirez, Juan Ignacio; Titto Omonte, Estela Edith; Gross Artega, Rosmery; Canales Beltrán, Magdy Teresa; Valdez, Pascual Ruben; Pugliese, Florencia; Castagna, Rosa; Huespe, Ivan A; Boietti, Bruno; Pollan, Javier A; Funke, Nico; Leiding, Benjamin; Gómez-Varela, DavidNew SARS-CoV-2 variants, breakthrough infections, waning immunity, and sub-optimal vaccination rates account for surges of hospitalizations and deaths. There is an urgent need for clinically valuable and generalizable triage tools assisting the allocation of hospital resources, particularly in resource-limited countries. We developed and validate CODOP, a machine learning-based tool for predicting the clinical outcome of hospitalized COVID-19 patients. CODOP was trained, tested and validated with six cohorts encompassing 29223 COVID-19 patients from more than 150 hospitals in Spain, the USA and Latin America during 2020-22. CODOP uses 12 clinical parameters commonly measured at hospital admission for reaching high discriminative ability up to 9 days before clinical resolution (AUROC: 0·90-0·96), it is well calibrated, and it enables an effective dynamic risk stratification during hospitalization. Furthermore, CODOP maintains its predictive ability independently of the virus variant and the vaccination status. To reckon with the fluctuating pressure levels in hospitals during the pandemic, we offer two online CODOP calculators, suited for undertriage or overtriage scenarios, validated with a cohort of patients from 42 hospitals in three Latin American countries (78-100% sensitivity and 89-97% specificity). The performance of CODOP in heterogeneous and geographically disperse patient cohorts and the easiness of use strongly suggest its clinical utility, particularly in resource-limited countries.Publication Gut Microbiota Composition Associated with Clostridioides difficile Colonization and Infection.(2022-07-08) Martinez, Elisa; Taminiau, Bernard; Rodriguez, Cristina; Daube, GeorgesClostridioides difficile is an anaerobic Gram-positive and spore-forming bacterium. The majority of C. difficile strains produce two toxins, A and B, associated with the development of acute diarrhea and/or colitis. In this review, two situations are distinguished: C. difficile infection (CDI) and asymptomatic colonization (AC). The main objective of this review is to explore the available data related to the link between the gut microbiota and the development of CDI. The secondary aim is to provide more information on why some people colonized with toxigenic C. difficile develop an infection while others show no signs of disease. Several factors, such as the use of antibiotics and proton pump inhibitors, hospitalization, and age, predispose individuals to C. difficile colonization and/or C. difficile infection. The gut microbiota of people with AC showed decreased abundances of Prevotella, Alistipes, Bacteroides, Bifidobacterium, Dorea, Coprococcus, and Roseburia. The gut microbiota of people suffering from CDI showed reductions in the abundances of Lachnospiraceae, Ruminococcaceae, Blautia spp., Prevotella spp., Dialister spp., Bifidobacterium spp., Roseburia spp., Anaerostipes spp., Faecalibacterium spp. and Coprococcus spp., in comparison with healthy people. Furthermore, increases in the abundances of Enterococcaceae and Enterococcus were associated with C. difficile infection.Publication Structural basis for interdomain communication in SHIP2 providing high phosphatase activity(eLife Sciences Publications, 2017) Le Coq, Johanne; Camacho-Artacho, Marta; Velázquez, José Vicente; Santiveri, Clara M; Gallego, Luis Heredia; Campos Olivas, Ramon; Dölker, Nicole; Lietha, Daniel; Ministerio de Economía y Competitividad (España); Comunidad de Madrid (España)SH2-containing-inositol-5-phosphatases (SHIPs) dephosphorylate the 5-phosphate of phosphatidylinositol-3,4,5-trisphosphate (PI(3,4,5)P3) and play important roles in regulating the PI3K/Akt pathway in physiology and disease. Aiming to uncover interdomain regulatory mechanisms in SHIP2, we determined crystal structures containing the 5-phosphatase and a proximal region adopting a C2 fold. This reveals an extensive interface between the two domains, which results in significant structural changes in the phosphatase domain. Both the phosphatase and C2 domains bind phosphatidylserine lipids, which likely helps to position the active site towards its substrate. Although located distant to the active site, the C2 domain greatly enhances catalytic turnover. Employing molecular dynamics, mutagenesis and cell biology, we identify two distinct allosteric signaling pathways, emanating from hydrophobic or polar interdomain interactions, differentially affecting lipid chain or headgroup moieties of PI(3,4,5)P3. Together, this study reveals details of multilayered C2-mediated effects important for SHIP2 activity and points towards interesting new possibilities for therapeutic interventions.Publication Urine Haptoglobin and Haptoglobin-Related Protein Predict Response to Spironolactone in Patients With Resistant Hypertension(2019-04) Martin-Lorenzo, Marta; Martinez, Paula J; Baldan-Martin, Montserrat; Lopez, Juan Antonio; Minguez, Pablo; Santiago-Hernandez, Aranzazu; Vazquez, Jesus; Segura, Julian; Ruiz-Hurtado, Gema; Vivanco, Fernando; Barderas, Maria G; Ruilope, Luis M; Alvarez-Llamas, Gloria; Instituto de Salud Carlos III; Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF); Fundación Conchita Rábago de Jiménez Díaz; Fundación SENEFROResistant hypertension prevalence is progressively increasing, and prolonged exposure to suboptimal blood pressure control results in higher cardiovascular risk and end-organ damage. Among various antihypertensive agents, spironolactone seems the most effective choice to treat resistant hypertension once triple therapy including a diuretic fails. However success in blood pressure control is not guaranteed, adverse effects are not negligible, and no clinical tools are available to predict patient's response. Complementary to our previous study of resistant hypertension metabolism, here we investigated urinary proteome changes with potential capacity to predict response to spironolactone. Twenty-nine resistant hypertensives were included. A prospective study was conducted and basal urine was collected before spironolactone administration. Patients were classified in responders or nonresponders in terms of blood pressure control. Protein quantitation was performed by liquid chromatography-mass spectrometry; ELISA and target mass spectrometry analysis were performed for confirmation. Among 3310 identified proteins, HP (haptoglobin) and HPR (haptoglobin-related protein) showed the most significant variations, with increased levels in nonresponders compared with responders before drug administration (variation rate, 5.98 and 7.83, respectively). Protein-coordinated responses were also evaluated by functional enrichment analysis, finding oxidative stress, chronic inflammatory response, blood coagulation, complement activation, and regulation of focal adhesions as physiopathological mechanisms in resistant hypertension. In conclusion, protein changes able to predict patients' response to spironolactone in basal urine were here identified for the first time. These data, once further confirmed, will support clinical decisions on patients' management while contributing to optimize the rate of control of resistant hypertensives with spironolactone.