Recovery of deformation substructure and coarsening of particles on annealing severely plastically deformedAl–Mg–Si alloy and analysis of strengthening mechanisms

An Al–Mg–Si alloy was annealed to various solutionized and aged states and was then severely plastically deformed by equal channel angular pressing (ECAP). These materials were subsequently annealed for a range of times and temperatures to induce precipitation, dislocation recovery, and grain growth, with changes of mechanical behavior followed by tensile testing. Precipitation of excess solute was seen to occur in all cases, independent of the initial heat treated state, but the particles present appear to play only a small role in stabilizing the deformation substructure, at least until significant particle and grain coarsening has occurred, when discontinuous grain coarsening can be provoked. The strength of materials is examined, and the respective contributions of loosely arranged dislocations, many grain boundaries, and dispersed particles are deduced. It is shown that dislocation strengthening is significant in as-deformed, as well as lightly annealed materials, with grain boundary strengthening providing the major contribution thereafterComunidad de Madrid (CAM) under Contract No. 07N/0087/2002Peer reviewe

Matrix grain refinement in Al-TiAl composites by severe plastic deformation: influence of particle size and processing route

The microstructure and mechanical behaviour of Al-based composites reinforced with TiAl intermetallic particles has been examined in the as-extruded state and after processing by equal channel angular pressing (ECAP). The latter produces a grain size reduction in the aluminium matrix to values of 500 nm, using route A, and 750 nm, using route C. The ECAP produces up to a 75% increase in the yield stress of the composites, being more rapid when route A is used. The strengthening effect by ECAP is much larger than that obtained by increasing the volume fraction of reinforcement particles from 25 to 50% in these compositesThanks to the Spanish Ministry of Education and Science for financing this study under project number MAT2003-01540.Peer reviewe

CHK1 expression in gastric cancer is modulated by p53 and RB1/E2F1: Implications in chemo/radiotherapy response

Radiation has a limited but relevant role in the adjuvant therapy of gastric cancer (GC) patients. Since Chk1 plays a critical function in cellular response to genotoxic agents, we aimed to analyze the role of Chk1 in GC as a biomarker for radiotherapy resistance. We analyzed Chk1 expression in AGS and MKN45 human GC cell lines by RT-QPCR and WB and in a small cohort of human patient’s samples. We demonstrated that Chk1 overexpression specifically increases resistance to radiation in GC cells. Accordingly, abrogation of Chk1 activity with UCN-01 and its expression with shChk1 increased sensitivity to bleomycin and radiation. Furthermore, when we assessed Chk1 expression in human samples, we found a correlation between nuclear Chk1 accumulation and a decrease in progression free survival. Moreover, using a luciferase assay we found that Chk1’s expression is controlled by p53 and RB/E2F1 at the transcriptional level. Additionally, we present preliminary data suggesting a posttranscriptional regulation mechanism, involving miR-195 and miR-503, which are inversely correlated with expression of Chk1 in radioresistant cells. In conclusion, Chk1/microRNA axis is involved in resistance to radiation in GC, and suggests Chk1 as a potential tool for optimal stratification of patients susceptible to receive adjuvant radiotherapy after surgeryThis work was supported by Instituto de Salud Carlos III–Fondo de Investigación Sanitaria (PS09/1988 to ISP; PI11-00949, pI014-1495 and Feder Funds to RP); Comunidad Autónoma de Madrid-Universidad Autónoma de Madrid (CCG10-UAM/BIO-5871 to ISP); Fundación Leticia Castillejo Castillo and Ministerio de Ciencia e Innovación (SAF2012-30862 to RSP), Spain

Enhancing a de novo enzyme activity by computationally-focused ultra-low-throughput screening

Directed evolution has revolutionized protein engineering. Still, enzyme optimization by random library screening remains sluggish, in large part due to futile probing of mutations that are catalytically neutral and/or impair stability and folding. FuncLib is a novel approach which uses phylogenetic analysis and Rosetta design to rank enzyme variants with multiple mutations, on the basis of predicted stability. Here, we use it to target the active site region of a minimalist-designed, de novo Kemp eliminase. The similarity between the Michaelis complex and transition state for the enzymatic reaction makes this system particularly challenging to optimize. Yet, experimental screening of a small number of active-site variants at the top of the predicted stability ranking leads to catalytic efficiencies and turnover numbers ( 2 104 M 1 s 1 and 102 s 1) for this anthropogenic reaction that compare favorably to those of modern natural enzymes. This result illustrates the promise of FuncLib as a powerful tool with which to speed up directed evolution, even on scaffolds that were not originally evolved for those functions, by guiding screening to regions of the sequence space that encode stable and catalytically diverse enzymes. Empirical valence bond calculations reproduce the experimental activation energies for the optimized eliminases to within 2 kcal mol 1 and indicate that the enhanced activity is linked to better geometric preorganization of the active site. This raises the possibility of further enhancing the stabilityguidance of FuncLib by computational predictions of catalytic activity, as a generalized approach for computational enzyme designKnut and Alice Wallenberg Foundation (Wallenberg Academy Fellowship) 2018.0140Human Frontier Science Program RGP0041/2017FEDER Funds/Spanish Ministry of Science, Innovation and Universities BIO2015-66426-R RTI2018-097142-B-100FEDER/Junta de Andalucia - Consejeria de Economia y Conocimiento E.FQM.113.UGR18Swedish National Infrastructure for computing (SNAC) 2018/2-3 2019/2-

Aprendizaje automático y métodos hedónicos en el mercado de autos usados en línea de Argentina

El presente trabajo utiliza métodos de machine learning para reducir el número de características determinantes del precio de automóviles usados en Argentina. Nos basamos en la especificación de un modelo de precios hedónicos en línea para los automóviles usados (Ramirez Muñoz del Toro et al ,2017). Específicamente aplicamos el método Least Absolute Shrinkage and Selection Operator (LASSO) y el Classification and Regression Tree (CART) junto a una estimación más tradicional de un modelo hedónico. Los datos fueron obtenidos de un sitio en línea. Mediante el uso de estas técnicas nos es posible realizar una selección de variables relevantes y explorar posibles no linealidades, que complementan el análisis de regresión tradicional.Fil: Gutierrez, Emiliano Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Larrosa, Juan Manuel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Delbianco, Fernando Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Economía; ArgentinaFil: Uriarte, Juan I.. Hyperia Big Data; ArgentinaFil: Muñoz del Toro, Gonzalo. Hyperia Big Data; Argentina. Universidad Nacional del Sur. Departamento de Derecho; ArgentinaLIII Reunión Anual de la Asociación Argentina de Economía PolíticaLa PlataArgentinaUniversidad Nacional de La Plat

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

Background: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health car

Toxicity results after treatment with Electronic Brachytherapy in patients with endometrial cancer

Poster Session [EP-2226] Purpose or Objective To analyse the toxicity outcomes after treatment with Electronic Brachytherapy (XB) in postsurgical endometrial cancer patients treated at our medical centre. Material and Methods Prospective study in which we selected 94 patients, between September/2015 and September/2017, that received treatment with XB administered twice a week after endometrial cancer surgery, with IMRT planificati on. The patients were divided in two groups: Group 1 (57/94) considered high risk received external beam radiotherapy (46Gy) followed by XB (15Gy in 5Gy fractions) and group 2 (37/94) considered intermediate risk received exclusive XB (25Gy in 5Gy fraction s). We analysed the median dose in bladder, rectum and sigmoid D2cc, V50, V35 with XB comparing the doses with Ir192. The vaginal mucosa, gastrointestinal (GI) and genitourinary (GU) toxicities were analysed with the Common Terminology Criteria for Adverse Events (CTCAE 4.0) scale. Results The median dose in bladder with XB vs. Ir192 was: 2cc 62.9 vs. 69.9%, V50 7.1 vs. 12.6Gy, V35 15 vs. 28.1. In rectum XB vs. Ir192 was: D 2cc 64.01% vs. 67.7%, V50 7.8 vs. 10.9Gy, V35 16.5 vs. 31.8Gy. In sigmoid XB vs. Ir 192 was: D 50.37%vs. 58.0%, V50 8.8 vs. 16.2Gy, V35 21.2 vs. 37.5Gy. The median follow- up was 11 months (range 1 - 23, 9 months). In group 1, acute vaginal mucositis (G1) was observed in 35.08% of the patients, GI toxicity (G1) in 5.26% and GU toxicity (G1) in 10.52%. In group 2, we observed acute vaginal mucositis G1 in 45% of the patients and G2 in 10.81%, GI toxicity (G1) occurred in 2.7% and GU toxicity (G1) was present in 16.21%. There was no grade 3 or greater toxicity in any of the groups. Late toxici ty was observed in only 4 patients: Mucositis (G1) in 3 patients and GU toxicity (G1) in 1 patient. Conclusion The dose received by the organs at risk with the XB is less compared to Ir192, with a good coverage of the PTV. The greater toxicity was observe d immediately after the treatment was finished with an important reduction of the symptoms after 6 months. This technique shows excellent results as for toxicity

HGF, IL-1α, and IL-27 are robust biomarkers in early severity stratification of COVID-19 patients

© 2021 by the authors.Pneumonia is the leading cause of hospital admission and mortality in coronavirus disease 2019 (COVID-19). We aimed to identify the cytokines responsible for lung damage and mortality. We prospectively recruited 108 COVID-19 patients between March and April 2020 and divided them into four groups according to the severity of respiratory symptoms. Twenty-eight healthy volunteers were used for normalization of the results. Multiple cytokines showed statistically significant differences between mild and critical patients. High HGF levels were associated with the critical group (OR = 3.51; p < 0.001; 95%CI = 1.95–6.33). Moreover, high IL-1α (OR = 1.36; p = 0.01; 95%CI = 1.07–1.73) and low IL-27 (OR = 0.58; p < 0.005; 95%CI = 0.39–0.85) greatly increased the risk of ending up in the severe group. This model was especially sensitive in order to predict critical status (AUC = 0.794; specificity = 69.74%; sensitivity = 81.25%). Furthermore, high levels of HGF and IL-1α showed significant results in the survival analysis (p = 0.033 and p = 0.011, respectively). HGF, IL-1α, and IL 27 at hospital admission were strongly associated with severe/critical COVID-19 patients and therefore are excellent predictors of bad prognosis. HGF and IL-1α were also mortality biomarkers.This work was supported by the Carlos III Health Institute (Grant COV20/00491)