Caracterización del interfaz forestal/urbano empleando LiDAR como herramienta para la estimación del riesgo de daños por incendios forestales

[EN] Galicia is a region in NW Spain which is usually affected by a high number of forest fires, and it should meet the current regulations regarding the distance between forests and buildings. This paper aims to identify and characterize woodlands and classify buildings according to their fire risk, for a 36 km2 area in Forcarei (Pontevedra, Spain). We used LiDAR data to generate three spatial models (DTM: Digital Terrain Model, DSM: Digital Surface Model and nDSM: Normalized Digital Surface Model) and two statistics to characterize the forest stands (density of dominant trees per hectare and their average height). The identification of forested areas was performed using an object-based classification method using the intensity image, the height model and an orthophotograph of the area, and a kappa coefficient of 0.82 was obtained in the validation. The woodlands were reclassified according to the magnitude of a possible fire, based on the density and the average height of the woodlands. The forest stands were mapped according to the magnitude of a possible fire and it was found that 1.18 km2 would be susceptible to a low magnitude fire, 3.75 km2 to a medium magnitude fire and 2.25 km2 to a fire of a high magnitude. Afterwards, it was determined whether the buildings in the area complied with the legislation relating to minimum distance from the forested areas (30 meters). For those that did not meet this distance, the risk of damage in case of a wildfire was calculated. The result was that 43.01% of buildings in the area complied with the regulations, 9.95% were located in a very low risk area, 25.74% in a low risk location, 12.37% in a medium risk area and 8.93% were in a high or very high risk area.S

La raza sayaguesa base de la marca silomaña. Actualidad y posibilidades

La utilización de los pastos de la montaña de León unido a una raza autóctona, la raza sayaguesa, para la obtención de un producto de calidad y diferenciado como es el buey. Nos ha permitido obtener un producto de unas características hasta ahora desconocidas, con un perfil de ácidos grasos mono y poliinsaturados, y unas características físico-químicas que hacen que nuestro producto puede considerarse como un “ALIMENTO FUNCIONAL”

Pancreatic and psoas abscesses as a late complication of intravesical administration of bacillus Calmette-Guerin for bladder cancer: a case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Bacillus Calmette-Guerin (BCG) is a live attenuated strain of <it>Mycobacterium bovis</it> that has been used to treat urothelial carcinoma since 1976, and has been reported to eradicate disease in more than 70% of patients with <it>in situ</it> and stage I disease. To the best of our knowledge, we report the first case of disseminated bacillus Calmette-Guerin infection causing multiple abscesses affecting the pancreatic head and right psoas muscle, diagnosed 5 years after intravesical treatment with bacillus Calmette-Guerin therapy for bladder cancer.</p> <p>Case presentation</p> <p>An 83-year-old Caucasian man was hospitalized with a 2-month history of back pain, anorexia, generalized weakness and a 47-pound weight loss. He had previously undergone two transurethral resections for high-grade transitional cell carcinoma of the bladder and had received 12 intravesical bacillus Calmette-Guerin instillations without any complications. He complained of abdominal pain in his right flank. A computed tomography scan of the abdomen showed multiple abscesses affecting the pancreatic head and right psoas muscle. Growth of <it>Mycobacterium bovis</it> was determined in cultures of the purulent material obtained by surgical drainage of the abscesses.</p> <p>Conclusions</p> <p>This case illustrates the fact that although intravesical administration of bacillus Calmette-Guerin is generally considered to be safe, it is not exempt from complications and these could appear immediately after treatment or as a delayed complication many years later.</p

Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification

[EN] Background The microvessels area (MVA), derived from microvascular proliferation, is a biomarker useful for high-grade glioma classification. Nevertheless, its measurement is costly, labor-intense, and invasive. Finding radiologic correlations with MVA could provide a complementary non-invasive approach without an extra cost and labor intensity and from the first stage. This study aims to correlate imaging markers, such as relative cerebral blood volume (rCBV), and local MVA in IDH-wildtype glioblastoma, and to propose this imaging marker as useful for astrocytoma grade 4 classification. Methods Data from 73 tissue blocks belonging to 17 IDH-wildtype glioblastomas and 7 blocks from 2 IDH-mutant astrocytomas were compiled from the Ivy GAP database. MRI processing and rCBV quantification were carried out using ONCOhabitats methodology. Histologic and MRI co-registration was done manually with experts' supervision, achieving an accuracy of 88.8% of overlay. Spearman's correlation was used to analyze the association between rCBV and microvessel area. Mann-Whitney test was used to study differences of rCBV between blocks with presence or absence of microvessels in IDH-wildtype glioblastoma, as well as to find differences with IDH-mutant astrocytoma samples. Results Significant positive correlations were found between rCBV and microvessel area in the IDH-wildtype blocks (p < 0.001), as well as significant differences in rCBV were found between blocks with microvascular proliferation and blocks without it (p < 0.0001). In addition, significant differences in rCBV were found between IDH-wildtype glioblastoma and IDH-mutant astrocytoma samples, being 2-2.5 times higher rCBV values in IDH-wildtype glioblastoma samples. Conclusions The proposed rCBV marker, calculated from diagnostic MRIs, can detect in IDH-wildtype glioblastoma those regions with microvessels from those without it, and it is significantly correlated with local microvessels area. In addition, the proposed rCBV marker can differentiate the IDH mutation status, providing a complementary non-invasive method for high-grade glioma classification.This work was funded by grants from the National Plan for Scientific and Technical Research and Innovation 2017-2020, No. PID2019-104978RB-I00) (JMGG); H2020-SC1-2016-CNECT Project (No. 727560) (JMGG), and H2020SC1-BHC-2018-2020 (No. 825750) (JMGG). M.A.T was supported by DPI201680054-R (Programa Estatal de Promocion del Talento y su Empleabilidad en I + D + i). EFG was supported by the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 844646. The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.Álvarez-Torres, MDM.; Fuster García, E.; Juan-Albarracín, J.; Reynes, G.; Aparici-Robles, F.; Ferrer Lozano, J.; Garcia-Gomez, JM. (2022). Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification. BMC Cancer. 22(1):1-13. https://doi.org/10.1186/s12885-021-09117-411322

Artificial Intelligence on FDG PET Images Identifies Mild Cognitive Impairment Patients with Neurodegenerative Disease

[EN] The purpose of this project is to develop and validate a Deep Learning (DL) FDG PET imaging algorithm able to identify patients with any neurodegenerative diseases (Alzheimer's Disease (AD), Frontotemporal Degeneration (FTD) or Dementia with Lewy Bodies (DLB)) among patients with Mild Cognitive Impairment (MCI). A 3D Convolutional neural network was trained using images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI dataset used for the model training and testing consisted of 822 subjects (472 AD and 350 MCI). The validation was performed on an independent dataset from La Fe University and Polytechnic Hospital. This dataset contained 90 subjects with MCI, 71 of them developed a neurodegenerative disease (64 AD, 4 FTD and 3 DLB) while 19 did not associate any neurodegenerative disease. The model had 79% accuracy, 88% sensitivity and 71% specificity in the identification of patients with neurodegenerative diseases tested on the 10% ADNI dataset, achieving an area under the receiver operating characteristic curve (AUC) of 0.90. On the external validation, the model preserved 80% balanced accuracy, 75% sensitivity, 84% specificity and 0.86 AUC. This binary classifier model based on FDG PET images allows the early prediction of neurodegenerative diseases in MCI patients in standard clinical settings with an overall 80% classification balanced accuracy.This work was financially supported by INBIO 2019 (DEEPBRAIN), INNVA1/2020/83(DEEPPET) funded by Generalitat Valenciana, and PID2019-107790RB-C22 funded by MCIN/AEI/10.13039/501100011033/. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org).The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.Prats-Climent, J.; Gandia-Ferrero, MT.; Torres-Espallardo, I.; Álvarez-Sanchez, L.; Martinez-Sanchis, B.; Cháfer-Pericás, C.; Gómez-Rico, I.... (2022). Artificial Intelligence on FDG PET Images Identifies Mild Cognitive Impairment Patients with Neurodegenerative Disease. Journal of Medical Systems. 46(8):1-13. https://doi.org/10.1007/s10916-022-01836-w11346

Assessing the presence of oligoclonal IgM bands as a prognostic biomarker of cognitive decline in the early stages of multiple sclerosis

Bandes oligoclonals; Esclerosi múltiple; Disfunció cognitivaBandas oligoclonales; Esclerosis múltiple; Disfunción cognitivaOligoclonal bands; Multiple sclerosis; Cognitive dysfunctionBackground: An association has been found between the presence of lipid-specific oligoclonal IgM bands (LS-OCMB) in cerebrospinal fluid and a more severe clinical multiple sclerosis course. Objective: To investigate lipid-specific oligoclonal IgM bands as a prognostic biomarker of cognitive impairment in the early stages of multiple sclerosis. Methods: Forty-four patients underwent neuropsychological assessment at baseline and 4 years. Cognitive performance at follow-up was compared adjusting by age, education, anxiety-depression, and baseline performance. Results: LS-OCMB+ patients only performed worse for Long-Term Storage in the Selective Reminding Test (p = .018). Conclusion: There are no remarkable cognitive differences between LS-OCMB- and LS-OCMB+ patients in the early stages of MS

La Base de Datos de Fallas Activas en el Cuaternario de Iberia (QAFI v.2.0)

ABSTRACT. The Quaternary Active Faults Database of Iberia (QAFI) is an initiative lead by the Institute of Geology and Mines of Spain (IGME) for building a public repository of scientific data regarding faults having documented activity during the last 2.59 Ma (Quaternary). QAFI also addresses a need to transfer geologic knowledge to practitioners of seismic hazard and risk in Iberia by identifying and characterizing seismogenic fault-sources. QAFI is populated by the information freely provided by more than 40 Earth science researchers, storing to date a total of 262 records. In this article we describe the development and evolution of the database, as well as its internal architecture. Additionally, a first global analysis of the data is provided with a special focus on length and slip-rate fault parameters. Finally, the database completeness and the internal consistency of the data are discussed. Even though QAFI v.2.0 is the most current resource for calculating fault-related seismic hazard in Iberia, the database is still incomplete and requires further review.RESUMEN. La Base de Datos de Fallas Activas de Iberia (QAFI) es una iniciativa promovida por el Instituto Geológico y Minero de España (IGME) para construir un repositorio público de información científica sobre fallas con actividad en los últimos 2,59 Ma (Cuaternario). Además, la QAFI persigue establecer una base sobre la que facilitar la transferencia de conocimiento geológico al ámbito tecnológico de la gestión del riesgo sísmico en Iberia, en particular en la identificación y caracterización de fuentes sismogénicas tipo falla. La QAFI se ha construido a partir de la información proporcionada de modo altruista por más de 40 investigadores en ciencias de la Tierra conteniendo actualmente un total de de 262 registros. En este artículo se describe la concepción y evolución de la base de datos, y su arquitectura interna. Además, se ofrece un primer análisis global de los datos que contiene, con especial interés en parámetros tan importantes como la longitud y tasa de deslizamiento de las fallas. Finalmente se discuten dos temas cruciales en cualquier base de datos: su completitud y la homogeneidad de los datos. Se concluye que QAFI v.2.0, pese a ser la fuente más actualizada de información disponible en Iberia sobre peligrosidad sísmica de fallas concretas, dista aun de ser completa, por lo que nuevas revisiones y versiones deberán seguir llevándose a cabo en el futuro