Identifying human diamine sensors for death related putrescine and cadaverine molecules

Pungent chemical compounds originating from decaying tissue are strong drivers of animal behavior. Two of the best-characterized death smell components are putrescine (PUT) and cadaverine (CAD), foul-smelling molecules produced by decarboxylation of amino acids during decomposition. These volatile polyamines act as 'necromones', triggering avoidance or attractive responses, which are fundamental for the survival of a wide range of species. The few studies that have attempted to identify the cognate receptors for these molecules have suggested the involvement of the seven-helix trace amine-associated receptors (TAARs), localized in the olfactory epithelium. However, very little is known about the precise chemosensory receptors that sense these compounds in the majority of organisms and the molecular basis of their interactions. In this work, we have used computational strategies to characterize the binding between PUT and CAD with the TAAR6 and TAAR8 human receptors. Sequence analysis, homology modeling, docking and molecular dynamics studies suggest a tandem of negatively charged aspartates in the binding pocket of these receptors which are likely to be involved in the recognition of these small biogenic diamines

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Ecos de la academia: Revista de la Facultad de Educación, Ciencia y Tecnología - FECYT Nro 6

Ecos de la academia, Revista de la Facultad de Educación Ciencia y Tecnología es una publicación científica de la Universidad Técnica del Norte, con revisión por pares a doble ciego que publica artículos en idioma español, quichua, portugués e inglés. Se edita con una frecuencia semestral con dos números por año.En ella se divulgan trabajos originales e inéditos generados por los investigadores, docentes y estudiantes de la FECYT, y contribuciones de profesionales de instituciones docentes e investigativas dentro y fuera del país, con calidad, originalidad y relevancia en las áreas de ciencias sociales y tecnología aplicada.Modelos multidimensionales del bienestar en contextos de enseñanza- aprendizaje: una revisión sistemática. Nuevas tendencias para el área académica de la Publicidad en la zona 1 del Ecuador. Propuesta de un curso de escritura académica bajo la base de modelos experienciales. Aproximación al estudio de las emociones. Seguimiento a egresados y graduados para actualizar el perfil de egreso y profesional. Impacto de la Gerencia de Calidad en el clima organizacional en Educación Básica. Comunicación efectiva del gerente educativo orientada al manejo de conflictos en el personal docente. Meritocracia: Democratización o exclusión en el acceso a la educación superior en Ecuador. Asertividad y desempeño académico en estudiantes universitarios. La creatividad en la formación profesional. Aspectos metodológicos en el proceso de enseñanza- aprendizaje de la gimnasia en estudiantes de Educación Física. English Language Learning Interaction through Web 2.0 Technologies. La sistematización de la práctica educativa y su relación con la metodología de la investigación. El ozono y la oxigenación hiperbárica: una vía para mejorar la recuperación en lesiones deportivas. La labor tutorial: Independencia del aprendizaje en el contexto universitario. Motivación hacia la profesión docente en la Enseñanza Secundaria. El uso académico de Facebook y WhatsApp en estudiantes universitarios... La educación superior en Ecuador: situación actual y factores de mejora de la calidad. El Proyecto de Investigación “Imbabura Étnica”

Evaluation of factors leading to poor outcomes for pediatric acute lymphoblastic leukemia in Mexico: a multi-institutional report of 2,116 patients

Background and aimsPediatric acute lymphoblastic leukemia (ALL) survival rates in low- and middle-income countries are lower due to deficiencies in multilevel factors, including access to timely diagnosis, risk-stratified therapy, and comprehensive supportive care. This retrospective study aimed to analyze outcomes for pediatric ALL at 16 centers in Mexico.MethodsPatients <18 years of age with newly diagnosed B- and T-cell ALL treated between January 2011 and December 2019 were included. Clinical and biological characteristics and their association with outcomes were examined.ResultsOverall, 2,116 patients with a median age of 6.3 years were included. B-cell immunophenotype was identified in 1,889 (89.3%) patients. The median white blood cells at diagnosis were 11.2.5 × 103/mm3. CNS-1 status was reported in 1,810 (85.5%), CNS-2 in 67 (3.2%), and CNS-3 in 61 (2.9%). A total of 1,488 patients (70.4%) were classified as high-risk at diagnosis. However, in 52.5% (991/1,889) of patients with B-cell ALL, the reported risk group did not match the calculated risk group allocation based on National Cancer Institute (NCI) criteria. Fluorescence in situ hybridization (FISH) and PCR tests were performed for 407 (19.2%) and 736 (34.8%) patients, respectively. Minimal residual disease (MRD) during induction was performed in 1,158 patients (54.7%). The median follow-up was 3.7 years. During induction, 191 patients died (9.1%), and 45 patients (2.1%) experienced induction failure. A total of 365 deaths (17.3%) occurred, including 174 deaths after remission. Six percent (176) of patients abandoned treatment. The 5-year event-free survival (EFS) was 58.9% ± 1.7% for B-cell ALL and 47.4% ± 5.9% for T-cell ALL, while the 5-year overall survival (OS) was 67.5% ± 1.6% for B-cell ALL and 54.3% ± 0.6% for T-cell ALL. The 5-year cumulative incidence of central nervous system (CNS) relapse was 5.5% ± 0.6%. For the whole cohort, significantly higher outcomes were seen for patients aged 1–10 years, with DNA index >0.9, with hyperdiploid ALL, and without substantial treatment modifications. In multivariable analyses, age and Day 15 MRD continued to have a significant effect on EFS.ConclusionOutcomes in this multi-institutional cohort describe poor outcomes, influenced by incomplete and inconsistent risk stratification, early toxic death, high on-treatment mortality, and high CNS relapse rate. Adopting comprehensive risk-stratification strategies, evidence-informed de-intensification for favorable-risk patients and optimized supportive care could improve outcomes

Gestión del conocimiento: perspectiva multidisciplinaria. Volumen 13

El libro “Gestión del Conocimiento. Perspectiva Multidisciplinaria”, Volumen 13 de la Colección Unión Global, es resultado de investigaciones. Los capítulos del libro, son resultados de investigaciones desarrolladas por sus autores. El libro es una publicación internacional, seriada, continua, arbitrada, de acceso abierto a todas las áreas del conocimiento, orientada a contribuir con procesos de gestión del conocimiento científico, tecnológico y humanístico. Con esta colección, se aspira contribuir con el cultivo, la comprensión, la recopilación y la apropiación social del conocimiento en cuanto a patrimonio intangible de la humanidad, con el propósito de hacer aportes con la transformación de las relaciones socioculturales que sustentan la construcción social de los saberes y su reconocimiento como bien público. El libro “Gestión del Conocimiento. Perspectiva Multidisciplinaria”, Volumen 13, de la Colección Unión Global, es resultado de investigaciones. Los capítulos del libro, son resultados de investigaciones desarrolladas por sus autores. El libro cuenta con el apoyo de los grupos de investigación: Universidad Sur del Lago “Jesús María Semprúm” (UNESUR) - Zulia – Venezuela; Universidad Politécnica Territorial de Falcón Alonso Gamero (UPTFAG) - Falcón – Venezuela; Universidad Politécnica Territorial de Mérida Kléber Ramírez (UPTM) - Mérida - Venezuela; Universidad Guanajuato (UG) - Campus Celaya - Salvatierra - Cuerpo Académico de Biodesarrollo y Bioeconomía en las Organizaciones y Políticas Públicas (CABBOPP) - Guanajuato – México; Centro de Altos Estudios de Venezuela (CEALEVE) - Zulia – Venezuela, Centro Integral de Formación Educativa Especializada del Sur (CIFE - SUR) - Zulia – Venezuela; Centro de Investigaciones Internacionales SAS (CEDINTER) - Antioquia – Colombia y diferentes grupos de investigación del ámbito nacional e internacional que hoy se unen para estrechar vínculos investigativos, para que sus aportes científicos formen parte de los libros que se publiquen en formatos digital e impreso

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Ensemble prediction of mitochondrial toxicity using machine learning technology

Mitochondria are intracellular organelles found in most eukaryotic cells. Mitochondrial function includes the generation of cellular energy, maintenance of cellular homeostasis, and metabolic processes. Mitochondrial impairment has increasingly been recognized as a contributor to drug-induced toxicity. We have developed predictive models using machine learning methods for the prediction of the in vitro outcome of the MMP and the GluGal assays. These models were built using the open-source software Flame, which supports the combination of models in ensembles and the extension of the training data with further experimental data, continuously improving the predictive power of the models Despite the large amount of available data for training of models, most compounds are evaluated as negative, resulting in an imbalanced class distribution. This paper demonstrates the application of a combination of equally distributed low-level models in an ensemble to account for the imbalance in the training set resulting in a classifier providing high sensitivity and specificity of 92 and 87% respectively. The model generated can further be integrated with mechanistic in vitro data for improved screening for mitochondrial toxicity.This research was funded from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreements eTRANSAFE (777365). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA companies in kind contribution

Flame: an open source framework for model development, hosting, and usage in production environments

This article describes Flame, an open source software for building predictive models and supporting their use in production environments. Flame is a web application with a web-based graphic interface, which can be used as a desktop application or installed in a server receiving requests from multiple users. Models can be built starting from any collection of biologically annotated chemical structures since the software supports structural normalization, molecular descriptor calculation, and machine learning model generation using predefined workflows. The model building workflow can be customized from the graphic interface, selecting the type of normalization, molecular descriptors, and machine learning algorithm to be used from a panel of state-of-the-art methods implemented natively. Moreover, Flame implements a mechanism allowing to extend its source code, adding unlimited model customization. Models generated with Flame can be easily exported, facilitating collaborative model development. All models are stored in a model repository supporting model versioning. Models are identified by unique model IDs and include detailed documentation formatted using widely accepted standards. The current version is the result of nearly 3 years of development in collaboration with users from the pharmaceutical industry within the IMI eTRANSAFE project, which aims, among other objectives, to develop high-quality predictive models based on shared legacy data for assessing the safety of drug candidates.This work has received funding from the eTRANSAFE project (Grant Agreement No. 777365), developed under the Innovative Medicines Initiative Joint Undertaking (IMI2), resources of which are composed of a financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in kind contributions. The authors of this article are also involved in other related IMI projects which contributed funding, such as TransQST (No. 116030) as well as the H2020 EU-ToxRisk project (No. 681002) and FAIRplus (No. 802750). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), funded by ISCIII and FEDER (PT17/0009/0014). The DCEXS is a ‘Unidad de Excelencia María de Maeztu’, funded by the AEI (CEX2018-000782-M). The GRIB is also supported by the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR), Generalitat de Catalunya (2017 SGR 00519)

Atmospheric deterioration of ceramic building materials and future trends in the field: a review

Multiple techniques have been developed and implemented around the world to monitor structures and minimize the costs of repairing, maintaining, and losing ceramic building materials due to environmental factors. Understanding the different degradation phenomena that affect ceramic building materials and evaluating their condition can help reduce material losses caused by deterioration and the need for interventions. This study reviews the main forms of atmospheric degradation that affect ceramic materials and the commonly employed methods to evaluate their deterioration. The aim is to illustrate the different types of atmospheric deterioration that affect ceramic materials and to demonstrate the current monitoring methods and testing. In addition to a literature review, a bibliometric analysis was conducted to highlight the available tools to counter atmospheric deterioration. The analysis shows that CO2, sulfates, and temperature are the most important types of degradation for ceramic construction materials. It was also discovered that due to their porous nature, ceramic construction materials require careful control as contaminants and water can easily penetrate them. The two most severe types of deterioration identified in this analysis for reinforced concrete were chloride-induced corrosion and carbonation