Residual ridge resorption on mandibular bone. Pathology and quality of life

La colocación de implantes dentales y de dentaduras artificiales en pacientes parcial o totalmente desdentados, ha mejorado la calidad y la esperanza de vida de millones de estos pacientes en el mundo. Sin embargo, de existir atrofia mandibular a causa de la reabsorción ósea de los bordes residuales mandibulares, las posibilidades de tratamiento por estos medios protésicos y de cirugía maxilofacial disminuyen en forma considerable. En este trabajo de revisión se ha definido el concepto de atrofia mandibular, su etiología y patología. Así mismo se han revisado los tratamientos buco-dentales y los pronósticos más frecuentes relacionados con la atrofia mandibular, que pueden incrementar las expectativas de la calidad de vida de estos pacientes.Abstract. The employment of titanium dental implants and total dentures in edentulous patients has increased the quality and life expectancy of millions of these patients around the world. Nevertheless, if mandibular atrophy exists because of bone resorption of mandibular residual ridges, related prosthetic and maxillofacial treatment possibilities fall considerably. In this review it has been defined the concept of mandibular resorption, its etiology and pathology. Also buco-dental treatments and the most frequent prognoses related to the mandibular atrophy have been reviewed, which can increase the expectations of the quality of life of these patients

Cartografía social como herramienta de diagnóstico participativo en la actividad turística.

Este estudio propone la aplicación de la cartografía social como herramienta de diagnóstico participativo -de abajo hacia arriba- en torno a la identificación de problemas para la planificación del turismo en el cantón Limón-Indanza (provincia de Morona Santiago) ubicado al sureste de la Amazonía del Ecuador. El enfoque del estudio fue cualitativo, a través de la cartografía social y observación participante mediante un taller con las partes interesadas. Los resultados muestran un diagnóstico de la situación turística como punto de partida para desarrollar otras herramientas y dar pasos hacia la planificación del territorio en materia de turismo. De hecho, se encontraron problemáticas relativas a un desarrollo espontáneo del turismo en torno a la singularidad de sus atractivos turísticos, pero que se ve amenazado por la falta de asociatividad entre sus partes interesadas y de amenazas más grandes como la minería. Finalmente, se sugiere la utilización de herramientas participativas para captar las percepciones, imaginarios y construcciones sociales en torno al turismo y se recomienda el uso de la cartografía social como herramienta de diagnóstico participativo debido a la inclusión participación, camaradería y costo-beneficio que posee la herramienta

Frequency of gastronintestinal parasite of dogs in public parks in two neighboring municipalities of state of Mexico

Artículo científicoLa contaminación de suelos por parásitos gastrointestinales representa un problema mundial y un riesgo a la salud. Objetivo. Determinar la presencia de parásitos en heces de perros en los parques públicos del área. Materiales y métodos. Se recolectaron muestras de heces en 27 parques públicos de Metepec y Toluca Estado de México, mismos que se procesaron con 3 técnicas parasitológicas; 81.4% de los parques públicos resultaron positivos a parásitos gastrointestinales, con una frecuencia global de muestras del 16.5%. El porcentaje de parasitosis con potencial zoonótico fue de 81.3%; Toxocara spp, Ancylostoma spp y Giardia spp fueron las especies zoonóticas identificadas. Conclusiones. Los resultados indican que los parques de la zona conurbada de Toluca representan un problema de salud pública importante al ser una fuente de parásitos gastrointestinales zoonóticos de perro

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones

The Tree Biodiversity Network (BIOTREE-NET): prospects for biodiversity research and conservation in the Neotropics

Biodiversity research and conservation efforts in the tropics are hindered by the lack of knowledge of the assemblages found there, with many species undescribed or poorly known. Our initiative, the Tree Biodiversity Network (BIOTREE-NET), aims to address this problem by assembling georeferenced data from a wide range of sources, making these data easily accessible and easily queried, and promoting data sharing. The database (GIVD ID NA-00-002) currently comprises ca. 50,000 tree records of ca. 5,000 species (230 in the IUCN Red List) from \u3e2,000 forest plots in 11 countries. The focus is on trees because of their pivotal role in tropical forest ecosystems (which contain most of the world\u27s biodiversity) in terms of ecosystem function, carbon storage and effects on other species. BIOTREE-NET currently focuses on southern Mexico and Central America, but we aim to expand coverage to other parts of tropical America. The database is relational, comprising 12 linked data tables. We summarise its structure and contents. Key tables contain data on forest plots (including size, location and date(s) sampled), individual trees (including diameter, when available, and both recorded and standardised species name), species (including biological traits of each species) and the researchers who collected the data. Many types of queries are facilitated and species distribution modelling is enabled. Examining the data in BIOTREE-NET to date, we found an uneven distribution of data in space and across biomes, reflecting the general state of knowledge of the tropics. More than 90% of the data were collected since 1990 and plot size varies widely, but with most less than one hectare in size. A wide range of minimum sizes is used to define a \u27tree\u27. The database helps to identify gaps that need filling by further data collection and collation. The data can be publicly accessed through a web application at http://portal.biotreenet.com. Researchers are invited and encouraged to contribute data to BIOTREE-NET

Anti-tumour necrosis factor discontinuation in inflammatory bowel disease patients in remission: study protocol of a prospective, multicentre, randomized clinical trial

Background: Patients with inflammatory bowel disease who achieve remission with anti-tumour necrosis factor (anti-TNF) drugs may have treatment withdrawn due to safety concerns and cost considerations, but there is a lack of prospective, controlled data investigating this strategy. The primary study aim is to compare the rates of clinical remission at 1?year in patients who discontinue anti-TNF treatment versus those who continue treatment. Methods: This is an ongoing, prospective, double-blind, multicentre, randomized, placebo-controlled study in patients with Crohn?s disease or ulcerative colitis who have achieved clinical remission for ?6?months with an anti-TNF treatment and an immunosuppressant. Patients are being randomized 1:1 to discontinue anti-TNF therapy or continue therapy. Randomization stratifies patients by the type of inflammatory bowel disease and drug (infliximab versus adalimumab) at study inclusion. The primary endpoint of the study is sustained clinical remission at 1?year. Other endpoints include endoscopic and radiological activity, patient-reported outcomes (quality of life, work productivity), safety and predictive factors for relapse. The required sample size is 194 patients. In addition to the main analysis (discontinuation versus continuation), subanalyses will include stratification by type of inflammatory bowel disease, phenotype and previous treatment. Biological samples will be obtained to identify factors predictive of relapse after treatment withdrawal. Results: Enrolment began in 2016, and the study is expected to end in 2020. Conclusions: This study will contribute prospective, controlled data on outcomes and predictors of relapse in patients with inflammatory bowel disease after withdrawal of anti-TNF agents following achievement of clinical remission. Clinical trial reference number: EudraCT 2015-001410-1

La Red Internacional de Inventarios Forestales (BIOTREE-NET) en Mesoamérica: avances, retos y perspectivas futuras

Conservation efforts in Neotropical regions are often hindered by lack of data, since for many species there is a vacuum of information, and many species have not even been described yet. The International Network of Forest Inventory Plots (BIOTREE-NET) gathers and facilitates access to tree data from forest inventory plots in Mesoamerica, while encouraging data exchange between researchers, managers and conservationists. The information is organised and standardised into a single database that includes spatially explicit data. This article describes the scope and objectives of the network, its progress, and the challenges and future perspectives. The database includes above 50000 tree records of over 5000 species from more than 2000 plots distributed from southern Mexico through to Panama. Information is heterogeneous, both in nature and shape, as well as in the geographical coverage of inventory plots. The database has a relational structure, with 12 inter-connected tables that include information about plots, species names, dbh, and functional attributes of trees. A new system that corrects typographical errors and achieves taxonomic and nomenclatural standardization was developed using The Plant List (http://theplantlist.org/) as reference. Species distribution models have been computed for around 1700 species using different methods, and they will be publicly accessible through the web site in the future (http://portal.biotreenet.com). Although BIOTREE-NET has contributed to the development of improved species distribution models, its main potential lies, in our opinion, in studies at the community level. Finally, we emphasise the need to expand the network and encourage researchers willing to share data and to join the network and contribute to the generation of further knowledge about forest biodiversity in Neotropical regions

Estudio anatomo-radiológico estático y dinámico del espacio retroperitoneal. Análisis de los compartimentos multiestratificados. Análisis actual del diagnóstico por imagen en el cólico nefrítico/

Tesis Univ. Granada. Departamento de Radiología y Medicina Física. Leída el 24 de mayo de 201

MRI of nigrosome-1 : A potential triage tool for patients with suspected parkinsonism

Background and Purpose Susceptibility-weighted imaging (SWI) of nigrosome-1 is an emerging and clinically applicable imaging marker for parkinsonism, which can be derived from routinely performed brain MRI. The purpose of the study was to assess whether SWI can be used as a triage tool for more efficient selection of subsequent Dopamine Transporter Scan (DaTSCAN) single-photon emission computed tomography (SPECT). Methods We examined 72 consecutive patients with suspected parkinsonism with both DaTSCAN SPECT and SWI (48 in Philips Ingenia, 24 in GE Signa). Additionally, we examined 24 healthy controls with SWI (14 in Philips Ingenia, 10 in GE Signa). Diagnostic performance of SWI and DaTSCAN SPECT was assessed on the basis of clinical diagnosis, in terms of sensitivity, specificity, and diagnostic accuracy. Results A total of 54 parkinsonism patients (69 years +/- 9, 32 men), 18 nonparkinsonism patients (69.4 years +/- 9, 10 men), and 24 healthy controls (62 years +/- 8, 10 men) were recruited. SWI had a specificity of 92% and a sensitivity of 74%, whereas DaTSCAN SPECT had 83% and 94%, respectively. By preselecting patients with abnormal or inconclusive SWI, the diagnostic performance of DaTSCAN SPECT improved (specificity 100%, sensitivity 95%). Scans from Philips were associated with significantly lower image quality compared to GE (p &amp;lt; .001). The experienced rater outperformed the less experienced one in diagnostic accuracy (82% vs. 68%). Conclusions SWI can be used as triage tool because normal SWI can in most cases rule out parkinsonism. However, the performance of SWI depends on acquisition parameters and raters experience.Funding Agencies|ALF-grants from Region Ostergotland; local LIONS research fund</p

Peeking inside the box : Transfer Learning vs 3D convolutional neural networks applied in neurodegenerative diseases

Convolutional Neural Networks (CNNs) have shown their effectiveness in a variety of imaging applications including medical imaging diagnostics. However, these deep learning models are data-hungry and need enough labeled samples for the training phase which is limited in the medical domain. Transfer learning is one possible solution to this challenge with training a new model. Assessing model performance should be done not only based on criteria like accuracy, and area under the ROC curve, but also it is important to investigate what regions were of most interest for the classification decisions, especially for medical applications. We performed a case study on neurodegenerative disorders, in specific Alzheimer’s disease, mild cognitive im- pairment, dementia with lewy bodies and cognitively normal brains using 3D 18F-FDG-PET brain scans. Two transfer learning models, InceptionV3 and ResNet50, as well as a custom 3D-CNN that is trained from scratch are compared. Two XAI methods, occlusion and Grad-CAM are chosen to visualize the important brain regions using correctly classified cases. We found that the TL models learn significantly different decision surfaces than the 3D-CNN model. The 3D spatial structure of the brain regions are better kept in the 3D-CNN model, and that might explain the higher performance of this model over 2D-TL models. Moreover, we found out the two XAI methods provide different results, where occlusion method focused more on specific brain regions