Identificación y caracterización de especies de Botryosphaeriaceae asociadas a muerte regresiva de manzanos

48 p.Chile se encuentra dentro de los principales países exportadores de manzanas (Malus x domestica) en el hemisferio sur, con una superficie de 32.370 hectáreas aproximadamente. La Región del Maule es donde se encuentra la mayor concentración de superficie plantada con 19.636 hectáreas. Sin embargo, la producción de este frutal se ve afectada por problemas de enfermedades de tipo fungoso. Previamente, en Chile solo se ha identificado a Botryosphaeria dothidea causando muerte regresiva en manzanos, estudio de la década de los 80. En este sentido, recientemente se reportó la presencia de Diplodia seriata causando muerte regresiva en la Región del Maule. Por lo tanto, el objetivo de este trabajo fue identificar y caracterizar especies de la familia Botryosphaeriaceae a través de una caracterización cultural, morfológica y molecular utilizando doce aislados obtenidos desde brazos con muerte regresiva de diferentes zonas de Chile. Además, se determinó la patogenicidad en ramillas cv. Cripps Pink, Fuji, Gala y Granny Smith y en frutos de manzana cv. Fuji, Pink Lady, Braeburn, Granny Smith, Premium Gala, Modi, Red Chief y Scarlett. Los resultados indican que a través de características culturales, morfológicas y moleculares se identificaron nueve aislados como Diplodia seriata, dos aislados a la especie Neofusicoccum arbuti y un solo aislado como Lasiodiplodia theobromae. Todos los aislados causaron lesiones necróticas en ramillas y pudrición en frutos. Finalmente, este trabajo identificó a D. seriata, L. theobromae y N. arbuti como especies de hongos causales de la muerte regresiva en manzanos en Chile./ABSTRACT: Chile is located within the main apple exporting countries (Malus x domestica) in the southern hemisphere, with an area of approximately 32,370 hectares. The Maule Region is where the highest concentration of planted area with 19,636 hectares. However, the production of this fruit is affected by fungal diseases. Previously, in Chile only Botryosphaeria dothidea has been identified causing dieback in apple trees, but the study was conducted during the 80s. In this sense, recently the presence of Diplodia seriata was reported causing apple dieback in the Region of Maule. Therefore, the objective of this work was to identify and characterize species belonging to the family Botryosphaeriaceae through a cultural, morphological and molecular characterization using twelve isolates obtained from arms dieback of different areas of apple production in Chile. In addition, pathogenicity was determined on twigs (2yrs-old) of cvs. Cripps Pink, Fuji, Gala and Granny Smith, and on apple fruits cv. Cripps Pink, Fuji, Braeburn, Granny Smith, Gala, Modi, Red Chief and Scarlett. The results indicate that through cultural, morphological and molecular characteristics nine isolates were identified as Diplodia seriata, two isolates as Neofusicoccum arbuti and one isolate as Lasiodiplodia theobromae. All isolates caused necrotic lesions in twigs and rot in fruits. Finally, this work identified to D. seriata, L. theobromae and N. arbuti as species of fungal belonging to Botryosphaeriaceae causing symptoms of dieback in apple trees in Chile

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use