Modeling internal flow and primary atomization in a simplex pressure-swirl atomizer

Authors from Universite¿ de Rouen Normandie thankfully acknowledge the computer resources at IDRIS, TGCC, and CINES under the allocation A0112B06153 and A0092B06153 made by Grand Equipement National de Calcul Intensit (GENCI) and also for the computing time at Centre Regional Informatique et d Applications Numeriques de Normandie (CRIANN) under the scientific Project No. 2006011. This work has been possible thanks to the CHAIRLIFT European Project No. 831881-CHAiRLIFT-H2020-CS2-CFP08-2018-01. Authors from Universitat Polite`cnica de Vale`ncia thankfully acknowledge the computer resources at Altamira (RES-IM-2020-1-0018) and MareNostrum (RES-IM-2020-412-0009) in the frame of the Spanish Supercomputing Network. Additionally, the support given to Dr. Marcos Carreres by Ministerio de Educacio¿n, Cultura y Deporte through the Estancias de movilidad en el extranjero Jose¿ Castillejo para jo¿venes doctores Grant (ref. CAS18/00289) within the Programa Estatal de Promocio¿n del Talento y su Empleabilidad en I+D+I, Subprograma Estatal de Movilidad, del Plan Estatal de I+D+I is gratefully acknowledged.Ferrando, D.; Carreres, M.; Belmar-Gil, M.; Cervelló-Sanz, D.; Duret, B.; Reveillon, J.; Salvador, FJ.... (2023). Modeling internal flow and primary atomization in a simplex pressure-swirl atomizer. Atomization and Sprays. 33(3):1-28. https://doi.org/10.1615/AtomizSpr.202204482412833

MED15 prion-like domain forms a coiled-coil responsible for its amyloid conversion and propagation

Altres ajuts: "la Caixa" Foundation i ICREA-Academia 2016A disordered to β-sheet transition was thought to drive the functional switch of Q/N-rich prions, similar to pathogenic amyloids. However, recent evidence indicates a critical role for coiled-coil (CC) regions within yeast prion domains in amyloid formation. We show that many human prion-like domains (PrLDs) contain CC regions that overlap with polyQ tracts. Most of the proteins bearing these domains are transcriptional coactivators, including the Mediator complex subunit 15 (MED15) involved in bridging enhancers and promoters. We demonstrate that the human MED15-PrLD forms homodimers in solution sustained by CC interactions and that it is this CC fold that mediates the transition towards a β-sheet amyloid state, its chemical or genetic disruption abolishing aggregation. As in functional yeast prions, a GFP globular domain adjacent to MED15-PrLD retains its structural integrity in the amyloid state. Expression of MED15-PrLD in human cells promotes the formation of cytoplasmic and perinuclear inclusions, kidnapping endogenous full-length MED15 to these aggregates in a prion-like manner. The prion-like properties of MED15 are conserved, suggesting novel mechanisms for the function and malfunction of this transcription coactivator

MED15 prion-like domain forms a coiled-coil responsible for its amyloid conversion and propagation

A disordered to β-sheet transition was thought to drive the functional switch of Q/N-rich prions, similar to pathogenic amyloids. However, recent evidence indicates a critical role for coiled-coil (CC) regions within yeast prion domains in amyloid formation. We show that many human prion-like domains (PrLDs) contain CC regions that overlap with polyQ tracts. Most of the proteins bearing these domains are transcriptional coactivators, including the Mediator complex subunit 15 (MED15) involved in bridging enhancers and promoters. We demonstrate that the human MED15-PrLD forms homodimers in solution sustained by CC interactions and that it is this CC fold that mediates the transition towards a β-sheet amyloid state, its chemical or genetic disruption abolishing aggregation. As in functional yeast prions, a GFP globular domain adjacent to MED15-PrLD retains its structural integrity in the amyloid state. Expression of MED15-PrLD in human cells promotes the formation of cytoplasmic and perinuclear inclusions, kidnapping endogenous full-length MED15 to these aggregates in a prion-like manner. The prion-like properties of MED15 are conserved, suggesting novel mechanisms for the function and malfunction of this transcription coactivator

Depression in internal medicine inpatients at the time of hospital discharge and referral to primary care

Background and objectives: This is the first multi-center study intended to document the prevalence, characteristics, and associations of depression in Medicine patients at the time of hospital discharge and their referral to Primary Care (PC). Methods: Adult patients randomly selected among consecutive admissions to Medicine wards in 8 hospitals in Spain, covering health districts, were examined in a two-phase ''case-finding'' procedure. Standardized, Spanish versions of instruments were used, including the Standardized Polyvalent Psychiatric Interview (SPPI) and Cumulative Illness Rating Scale (CIRS). Cases of depression were diagnosed according to ICD-10 general hospital research criteria. Results: Three hundred and twelve patients with treatable depression and 777 non-depressed controls were identified. In a conservative estimate, the global prevalence of major depression was 7.1%, dysthymia 4.2% and adjustment depression 7.1%, and 51.9% of cases were of moderate/ severe intensity. Depression was more frequent in women, the differences being significant in all categories of depression. The prevalence of depression was lower in individuals aged 85 or more years, the differences being significant in cases of both dysthymia and adjustment depression. A clear pattern of decreasing prevalence with age was observed in women. The depressed had as an average five medical systems affected, and higher CIRS scores compared with the controls, the differences being significant in cases of both major depression and dysthymia. Conclusions: This is the first report showing a considerable prevalence of treatable cases of depression in Medicine patients at the time of hospital discharge and referral to PC. Depression is associated with the severity of the medical condition, and differences observed by age and sex have clinical implications. Paper read at the 3rd Annual Meeting of the European Association of Psychosomatic Medicine, Nuremberg 2015. © 2022 Asociación Universitaria de Zaragoza para el Progreso de la Psiquiatría y la Salud Menta

Things are not always what they seem: From Cornelia de Lange to KBG phenotype in a girl with genetic variants in NIPBL and ANKRD11.

post-print509 K

Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdL

Evaluating face2gene as a tool to identify cornelia de lange syndrome by facial phenotypes

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS.Spanish Ministry of Science, Innovation and Universities/State Research Agency RTC-2017-6494-1; RTI2018-094434-B-I00 (MCIU/AEI/FEDER, UE) to P.G.-P.; Diputación General de Aragón - FEDER: European Social Fund [Grupo de Referencia B32_17R, to J.P.] as well as funds from the European JPIAMR-VRI network “CONNECT” to P.G.-P.; Medical Faculty of the University of Lübeck J09-2017 to I. P.; German Federal Ministry of Education and Research (BMBF

Isolation and HPLC Quantitative Analysis of Antioxidant Flavonoids from Alternanthera tenella Colla

Phytochemical analysis of the antioxidant ethanolic extract of Alternanthera tenella Colla led to the isolation of six flavonoids, acacetin 8

On the Influence of VOCs on New Particle Growth in a Continental-Mediterranean Region

[Abstract] A field campaign has been performed in the Madrid region to study the VOC influence in the growth of new particles in ambient air. A number of instruments have been deployed to characterize the main pollutant gases and particle properties and composition. The measurements were performed simultaneously at three sites (rural, urban background and urban traffic influenced) in the period 1–17 July 2019. The sites: Tres Cantos (rural), CIEMAT (urban background) and Leganés (urban traffic) were located within the Madrid airshed. Particle size distributions, mass concentrations at fractions PM10, PM2.5 and PM1, black carbon, VOCs species and gaseous pollutants (NOx and O3) were obtained in the sites. Some supplementary measurements were obtained in at least one of the sites: meteorological parameters, non-refractory submicron aerosol species and vertical profiles of aerosol optical properties. It has been observed that the new particle formation (NPF) events, nucleation and subsequent growth, happened at a regional scale, although differently among the sites. In the rural site, fewer events than expected were observed because of the high temperatures that affected the BVOC emissions. In the urban background site, the highest number of events was reached. In this station, it is common to receive air masses from the nearby forest and from the urban area, producing a mix of conditions with high BVOC and AVOC concentrations. In the urban traffic site, several NPF cases appeared, being a site dominated by AVOCs. Among the BVOCs measured in the three stations, the most common were α-Pinene and Limonene. Among the AVOCs measured, aromatics and linear hydrocarbon compounds for C10 and above were found. The linear group was found to be predominant during the NPF event days in the urban background site. This work provides new insights about the aerosol-forming precursors and growth of new particles in the Madrid region.This research has been partially funded by the CRISOL Project (CGL2017-85344-R MINECO/AEI/FEDER, UE), OASIS project (PID2021-127885OB-I00 fund by MCIN/ AEI/10.13039/501100011033 and by 'ERDF A way of making Europe') and by the TIGAS-CM project (Madrid Regional Government Y2018/EMT-5177)Comunidad de Madrid; Y2018/EMT-517