Comparación de la angioplastia primaria frente a la angioplastia post-fibrinolisis en pacientes con infarto agudo de miocardio con elevación del segmento ST. El ensayo clínico GRACIA 4

Nuestro estudio comparó el intervencionismo coronario percutáneo primario (ICPP) y la fibrinolisis inmediata seguida de ICP (ICP post-fibrinolisis o ICPP-FBL) en pacientes con infarto agudo de miocardio con elevación del segmento ST (IAMEST). El objetivo primario fue el compuesto por muerte, reinfarto, nueva revascularización, rehospitalización y hemorragia grave a los 12 meses. Se incluyeron 355 pacientes (177 asignados a ICPP-FBL y 178 a ICPP). El objetivo primario se alcanzó en 25 pacientes (14,9%) en el grupo de ICPP-FBL y en 26 pacientes (15,0%) en el de ICPP (OR 0,99; IC al 95% 0,55-1,79; p=0.96). Del mismo modo, no hubo reducciones significativas en mortalidad (4,2% vs 4,6%; p=0,84), reinfarto (3,0% vs 4,7%; p=0,43), nueva revascularización (4,3% vs 5,3%; p=0,65), rehospitalización (9,8% vs 8,3%; p=0,64) o hemorragia grave (1,2% vs 0%; p=0,24). Concluimos que en pacientes con IAMEST el ICPP no fue clínicamente superior a la fibrinolisis seguida de ICP precoz programado.Departamento de Biología Celular, Histología y FarmacologíaDoctorado en Investigación en Ciencias de la Salu

Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry

The present dataset contains colour images acquired in a commercial Fuji apple orchard (Malus domestica Borkh. cv. Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry. The data provided in this article is related to the research article entitled “Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry” [1]. The Fuji-SfM dataset includes: (1) a set of 288 colour images and the corresponding annotations (apples segmentation masks) for training instance segmentation neural networks such as Mask-RCNN; (2) a set of 582 images defining a motion sequence of the scene which was used to generate the 3D model of 11 Fuji apple trees containing 1455 apples by using SfM; (3) the 3D point cloud of the scanned scene with the corresponding apple positions ground truth in global coordinates. With that, this is the first dataset for fruit detection containing images acquired in a motion sequence to build the 3D model of the scanned trees with SfM and including the corresponding 2D and 3D apple location annotations. This data allows the development, training, and test of fruit detection algorithms either based on RGB images, on coloured point clouds or on the combination of both types of data. Dades primàries associades a l'article http://hdl.handle.net/10459.1/68505This work was partly funded by the Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya (grant 2017 SGR 646), the Spanish Ministry of Economy and Competitiveness (project AGL2013-48297-C2-2-R) and the Spanish Ministry of Science, Innovation and Universities (project RTI2018-094222-B-I00). Part of the work was also developed within the framework of the project TEC2016-75976-R, financed by the Spanish Ministry of Economy, Industry and Competitiveness and the European Regional Development Fund (ERDF). The Spanish Ministry of Education is thanked for Mr. J. Gené’s pre-doctoral fellowships (FPU15/03355)

Clinical and epidemiologic characteristics of hospitalized oncological patients with hypercalcemia: a longitudinal, multicenter study

Background There are few studies that have analyzed the characteristics of hypercalcemia in hospitalized oncological patients. Our objectives were to describe the clinical characteristics of hospitalized patients with paraneoplastic hypercalcemia and to identify prognostic variables for mortality. Methods This was an observational, longitudinal, retrospective, and bicentric study. It included adult patients admitted to two hospitals in Málaga, Spain (2014–2018). The minimum follow-up period was 2 years or until death. Results A total of 154 patients were included; the majority (71.4%) were admitted to the internal medicine department. The median follow-up was 3.5 weeks (interquartile range [IQR] 1.1–11.5). The mean (standard deviation) age was 67.6 (12.3) years, with a predominance of males (58.4%). The median (IQR) serum calcium at admission was 13.2 (11.8–14.6) mg/dl. The most common neoplasms were pulmonary (27.3%), hematologic (23.4%), urological (13%), and breast (12.3%). Furthermore, 56.5% of cases had a known history of neoplasia at the time of diagnosis. The parathyroid hormone (PTH) level was determined in 24%; of these, 10.8% had elevated levels. In all, 95.5% of patients died during follow-up. The median survival was 3.4 weeks (95% confidence interval 2.6–4.3). Factors associated with higher mortality were age, serum calcium at admission, previous history of neoplasia, etiology other than multiple myeloma, and noncorrection of hypercalcemia. Conclusions In hospitalized patients, paraneoplastic hypercalcemia was associated with high short-term mortality. Several factors associated with a worse prognosis were identified in these patients.Funding for open access charge: Universidad de Málaga / CBU

Phases I–III Clinical Trials Using Adult Stem Cells

First randomized clinical trials have demonstrated that stem cell therapy can improve cardiac recovery after the acute phase of myocardial ischemia and in patients with chronic ischemic heart disease. Nevertheless, some trials have shown that conflicting results and uncertainties remain in the case of mechanisms of action and possible ways to improve clinical impact of stem cells in cardiac repair. In this paper we will examine the evidence available, analyze the main phase I and II randomized clinical trials and their limitations, discuss the key points in the design of future trials, and depict new directions of research in this fascinating field

Vibrotactile captioning of musical effects in audio-visual media as an alternative for deaf and hard of hearing people: An EEG study

Standard captioning for the deaf and hard of hearing people cannot transmit the emotional information that music provides in support of the narrative in audio-visual media. We explore an alternative method using vibrotactile stimulation as a possible channel to transmit the emotional information contained in an audio-visual soundtrack and, thus, elicit a greater emotional reaction in hearing-impaired people. To achieve this objective, we applied two one-minute videos that were based on image sequences that were unassociated with dramatic action, maximizing the effect of the music and vibrotactile stimuli. While viewing the video, using EEG we recorded the brain activity of 9 female participants with normal hearing, and 7 female participants with very severe and profound hearing loss. The results show that the same brain areas are activated in participants with normal hearing watching the video with the soundtrack, and in participants with hearing loss watching the same video with a soft and rhythmic vibrotactile stimulation on the palm and fingertips, although in different hemispheres. These brain areas (auditory cortex, superior temporal cortex, medial frontal cortex, inferior frontal gyrus, superior temporal pole and insula) have been consistently reported as areas involved in the emotional perception of music. We conclude that vibrotactile stimuli can generate cortex activation while watching audio-visual media in a similar way to sound. Thus, a further in-depth study of the possibilities of these stimuli can contribute to an alternative subtitling channel for enriching the audiovisual experience of hearing-impaired people.This work was supported in part by the Comunidad de Madrid through the SINFOTON2-CM Research Program under Grant S2018/NMT-4326-SINFOTON2-CM

Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry

The development of remote fruit detection systems able to identify and 3D locate fruits provides opportunities to improve the efficiency of agriculture management. Most of the current fruit detection systems are based on 2D image analysis. Although the use of 3D sensors is emerging, precise 3D fruit location is still a pending issue. This work presents a new methodology for fruit detection and 3D location consisting of: (1) 2D fruit detection and segmentation using Mask R-CNN instance segmentation neural network; (2) 3D point cloud generation of detected apples using structure-from-motion (SfM) photogrammetry; (3) projection of 2D image detections onto 3D space; (4) false positives removal using a trained support vector machine. This methodology was tested on 11 Fuji apple trees containing a total of 1455 apples. Results showed that, by combining instance segmentation with SfM the system performance increased from an F1-score of 0.816 (2D fruit detection) to 0.881 (3D fruit detection and location) with respect to the total amount of fruits. The main advantages of this methodology are the reduced number of false positives and the higher detection rate, while the main disadvantage is the high processing time required for SfM, which makes it presently unsuitable for real-time work. From these results, it can be concluded that the combination of instance segmentation and SfM provides high performance fruit detection with high 3D data precision. The dataset has been made publicly available and an interactive visualization of fruit detection results is accessible at http://www.grap.udl.cat/documents/photogrammetry_fruit_detection.html. Dades primàries associades a l'article http://hdl.handle.net/10459.1/68505This work was partly funded by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya (grant 2017 SGR646), the Spanish Ministry of Economy and Competitiveness (project AGL2013-48297-C2-2-R) and the Spanish Ministry of Science, Innovation and Universities (project RTI2018-094222-B-I00). Part of the work was also developed within the framework of the project TEC2016-75976-R, financed by the Spanish Ministry of Economy, Industry and Competitiveness and the European Regional Development Fund (ERDF). The Spanish Ministry of Educationis thanked for Mr. J.Gené’s pre-doctoral fellowships (FPU15/03355). We would also like to thank Nufri (especially Santiago Salamero and Oriol Morreres) and Vicens Maquinària Agrícola S.A. for their support during data acquisition, and Ernesto Membrillo and Roberto Maturino for their support in dataset labelling