MIL-101 promotes the efficient aerobic oxidative desulfurization of dibenzothiophenes

[EN] MIL-101 promotes aerobic oxidation in n-dodecane of dibenzothiophene (DBT) and its methyl-substituted derivatives to their corresponding sulfones with complete selectivity, without observation of the sulfoxide. DBT sulfones can be completely separated from n-dodecane by water extraction. MIL-101(Cr) without the need of pre-activation was found to be more convenient than the also-active MIL-101(Fe) analog. The reaction exhibits an induction period due to the diffusion inside the pore system of the solvent or oxygen and it is not observed if the MIL-101 sample is first in contact with the solvent at the reaction temperature for a sufficiently long time. MIL-101 is reusable for at least five times without any sign of deactivation according to the time-conversion plots. Evidence by electron paramagnetic resonance spectroscopy detecting the hydroperoxide radical adduct with a spin trapping agent and Raman spectroscopy detection of superoxide supports that the process is an auto-oxidation reaction initiated by MIL-101 following the expected radical chain mechanism inside the MIL-101 cages.Financial support by the Spanish Ministry of Economy and Competitiveness (Severo Ochoa and CTQ2012-32315) is gratefully acknowledged. Generalidad Valenciana is also thanked for funding (Prometeo 2012/013 and GV/2013/040).Gómez Paricio, A.; Santiago Portillo, A.; Navalón Oltra, S.; Concepción Heydorn, P.; Alvaro Rodríguez, MM.; García Gómez, H. (2016). MIL-101 promotes the efficient aerobic oxidative desulfurization of dibenzothiophenes. Green Chemistry. 18(2):508-515. doi:10.1039/C5GC00862JS50851518

Machine Learning Improves Risk Stratification in Myelofibrosis: An Analysis of the Spanish Registry of Myelofibrosis

Myelofibrosis (MF) is a myeloproliferative neoplasm (MPN) with heterogeneous clinical course. Allogeneic hematopoietic cell transplantation remains the only curative therapy, but its morbidity and mortality require careful candidate selection. Therefore, accurate disease risk prognostication is critical for treatment decision-making. We obtained registry data from patients diagnosed with MF in 60 Spanish institutions (N = 1386). These were randomly divided into a training set (80%) and a test set (20%). A machine learning (ML) technique (random forest) was used to model overall survival (OS) and leukemia-free survival (LFS) in the training set, and the results were validated in the test set. We derived the AIPSS-MF (Artificial Intelligence Prognostic Scoring System for Myelofibrosis) model, which was based on 8 clinical variables at diagnosis and achieved high accuracy in predicting OS (training set c-index, 0.750; test set c-index, 0.744) and LFS (training set c-index, 0.697; test set c-index, 0.703). No improvement was obtained with the inclusion of MPN driver mutations in the model. We were unable to adequately assess the potential benefit of including adverse cytogenetics or high-risk mutations due to the lack of these data in many patients. AIPSS-MF was superior to the IPSS regardless of MF subtype and age range and outperformed the MYSEC-PM in patients with secondary MF. In conclusion, we have developed a prediction model based exclusively on clinical variables that provides individualized prognostic estimates in patients with primary and secondary MF. The use of AIPSS-MF in combination with predictive models that incorporate genetic information may improve disease risk stratification

Materiales híbridos metal-orgánicos como catalizadores de oxidacción aeróbica para la desulfuración de modelos del gasóil

Gómez Paricio, A. (2014). Materiales híbridos metal-orgánicos como catalizadores de oxidacción aeróbica para la desulfuración de modelos del gasóil. http://hdl.handle.net/10251/53789Archivo delegad

Use the Cpo-27 to Degrade Simulant of Nerve Agents

EN] Metal-organic frameworks are a recently-identified class of porous material, consisting of metal ions linked together with organic bridging ligands. The porosity of these materials allows the absorption of suitable molecules into the structure. The [Co2(C8H2O6)(H2O)2]·8H2O MOF(CPO-27) has been synthetized by solvothermal methodology following the procedure described by Dietzel et al.[1]. Activation of MOF was carried out in order to remove water molecules linked to the cobalt; consequently metal active sites are available to perform catalytic reactions. Well-known simulant of nerve gases, such as diethylchlorophosphate (DCP) and dimethylmethyl phosphate (DMP), are extremely harmful and stable, and consequently, hardly to degrade. In order to evaluate the potential capacity of the CPO- 27 as catalyst in the degradation of DCP and DMP, several attempts have been carried out by using different media. The reactions were followed by 1H, 13C, 31P NMR and XRD spectroscopies to monitorize the resultsGómez Paricio, A. (2013). Use the Cpo-27 to Degrade Simulant of Nerve Agents. http://hdl.handle.net/10251/17604